commit d8e36f6aa880ce2f1ec995f3b741e4cca539370a Author: Jarca Date: Fri Jun 26 22:15:15 2026 +0900 Initial Jarca Ledger MCP implementation diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..1765908 --- /dev/null +++ b/.env.example @@ -0,0 +1,2 @@ +# Optional. Defaults to ~/.local/share/jarca/ledger.sqlite3 +JARCA_LEDGER_DB_PATH= diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..adc2fa4 --- /dev/null +++ b/.gitignore @@ -0,0 +1,18 @@ +.venv/ +.env +.env.* +!.env.example +__pycache__/ +*.py[cod] +.pytest_cache/ +*.egg-info/ +*.sqlite3 +*.sqlite +*.db +*.db-* +*.pdf +*.xls +*.xlsx +*.csv +tmp_* +.DS_Store diff --git a/README.md b/README.md new file mode 100644 index 0000000..edacb45 --- /dev/null +++ b/README.md @@ -0,0 +1,77 @@ +# jarca-ledger-mcp + +Jarca 가계부 전용 MCP 서버입니다. 계좌/카드, 수입·지출 거래, 예산, 월간 현금흐름, 고정비, 투자 여력 분석을 SQLite에 저장하고 MCP 도구로 제공합니다. + +## 설치 + +```bash +cd /root/projects/jarca-ledger-mcp +python3.11 -m venv .venv +. .venv/bin/activate +pip install -e '.[dev,dashboard]' +``` + +기본 DB 위치는 `~/.local/share/jarca/ledger.sqlite3`입니다. 바꾸려면 `.env`에 설정하세요. + +```bash +cp .env.example .env +# JARCA_LEDGER_DB_PATH=/원하는/경로/ledger.sqlite3 +``` + +## Hermes 등록 + +```bash +hermes mcp add jarca-ledger --command /root/projects/jarca-ledger-mcp/.venv/bin/jarca-ledger-mcp +hermes mcp test jarca-ledger +``` + +게이트웨이/현재 세션에는 `/reload-mcp` 또는 재시작 후 반영됩니다. + +## Streamlit Dashboard + +로컬 웹 대시보드는 실제 기본 DB `~/.local/share/jarca/ledger.sqlite3`를 읽고 씁니다. + +```bash +cd /root/projects/jarca-ledger-mcp +. .venv/bin/activate +streamlit run dashboard/app.py --server.address 0.0.0.0 --server.port 8501 +``` + +주요 화면: + +- 요약: 실제 수입/지출과 계좌 입출금을 분리 표시, 월별 현금흐름, 지출 카테고리 차트 +- 거래내역: 검색/필터 및 개별 거래 카테고리 수정 +- 미분류: 미분류 거래 요약, 거래별 분류, 규칙 저장 +- 분류 규칙: 규칙 seed/preview/apply, 사용자 규칙 생성 +- 카테고리: 대/소분류 추가, 비활성화/삭제, 사용 건수 확인 +- 계좌: 등록 계좌/잔액 확인 +- Import: PDF/CSV/API import batch 조회 및 rollback + +## 주요 도구 + +- `ledger_health_check` +- `create_ledger_account`, `list_ledger_accounts` +- `create_ledger_transaction`, `list_ledger_transactions`, `update_ledger_transaction`, `delete_ledger_transaction` +- `create_ledger_budget`, `list_ledger_budgets` +- `get_monthly_cashflow_report` +- `get_category_spending_report` +- `get_fixed_cost_report` +- `get_budget_vs_actual_report` +- `get_investable_cashflow_report` +- `preview_ledger_csv_import` +- `preview_kb_bank_pdf_import`, `import_kb_bank_pdf` +- `list_ledger_import_batches`, `rollback_ledger_import_batch` +- `create_category_rule`, `seed_default_category_rules`, `list_category_rules` +- `preview_categorization`, `apply_categorization_rules` +- `list_uncategorized_transactions`, `get_uncategorized_merchant_summary` +- `create_ledger_category`, `seed_default_ledger_categories`, `list_ledger_categories`, `delete_ledger_category` + +## 설계 원칙 + +- 금액은 원화 정수 원 단위로 저장합니다. +- 거래 금액은 양수로 넣고, `type`이 `income`, `expense`, `transfer`, `refund`, `adjustment` 중 하나로 방향을 나타냅니다. +- 금융 데이터이므로 Jarca 본체 MCP와 분리된 DB/서버로 운영합니다. +- 국민은행 PDF import는 암호화 PDF 비밀번호를 입력받아 PyMuPDF로 표를 추출하고, `transaction_datetime`, `counterparty`, `balance_after`, `branch`, `raw_summary`, `raw_payload`에 원본 세부 정보를 보존합니다. +- CSV/PDF/API import는 `import_batches`에 묶음 이력을 남기고, 잘못 가져온 batch는 `rollback_ledger_import_batch`로 되돌릴 수 있습니다. +- 카테고리에는 `cashflow_kind`를 저장해 실제 가계부 수입/지출(`income`, `expense`)과 계좌이체/투자이동/분석제외(`transfer`, `investment`, `exclude`, `debt_payment`, `unknown`)를 분리합니다. +- CSV import는 먼저 preview 후 저장하는 흐름으로 확장합니다. diff --git a/dashboard/app.py b/dashboard/app.py new file mode 100644 index 0000000..3edd170 --- /dev/null +++ b/dashboard/app.py @@ -0,0 +1,1040 @@ +from __future__ import annotations + +import sqlite3 +from html import escape +from pathlib import Path +from typing import Any +from urllib.parse import quote + +import pandas as pd +import plotly.express as px +import streamlit as st + +from jarca_ledger_mcp import service +from jarca_ledger_mcp.db import resolve_db_path + +st.set_page_config(page_title="Jarca Ledger", page_icon="💰", layout="wide") + +DEFAULT_CATEGORIES = [ + "", "수입", "이체", "식비", "주거", "통신", "교통", "교육", "의료", "생활", "문화/여가", "금융", "가족/용돈", "미분류" +] +DEFAULT_SUBCATEGORIES: dict[str, list[str]] = { + "수입": ["", "급여", "이자", "환급", "배당", "기타수입"], + "이체": ["", "본인계좌이동", "현금입출금", "가족송금", "투자이동", "확인필요"], + "식비": ["", "마트", "외식", "카페", "배달"], + "주거": ["", "관리비", "전기", "가스", "수도", "인터넷"], + "통신": ["", "휴대폰", "인터넷", "통신요금"], + "교통": ["", "대중교통", "택시", "주유", "주차", "차량정비"], + "교육": ["", "학원", "교재", "학교", "예체능"], + "의료": ["", "병원", "약국", "치과", "보험"], + "생활": ["", "생필품", "의류", "미용", "세탁"], + "문화/여가": ["", "여행", "숙박", "공연", "취미", "스포츠"], + "금융": ["", "카드대금", "대출상환", "수수료", "보험료"], + "가족/용돈": ["", "부모님", "자녀", "가족송금"], + "미분류": ["", "확인필요"], +} +CASHFLOW_KIND_OPTIONS = ["income", "expense", "transfer", "investment", "debt_payment", "exclude", "unknown"] +CASHFLOW_KIND_LABELS = { + "income": "실제 수입", + "expense": "실제 지출", + "transfer": "이체/제외", + "investment": "투자이동/제외", + "debt_payment": "부채상환/별도", + "exclude": "분석 제외", + "unknown": "확인필요", +} + + +def format_krw(value: Any) -> str: + try: + if value is None: + return "-" + return f"{int(value):,}원" + except Exception: + return str(value) + + +@st.cache_data(ttl=5) +def read_sql(db_path: str, sql: str, params: tuple[Any, ...] = ()) -> pd.DataFrame: + with sqlite3.connect(db_path) as conn: + return pd.read_sql_query(sql, conn, params=params) + + +def clear_cache() -> None: + read_sql.clear() + + +def get_db_path() -> str: + return str(resolve_db_path()) + + +def inject_sidebar_nav_css() -> None: + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + +def render_sidebar_nav(pages: list[str], current_page: str) -> None: + items = [] + for name in pages: + active = " active" if name == current_page else "" + href = f"?page={quote(name)}" + items.append(f'{escape(name)}') + st.markdown(f'
{"".join(items)}
', unsafe_allow_html=True) + + +def parse_optional_int(value: str, field_name: str) -> int | None: + value = (value or "").strip() + if not value: + return None + try: + return int(value) + except ValueError as exc: + raise ValueError(f"{field_name}는 정수여야 합니다.") from exc + + +def get_category_options(db_path: str) -> tuple[list[str], dict[str, list[str]]]: + result = service.list_ledger_categories(active_only=True, include_usage=False, db_path=db_path) + if result.get("success") and result.get("count", 0) == 0: + service.seed_default_ledger_categories(db_path=db_path) + result = service.list_ledger_categories(active_only=True, include_usage=False, db_path=db_path) + grouped = result.get("grouped", {}) if result.get("success") else {} + categories = [""] + sorted(grouped.keys()) + subcategories = {cat: [""] + sorted([s for s in subs if s]) for cat, subs in grouped.items()} + # Keep hardcoded defaults as fallback for fresh/broken DBs and for existing transaction values. + for cat in DEFAULT_CATEGORIES: + if cat and cat not in categories: + categories.append(cat) + for cat, subs in DEFAULT_SUBCATEGORIES.items(): + subcategories.setdefault(cat, [""]) + for sub in subs: + if sub not in subcategories[cat]: + subcategories[cat].append(sub) + return categories, subcategories + + +def transaction_df(db_path: str, where: str = "", params: tuple[Any, ...] = (), limit: int = 1000) -> pd.DataFrame: + sql = f""" + SELECT t.id, t.transaction_datetime, t.transaction_date, t.type, t.amount, t.category, t.subcategory, + COALESCE(lc.cashflow_kind, 'unknown') AS cashflow_kind, + t.merchant, t.raw_summary, t.counterparty, t.person, t.is_fixed, t.balance_after, t.branch, + t.source, t.import_batch_id, t.memo, t.status + FROM transactions t + LEFT JOIN ledger_categories lc + ON lc.active=1 AND t.category=lc.category AND t.subcategory=lc.subcategory + {where} + ORDER BY COALESCE(NULLIF(t.transaction_datetime,''), t.transaction_date) DESC, t.created_at DESC + LIMIT ? + """ + df = read_sql(db_path, sql, params + (limit,)) + if not df.empty: + df["금액"] = df["amount"].map(format_krw) + df["거래후잔액"] = df["balance_after"].map(format_krw) + df["고정비"] = df["is_fixed"].fillna(0).astype(bool) + return df + + +def update_transaction_form(tx: dict[str, Any], key_prefix: str, db_path: str | None = None) -> None: + db_path = db_path or get_db_path() + category_options, subcategory_options = get_category_options(db_path) + + category_key = f"{key_prefix}_category" + subcategory_key = f"{key_prefix}_subcategory" + person_key = f"{key_prefix}_person" + fixed_key = f"{key_prefix}_fixed" + memo_key = f"{key_prefix}_memo" + save_rule_key = f"{key_prefix}_save_rule" + tx_marker_key = f"{key_prefix}_tx_id" + + current_category = tx.get("category", "") or "" + if current_category and current_category not in category_options: + category_options = category_options + [current_category] + + if st.session_state.get(tx_marker_key) != tx["id"]: + st.session_state[tx_marker_key] = tx["id"] + st.session_state[category_key] = current_category + st.session_state[subcategory_key] = tx.get("subcategory", "") or "" + st.session_state[person_key] = tx.get("person", "") or "" + st.session_state[fixed_key] = bool(tx.get("is_fixed") or False) + st.session_state[memo_key] = tx.get("memo", "") or "" + st.session_state[save_rule_key] = False + + st.caption(f"거래 ID: `{tx['id']}`") + st.write(f"**{tx.get('transaction_datetime') or tx.get('transaction_date')}** · {tx.get('merchant')} · {format_krw(tx.get('amount'))}") + + category = st.selectbox( + "대분류", + category_options, + index=category_options.index(st.session_state.get(category_key, current_category)) if st.session_state.get(category_key, current_category) in category_options else 0, + key=category_key, + ) + + sub_opts = subcategory_options.get(category, [""]) + current_sub = st.session_state.get(subcategory_key, tx.get("subcategory", "") or "") or "" + if current_sub and current_sub not in sub_opts: + current_sub = "" + st.session_state[subcategory_key] = "" + subcategory = st.selectbox( + "소분류", + sub_opts, + index=sub_opts.index(current_sub) if current_sub in sub_opts else 0, + key=subcategory_key, + ) + person = st.text_input("가족 구성원/person", key=person_key) + is_fixed = st.checkbox("고정비", key=fixed_key) + memo = st.text_input("메모", key=memo_key) + save_rule = st.checkbox("이 사용처 패턴을 규칙으로 저장", key=save_rule_key) + submitted = st.button("저장", type="primary", key=f"{key_prefix}_submit") + + if submitted: + result = service.update_ledger_transaction( + tx["id"], category=category, subcategory=subcategory, person=person, + is_fixed=is_fixed, memo=memo, + ) + if not result.get("success"): + st.error(result.get("error", result)) + return + if save_rule and tx.get("merchant") and category: + rule = service.create_category_rule( + match_field="merchant", + pattern=tx["merchant"], + category=category, + subcategory=subcategory, + transaction_type=tx.get("type", ""), + person=person, + is_fixed=is_fixed, + priority=70, + memo="dashboard: user-confirmed rule", + ) + if not rule.get("success"): + st.warning(f"거래는 저장됐지만 규칙 저장 실패: {rule.get('error')}") + clear_cache() + st.success("저장했습니다.") + st.rerun() + + +@st.dialog("거래 분류", width="large") +def transaction_edit_dialog(tx: dict[str, Any], key_prefix: str, db_path: str) -> None: + update_transaction_form(tx, key_prefix, db_path) + + +@st.dialog("연결 거래 후보", width="large") +def linked_transfer_candidates_dialog(tx: dict[str, Any], db_path: str) -> None: + st.caption(f"기준 거래: `{tx['id']}`") + st.write(f"**{tx.get('transaction_datetime') or tx.get('transaction_date')}** · {tx.get('merchant')} · {format_krw(tx.get('amount'))}") + result = service.find_self_transfer_candidates(tx["id"], limit=20, db_path=db_path) + if not result.get("success"): + st.error(result.get("error", result)) + return + candidates = result.get("candidates", []) + if not candidates: + st.info("같은 금액/가까운 날짜 조건에서 연결 후보를 찾지 못했습니다.") + return + + st.success(f"연결 후보 {result.get('count', len(candidates))}건") + for idx, candidate in enumerate(candidates): + cols = st.columns([1.45, 0.95, 0.7, 1.2, 1.15, 0.95]) + cols[0].write(candidate.get("transaction_datetime") or candidate.get("transaction_date") or "") + cols[1].write(candidate.get("source") or "") + cols[2].write(candidate.get("type") or "") + cols[3].write(format_krw(candidate.get("amount"))) + cols[4].write(candidate.get("merchant") or candidate.get("counterparty") or "") + if cols[5].button("이 거래와 연결", key=f"link_pair_{tx['id']}_{candidate['id']}_{idx}", use_container_width=True, type="primary"): + link_res = service.link_self_transfer_pair(tx["id"], candidate["id"], db_path=db_path) + if not link_res.get("success"): + st.error(link_res.get("error", link_res)) + else: + clear_cache() + st.success("양쪽 거래를 본인계좌이동으로 연결했습니다.") + st.rerun() + meta = [] + if candidate.get("account_name"): + meta.append(f"계좌: {candidate['account_name']}") + if candidate.get("category") or candidate.get("subcategory"): + meta.append(f"현재 분류: {candidate.get('category', '')} / {candidate.get('subcategory', '')}") + if candidate.get("score") is not None: + meta.append(f"score={candidate['score']}") + if candidate.get("reason"): + meta.append(candidate["reason"]) + st.caption(" · ".join(meta)) + if idx < len(candidates) - 1: + st.divider() + + +@st.dialog("원거래 후보", width="large") +def cancel_original_candidates_dialog(tx: dict[str, Any], db_path: str) -> None: + st.caption(f"취소/환급 거래: `{tx['id']}`") + st.write(f"**{tx.get('transaction_datetime') or tx.get('transaction_date')}** · {tx.get('merchant')} · {format_krw(tx.get('amount'))}") + result = service.find_cancel_original_candidates(tx["id"], limit=20, db_path=db_path) + if not result.get("success"): + st.error(result.get("error", result)) + return + candidates = result.get("candidates", []) + if not candidates: + st.info("같은 금액 기준으로 연결할 원거래 후보를 찾지 못했습니다.") + return + + st.success(f"원거래 후보 {result.get('count', len(candidates))}건") + for idx, candidate in enumerate(candidates): + cols = st.columns([1.4, 0.95, 0.7, 1.25, 1.15, 0.95]) + cols[0].write(candidate.get("transaction_datetime") or candidate.get("transaction_date") or "") + cols[1].write(candidate.get("source") or "") + cols[2].write(candidate.get("type") or "") + cols[3].write(format_krw(candidate.get("amount"))) + cols[4].write(candidate.get("merchant") or candidate.get("counterparty") or "") + if cols[5].button("이 원거래와 연결", key=f"cancel_pair_{tx['id']}_{candidate['id']}_{idx}", use_container_width=True, type="primary"): + link_res = service.link_cancel_to_original(tx["id"], candidate["id"], db_path=db_path) + if not link_res.get("success"): + st.error(link_res.get("error", link_res)) + else: + clear_cache() + st.success("취소/환급 거래를 원거래와 연결했습니다.") + st.rerun() + meta = [] + if candidate.get("account_name"): + meta.append(f"계좌: {candidate['account_name']}") + if candidate.get("category") or candidate.get("subcategory"): + meta.append(f"현재 분류: {candidate.get('category', '')} / {candidate.get('subcategory', '')}") + if candidate.get("score") is not None: + meta.append(f"score={candidate['score']}") + if candidate.get("reason"): + meta.append(candidate["reason"]) + st.caption(" · ".join(meta)) + if idx < len(candidates) - 1: + st.divider() + + +RULE_MATCH_FIELDS = ["merchant", "raw_summary", "counterparty", "payment_method", "branch", "description", "memo"] +RULE_MATCH_TYPES = ["contains", "equals", "starts_with", "ends_with", "regex"] +RULE_TX_TYPES = ["", "income", "expense", "transfer", "refund", "adjustment"] +RULE_FIXED_LABELS = ["변경안함", "예", "아니오"] + + +@st.dialog("분류 규칙 추가", width="large") +def category_rule_create_dialog(db_path: str) -> None: + category_options, _ = get_category_options(db_path) + editable_categories = [c for c in category_options if c] + + with st.form("rule_create_dialog"): + cols = st.columns(4) + match_field = cols[0].selectbox("대상 필드", RULE_MATCH_FIELDS) + match_type = cols[1].selectbox("매칭 방식", RULE_MATCH_TYPES) + pattern = cols[2].text_input("패턴") + tx_type = cols[3].selectbox("거래 유형", RULE_TX_TYPES) + + cols2 = st.columns(5) + category = cols2[0].selectbox("대분류", editable_categories) + subcategory = cols2[1].text_input("소분류") + person = cols2[2].text_input("person") + priority = cols2[3].number_input("우선순위", value=100, step=10) + is_fixed = cols2[4].selectbox("고정비", RULE_FIXED_LABELS) + + cols3 = st.columns(3) + amount_min_text = cols3[0].text_input("최소 금액(선택)", placeholder="예: 1200000") + amount_max_text = cols3[1].text_input("최대 금액(선택)", placeholder="예: 1200000") + day_of_month_text = cols3[2].text_input("매월 일자(선택)", placeholder="1~31") + memo = st.text_input("메모", value="dashboard: user rule") + submitted = st.form_submit_button("규칙 저장", type="primary") + + if submitted: + try: + amount_min = parse_optional_int(amount_min_text, "최소 금액") + amount_max = parse_optional_int(amount_max_text, "최대 금액") + day_of_month = parse_optional_int(day_of_month_text, "매월 일자") + except ValueError as exc: + st.error(str(exc)) + else: + fixed_value = None if is_fixed == "변경안함" else is_fixed == "예" + res = service.create_category_rule(match_field, pattern, category, subcategory, tx_type, match_type, int(priority), person, fixed_value, 1.0, memo, amount_min, amount_max, day_of_month, db_path=db_path) + clear_cache() + if res.get("success"): + st.success("규칙을 저장했습니다.") + st.rerun() + else: + st.error(res.get("error", res)) + + +@st.dialog("분류 규칙 수정", width="large") +def category_rule_edit_dialog(rule: dict[str, Any], db_path: str) -> None: + category_options, _ = get_category_options(db_path) + current_category = rule.get("category", "") or "" + editable_categories = [c for c in category_options if c] + if current_category and current_category not in editable_categories: + editable_categories.append(current_category) + fixed_value = "변경안함" if rule.get("is_fixed") is None else ("예" if rule.get("is_fixed") else "아니오") + + st.caption(f"규칙 ID: `{rule['id']}`") + st.write(f"**{rule.get('pattern') or '-'}**") + + with st.form(f"rule_edit_dialog_{rule['id']}"): + cols = st.columns(4) + edit_match_field = cols[0].selectbox("대상 필드", RULE_MATCH_FIELDS, index=RULE_MATCH_FIELDS.index(rule.get("match_field", "merchant")) if rule.get("match_field", "merchant") in RULE_MATCH_FIELDS else 0) + edit_match_type = cols[1].selectbox("매칭 방식", RULE_MATCH_TYPES, index=RULE_MATCH_TYPES.index(rule.get("match_type", "contains")) if rule.get("match_type", "contains") in RULE_MATCH_TYPES else 0) + edit_pattern = cols[2].text_input("패턴", value=rule.get("pattern", "") or "") + edit_tx_type = cols[3].selectbox("거래 유형", RULE_TX_TYPES, index=RULE_TX_TYPES.index(rule.get("transaction_type", "") or "") if (rule.get("transaction_type", "") or "") in RULE_TX_TYPES else 0) + + cols2 = st.columns(5) + edit_category = cols2[0].selectbox("대분류", editable_categories, index=editable_categories.index(current_category) if current_category in editable_categories else 0) + edit_subcategory = cols2[1].text_input("소분류", value=rule.get("subcategory", "") or "") + edit_person = cols2[2].text_input("person", value=rule.get("person", "") or "") + edit_priority = cols2[3].number_input("우선순위", value=int(rule.get("priority", 100) or 100), step=10) + edit_is_fixed = cols2[4].selectbox("고정비", RULE_FIXED_LABELS, index=RULE_FIXED_LABELS.index(fixed_value)) + + cols3 = st.columns(4) + edit_amount_min_text = cols3[0].text_input("최소 금액(선택)", value="" if rule.get("amount_min") is None else str(rule.get("amount_min"))) + edit_amount_max_text = cols3[1].text_input("최대 금액(선택)", value="" if rule.get("amount_max") is None else str(rule.get("amount_max"))) + edit_day_of_month_text = cols3[2].text_input("매월 일자(선택)", value="" if rule.get("day_of_month") is None else str(rule.get("day_of_month"))) + edit_active = cols3[3].checkbox("활성", value=bool(rule.get("active", True))) + edit_memo = st.text_input("메모", value=rule.get("memo", "") or "") + edit_submitted = st.form_submit_button("규칙 수정", type="primary") + + if edit_submitted: + try: + edit_amount_min = parse_optional_int(edit_amount_min_text, "최소 금액") + edit_amount_max = parse_optional_int(edit_amount_max_text, "최대 금액") + edit_day_of_month = parse_optional_int(edit_day_of_month_text, "매월 일자") + except ValueError as exc: + st.error(str(exc)) + else: + edit_fixed_value = None if edit_is_fixed == "변경안함" else edit_is_fixed == "예" + update_rule = getattr(service, "update_category_rule", None) + if update_rule is None: + st.error("현재 실행 중인 서비스에 update_category_rule 함수가 없습니다. 앱을 재시작해 최신 코드를 다시 불러오세요.") + else: + res = update_rule( + rule["id"], edit_match_field, edit_pattern, edit_category, edit_subcategory, + edit_tx_type, edit_match_type, int(edit_priority), edit_person, edit_fixed_value, + 1.0, edit_memo, edit_amount_min, edit_amount_max, edit_day_of_month, edit_active, + db_path=db_path, + ) + clear_cache() + if res.get("success"): + st.success("규칙을 수정했습니다.") + st.rerun() + else: + st.error(res.get("error", res)) + + +def render_uncategorized_action_table(rows: list[dict[str, Any]], db_path: str) -> None: + header_cols = st.columns([1.45, 0.6, 0.8, 1.35, 1.3, 0.7, 1.0, 1.0]) + headers = ["일시", "구분", "금액", "사용처", "요약", "", "", ""] + for col, label in zip(header_cols, headers): + col.markdown(f"**{label}**") + + for idx, row in enumerate(rows): + cols = st.columns([1.45, 0.6, 0.8, 1.35, 1.3, 0.7, 1.0, 1.0]) + cols[0].write(row.get("transaction_datetime") or row.get("transaction_date") or "") + cols[1].write(row.get("type") or "") + cols[2].write(format_krw(row.get("amount"))) + cols[3].write(row.get("merchant") or "") + cols[4].write(row.get("raw_summary") or "") + if cols[5].button("분류", key=f"uncat_dialog_{row['id']}_{idx}", use_container_width=True, type="tertiary"): + transaction_edit_dialog(row, f"uncat_dialog_{row['id']}", db_path) + if cols[6].button("연결거래찾기", key=f"uncat_link_{row['id']}_{idx}", use_container_width=True, type="tertiary"): + linked_transfer_candidates_dialog(row, db_path) + if cols[7].button("원거래찾기", key=f"uncat_cancel_{row['id']}_{idx}", use_container_width=True, type="tertiary"): + cancel_original_candidates_dialog(row, db_path) + + +def page_overview(db_path: str) -> None: + st.title("📊 요약") + health = service.health_check(db_path) + st.caption(f"DB: `{health.get('db_path')}` · schema v{health.get('schema_version')}") + df = read_sql(db_path, "SELECT * FROM transactions WHERE status='active'") + accounts = read_sql(db_path, "SELECT * FROM accounts WHERE active=1") + categories = read_sql(db_path, "SELECT category, subcategory, cashflow_kind FROM ledger_categories WHERE active=1") + if df.empty: + st.info("거래가 없습니다.") + return + df["month"] = pd.to_datetime(df["transaction_date"]).dt.strftime("%Y-%m") + if not categories.empty: + df = df.merge(categories, how="left", on=["category", "subcategory"]) + else: + df["cashflow_kind"] = None + df["cashflow_kind"] = df["cashflow_kind"].fillna("unknown") + + account_in = int(df.loc[df["type"] == "income", "amount"].sum()) + account_out = int(df.loc[df["type"] == "expense", "amount"].sum()) + account_net = account_in - account_out + actual_income = int(df.loc[df["cashflow_kind"] == "income", "amount"].sum()) + actual_expense = int(df.loc[df["cashflow_kind"] == "expense", "amount"].sum()) + actual_net = actual_income - actual_expense + savings_rate = actual_net / actual_income if actual_income else None + transfer_like = int(df.loc[df["cashflow_kind"].isin(["transfer", "investment", "exclude"]), "amount"].sum()) + unknown_amount = int(df.loc[df["cashflow_kind"] == "unknown", "amount"].sum()) + uncategorized = int((df["category"].fillna("") == "").sum()) + + st.subheader("실제 가계부 기준") + c1, c2, c3, c4, c5 = st.columns(5) + c1.metric("실제 수입", format_krw(actual_income)) + c2.metric("실제 지출", format_krw(actual_expense)) + c3.metric("실제 순현금흐름", format_krw(actual_net)) + c4.metric("저축률", f"{savings_rate:.1%}" if savings_rate is not None else "-") + c5.metric("확인필요", format_krw(unknown_amount)) + + st.subheader("계좌 입출금 흐름") + b1, b2, b3, b4, b5 = st.columns(5) + b1.metric("계좌", len(accounts)) + b2.metric("거래", len(df)) + b3.metric("총 입금", format_krw(account_in)) + b4.metric("총 출금", format_krw(account_out)) + b5.metric("계좌 순증감", format_krw(account_net)) + st.caption(f"이체/투자/분석제외성 거래 합계: {format_krw(transfer_like)} · 미분류 거래: {uncategorized:,}건") + + monthly = df.pivot_table(index="month", columns="cashflow_kind", values="amount", aggfunc="sum", fill_value=0).reset_index() + for col in ["income", "expense"]: + if col not in monthly.columns: + monthly[col] = 0 + monthly["actual_net_cashflow"] = monthly["income"] - monthly["expense"] + st.plotly_chart(px.bar(monthly, x="month", y=["income", "expense", "actual_net_cashflow"], barmode="group", title="월별 실제 수입/지출"), width="stretch") + + account_monthly = df.pivot_table(index="month", columns="type", values="amount", aggfunc="sum", fill_value=0).reset_index() + for col in ["income", "expense"]: + if col not in account_monthly.columns: + account_monthly[col] = 0 + account_monthly["account_net"] = account_monthly["income"] - account_monthly["expense"] + st.plotly_chart(px.line(account_monthly, x="month", y=["income", "expense", "account_net"], title="월별 계좌 입출금 흐름"), width="stretch") + + person_summary = df[df["cashflow_kind"].isin(["income", "expense"])].pivot_table(index="person", columns="cashflow_kind", values="amount", aggfunc="sum", fill_value=0).reset_index() + if not person_summary.empty: + person_summary["person"] = person_summary["person"].replace("", "미지정") + for col in ["income", "expense"]: + if col not in person_summary.columns: + person_summary[col] = 0 + person_summary["net_cashflow"] = person_summary["income"] - person_summary["expense"] + st.subheader("인원별 실제 수입/지출") + st.dataframe(person_summary, width="stretch", height=220) + st.plotly_chart(px.bar(person_summary, x="person", y=["income", "expense", "net_cashflow"], barmode="group", title="인원별 실제 수입/지출"), width="stretch") + + cat = df[df["cashflow_kind"] == "expense"].groupby(["category", "subcategory"], dropna=False)["amount"].sum().reset_index() + cat["label"] = cat.apply(lambda r: f"{r['category'] or '미분류'} / {r['subcategory'] or '-'}", axis=1) + cat = cat.sort_values("amount", ascending=False).head(20) + st.plotly_chart(px.bar(cat, x="amount", y="label", orientation="h", title="실제 지출 카테고리 Top 20"), width="stretch") + + +def page_transactions(db_path: str) -> None: + st.title("📒 거래내역") + category_options, _ = get_category_options(db_path) + people_df = read_sql(db_path, "SELECT DISTINCT person FROM transactions WHERE status='active' AND person<>'' ORDER BY person") + people = people_df["person"].tolist() if not people_df.empty else [] + col1, col2, col3, col4, col5 = st.columns(5) + start = col1.date_input("시작일", value=None) + end = col2.date_input("종료일", value=None) + category = col3.selectbox("카테고리", ["전체"] + [c for c in category_options if c]) + person = col4.selectbox("인원", ["전체"] + people) + text = col5.text_input("사용처 검색") + clauses = ["t.status='active'"] + params: list[Any] = [] + if start: + clauses.append("t.transaction_date>=?"); params.append(str(start)) + if end: + clauses.append("t.transaction_date<=?"); params.append(str(end)) + if category != "전체": + clauses.append("t.category=?"); params.append(category) + if person != "전체": + clauses.append("t.person=?"); params.append(person) + if text: + clauses.append("t.merchant LIKE ?"); params.append(f"%{text}%") + df = transaction_df(db_path, "WHERE " + " AND ".join(clauses), tuple(params), limit=2000) + st.dataframe(df.drop(columns=["id", "amount", "balance_after", "is_fixed"], errors="ignore"), width="stretch", height=500) + + if not df.empty: + st.subheader("선택 거래 수정") + options = {f"{r.transaction_datetime or r.transaction_date} · {r.merchant} · {format_krw(r.amount)} · {r.category or '미분류'}": r.id for r in df.itertuples()} + label = st.selectbox("수정할 거래", list(options.keys())) + tx_id = options[label] + tx = df[df["id"] == tx_id].iloc[0].to_dict() + update_transaction_form(tx, "tx", db_path) + + +def page_cross_transfer_review(db_path: str) -> None: + st.header("🔁 KB↔토스뱅크 확인필요 큐") + st.caption("KB와 토스뱅크 거래를 날짜·금액·상대 기준으로 자동 대조합니다. 먼저 미리보기(드라이런)로 후보를 확인한 뒤 실행하세요.") + c1, c2 = st.columns(2) + with c1: + if st.button("미리보기(드라이런)"): + st.session_state["cross_transfer_preview"] = service.preview_cross_account_transfers(db_path=db_path) + with c2: + if st.button("자동 매칭 실행"): + res = service.run_cross_account_transfer_match(db_path=db_path) + clear_cache() + st.session_state["cross_transfer_last_run"] = res + st.success(f"매칭 {res.get('matched_count', 0)}건 적용, 확인필요 {res.get('review_count', 0)}건") + st.rerun() + + if "cross_transfer_preview" in st.session_state: + prev = st.session_state["cross_transfer_preview"] + st.subheader("미리보기 결과") + st.info(f"예상 매칭 {prev.get('matched_count', 0)}건 / 확인필요 {prev.get('review_count', 0)}건") + if prev.get("matched_pairs"): + st.dataframe(pd.DataFrame(prev.get("matched_pairs")), width="stretch", height=250) + if prev.get("review_items"): + st.dataframe(pd.DataFrame(prev.get("review_items")), width="stretch", height=250) + + st.divider() + st.subheader("확인필요 큐") + list_queue_fn = getattr(service, "list_cross_transfer_review_queue", None) + if callable(list_queue_fn): + queue = list_queue_fn(db_path=db_path) + rows = queue.get("transactions", []) + else: + # 호환성 보호: 구버전 서비스에서 메서드가 없을 때 직접 조회 + st.info("확인필요 큐 조회 함수가 현재 서비스 모듈에 없어 직접 DB 조회로 표시합니다.") + with sqlite3.connect(db_path) as _conn: + _conn.row_factory = lambda cursor, row: {description[0]: row[idx] for idx, description in enumerate(cursor.description)} + _rows = _conn.execute( + """ + SELECT * FROM transactions + WHERE status='active' + AND source IN ('kb_bank_pdf','toss_bank_pdf') + AND memo LIKE '%cross_transfer_review:%' + ORDER BY transaction_date DESC, created_at DESC + LIMIT 300 + """ + ).fetchall() + rows = [dict(r) for r in _rows] + + if not rows: + st.success("현재 확인필요 큐가 비어 있습니다.") + return + df = pd.DataFrame(rows) + if "cashflow_kind" in df.columns: + df["cashflow_kind"] = df["cashflow_kind"].fillna("") + st.dataframe(df[["transaction_date", "source", "type", "amount", "counterparty", "category", "subcategory", "memo", "id"]].rename(columns={"amount": "금액"}), width="stretch", height=320) + + options = { + f"{r.get('transaction_date')} · {r.get('source')} · {r.get('type')} · {int(r.get('amount', 0)):,}원 · {r.get('counterparty', '')}": r + for r in rows + } + selected = st.selectbox("수동 수정할 거래", list(options.keys())) + update_transaction_form(options[selected], "transfer_review", db_path) + + +def page_uncategorized(db_path: str) -> None: + st.title("🧩 미분류 거래") + col1, col2 = st.columns([1, 3]) + min_amount = col1.number_input("최소 금액", min_value=0, value=0, step=10000) + limit = col2.slider("표시 건수", 10, 500, 100) + summary = service.get_uncategorized_merchant_summary(limit=50) + st.header("미분류 사용처 요약") + st.dataframe(pd.DataFrame(summary.get("items", [])), width="stretch", height=280) + + result = service.list_uncategorized_transactions(limit=limit, min_amount=int(min_amount)) + rows = result.get("transactions", []) + if not rows: + st.success("미분류 거래가 없습니다.") + return + df = pd.DataFrame(rows) + df["금액"] = df["amount"].map(format_krw) + st.subheader("미분류 거래 수정") + render_uncategorized_action_table(rows, db_path) + + +def render_rule_list_items(rules: list[dict[str, Any]], db_path: str) -> None: + if not rules: + st.info("등록된 규칙이 없습니다.") + return + + st.markdown( + """ + + """, + unsafe_allow_html=True, + ) + + wrapper = st.container(border=True) + with wrapper: + for idx, rule in enumerate(rules): + rule_id = rule.get("id", "") + active = bool(rule.get("active", True)) + status_label = "활성" if active else "비활성" + tx_type = rule.get("transaction_type") or "전체" + person = rule.get("person") or "-" + fixed = rule.get("is_fixed") + fixed_label = "예" if fixed is True else "아니오" if fixed is False else "변경안함" + amount_bits = [] + if rule.get("amount_min") is not None: + amount_bits.append(f"최소 {format_krw(rule.get('amount_min'))}") + if rule.get("amount_max") is not None: + amount_bits.append(f"최대 {format_krw(rule.get('amount_max'))}") + if rule.get("day_of_month") is not None: + amount_bits.append(f"매월 {rule.get('day_of_month')}일") + condition_text = " · ".join(amount_bits) if amount_bits else "추가 조건 없음" + target_text = f"{rule.get('match_field') or '-'} / {rule.get('match_type') or '-'}" + pattern_text = rule.get("pattern") or "-" + result_text = f"{rule.get('category') or '-'} / {rule.get('subcategory') or '-'}" + memo = rule.get("memo") or "" + + title_cols = st.columns([16, 1], gap="small", vertical_alignment="center") + with title_cols[0]: + st.markdown( + f'
{escape(pattern_text)}p{escape(str(rule.get("priority", "-")))}
', + unsafe_allow_html=True, + ) + with title_cols[1]: + with st.popover("⋮"): + if st.button("변경", key=f"rule_menu_edit_{rule_id}", use_container_width=True): + category_rule_edit_dialog(rule, db_path) + if st.button("삭제", key=f"rule_menu_delete_{rule_id}", use_container_width=True): + delete_rule = getattr(service, "delete_category_rule", None) + if delete_rule is None: + st.error("현재 실행 중인 서비스에 delete_category_rule 함수가 없습니다. 앱을 재시작해 최신 코드를 다시 불러오세요.") + else: + res = delete_rule(rule_id, db_path=db_path) + clear_cache() + if res.get("success"): + if st.session_state.get("rules_edit_rule_id") == rule_id: + st.session_state.pop("rules_edit_rule_id", None) + st.success("규칙을 삭제했습니다.") + st.rerun() + else: + st.error(res.get("error", res)) + + st.markdown( + f""" +
+
대상: {escape(target_text)}
+
추가 조건: {escape(condition_text)}
+
분류 결과: {escape(result_text)}
+
+
거래유형: {escape(tx_type)}
+
person: {escape(person)}
+
고정비: {escape(fixed_label)}
+
상태: {escape(status_label)}
+
ID: {escape(rule_id)}
+ {f'
메모: {escape(memo)}
' if memo else '
'} +
+
+ """, + unsafe_allow_html=True, + ) + if idx < len(rules) - 1: + st.divider() + + +def page_rules(db_path: str) -> None: + title_cols = st.columns([8, 1], vertical_alignment="center") + with title_cols[0]: + st.title("⚙️ 분류 규칙") + with title_cols[1]: + if st.button("추가", key="rule_add_dialog_open", use_container_width=True, type="primary"): + category_rule_create_dialog(db_path) + rules = service.list_category_rules(active_only=False, db_path=db_path).get("rules", []) + st.subheader("현재 분류 규칙") + render_rule_list_items(rules, db_path) + + st.caption("규칙 추가는 제목 오른쪽 `추가` 버튼, 기존 규칙 수정은 각 항목의 `⋮ → 변경` 팝업을 사용하세요.") + + c1, c2, c3 = st.columns(3) + if c1.button("기본 규칙 seed/update"): + res = service.seed_default_category_rules() + clear_cache(); st.success(res) + if c2.button("규칙 preview"): + st.session_state["rule_preview"] = service.preview_categorization(limit=5000) + if c3.button("규칙 적용"): + res = service.apply_categorization_rules(limit=5000) + clear_cache(); st.success(f"{res.get('applied_count', 0)}건 적용") + if "rule_preview" in st.session_state: + prev = st.session_state["rule_preview"] + st.info(f"스캔 {prev.get('scanned')}건 · 매칭 {prev.get('matched_count')}건 · 미분류 {prev.get('unmatched_count')}건") + st.write("카테고리별 예상") + st.dataframe(pd.DataFrame([{"category": k, **v} for k, v in prev.get("by_category", {}).items()]), width="stretch") + with st.expander("매칭 샘플"): + st.dataframe(pd.DataFrame(prev.get("matches", [])), width="stretch") + with st.expander("미매칭 샘플"): + st.dataframe(pd.DataFrame(prev.get("unmatched", [])), width="stretch") + + +def page_categories(db_path: str) -> None: + st.header("🏷️ 카테고리 관리") + st.caption("카테고리 삭제는 기본적으로 비활성화 처리합니다. 기존 거래의 과거 category 값은 보존됩니다.") + + c1, c2 = st.columns(2) + if c1.button("기본 카테고리 seed/update"): + res = service.seed_default_ledger_categories(db_path=db_path) + clear_cache() + st.success(f"{res.get('created_or_updated', 0)}개 카테고리를 생성/갱신했습니다.") + st.rerun() + show_inactive = c2.checkbox("비활성 카테고리도 보기", value=False) + + st.subheader("카테고리 추가") + with st.form("create_ledger_category"): + cols = st.columns([2, 2, 2, 1, 3]) + category = cols[0].text_input("대분류", placeholder="예: 반려동물") + subcategory = cols[1].text_input("소분류", placeholder="예: 사료") + cashflow_kind_label = cols[2].selectbox("현금흐름 성격", [CASHFLOW_KIND_LABELS[k] for k in CASHFLOW_KIND_OPTIONS], index=1) + sort_order = cols[3].number_input("정렬", value=100, step=10) + memo = cols[4].text_input("메모", value="dashboard: user category") + submitted = st.form_submit_button("추가/재활성화", type="primary") + if submitted: + cashflow_kind = next(k for k, v in CASHFLOW_KIND_LABELS.items() if v == cashflow_kind_label) + res = service.create_ledger_category(category, subcategory, int(sort_order), memo, cashflow_kind, db_path=db_path) + clear_cache() + if res.get("success"): + st.success("카테고리를 저장했습니다.") + st.rerun() + else: + st.error(res.get("error", res)) + + result = service.list_ledger_categories(active_only=not show_inactive, include_usage=True, db_path=db_path) + rows = result.get("categories", []) + st.subheader("카테고리 목록") + if rows: + df = pd.DataFrame(rows) + if "cashflow_kind" in df: + df["cashflow_kind_label"] = df["cashflow_kind"].map(CASHFLOW_KIND_LABELS).fillna(df["cashflow_kind"]) + if "total_amount" in df: + df["total_amount_display"] = df["total_amount"].map(format_krw) + st.dataframe(df, width="stretch", height=360) + else: + st.info("등록된 카테고리가 없습니다. 기본 카테고리를 seed하거나 새 카테고리를 추가하세요.") + return + + st.subheader("카테고리 삭제/비활성화") + options = { + f"{r['category']} / {r['subcategory'] or '-'} · 사용 {r.get('transaction_count', 0)}건 · {'활성' if r.get('active') else '비활성'}": r + for r in rows + } + selected = st.selectbox("대상", list(options.keys())) + target = options[selected] + hard_delete = st.checkbox("DB에서 완전 삭제", value=False, help="보통은 끄고 비활성화만 하세요. 거래 기록은 별도 보존됩니다.") + force = st.checkbox("사용 중이어도 강제", value=False, help="거래/예산/규칙에서 사용 중인 카테고리도 삭제/비활성화합니다. 거래 category 값은 변경하지 않습니다.") + if st.button("삭제/비활성화 실행", type="secondary"): + res = service.delete_ledger_category(target["category"], target.get("subcategory", ""), hard_delete=hard_delete, force=force, db_path=db_path) + clear_cache() + if res.get("success"): + st.warning(f"처리했습니다. 사용 거래 {res.get('transaction_count', 0)}건") + st.rerun() + else: + st.error(res.get("error", res)) + + +def page_accounts(db_path: str) -> None: + st.header("🏦 계좌") + accounts = read_sql(db_path, "SELECT * FROM accounts ORDER BY created_at DESC") + if not accounts.empty: + accounts["last_balance_display"] = accounts["last_balance"].map(format_krw) + st.dataframe(accounts, width="stretch") + + +def page_imports(db_path: str) -> None: + st.header("📥 Import") + + st.subheader("토스증권 거래내역 PDF 가져오기") + st.caption("토스증권 거래내역서 PDF를 업로드하면 투자계좌 거래로 가져옵니다. 매수/매도/환전/입출금은 `이체/투자이동`, 배당/이자는 실제 수입으로 분류합니다.") + uploaded = st.file_uploader("토스증권 PDF", type=["pdf"], key="toss_pdf") + if uploaded is not None: + upload_dir = Path.home() / ".local" / "share" / "jarca" / "uploads" + upload_dir.mkdir(parents=True, exist_ok=True) + upload_path = upload_dir / uploaded.name + upload_path.write_bytes(uploaded.getbuffer()) + c1, c2 = st.columns(2) + if c1.button("토스증권 Preview"): + res = service.preview_toss_securities_pdf_import(str(upload_path), db_path=db_path) + st.session_state["toss_preview"] = res + if c2.button("토스증권 Import", type="primary"): + res = service.import_toss_securities_pdf(str(upload_path), db_path=db_path) + clear_cache() + st.session_state["toss_import_result"] = res + st.rerun() + if "toss_preview" in st.session_state: + res = st.session_state["toss_preview"] + if res.get("success"): + st.success(f"Preview: {res.get('row_count', 0)}건, 중복 {res.get('duplicate_count', 0)}건") + st.json({"metadata": res.get("metadata"), "by_action": res.get("by_action"), "validation": res.get("validation")}) + st.dataframe(pd.DataFrame(res.get("preview", [])), width="stretch", height=300) + else: + st.error(res) + if "toss_import_result" in st.session_state: + res = st.session_state["toss_import_result"] + if res.get("success"): + st.success(f"Import 완료: {res.get('inserted_count', 0)}건 추가, 중복 skip {res.get('skipped_duplicate_count', 0)}건") + st.json(res) + else: + st.error(res) + + st.divider() + st.subheader("토스뱅크 거래내역 PDF 가져오기") + st.caption("토스뱅크 계좌 거래내역 PDF를 업로드하면 입출금/이체/카드결제를 가져옵니다. 타인 이체/출금은 `이체/확인필요`로 분류됩니다.") + toss_bank_uploaded = st.file_uploader("토스뱅크 PDF", type=["pdf"], key="tossbank_pdf") + if toss_bank_uploaded is not None: + upload_dir = Path.home() / ".local" / "share" / "jarca" / "uploads" + upload_dir.mkdir(parents=True, exist_ok=True) + upload_path = upload_dir / toss_bank_uploaded.name + upload_path.write_bytes(toss_bank_uploaded.getbuffer()) + c1, c2 = st.columns(2) + if c1.button("토스뱅크 Preview"): + res = service.preview_toss_bank_pdf_import(str(upload_path), db_path=db_path) + st.session_state["toss_bank_preview"] = res + if c2.button("토스뱅크 Import", type="primary"): + res = service.import_toss_bank_pdf(str(upload_path), db_path=db_path) + clear_cache() + st.session_state["toss_bank_import_result"] = res + st.rerun() + if "toss_bank_preview" in st.session_state: + res = st.session_state["toss_bank_preview"] + if res.get("success"): + st.success(f"Preview: {res.get('row_count', 0)}건, 중복 {res.get('duplicate_count', 0)}건") + st.json({"metadata": res.get("metadata"), "by_action": res.get("by_action"), "validation": res.get("validation")}) + st.dataframe(pd.DataFrame(res.get("preview", [])), width="stretch", height=300) + else: + st.error(res) + if "toss_bank_import_result" in st.session_state: + res = st.session_state["toss_bank_import_result"] + if res.get("success"): + st.success(f"Import 완료: {res.get('inserted_count', 0)}건 추가, 중복 skip {res.get('skipped_duplicate_count', 0)}건") + st.json(res) + else: + st.error(res) + + st.divider() + st.subheader("Import 이력") + batches = service.list_ledger_import_batches(limit=100).get("import_batches", []) + st.dataframe(pd.DataFrame(batches), width="stretch", height=350) + if batches: + with st.form("rollback"): + batch_id = st.selectbox("Rollback batch", [b["id"] for b in batches]) + hard = st.checkbox("Hard delete", value=False) + submitted = st.form_submit_button("Rollback 실행", type="secondary") + if submitted: + res = service.rollback_ledger_import_batch(batch_id, hard_delete=hard) + clear_cache() + st.warning(res) + st.rerun() + + +def main() -> None: + db_path = get_db_path() + inject_sidebar_nav_css() + + pages = ["요약", "거래내역", "확인필요 큐", "미분류", "분류 규칙", "카테고리", "계좌", "Import"] + query_page = st.query_params.get("page", "요약") + page = query_page if query_page in pages else "요약" + st.session_state["page"] = page + + with st.sidebar: + st.markdown("## Jarca Ledger") + st.markdown('
메뉴
', unsafe_allow_html=True) + render_sidebar_nav(pages, page) + if st.button("새로고침", key="refresh_button", use_container_width=True): + clear_cache() + st.rerun() + + if page == "요약": + page_overview(db_path) + elif page == "거래내역": + page_transactions(db_path) + elif page == "확인필요 큐": + page_cross_transfer_review(db_path) + elif page == "미분류": + page_uncategorized(db_path) + elif page == "분류 규칙": + page_rules(db_path) + elif page == "카테고리": + page_categories(db_path) + elif page == "계좌": + page_accounts(db_path) + elif page == "Import": + page_imports(db_path) + + +if __name__ == "__main__": + main() diff --git a/jarca_ledger_mcp/__init__.py b/jarca_ledger_mcp/__init__.py new file mode 100644 index 0000000..1b71774 --- /dev/null +++ b/jarca_ledger_mcp/__init__.py @@ -0,0 +1,3 @@ +"""Jarca Ledger MCP server.""" + +__version__ = "0.1.0" diff --git a/jarca_ledger_mcp/db.py b/jarca_ledger_mcp/db.py new file mode 100644 index 0000000..dbc2d43 --- /dev/null +++ b/jarca_ledger_mcp/db.py @@ -0,0 +1,247 @@ +from __future__ import annotations + +import os +import sqlite3 +from contextlib import contextmanager +from pathlib import Path +from typing import Iterator + +DEFAULT_DB_PATH = Path.home() / ".local" / "share" / "jarca" / "ledger.sqlite3" +SCHEMA_VERSION = "6" + +SCHEMA_SQL = """ +PRAGMA journal_mode=WAL; +PRAGMA foreign_keys=ON; + +CREATE TABLE IF NOT EXISTS schema_meta ( + key TEXT PRIMARY KEY, + value TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS accounts ( + id TEXT PRIMARY KEY, + name TEXT NOT NULL, + type TEXT NOT NULL DEFAULT 'bank', + institution TEXT NOT NULL DEFAULT '', + currency TEXT NOT NULL DEFAULT 'KRW', + active INTEGER NOT NULL DEFAULT 1, + memo TEXT NOT NULL DEFAULT '', + account_number_masked TEXT NOT NULL DEFAULT '', + holder_name TEXT NOT NULL DEFAULT '', + last_balance INTEGER, + last_synced_at TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS transactions ( + id TEXT PRIMARY KEY, + transaction_date TEXT NOT NULL, + posted_date TEXT NOT NULL DEFAULT '', + type TEXT NOT NULL, + amount INTEGER NOT NULL, + currency TEXT NOT NULL DEFAULT 'KRW', + category TEXT NOT NULL DEFAULT '', + subcategory TEXT NOT NULL DEFAULT '', + merchant TEXT NOT NULL DEFAULT '', + description TEXT NOT NULL DEFAULT '', + account_id TEXT NOT NULL DEFAULT '', + payment_method TEXT NOT NULL DEFAULT '', + person TEXT NOT NULL DEFAULT '', + project TEXT NOT NULL DEFAULT '', + tags TEXT NOT NULL DEFAULT '[]', + is_fixed INTEGER NOT NULL DEFAULT 0, + source TEXT NOT NULL DEFAULT 'manual', + import_batch_id TEXT NOT NULL DEFAULT '', + external_id TEXT NOT NULL DEFAULT '', + dedupe_key TEXT NOT NULL DEFAULT '', + memo TEXT NOT NULL DEFAULT '', + status TEXT NOT NULL DEFAULT 'active', + transaction_datetime TEXT NOT NULL DEFAULT '', + counterparty TEXT NOT NULL DEFAULT '', + balance_after INTEGER, + branch TEXT NOT NULL DEFAULT '', + raw_summary TEXT NOT NULL DEFAULT '', + raw_payload TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL +); + +CREATE INDEX IF NOT EXISTS idx_transactions_date ON transactions(transaction_date); +CREATE INDEX IF NOT EXISTS idx_transactions_category ON transactions(category, subcategory); +CREATE INDEX IF NOT EXISTS idx_transactions_person ON transactions(person); +CREATE INDEX IF NOT EXISTS idx_transactions_account ON transactions(account_id); +CREATE UNIQUE INDEX IF NOT EXISTS idx_transactions_dedupe ON transactions(dedupe_key) WHERE dedupe_key <> ''; + +CREATE TABLE IF NOT EXISTS budgets ( + id TEXT PRIMARY KEY, + month TEXT NOT NULL, + category TEXT NOT NULL, + subcategory TEXT NOT NULL DEFAULT '', + person TEXT NOT NULL DEFAULT '', + amount INTEGER NOT NULL, + currency TEXT NOT NULL DEFAULT 'KRW', + memo TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL +); +CREATE INDEX IF NOT EXISTS idx_budgets_month ON budgets(month); +CREATE UNIQUE INDEX IF NOT EXISTS idx_budgets_unique ON budgets(month, category, subcategory, person); + +CREATE TABLE IF NOT EXISTS import_batches ( + id TEXT PRIMARY KEY, + source TEXT NOT NULL, + filename TEXT NOT NULL DEFAULT '', + imported_at TEXT NOT NULL, + row_count INTEGER NOT NULL DEFAULT 0, + status TEXT NOT NULL DEFAULT 'active', + memo TEXT NOT NULL DEFAULT '' +); + +CREATE TABLE IF NOT EXISTS category_rules ( + id TEXT PRIMARY KEY, + priority INTEGER NOT NULL DEFAULT 100, + match_field TEXT NOT NULL, + match_type TEXT NOT NULL DEFAULT 'contains', + pattern TEXT NOT NULL, + amount_min INTEGER, + amount_max INTEGER, + day_of_month INTEGER, + transaction_type TEXT NOT NULL DEFAULT '', + category TEXT NOT NULL, + subcategory TEXT NOT NULL DEFAULT '', + person TEXT NOT NULL DEFAULT '', + is_fixed INTEGER, + confidence REAL NOT NULL DEFAULT 1.0, + active INTEGER NOT NULL DEFAULT 1, + memo TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL +); +CREATE INDEX IF NOT EXISTS idx_category_rules_active_priority ON category_rules(active, priority); +CREATE UNIQUE INDEX IF NOT EXISTS idx_category_rules_unique ON category_rules(match_field, match_type, pattern, transaction_type, category, subcategory, person); + +CREATE TABLE IF NOT EXISTS ledger_categories ( + id TEXT PRIMARY KEY, + category TEXT NOT NULL, + subcategory TEXT NOT NULL DEFAULT '', + cashflow_kind TEXT NOT NULL DEFAULT 'expense', + active INTEGER NOT NULL DEFAULT 1, + sort_order INTEGER NOT NULL DEFAULT 100, + memo TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL +); +CREATE INDEX IF NOT EXISTS idx_ledger_categories_active_sort ON ledger_categories(active, sort_order, category, subcategory); +CREATE UNIQUE INDEX IF NOT EXISTS idx_ledger_categories_unique ON ledger_categories(category, subcategory); + +INSERT OR REPLACE INTO schema_meta(key, value) VALUES ('schema_version', '6'); +""" + +ACCOUNT_ADDITIVE_COLUMNS: dict[str, str] = { + "account_number_masked": "TEXT NOT NULL DEFAULT ''", + "holder_name": "TEXT NOT NULL DEFAULT ''", + "last_balance": "INTEGER", + "last_synced_at": "TEXT NOT NULL DEFAULT ''", +} + +TRANSACTION_ADDITIVE_COLUMNS: dict[str, str] = { + "transaction_datetime": "TEXT NOT NULL DEFAULT ''", + "counterparty": "TEXT NOT NULL DEFAULT ''", + "balance_after": "INTEGER", + "branch": "TEXT NOT NULL DEFAULT ''", + "raw_summary": "TEXT NOT NULL DEFAULT ''", + "raw_payload": "TEXT NOT NULL DEFAULT ''", +} + + +def resolve_db_path(db_path: str | None = None) -> Path: + raw = db_path or os.getenv("JARCA_LEDGER_DB_PATH") or str(DEFAULT_DB_PATH) + return Path(raw).expanduser().resolve() + + +def connect(db_path: str | None = None) -> sqlite3.Connection: + path = resolve_db_path(db_path) + path.parent.mkdir(parents=True, exist_ok=True) + conn = sqlite3.connect(path) + conn.row_factory = sqlite3.Row + conn.execute("PRAGMA foreign_keys=ON") + return conn + + +def _existing_columns(conn: sqlite3.Connection, table: str) -> set[str]: + return {row["name"] for row in conn.execute(f"PRAGMA table_info({table})")} + + +def _add_missing_columns(conn: sqlite3.Connection, table: str, columns: dict[str, str]) -> None: + existing = _existing_columns(conn, table) + for name, definition in columns.items(): + if name not in existing: + conn.execute(f"ALTER TABLE {table} ADD COLUMN {name} {definition}") + + +def migrate_db(conn: sqlite3.Connection) -> None: + """Apply additive, idempotent migrations only.""" + _add_missing_columns(conn, "accounts", ACCOUNT_ADDITIVE_COLUMNS) + _add_missing_columns(conn, "transactions", TRANSACTION_ADDITIVE_COLUMNS) + conn.execute("CREATE INDEX IF NOT EXISTS idx_transactions_datetime ON transactions(transaction_datetime)") + conn.execute("""CREATE TABLE IF NOT EXISTS category_rules ( + id TEXT PRIMARY KEY, + priority INTEGER NOT NULL DEFAULT 100, + match_field TEXT NOT NULL, + match_type TEXT NOT NULL DEFAULT 'contains', + pattern TEXT NOT NULL, + amount_min INTEGER, + amount_max INTEGER, + day_of_month INTEGER, + transaction_type TEXT NOT NULL DEFAULT '', + category TEXT NOT NULL, + subcategory TEXT NOT NULL DEFAULT '', + person TEXT NOT NULL DEFAULT '', + is_fixed INTEGER, + confidence REAL NOT NULL DEFAULT 1.0, + active INTEGER NOT NULL DEFAULT 1, + memo TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL + )""") + _add_missing_columns(conn, "category_rules", {"amount_min": "INTEGER", "amount_max": "INTEGER", "day_of_month": "INTEGER"}) + conn.execute("CREATE INDEX IF NOT EXISTS idx_category_rules_active_priority ON category_rules(active, priority)") + conn.execute("CREATE UNIQUE INDEX IF NOT EXISTS idx_category_rules_unique ON category_rules(match_field, match_type, pattern, transaction_type, category, subcategory, person)") + conn.execute("""CREATE TABLE IF NOT EXISTS ledger_categories ( + id TEXT PRIMARY KEY, + category TEXT NOT NULL, + subcategory TEXT NOT NULL DEFAULT '', + cashflow_kind TEXT NOT NULL DEFAULT 'expense', + active INTEGER NOT NULL DEFAULT 1, + sort_order INTEGER NOT NULL DEFAULT 100, + memo TEXT NOT NULL DEFAULT '', + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL + )""") + _add_missing_columns(conn, "ledger_categories", {"cashflow_kind": "TEXT NOT NULL DEFAULT 'expense'"}) + conn.execute("CREATE INDEX IF NOT EXISTS idx_ledger_categories_active_sort ON ledger_categories(active, sort_order, category, subcategory)") + conn.execute("CREATE UNIQUE INDEX IF NOT EXISTS idx_ledger_categories_unique ON ledger_categories(category, subcategory)") + conn.execute("INSERT OR REPLACE INTO schema_meta(key, value) VALUES ('schema_version', ?)", (SCHEMA_VERSION,)) + + +def init_db(db_path: str | None = None) -> str: + path = resolve_db_path(db_path) + with connect(str(path)) as conn: + conn.executescript(SCHEMA_SQL) + migrate_db(conn) + return str(path) + + +@contextmanager +def db(db_path: str | None = None) -> Iterator[sqlite3.Connection]: + init_db(db_path) + conn = connect(db_path) + try: + yield conn + conn.commit() + except Exception: + conn.rollback() + raise + finally: + conn.close() diff --git a/jarca_ledger_mcp/kb_bank_pdf.py b/jarca_ledger_mcp/kb_bank_pdf.py new file mode 100644 index 0000000..27fab2d --- /dev/null +++ b/jarca_ledger_mcp/kb_bank_pdf.py @@ -0,0 +1,250 @@ +from __future__ import annotations + +import hashlib +import json +import re +from dataclasses import dataclass +from datetime import datetime +from pathlib import Path +from typing import Any + +try: + import fitz # PyMuPDF +except ImportError: # pragma: no cover - exercised as runtime config error + fitz = None # type: ignore[assignment] + + +@dataclass(frozen=True) +class KbPdfTransaction: + page: int + transaction_datetime: str + transaction_date: str + raw_summary: str + counterparty: str + withdrawal: int + deposit: int + balance_after: int + remittance_memo: str + branch: str + + @property + def type(self) -> str: + if self.deposit > 0 and self.withdrawal == 0: + return "income" + if self.withdrawal > 0 and self.deposit == 0: + return "expense" + return "adjustment" + + @property + def amount(self) -> int: + return self.deposit or self.withdrawal + + def external_id(self, source_hash: str) -> str: + raw = "|".join( + [ + "kb_bank_pdf", + source_hash[:16], + self.transaction_datetime, + self.raw_summary, + self.counterparty, + str(self.withdrawal), + str(self.deposit), + str(self.balance_after), + ] + ) + return hashlib.sha256(raw.encode("utf-8")).hexdigest() + + def raw_payload(self) -> str: + return json.dumps( + { + "page": self.page, + "transaction_datetime": self.transaction_datetime, + "raw_summary": self.raw_summary, + "counterparty": self.counterparty, + "withdrawal": self.withdrawal, + "deposit": self.deposit, + "balance_after": self.balance_after, + "remittance_memo": self.remittance_memo, + "branch": self.branch, + }, + ensure_ascii=False, + separators=(",", ":"), + ) + + +def _parse_int(value: str) -> int: + value = value.replace(",", "").replace("원", "").strip() + return int(value) if value and re.fullmatch(r"-?\d+", value) else 0 + + +def _mask_account_number(account_number: str) -> str: + digits = re.sub(r"\D", "", account_number) + if len(digits) <= 4: + return f"****{digits}" if digits else "" + return f"****{digits[-4:]}" + + +def _extract_metadata(first_page_text: str) -> dict[str, Any]: + lines = [line.strip() for line in first_page_text.splitlines() if line.strip()] + + def after_label(label: str) -> str: + try: + return lines[lines.index(label) + 1] + except (ValueError, IndexError): + return "" + + account_number = after_label("계좌번호") + query_period = "" + for line in lines: + if re.fullmatch(r"\d{4}\.\d{2}\.\d{2}\s+~\s+\d{4}\.\d{2}\.\d{2}", line): + query_period = line + break + query_generated_at = "" + for line in lines: + if line.startswith("조회기준일시:"): + query_generated_at = line.replace("조회기준일시:", "").strip() + break + return { + "account_name": after_label("계좌명"), + "account_number_masked": _mask_account_number(account_number), + "holder_name": after_label("예금주"), + "final_balance": _parse_int(after_label("총 잔액")), + "withdrawable_amount": _parse_int(after_label("출금가능금액")), + "header_total_deposit": _parse_int(after_label("총 입금금액")), + "header_total_withdrawal": _parse_int(after_label("총 출금금액")), + "query_generated_at": query_generated_at, + "query_period": query_period, + } + + +def _open_pdf(path: Path, password: str) -> Any: + if fitz is None: + raise RuntimeError("PyMuPDF is required. Install pymupdf to parse KB Bank PDFs.") + doc = fitz.open(path) + if doc.needs_pass and not doc.authenticate(password): + raise ValueError("PDF password is required or incorrect") + return doc + + +def parse_kb_bank_pdf(file_path: str, password: str) -> dict[str, Any]: + path = Path(file_path).expanduser().resolve() + if not path.exists(): + raise FileNotFoundError(f"PDF file not found: {path}") + source_hash = hashlib.sha256(path.read_bytes()).hexdigest() + doc = _open_pdf(path, password) + metadata = _extract_metadata(doc[0].get_text("text") if doc.page_count else "") + columns = [ + ("datetime", 0, 115), + ("summary", 115, 165), + ("counterparty", 165, 255), + ("withdrawal", 255, 315), + ("deposit", 315, 375), + ("balance", 375, 450), + ("memo", 450, 520), + ("branch", 520, 999), + ] + transactions: list[KbPdfTransaction] = [] + for page_index, page in enumerate(doc, start=1): + lines: dict[int, list[tuple[float, str]]] = {} + for x0, y0, _x1, _y1, word, _block, _line, _wordno in page.get_text("words"): + # Header rows live above 110. Footer/help text lives below roughly 735. + if y0 < 110 or y0 > 735: + continue + key = round(y0 / 3) * 3 + lines.setdefault(key, []).append((x0, word)) + for y in sorted(lines): + cells: dict[str, list[str]] = {name: [] for name, _start, _end in columns} + for x, word in sorted(lines[y]): + for name, start, end in columns: + if start <= x < end: + cells[name].append(word) + break + values = {key: " ".join(parts).strip() for key, parts in cells.items()} + raw_datetime = values["datetime"] + if not re.fullmatch(r"20\d{2}\.\d{2}\.\d{2}\s+\d{2}:\d{2}:\d{2}", raw_datetime): + continue + dt = datetime.strptime(raw_datetime, "%Y.%m.%d %H:%M:%S") + transactions.append( + KbPdfTransaction( + page=page_index, + transaction_datetime=dt.isoformat(), + transaction_date=dt.date().isoformat(), + raw_summary=values["summary"], + counterparty=values["counterparty"], + withdrawal=_parse_int(values["withdrawal"]), + deposit=_parse_int(values["deposit"]), + balance_after=_parse_int(values["balance"]), + remittance_memo=values["memo"], + branch=values["branch"], + ) + ) + validation = validate_balance_flow(transactions) + return { + "file_path": str(path), + "source_hash": source_hash, + "page_count": doc.page_count, + "metadata": metadata, + "transactions": transactions, + "validation": validation, + } + + +def validate_balance_flow(transactions: list[KbPdfTransaction]) -> dict[str, Any]: + if not transactions: + return { + "ok": True, + "row_count": 0, + "opening_balance": None, + "final_balance": None, + "total_deposit": 0, + "total_withdrawal": 0, + "net_change": 0, + "errors": [], + } + opening_balance = transactions[0].balance_after + transactions[0].withdrawal - transactions[0].deposit + previous_balance = opening_balance + errors = [] + total_deposit = 0 + total_withdrawal = 0 + for index, tx in enumerate(transactions, start=1): + expected = previous_balance - tx.withdrawal + tx.deposit + if expected != tx.balance_after: + errors.append( + { + "row_number": index, + "transaction_datetime": tx.transaction_datetime, + "expected_balance": expected, + "actual_balance": tx.balance_after, + "difference": tx.balance_after - expected, + } + ) + previous_balance = tx.balance_after + total_deposit += tx.deposit + total_withdrawal += tx.withdrawal + final_balance = transactions[-1].balance_after + return { + "ok": not errors, + "row_count": len(transactions), + "opening_balance": opening_balance, + "final_balance": final_balance, + "total_deposit": total_deposit, + "total_withdrawal": total_withdrawal, + "net_change": total_deposit - total_withdrawal, + "balance_delta": final_balance - opening_balance, + "errors": errors, + } + + +def transaction_preview(tx: KbPdfTransaction, source_hash: str) -> dict[str, Any]: + return { + "transaction_datetime": tx.transaction_datetime, + "transaction_date": tx.transaction_date, + "type": tx.type, + "amount": tx.amount, + "merchant": tx.counterparty, + "payment_method": tx.raw_summary, + "balance_after": tx.balance_after, + "branch": tx.branch, + "memo": tx.remittance_memo, + "external_id": tx.external_id(source_hash), + } diff --git a/jarca_ledger_mcp/seoulpay_xlsx.py b/jarca_ledger_mcp/seoulpay_xlsx.py new file mode 100644 index 0000000..e6d6806 --- /dev/null +++ b/jarca_ledger_mcp/seoulpay_xlsx.py @@ -0,0 +1,215 @@ +from __future__ import annotations + +import hashlib +import io +from dataclasses import dataclass +from datetime import datetime +from pathlib import Path +from typing import Any + + +@dataclass(frozen=True) +class SeoulPayTransaction: + row_index: int + channel: str + transaction_no: str + transaction_datetime: str + transaction_date: str + merchant: str + business_no: str + merchant_id: str + transaction_kind: str + payment_kind: str + amount: int + supply_amount: int + service_fee: int + vat: int + tax_status: str + + @property + def type(self) -> str: + text = f"{self.transaction_kind} {self.payment_kind}" + if any(keyword in text for keyword in ("취소", "환불", "승인취소")): + return "refund" + return "expense" + + def external_id(self, source_hash: str) -> str: + base = self.transaction_no or f"{self.transaction_datetime}:{self.merchant}:{self.amount}:{self.row_index}" + return f"seoulpay_xlsx:{source_hash}:{base}" + + def raw_payload(self) -> str: + import json + + return json.dumps( + { + "row_index": self.row_index, + "channel": self.channel, + "transaction_no": self.transaction_no, + "transaction_datetime": self.transaction_datetime, + "merchant": self.merchant, + "business_no": self.business_no, + "merchant_id": self.merchant_id, + "transaction_kind": self.transaction_kind, + "payment_kind": self.payment_kind, + "amount": self.amount, + "supply_amount": self.supply_amount, + "service_fee": self.service_fee, + "vat": self.vat, + "tax_status": self.tax_status, + }, + ensure_ascii=False, + ) + + +def _cell_text(value: Any) -> str: + if value is None: + return "" + return str(value).strip() + + +def _amount(value: Any) -> int: + if value is None or value == "": + return 0 + if isinstance(value, (int, float)): + return int(round(float(value))) + text = str(value).replace(",", "").strip() + if not text: + return 0 + return int(round(float(text))) + + +def _datetime_text(value: Any) -> tuple[str, str]: + if isinstance(value, datetime): + dt = value.replace(microsecond=0) + return dt.isoformat(sep=" "), dt.date().isoformat() + text = _cell_text(value) + if not text: + raise ValueError("결제일 is required") + for fmt in ("%Y-%m-%d %H:%M:%S", "%Y.%m.%d %H:%M:%S", "%Y/%m/%d %H:%M:%S"): + try: + dt = datetime.strptime(text, fmt) + return dt.isoformat(sep=" "), dt.date().isoformat() + except ValueError: + pass + # Excel sometimes returns an ISO-ish string; keep date if it is already first 10 chars. + if len(text) >= 10: + return text, text[:10].replace(".", "-").replace("/", "-") + raise ValueError(f"unsupported 결제일 format: {text}") + + +def _load_workbook(file_path: str, password: str = ""): + try: + import openpyxl + except ImportError as e: # pragma: no cover - environment guard + raise RuntimeError("openpyxl is required to parse SeoulPay XLSX files") from e + + path = Path(file_path) + data = path.read_bytes() + try: + return openpyxl.load_workbook(io.BytesIO(data), data_only=True) + except Exception as plain_error: + if not password: + raise ValueError("서울페이 XLSX 파일이 암호화되어 있습니다. password가 필요합니다.") from plain_error + try: + import msoffcrypto + except ImportError as e: # pragma: no cover - environment guard + raise RuntimeError("msoffcrypto-tool is required to decrypt password-protected SeoulPay files") from e + try: + office = msoffcrypto.OfficeFile(io.BytesIO(data)) + office.load_key(password=password) + decrypted = io.BytesIO() + office.decrypt(decrypted) + decrypted.seek(0) + return openpyxl.load_workbook(decrypted, data_only=True) + except Exception as e: + raise ValueError(f"서울페이 XLSX 복호화/파싱 실패: {e}") from e + + +def parse_seoulpay_xlsx(file_path: str, password: str = "") -> dict[str, Any]: + path = Path(file_path) + if not path.exists(): + raise FileNotFoundError(str(path)) + source_hash = hashlib.sha256(path.read_bytes()).hexdigest() + wb = _load_workbook(str(path), password=password) + ws = wb[wb.sheetnames[0]] + + metadata: dict[str, Any] = {"source": "seoulpay_xlsx"} + header_row = None + headers: list[str] = [] + for idx, row in enumerate(ws.iter_rows(values_only=True), start=1): + first = _cell_text(row[0] if row else None) + second = _cell_text(row[1] if row and len(row) > 1 else None) + if first == "성명": + metadata["holder_name"] = second + elif first == "생년월일": + metadata["birth_date_masked"] = "********" if second else "" + elif first == "조회기간": + metadata["period"] = second + if "거래번호" in [_cell_text(v) for v in row] and "결제일" in [_cell_text(v) for v in row]: + header_row = idx + headers = [_cell_text(v) for v in row] + break + if header_row is None: + raise ValueError("서울페이 이용내역 헤더를 찾을 수 없습니다") + + index = {name: i for i, name in enumerate(headers) if name} + required = ["결제채널", "거래번호", "결제일", "가맹점", "거래유형", "결제구분", "거래금액"] + missing = [name for name in required if name not in index] + if missing: + raise ValueError(f"서울페이 필수 컬럼 누락: {', '.join(missing)}") + + transactions: list[SeoulPayTransaction] = [] + errors: list[str] = [] + for row_index in range(header_row + 1, ws.max_row + 1): + values = [cell.value for cell in ws[row_index]] + if not any(v not in (None, "") for v in values): + continue + try: + tx_dt, tx_date = _datetime_text(values[index["결제일"]]) + tx = SeoulPayTransaction( + row_index=row_index, + channel=_cell_text(values[index["결제채널"]]), + transaction_no=_cell_text(values[index["거래번호"]]), + transaction_datetime=tx_dt, + transaction_date=tx_date, + merchant=_cell_text(values[index["가맹점"]]), + business_no=_cell_text(values[index.get("사업자번호", -1)]) if "사업자번호" in index else "", + merchant_id=_cell_text(values[index.get("가맹점ID", -1)]) if "가맹점ID" in index else "", + transaction_kind=_cell_text(values[index["거래유형"]]), + payment_kind=_cell_text(values[index["결제구분"]]), + amount=_amount(values[index["거래금액"]]), + supply_amount=_amount(values[index.get("공급가액", -1)]) if "공급가액" in index else 0, + service_fee=_amount(values[index.get("봉사료", -1)]) if "봉사료" in index else 0, + vat=_amount(values[index.get("부가세", -1)]) if "부가세" in index else 0, + tax_status=_cell_text(values[index.get("과세여부", -1)]) if "과세여부" in index else "", + ) + if tx.amount <= 0: + raise ValueError("거래금액이 0 이하입니다") + transactions.append(tx) + except Exception as e: + errors.append(f"row {row_index}: {e}") + + return { + "file_path": str(path), + "source_hash": source_hash, + "sheet_name": ws.title, + "metadata": metadata, + "transactions": transactions, + "validation": {"ok": bool(transactions) and not errors, "parsed_rows": len(transactions), "errors": errors}, + } + + +def transaction_preview(tx: SeoulPayTransaction, source_hash: str) -> dict[str, Any]: + return { + "transaction_datetime": tx.transaction_datetime, + "transaction_date": tx.transaction_date, + "type": tx.type, + "channel": tx.channel, + "transaction_no": tx.transaction_no, + "merchant": tx.merchant, + "transaction_kind": tx.transaction_kind, + "payment_kind": tx.payment_kind, + "amount": tx.amount, + "tax_status": tx.tax_status, + "external_id": tx.external_id(source_hash), + } diff --git a/jarca_ledger_mcp/server.py b/jarca_ledger_mcp/server.py new file mode 100644 index 0000000..ea438c6 --- /dev/null +++ b/jarca_ledger_mcp/server.py @@ -0,0 +1,216 @@ +from __future__ import annotations + +from pathlib import Path +from dotenv import load_dotenv +from mcp.server.fastmcp import FastMCP + +from . import service + +load_dotenv(Path(__file__).resolve().parent.parent / ".env") +mcp = FastMCP("jarca-ledger-mcp") + +@mcp.tool() +def ledger_health_check() -> dict: + """Verify the Jarca Ledger MCP server and SQLite database are reachable.""" + return service.health_check() + +@mcp.tool() +def create_ledger_account(name: str, type: str = "bank", institution: str = "", currency: str = "KRW", active: bool = True, memo: str = "", account_number_masked: str = "", holder_name: str = "", last_balance: int | None = None, last_synced_at: str = "") -> dict: + """Create an account/card/cash/investment/loan ledger account.""" + return service.create_ledger_account(name, type, institution, currency, active, memo, account_number_masked, holder_name, last_balance, last_synced_at) + +@mcp.tool() +def list_ledger_accounts(active_only: bool = True) -> dict: + """List ledger accounts and cards.""" + return service.list_ledger_accounts(active_only) + +@mcp.tool() +def create_ledger_transaction(transaction_date: str = "", type: str = "expense", amount: int = 0, category: str = "", subcategory: str = "", merchant: str = "", description: str = "", account_id: str = "", payment_method: str = "", person: str = "", project: str = "", tags: list[str] | str | None = None, is_fixed: bool = False, currency: str = "KRW", posted_date: str = "", source: str = "manual", external_id: str = "", memo: str = "", dedupe: bool = True) -> dict: + """Create an income, expense, transfer, refund, or adjustment transaction. Amount is positive KRW minor unit; type determines direction.""" + return service.create_ledger_transaction(transaction_date, type, amount, category, subcategory, merchant, description, account_id, payment_method, person, project, tags, is_fixed, currency, posted_date, source, external_id, memo, dedupe) + +@mcp.tool() +def list_ledger_transactions(start_date: str = "", end_date: str = "", type: str = "", category: str = "", person: str = "", account_id: str = "", include_deleted: bool = False, limit: int = 100) -> dict: + """List ledger transactions with date/category/person/account filters.""" + return service.list_ledger_transactions(start_date, end_date, type, category, person, account_id, include_deleted, limit) + +@mcp.tool() +def update_ledger_transaction(transaction_id: str, transaction_date: str | None = None, type: str | None = None, amount: int | None = None, category: str | None = None, subcategory: str | None = None, merchant: str | None = None, description: str | None = None, account_id: str | None = None, payment_method: str | None = None, person: str | None = None, project: str | None = None, tags: list[str] | str | None = None, is_fixed: bool | None = None, memo: str | None = None, status: str | None = None) -> dict: + """Update selected fields on a ledger transaction.""" + return service.update_ledger_transaction(transaction_id, transaction_date=transaction_date, type=type, amount=amount, category=category, subcategory=subcategory, merchant=merchant, description=description, account_id=account_id, payment_method=payment_method, person=person, project=project, tags=tags, is_fixed=is_fixed, memo=memo, status=status) + +@mcp.tool() +def delete_ledger_transaction(transaction_id: str, hard_delete: bool = False) -> dict: + """Soft-delete a ledger transaction by default, or permanently delete with hard_delete=true.""" + return service.delete_ledger_transaction(transaction_id, hard_delete) + +@mcp.tool() +def create_ledger_budget(month: str, category: str, amount: int, subcategory: str = "", person: str = "", currency: str = "KRW", memo: str = "") -> dict: + """Create or update a monthly category/person budget.""" + return service.create_ledger_budget(month, category, amount, subcategory, person, currency, memo) + +@mcp.tool() +def list_ledger_budgets(month: str = "") -> dict: + """List ledger budgets, optionally for a month YYYY-MM.""" + return service.list_ledger_budgets(month) + +@mcp.tool() +def get_monthly_cashflow_report(month: str = "") -> dict: + """Return income, expenses, net cashflow, and savings rate for a month.""" + return service.get_monthly_cashflow_report(month) + +@mcp.tool() +def get_category_spending_report(month: str = "", start_date: str = "", end_date: str = "", person: str = "") -> dict: + """Return category/subcategory spending for a month or date range.""" + return service.get_category_spending_report(month, start_date, end_date, person) + +@mcp.tool() +def get_fixed_cost_report(month: str = "") -> dict: + """Return fixed expense transactions and total fixed cost for a month.""" + return service.get_fixed_cost_report(month) + +@mcp.tool() +def get_budget_vs_actual_report(month: str = "") -> dict: + """Compare monthly budgets against actual spending.""" + return service.get_budget_vs_actual_report(month) + +@mcp.tool() +def get_investable_cashflow_report(month: str = "", minimum_cash_buffer: int = 0, planned_extra_expense: int = 0) -> dict: + """Estimate cashflow available for investing after buffer and planned extra expenses.""" + return service.get_investable_cashflow_report(month, minimum_cash_buffer, planned_extra_expense) + +@mcp.tool() +def preview_ledger_csv_import(file_path: str, source: str = "generic") -> dict: + """Preview a UTF-8/UTF-8-BOM CSV import before saving transactions.""" + return service.preview_ledger_csv_import(file_path, source) + +@mcp.tool() +def preview_kb_bank_pdf_import(file_path: str, password: str, preview_limit: int = 20) -> dict: + """Preview transactions from a password-protected KB Kookmin Bank account-history PDF without saving them.""" + return service.preview_kb_bank_pdf_import(file_path, password, preview_limit) + +@mcp.tool() +def import_kb_bank_pdf(file_path: str, password: str, account_id: str = "", skip_duplicates: bool = True, skip_validation: bool = False) -> dict: + """Import transactions from a KB Kookmin Bank account-history PDF into the ledger database.""" + return service.import_kb_bank_pdf(file_path, password, account_id, skip_duplicates, skip_validation=skip_validation) + +@mcp.tool() +def preview_seoulpay_xlsx_import(file_path: str, password: str = "", preview_limit: int = 20) -> dict: + """Preview transactions from a SeoulPay usage-history XLSX before saving them.""" + return service.preview_seoulpay_xlsx_import(file_path, password, preview_limit) + +@mcp.tool() +def import_seoulpay_xlsx(file_path: str, password: str = "", account_id: str = "", skip_duplicates: bool = True) -> dict: + """Import transactions from a SeoulPay usage-history XLSX into the ledger database.""" + return service.import_seoulpay_xlsx(file_path, password, account_id, skip_duplicates) + +@mcp.tool() +def preview_toss_securities_pdf_import(file_path: str, preview_limit: int = 20) -> dict: + """Preview transactions from a Toss Securities transaction-history PDF without saving them.""" + return service.preview_toss_securities_pdf_import(file_path, preview_limit) + +@mcp.tool() +def import_toss_securities_pdf(file_path: str, account_id: str = "", skip_duplicates: bool = True) -> dict: + """Import transactions from a Toss Securities transaction-history PDF into the ledger database.""" + return service.import_toss_securities_pdf(file_path, account_id, skip_duplicates) + +@mcp.tool() +def preview_toss_bank_pdf_import(file_path: str, preview_limit: int = 20) -> dict: + """Preview transactions from a Toss Bank transaction-history PDF without saving them.""" + return service.preview_toss_bank_pdf_import(file_path, preview_limit) + +@mcp.tool() +def import_toss_bank_pdf(file_path: str, account_id: str = "", skip_duplicates: bool = True) -> dict: + """Import transactions from a Toss Bank transaction-history PDF into the ledger database.""" + return service.import_toss_bank_pdf(file_path, account_id, skip_duplicates) + +@mcp.tool() +def list_ledger_import_batches(source: str = "", include_rolled_back: bool = True, limit: int = 50) -> dict: + """List CSV/PDF/API import batches.""" + return service.list_ledger_import_batches(source, include_rolled_back, limit) + +@mcp.tool() +def rollback_ledger_import_batch(import_batch_id: str, hard_delete: bool = False) -> dict: + """Roll back all transactions created by one import batch. Soft-deletes by default.""" + return service.rollback_ledger_import_batch(import_batch_id, hard_delete) + +@mcp.tool() +def create_category_rule(match_field: str, pattern: str, category: str, subcategory: str = "", transaction_type: str = "", match_type: str = "contains", priority: int = 100, person: str = "", is_fixed: bool | None = None, confidence: float = 1.0, memo: str = "", amount_min: int | None = None, amount_max: int | None = None, day_of_month: int | None = None) -> dict: + """Create or update a ledger transaction categorization rule.""" + return service.create_category_rule(match_field, pattern, category, subcategory, transaction_type, match_type, priority, person, is_fixed, confidence, memo, amount_min, amount_max, day_of_month) + +@mcp.tool() +def seed_default_category_rules(overwrite: bool = False) -> dict: + """Seed default Jarca category rules for common Korean household ledger patterns.""" + return service.seed_default_category_rules(overwrite) + +@mcp.tool() +def list_category_rules(active_only: bool = True) -> dict: + """List transaction categorization rules.""" + return service.list_category_rules(active_only) + +@mcp.tool() +def update_category_rule(rule_id: str, match_field: str, pattern: str, category: str, subcategory: str = "", transaction_type: str = "", match_type: str = "contains", priority: int = 100, person: str = "", is_fixed: bool | None = None, confidence: float = 1.0, memo: str = "", amount_min: int | None = None, amount_max: int | None = None, day_of_month: int | None = None, active: bool = True) -> dict: + """Update an existing ledger transaction categorization rule.""" + return service.update_category_rule(rule_id, match_field, pattern, category, subcategory, transaction_type, match_type, priority, person, is_fixed, confidence, memo, amount_min, amount_max, day_of_month, active) + +@mcp.tool() +def preview_categorization(limit: int = 1000, only_uncategorized: bool = True) -> dict: + """Preview category-rule matches before writing categories to transactions.""" + return service.preview_categorization(limit, only_uncategorized) + +@mcp.tool() +def apply_categorization_rules(limit: int = 1000, only_uncategorized: bool = True) -> dict: + """Apply active category rules to matching ledger transactions.""" + return service.apply_categorization_rules(limit, only_uncategorized) + +@mcp.tool() +def list_uncategorized_transactions(limit: int = 100, min_amount: int = 0) -> dict: + """List active transactions that still have no category.""" + return service.list_uncategorized_transactions(limit, min_amount) + +@mcp.tool() +def get_uncategorized_merchant_summary(limit: int = 50) -> dict: + """Summarize uncategorized transactions by merchant/raw_summary/type for user review.""" + return service.get_uncategorized_merchant_summary(limit) + +@mcp.tool() +def create_ledger_category(category: str, subcategory: str = "", sort_order: int = 100, memo: str = "", cashflow_kind: str = "") -> dict: + """Create or reactivate a ledger category/subcategory used by the dashboard and transactions.""" + return service.create_ledger_category(category, subcategory, sort_order, memo, cashflow_kind) + +@mcp.tool() +def seed_default_ledger_categories(overwrite: bool = False) -> dict: + """Seed default ledger categories and subcategories.""" + return service.seed_default_ledger_categories(overwrite) + +@mcp.tool() +def list_ledger_categories(active_only: bool = True, include_usage: bool = True) -> dict: + """List ledger categories and subcategories, optionally with usage counts.""" + return service.list_ledger_categories(active_only, include_usage) + +@mcp.tool() +def list_cross_transfer_review_queue(limit: int = 300) -> dict: + """List KB↔토스 계좌 이체 확인필요 큐 항목.""" + return service.list_cross_transfer_review_queue(limit) + +@mcp.tool() +def preview_cross_account_transfers(limit: int = 500) -> dict: + """Preview KB↔토스은행 이체 매칭 후보를 반환합니다.""" + return service.preview_cross_account_transfers(limit) + +@mcp.tool() +def run_cross_account_transfer_match(limit: int = 500) -> dict: + """Run KB↔토스은행 자동 이체 매칭 및 태그/분류 반영을 수행합니다.""" + return service.run_cross_account_transfer_match(limit) + +@mcp.tool() +def delete_ledger_category(category: str, subcategory: str = "", hard_delete: bool = False, force: bool = False) -> dict: + """Deactivate or delete a ledger category/subcategory.""" + return service.delete_ledger_category(category, subcategory, hard_delete, force) + +def main() -> None: + mcp.run() + +if __name__ == "__main__": + main() diff --git a/jarca_ledger_mcp/service.py b/jarca_ledger_mcp/service.py new file mode 100644 index 0000000..a56d8e2 --- /dev/null +++ b/jarca_ledger_mcp/service.py @@ -0,0 +1,2250 @@ +from __future__ import annotations + +import csv +import hashlib +import json +import re +from datetime import date, datetime +from pathlib import Path +from typing import Any +from uuid import uuid4 + +from .db import db, init_db, resolve_db_path +from .kb_bank_pdf import parse_kb_bank_pdf, transaction_preview +from .toss_bank_pdf import parse_toss_bank_pdf, transaction_preview as toss_bank_transaction_preview +from .toss_securities_pdf import parse_toss_securities_pdf, transaction_preview as toss_transaction_preview +from .seoulpay_xlsx import parse_seoulpay_xlsx, transaction_preview as seoulpay_transaction_preview + +VALID_TRANSACTION_TYPES = {"income", "expense", "transfer", "refund", "adjustment"} +VALID_ACCOUNT_TYPES = {"bank", "card", "cash", "investment", "loan", "other"} +VALID_CASHFLOW_KINDS = {"income", "expense", "transfer", "investment", "debt_payment", "exclude", "unknown"} +CASHFLOW_KIND_SQL = """COALESCE(lc.cashflow_kind, CASE + WHEN t.category='수입' THEN 'income' + WHEN t.category='이체' AND t.subcategory='투자이동' THEN 'investment' + WHEN t.category='이체' THEN 'transfer' + WHEN t.category='금융' AND t.subcategory='대출상환' THEN 'debt_payment' + WHEN t.category='금융' THEN 'exclude' + WHEN t.category='미분류' THEN 'unknown' + WHEN COALESCE(t.category, '')='' THEN 'unknown' + ELSE 'expense' +END)""" + +CROSS_TRANSFER_MATCH_TAG = "cross_transfer_match:" +CROSS_TRANSFER_REVIEW_TAG = "cross_transfer_review:" + + +def _normalize_counterparty_for_match(value: str) -> str: + if not value: + return "" + # normalize party names for fuzzy matching across KB/토스뱅크 records + normalized = re.sub(r"\\([^)]*\\)", "", value) + normalized = normalized.lower().strip() + normalized = normalized.replace("토스뱅크", "").replace("토스", "") + normalized = normalized.replace("kb", "").replace("국민은행", "") + normalized = re.sub(r"\\s+", "", normalized) + normalized = re.sub(r"[^0-9가-힣a-zA-Z]", "", normalized) + return normalized + + +def _party_match_score(left: str, right: str) -> int: + left_norm = _normalize_counterparty_for_match(left) + right_norm = _normalize_counterparty_for_match(right) + if not left_norm or not right_norm: + return 0 + if left_norm == right_norm: + return 2 + if left_norm in right_norm or right_norm in left_norm: + return 1 + return 0 + + +def _append_memo_tag(raw_memo: str, tag: str) -> str: + memo = (raw_memo or "").strip() + if not memo: + return tag + if tag in memo: + return memo + return f"{memo}; {tag}" + + +def _memo_has_tag(raw_memo: str, tag_prefix: str) -> bool: + memo = (raw_memo or "").strip() + return tag_prefix in memo + + +def now_iso() -> str: + return datetime.now().replace(microsecond=0).isoformat() + +def new_id(prefix: str) -> str: + return f"{prefix}_{uuid4().hex[:12]}" + +def ok(**data: Any) -> dict[str, Any]: + return {"success": True, **data} + +def fail(error_code: str, message: str, **data: Any) -> dict[str, Any]: + return {"success": False, "error_code": error_code, "error": message, **data} + +def row_to_dict(row: Any) -> dict[str, Any]: + d = dict(row) + if "tags" in d: + try: + d["tags"] = json.loads(d["tags"] or "[]") + except json.JSONDecodeError: + d["tags"] = [] + for k in ("active", "is_fixed"): + if k in d: + d[k] = bool(d[k]) + return d + +def normalize_date(value: str | None, default_today: bool = False) -> str: + if not value: + if default_today: + return date.today().isoformat() + raise ValueError("date is required") + return date.fromisoformat(value[:10]).isoformat() + +def normalize_month(value: str | None) -> str: + if not value: + return date.today().strftime("%Y-%m") + if re.fullmatch(r"\d{4}-\d{2}", value): + return value + return date.fromisoformat(value[:10]).strftime("%Y-%m") + +def normalize_tags(tags: Any) -> str: + if tags is None or tags == "": + return "[]" + if isinstance(tags, str): + parts = [p.strip() for p in re.split(r"[,#]", tags) if p.strip()] + return json.dumps(parts, ensure_ascii=False) + if isinstance(tags, list): + return json.dumps([str(x).strip() for x in tags if str(x).strip()], ensure_ascii=False) + raise ValueError("tags must be a list or comma-separated string") + +def make_dedupe_key(transaction_date: str, amount: int, merchant: str = "", account_id: str = "", external_id: str = "") -> str: + if external_id: + raw = f"external:{external_id}" + else: + raw = f"{transaction_date}|{amount}|{merchant.strip().lower()}|{account_id.strip().lower()}" + return hashlib.sha256(raw.encode("utf-8")).hexdigest() + +def health_check(db_path: str | None = None) -> dict[str, Any]: + path = init_db(db_path) + with db(path) as conn: + schema_version = conn.execute("SELECT value FROM schema_meta WHERE key='schema_version'").fetchone()[0] + tx_count = conn.execute("SELECT COUNT(*) FROM transactions WHERE status='active'").fetchone()[0] + return ok(server="jarca-ledger-mcp", db_path=path, schema_version=schema_version, active_transactions=tx_count) + +def create_ledger_account(name: str, type: str = "bank", institution: str = "", currency: str = "KRW", active: bool = True, memo: str = "", account_number_masked: str = "", holder_name: str = "", last_balance: int | None = None, last_synced_at: str = "", db_path: str | None = None) -> dict[str, Any]: + if not name.strip(): + return fail("validation_error", "account name is required") + if type not in VALID_ACCOUNT_TYPES: + return fail("validation_error", f"type must be one of {sorted(VALID_ACCOUNT_TYPES)}") + ts = now_iso(); account_id = new_id("acct") + with db(db_path) as conn: + conn.execute("""INSERT INTO accounts(id,name,type,institution,currency,active,memo,account_number_masked,holder_name,last_balance,last_synced_at,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?)""", (account_id, name.strip(), type, institution, currency, int(active), memo, account_number_masked, holder_name, last_balance, last_synced_at, ts, ts)) + row = conn.execute("SELECT * FROM accounts WHERE id=?", (account_id,)).fetchone() + return ok(account=row_to_dict(row)) + +def list_ledger_accounts(active_only: bool = True, db_path: str | None = None) -> dict[str, Any]: + sql = "SELECT * FROM accounts" + (" WHERE active=1" if active_only else "") + " ORDER BY name" + with db(db_path) as conn: + rows = conn.execute(sql).fetchall() + return ok(accounts=[row_to_dict(r) for r in rows], count=len(rows)) + +def create_ledger_transaction(transaction_date: str = "", type: str = "expense", amount: int | float = 0, category: str = "", subcategory: str = "", merchant: str = "", description: str = "", account_id: str = "", payment_method: str = "", person: str = "", project: str = "", tags: Any = None, is_fixed: bool = False, currency: str = "KRW", posted_date: str = "", source: str = "manual", external_id: str = "", memo: str = "", dedupe: bool = True, transaction_datetime: str = "", counterparty: str = "", balance_after: int | None = None, branch: str = "", raw_summary: str = "", raw_payload: str = "", db_path: str | None = None) -> dict[str, Any]: + try: + tx_date = normalize_date(transaction_date, default_today=True) + posted = normalize_date(posted_date, default_today=False) if posted_date else "" + amount_int = int(amount) + tags_json = normalize_tags(tags) + except Exception as e: + return fail("validation_error", str(e)) + if type not in VALID_TRANSACTION_TYPES: + return fail("validation_error", f"type must be one of {sorted(VALID_TRANSACTION_TYPES)}") + if amount_int <= 0: + return fail("validation_error", "amount must be a positive integer in minor units; type determines direction") + dedupe_key = make_dedupe_key(tx_date, amount_int, merchant, account_id, external_id) if dedupe else "" + ts = now_iso(); tx_id = new_id("tx") + try: + with db(db_path) as conn: + conn.execute("""INSERT INTO transactions(id,transaction_date,posted_date,type,amount,currency,category,subcategory,merchant,description,account_id,payment_method,person,project,tags,is_fixed,source,external_id,dedupe_key,memo,transaction_datetime,counterparty,balance_after,branch,raw_summary,raw_payload,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", (tx_id, tx_date, posted, type, amount_int, currency, category, subcategory, merchant, description, account_id, payment_method, person, project, tags_json, int(is_fixed), source, external_id, dedupe_key, memo, transaction_datetime, counterparty, balance_after, branch, raw_summary, raw_payload, ts, ts)) + row = conn.execute("SELECT * FROM transactions WHERE id=?", (tx_id,)).fetchone() + except Exception as e: + if "UNIQUE constraint failed" in str(e): + return fail("duplicate_transaction", "transaction appears to be duplicated", dedupe_key=dedupe_key) + return fail("db_error", str(e)) + return ok(transaction=row_to_dict(row)) + +def list_ledger_transactions(start_date: str = "", end_date: str = "", type: str = "", category: str = "", person: str = "", account_id: str = "", include_deleted: bool = False, limit: int = 100, db_path: str | None = None) -> dict[str, Any]: + clauses=[]; params=[] + if not include_deleted: + clauses.append("status='active'") + for field, value in [("type", type), ("category", category), ("person", person), ("account_id", account_id)]: + if value: + clauses.append(f"{field}=?"); params.append(value) + if start_date: + clauses.append("transaction_date>=?"); params.append(normalize_date(start_date)) + if end_date: + clauses.append("transaction_date<=?"); params.append(normalize_date(end_date)) + where = " WHERE " + " AND ".join(clauses) if clauses else "" + sql = f"SELECT * FROM transactions{where} ORDER BY transaction_date DESC, created_at DESC LIMIT ?" + params.append(max(1, min(int(limit), 1000))) + with db(db_path) as conn: + rows = conn.execute(sql, params).fetchall() + return ok(transactions=[row_to_dict(r) for r in rows], count=len(rows)) + +def update_ledger_transaction(transaction_id: str, db_path: str | None = None, **fields: Any) -> dict[str, Any]: + allowed = {"transaction_date","posted_date","type","amount","currency","category","subcategory","merchant","description","account_id","payment_method","person","project","tags","is_fixed","source","external_id","memo","status","transaction_datetime","counterparty","balance_after","branch","raw_summary","raw_payload"} + updates=[]; params=[] + for k,v in fields.items(): + if k not in allowed or v is None: + continue + if k == "tags": v = normalize_tags(v) + if k in {"transaction_date","posted_date"} and v: v = normalize_date(v) + if k == "amount": v = int(v) + if k == "is_fixed": v = int(bool(v)) + updates.append(f"{k}=?"); params.append(v) + if not updates: + return fail("validation_error", "no fields to update") + updates.append("updated_at=?"); params.append(now_iso()); params.append(transaction_id) + with db(db_path) as conn: + cur = conn.execute(f"UPDATE transactions SET {', '.join(updates)} WHERE id=?", params) + if cur.rowcount == 0: + return fail("not_found", "transaction not found") + row = conn.execute("SELECT * FROM transactions WHERE id=?", (transaction_id,)).fetchone() + return ok(transaction=row_to_dict(row)) + +def delete_ledger_transaction(transaction_id: str, hard_delete: bool = False, db_path: str | None = None) -> dict[str, Any]: + with db(db_path) as conn: + if hard_delete: + cur = conn.execute("DELETE FROM transactions WHERE id=?", (transaction_id,)) + else: + cur = conn.execute("UPDATE transactions SET status='deleted', updated_at=? WHERE id=?", (now_iso(), transaction_id)) + if cur.rowcount == 0: + return fail("not_found", "transaction not found") + return ok(transaction_id=transaction_id, deleted=True, hard_delete=hard_delete) + +def create_ledger_budget(month: str, category: str, amount: int | float, subcategory: str = "", person: str = "", currency: str = "KRW", memo: str = "", db_path: str | None = None) -> dict[str, Any]: + try: + month_norm = normalize_month(month); amount_int = int(amount) + except Exception as e: + return fail("validation_error", str(e)) + if not category: + return fail("validation_error", "category is required") + if amount_int < 0: + return fail("validation_error", "amount must be non-negative") + ts = now_iso(); budget_id = new_id("bud") + with db(db_path) as conn: + conn.execute("""INSERT INTO budgets(id,month,category,subcategory,person,amount,currency,memo,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?) + ON CONFLICT(month,category,subcategory,person) DO UPDATE SET amount=excluded.amount,currency=excluded.currency,memo=excluded.memo,updated_at=excluded.updated_at""", (budget_id, month_norm, category, subcategory, person, amount_int, currency, memo, ts, ts)) + row = conn.execute("SELECT * FROM budgets WHERE month=? AND category=? AND subcategory=? AND person=?", (month_norm, category, subcategory, person)).fetchone() + return ok(budget=row_to_dict(row)) + +def list_ledger_budgets(month: str = "", db_path: str | None = None) -> dict[str, Any]: + clauses=[]; params=[] + if month: + clauses.append("month=?"); params.append(normalize_month(month)) + where = " WHERE " + " AND ".join(clauses) if clauses else "" + with db(db_path) as conn: + rows = conn.execute(f"SELECT * FROM budgets{where} ORDER BY month DESC, category", params).fetchall() + return ok(budgets=[row_to_dict(r) for r in rows], count=len(rows)) + +def _month_range(month: str) -> tuple[str, str]: + m = normalize_month(month) + y, mo = map(int, m.split("-")) + start = date(y, mo, 1) + end = date(y + (mo == 12), 1 if mo == 12 else mo + 1, 1) + return start.isoformat(), end.isoformat() + +def get_monthly_cashflow_report(month: str = "", db_path: str | None = None) -> dict[str, Any]: + month_norm = normalize_month(month); start, next_month = _month_range(month_norm) + with db(db_path) as conn: + type_rows = conn.execute("""SELECT type, SUM(amount) AS total FROM transactions + WHERE status='active' AND transaction_date>=? AND transaction_date=? AND t.transaction_date dict[str, Any]: + if month: + start_date, next_month = _month_range(month); end_op = "<"; end_value = next_month + else: + start_date = normalize_date(start_date, default_today=False) if start_date else "0001-01-01" + end_value = normalize_date(end_date, default_today=False) if end_date else "9999-12-31"; end_op = "<=" + params=[start_date, end_value]; person_clause="" + if person: + person_clause=" AND t.person=?"; params.append(person) + sql=f"""SELECT t.category, t.subcategory, SUM(t.amount) AS total, COUNT(*) AS count FROM transactions t + LEFT JOIN ledger_categories lc ON lc.active=1 AND t.category=lc.category AND t.subcategory=lc.subcategory + WHERE t.status='active' AND {CASHFLOW_KIND_SQL}='expense' AND t.transaction_date>=? AND t.transaction_date{end_op}?{person_clause} + GROUP BY t.category, t.subcategory ORDER BY total DESC""" + with db(db_path) as conn: + rows=conn.execute(sql, params).fetchall() + total=sum(int(r["total"] or 0) for r in rows) + items=[{"category": r["category"], "subcategory": r["subcategory"], "amount": int(r["total"] or 0), "count": r["count"], "share": round((int(r["total"] or 0)/total),4) if total else 0} for r in rows] + return ok(total_expense=total, items=items, count=len(items)) + +def get_fixed_cost_report(month: str = "", db_path: str | None = None) -> dict[str, Any]: + month_norm=normalize_month(month); start,next_month=_month_range(month_norm) + with db(db_path) as conn: + rows=conn.execute(f"""SELECT t.category, t.merchant, t.amount, t.transaction_date, t.person, t.memo FROM transactions t + LEFT JOIN ledger_categories lc ON lc.active=1 AND t.category=lc.category AND t.subcategory=lc.subcategory + WHERE t.status='active' AND {CASHFLOW_KIND_SQL}='expense' AND t.is_fixed=1 AND t.transaction_date>=? AND t.transaction_date dict[str, Any]: + month_norm=normalize_month(month); start,next_month=_month_range(month_norm) + with db(db_path) as conn: + budgets=conn.execute("SELECT * FROM budgets WHERE month=?", (month_norm,)).fetchall() + actuals=conn.execute(f"""SELECT t.category, t.subcategory, t.person, SUM(t.amount) AS amount FROM transactions t + LEFT JOIN ledger_categories lc ON lc.active=1 AND t.category=lc.category AND t.subcategory=lc.subcategory + WHERE t.status='active' AND {CASHFLOW_KIND_SQL}='expense' AND t.transaction_date>=? AND t.transaction_datebudget else "ok"}) + return ok(month=month_norm, items=items, total_budget=sum(i["budget"] for i in items), total_actual=sum(i["actual"] for i in items)) + +def get_investable_cashflow_report(month: str = "", minimum_cash_buffer: int = 0, planned_extra_expense: int = 0, db_path: str | None = None) -> dict[str, Any]: + cashflow=get_monthly_cashflow_report(month, db_path) + if not cashflow.get("success"): + return cashflow + investable=max(0, int(cashflow["net_cashflow"]) - int(minimum_cash_buffer) - int(planned_extra_expense)) + return ok(month=cashflow["month"], income=cashflow["income"], expenses=cashflow["expenses"], net_cashflow=cashflow["net_cashflow"], minimum_cash_buffer=int(minimum_cash_buffer), planned_extra_expense=int(planned_extra_expense), investable_cashflow=investable) + +def preview_ledger_csv_import(file_path: str, source: str = "generic", db_path: str | None = None) -> dict[str, Any]: + path=Path(file_path).expanduser() + if not path.exists(): + return fail("not_found", f"CSV file not found: {path}") + with path.open("r", encoding="utf-8-sig", newline="") as f: + rows=list(csv.DictReader(f)) + preview=[] + for r in rows[:20]: + preview.append(r) + return ok(source=source, filename=str(path), row_count=len(rows), preview=preview, required_columns=["transaction_date/date", "amount", "type optional", "category optional", "merchant/description optional"]) + + +def preview_kb_bank_pdf_import(file_path: str, password: str, preview_limit: int = 20, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_kb_bank_pdf(file_path, password) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_password_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + transactions = parsed["transactions"] + validation = parsed["validation"] + source_hash = parsed["source_hash"] + duplicate_count = 0 + with db(db_path) as conn: + for tx in transactions: + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, tx.counterparty, "", tx.external_id(source_hash)) + found = conn.execute("SELECT 1 FROM transactions WHERE dedupe_key=?", (dedupe_key,)).fetchone() + duplicate_count += 1 if found else 0 + preview = [transaction_preview(tx, source_hash) for tx in transactions[: max(1, min(int(preview_limit), 100))]] + return ok( + source="kb_bank_pdf", + file_path=parsed["file_path"], + source_hash=source_hash, + page_count=parsed["page_count"], + metadata=parsed["metadata"], + row_count=len(transactions), + duplicate_count=duplicate_count, + validation=validation, + preview=preview, + ) + + +def _find_or_create_kb_account(conn: Any, metadata: dict[str, Any], account_id: str = "") -> str: + if account_id: + row = conn.execute("SELECT id FROM accounts WHERE id=?", (account_id,)).fetchone() + if row: + return account_id + raise ValueError(f"account_id not found: {account_id}") + account_number_masked = metadata.get("account_number_masked") or "" + row = None + if account_number_masked: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND account_number_masked=? AND active=1 ORDER BY created_at LIMIT 1", + ("KB국민은행", account_number_masked), + ).fetchone() + if row: + return row["id"] + ts = now_iso() + new_account_id = new_id("acct") + account_name = metadata.get("account_name") or "KB국민은행 계좌" + display_name = f"KB국민은행 {account_name} {account_number_masked}".strip() + conn.execute( + """INSERT INTO accounts(id,name,type,institution,currency,active,memo,account_number_masked,holder_name,last_balance,last_synced_at,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + new_account_id, + display_name, + "bank", + "KB국민은행", + "KRW", + 1, + "국민은행 거래내역 PDF import로 자동 생성", + account_number_masked, + metadata.get("holder_name") or "", + metadata.get("final_balance"), + ts, + ts, + ts, + ), + ) + return new_account_id + + +def import_kb_bank_pdf(file_path: str, password: str, account_id: str = "", skip_duplicates: bool = True, db_path: str | None = None, skip_validation: bool = False) -> dict[str, Any]: + try: + parsed = parse_kb_bank_pdf(file_path, password) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_password_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + transactions = parsed["transactions"] + validation = parsed["validation"] + if not validation.get("ok") and not skip_validation: + return fail("balance_validation_failed", "KB Bank PDF balance flow validation failed", validation=validation) + source_hash = parsed["source_hash"] + metadata = parsed["metadata"] + ts = now_iso() + batch_id = new_id("imp") + inserted = 0 + skipped_duplicates = 0 + inserted_ids: list[str] = [] + try: + with db(db_path) as conn: + linked_account_id = _find_or_create_kb_account(conn, metadata, account_id) + conn.execute( + """INSERT INTO import_batches(id,source,filename,imported_at,row_count,status,memo) + VALUES(?,?,?,?,?,?,?)""", + ( + batch_id, + "kb_bank_pdf", + parsed["file_path"], + ts, + 0, + "active", + json.dumps( + { + "source_hash": source_hash, + "page_count": parsed["page_count"], + "metadata": metadata, + "validation": validation, + "parsed_row_count": len(transactions), + }, + ensure_ascii=False, + ), + ), + ) + for tx in transactions: + tx_id = new_id("tx") + external_id = tx.external_id(source_hash) + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, tx.counterparty, linked_account_id, external_id) + payload = tx.raw_payload() + description = f"국민은행 PDF import; 적요={tx.raw_summary}; 거래점={tx.branch}; 잔액={tx.balance_after}" + try: + conn.execute( + """INSERT INTO transactions(id,transaction_date,posted_date,type,amount,currency,category,subcategory,merchant,description,account_id,payment_method,person,project,tags,is_fixed,source,import_batch_id,external_id,dedupe_key,memo,transaction_datetime,counterparty,balance_after,branch,raw_summary,raw_payload,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + tx_id, + tx.transaction_date, + "", + tx.type, + tx.amount, + "KRW", + "", + "", + tx.counterparty, + description, + linked_account_id, + tx.raw_summary, + "", + "", + normalize_tags(["kb_bank_pdf", tx.raw_summary] if tx.raw_summary else ["kb_bank_pdf"]), + 0, + "kb_bank_pdf", + batch_id, + external_id, + dedupe_key, + tx.remittance_memo, + tx.transaction_datetime, + tx.counterparty, + tx.balance_after, + tx.branch, + tx.raw_summary, + payload, + ts, + ts, + ), + ) + inserted += 1 + inserted_ids.append(tx_id) + except Exception as e: + if "UNIQUE constraint failed" in str(e) and skip_duplicates: + skipped_duplicates += 1 + continue + raise + conn.execute("UPDATE import_batches SET row_count=? WHERE id=?", (inserted, batch_id)) + if transactions: + conn.execute( + "UPDATE accounts SET last_balance=?, last_synced_at=?, updated_at=? WHERE id=?", + (transactions[-1].balance_after, ts, ts, linked_account_id), + ) + except ValueError as e: + return fail("validation_error", str(e)) + except Exception as e: + return fail("db_error", str(e)) + return ok( + import_batch_id=batch_id, + account_id=linked_account_id, + source="kb_bank_pdf", + parsed_row_count=len(transactions), + inserted_count=inserted, + skipped_duplicate_count=skipped_duplicates, + inserted_transaction_ids=inserted_ids[:20], + validation=validation, + metadata=metadata, + ) + + +def _find_or_create_seoulpay_account(conn: Any, metadata: dict[str, Any], account_id: str = "") -> str: + if account_id: + row = conn.execute("SELECT id FROM accounts WHERE id=?", (account_id,)).fetchone() + if row: + return account_id + raise ValueError(f"account_id not found: {account_id}") + holder_name = metadata.get("holder_name") or "" + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND name=? AND active=1 ORDER BY created_at LIMIT 1", + ("서울페이", f"서울페이 이용내역 {holder_name}".strip()), + ).fetchone() + if row: + return row["id"] + ts = now_iso() + new_account_id = new_id("acct") + display_name = f"서울페이 이용내역 {holder_name}".strip() + conn.execute( + """INSERT INTO accounts(id,name,type,institution,currency,active,memo,account_number_masked,holder_name,last_balance,last_synced_at,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + new_account_id, + display_name, + "cash", + "서울페이", + "KRW", + 1, + "서울페이 이용내역 XLSX import로 자동 생성", + "", + holder_name, + None, + ts, + ts, + ts, + ), + ) + return new_account_id + + +def _classify_seoulpay_transaction(tx: Any) -> tuple[str, str, str, bool]: + merchant = (tx.merchant or "").strip() + text = f"{merchant} {tx.transaction_kind} {tx.payment_kind}" + if tx.type == "refund": + return "수입", "환급", merchant, False + if "땡겨요" in text or "배달" in text: + return "식비", "배달", merchant, False + if any(keyword in text for keyword in ("교습소", "학원", "바이올린", "피아노")): + return "교육", "학원", merchant, False + if any(keyword in text for keyword in ("김영모", "베이커리", "제과", "카페", "커피")): + return "식비", "카페", merchant, False + if "온라인" in text: + return "쇼핑", "온라인", merchant, False + return "쇼핑", "생활용품", merchant, False + + +def _find_or_create_toss_bank_account(conn: Any, metadata: dict[str, Any], account_id: str = "") -> str: + if account_id: + row = conn.execute("SELECT id FROM accounts WHERE id=?", (account_id,)).fetchone() + if row: + return account_id + raise ValueError(f"account_id not found: {account_id}") + account_number_masked = metadata.get("account_number_masked") or "" + row = None + if account_number_masked: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND account_number_masked=? AND active=1 ORDER BY created_at LIMIT 1", + ("토스뱅크", account_number_masked), + ).fetchone() + if row: + return row["id"] + ts = now_iso() + new_account_id = new_id("acct") + account_name = metadata.get("account_name") or "토스뱅크 계좌" + display_name = f"토스뱅크 {account_name} {account_number_masked}".strip() + conn.execute( + """INSERT INTO accounts(id,name,type,institution,currency,active,memo,account_number_masked,holder_name,last_balance,last_synced_at,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + new_account_id, + display_name, + "bank", + "토스뱅크", + "KRW", + 1, + "토스뱅크 거래내역 PDF import로 자동 생성", + account_number_masked, + metadata.get("holder_name") or "", + metadata.get("final_balance"), + ts, + ts, + ts, + ), + ) + return new_account_id + + +def _classify_toss_bank_transaction(tx: Any, owner_name: str = "") -> tuple[str, str, str, bool]: + action = (tx.action or "").strip() + counterparty = (tx.counterparty or "").strip() + owner_name = (owner_name or "").strip() + if "이자" in action: + return "수입", "이자", counterparty, False + if "캐시백" in action: + return "수입", "캐시백", counterparty, False + if "체크카드결제" in action: + return "식비", "카드결제", counterparty, False + transfer_like = { + "이체", + "내계좌간자동이체", + "오픈뱅킹", + "펌뱅킹출금", + "펌뱅킹입금", + "적금 개설", + "출금", + "입금", + "ATM출금", + } + if any(keyword in action for keyword in transfer_like): + if counterparty and owner_name and counterparty != owner_name: + return "이체", "확인필요", counterparty, False + return "이체", "본인계좌이동", counterparty, False + if "캐시백" in action: + return "수입", "캐시백", counterparty, False + return "이체", "확인필요", counterparty, False + + +def _build_cross_transfer_index(transactions: list[dict[str, Any]]) -> dict[tuple[str, int, str], list[dict[str, Any]]]: + index: dict[tuple[str, int, str], list[dict[str, Any]]] = {} + for tx in transactions: + if tx.get("status") != "active": + continue + key = (tx["transaction_date"], int(tx["amount"]), tx["type"]) + index.setdefault(key, []).append(tx) + return index + + +def _fetch_transfer_candidates(db_conn: Any, source: str) -> list[dict[str, Any]]: + rows = db_conn.execute( + """ + SELECT t.id, t.transaction_datetime, t.transaction_date, t.type, t.amount, t.category, t.subcategory, + t.counterparty, t.memo, t.person, t.account_id, t.payment_method, t.status, + a.holder_name, t.merchant + FROM transactions t + LEFT JOIN accounts a ON a.id = t.account_id + WHERE t.source=? + AND t.type IN ('income','expense') + AND ( + t.category='이체' + OR t.subcategory IN ('확인필요', '본인계좌이동', '투자이동') + OR t.payment_method IN ('내계좌간자동이전', '내계좌간자동이체', '오픈뱅킹', '펌뱅킹출금', '펌뱅킹입금', '입금', '출금', 'ATM출금', '적금개설') + OR t.merchant LIKE '%이체%' + ) + """, + (source,), + ).fetchall() + return [dict(r) for r in rows] + + +def _parse_tx_datetime(value: str | None) -> datetime | None: + if not value: + return None + text = value.strip() + for fmt in ("%Y-%m-%dT%H:%M:%S", "%Y-%m-%d %H:%M:%S"): + try: + return datetime.strptime(text, fmt) + except ValueError: + continue + try: + return datetime.fromisoformat(text) + except ValueError: + return None + + +def _self_transfer_direction_score(source_type: str, candidate_type: str) -> int: + if source_type == "expense": + if candidate_type == "income": + return 3 + if candidate_type == "transfer": + return 2 + elif source_type == "income": + if candidate_type == "expense": + return 3 + if candidate_type == "transfer": + return 2 + elif source_type == "transfer": + if candidate_type in {"income", "expense"}: + return 2 + if candidate_type == "transfer": + return 1 + return 0 + + +def _normalize_cancel_lookup_text(value: str) -> str: + if not value: + return "" + text = value.lower().strip() + replacements = [ + "kb체크취소", "승인취소", "취소", "환불", "환급", "refund", "reversal", + "카드입금", "카드환급", "매출취소", "입금", "출금", "체크카드", "신용카드", + ] + for token in replacements: + text = text.replace(token, " ") + text = re.sub(r"\s+", " ", text) + return _normalize_counterparty_for_match(text) + + +def _cancel_channel(value: str) -> str: + text = (value or "").lower() + if any(token in text for token in ("카드", "check", "credit")): + return "card" + if any(token in text for token in ("이체", "오픈뱅킹", "출금", "입금", "bank")): + return "bank" + return "other" + + +def _is_cancel_like_transaction(tx: dict[str, Any]) -> bool: + if str(tx.get("type") or "") == "refund": + return True + combined = " ".join( + str(tx.get(key) or "") for key in ("merchant", "raw_summary", "payment_method", "memo", "description") + ).lower() + keywords = ("취소", "환불", "환급", "refund", "reversal", "카드입금", "매출취소") + return str(tx.get("type") or "") == "income" and any(token in combined for token in keywords) + + +def find_cancel_original_candidates(transaction_id: str, limit: int = 20, lookback_days: int = 365, db_path: str | None = None) -> dict[str, Any]: + limit = max(1, min(int(limit), 50)) + lookback_days = max(1, min(int(lookback_days), 730)) + with db(db_path) as conn: + source_row = conn.execute( + """ + SELECT t.*, a.name AS account_name, a.institution, a.holder_name + FROM transactions t + LEFT JOIN accounts a ON a.id = t.account_id + WHERE t.id=? + """, + (transaction_id,), + ).fetchone() + if not source_row: + return fail("not_found", f"transaction not found: {transaction_id}") + source = row_to_dict(source_row) + explicit_cancel_like = _is_cancel_like_transaction(source) + source_type = str(source.get("type") or "") + if source_type not in {"income", "refund"} and not explicit_cancel_like: + return fail("not_cancel_like", "cancel/original lookup is intended for 취소·환급성 거래") + + source_date = normalize_date(source.get("transaction_date"), default_today=False) + source_dt = _parse_tx_datetime(source.get("transaction_datetime")) + source_day = date.fromisoformat(source_date) + start_date = date.fromordinal(source_day.toordinal() - lookback_days).isoformat() + source_text = " ".join(str(source.get(key) or "") for key in ("merchant", "counterparty", "raw_summary", "payment_method")) + source_norm_text = _normalize_cancel_lookup_text(source_text) + source_channel = _cancel_channel(str(source.get("payment_method") or "") + " " + str(source.get("raw_summary") or "") + " " + str(source.get("merchant") or "")) + candidate_rows = conn.execute( + """ + SELECT t.*, a.name AS account_name, a.institution, a.holder_name + FROM transactions t + LEFT JOIN accounts a ON a.id = t.account_id + WHERE t.status='active' + AND t.id<>? + AND t.amount=? + AND t.transaction_date BETWEEN ? AND ? + AND t.type IN ('expense', 'adjustment') + ORDER BY t.transaction_date DESC, t.transaction_datetime DESC, t.created_at DESC + """, + (transaction_id, int(source.get("amount") or 0), start_date, source_date), + ).fetchall() + + candidates: list[dict[str, Any]] = [] + for row in candidate_rows: + candidate = row_to_dict(row) + candidate_date = normalize_date(candidate.get("transaction_date"), default_today=False) + candidate_day = date.fromisoformat(candidate_date) + day_delta = (source_day - candidate_day).days + if day_delta < 0: + continue + candidate_dt = _parse_tx_datetime(candidate.get("transaction_datetime")) + time_delta_seconds = abs(int((source_dt - candidate_dt).total_seconds())) if source_dt and candidate_dt else None + same_account = bool(source.get("account_id") and source.get("account_id") == candidate.get("account_id")) + source_same = bool(source.get("source") and source.get("source") == candidate.get("source")) + candidate_text = " ".join(str(candidate.get(key) or "") for key in ("merchant", "counterparty", "raw_summary", "payment_method")) + candidate_norm_text = _normalize_cancel_lookup_text(candidate_text) + merchant_score = 0 + if source_norm_text and candidate_norm_text: + if source_norm_text == candidate_norm_text: + merchant_score = 4 + elif source_norm_text in candidate_norm_text or candidate_norm_text in source_norm_text: + merchant_score = 2 + channel_score = 0 + candidate_channel = _cancel_channel(str(candidate.get("payment_method") or "") + " " + str(candidate.get("raw_summary") or "") + " " + str(candidate.get("merchant") or "")) + if source_channel != "other" and source_channel == candidate_channel: + channel_score = 2 + if not explicit_cancel_like and not (same_account and merchant_score >= 2 and channel_score >= 1): + continue + recency_score = 0 + if day_delta == 0: + recency_score = 5 + elif day_delta <= 7: + recency_score = 4 + elif day_delta <= 30: + recency_score = 3 + elif day_delta <= 90: + recency_score = 2 + else: + recency_score = 1 + time_score = 0 + if time_delta_seconds is not None: + if time_delta_seconds <= 3600: + time_score = 2 + elif time_delta_seconds <= 86400: + time_score = 1 + score = merchant_score + channel_score + recency_score + time_score + (3 if same_account else 0) + (1 if source_same else 0) + reason_bits = [ + f"same_account={int(same_account)}", + f"merchant={merchant_score}", + f"channel={channel_score}", + f"days={day_delta}", + ] + if time_delta_seconds is not None: + reason_bits.append(f"time_delta={time_delta_seconds}s") + candidates.append({ + "id": candidate.get("id"), + "transaction_date": candidate.get("transaction_date"), + "transaction_datetime": candidate.get("transaction_datetime"), + "source": candidate.get("source"), + "type": candidate.get("type"), + "amount": candidate.get("amount"), + "category": candidate.get("category"), + "subcategory": candidate.get("subcategory"), + "merchant": candidate.get("merchant"), + "raw_summary": candidate.get("raw_summary"), + "counterparty": candidate.get("counterparty"), + "account_id": candidate.get("account_id"), + "account_name": candidate.get("account_name"), + "institution": candidate.get("institution"), + "payment_method": candidate.get("payment_method"), + "memo": candidate.get("memo"), + "score": score, + "day_delta": day_delta, + "time_delta_seconds": time_delta_seconds, + "reason": ", ".join(reason_bits), + }) + + candidates.sort(key=lambda item: (-int(item.get("score", 0)), int(item.get("day_delta", 9999)), int(item.get("time_delta_seconds") or 99999999), str(item.get("transaction_datetime") or ""))) + return ok(source_tx=source, count=len(candidates[:limit]), candidates=candidates[:limit], source="cancel_original_candidate_search") + + +def find_self_transfer_candidates(transaction_id: str, limit: int = 20, db_path: str | None = None) -> dict[str, Any]: + limit = max(1, min(int(limit), 50)) + with db(db_path) as conn: + source_row = conn.execute( + """ + SELECT t.*, a.name AS account_name, a.institution, a.holder_name + FROM transactions t + LEFT JOIN accounts a ON a.id = t.account_id + WHERE t.id=? + """, + (transaction_id,), + ).fetchone() + if not source_row: + return fail("not_found", f"transaction not found: {transaction_id}") + + source = row_to_dict(source_row) + source_date = normalize_date(source.get("transaction_date"), default_today=False) + source_dt = _parse_tx_datetime(source.get("transaction_datetime")) + source_holder = _normalize_counterparty_for_match(source.get("holder_name", "")) + window_start = (date.fromisoformat(source_date) if source_date else date.today()).toordinal() - 1 + window_end = (date.fromisoformat(source_date) if source_date else date.today()).toordinal() + 1 + candidate_rows = conn.execute( + """ + SELECT t.*, a.name AS account_name, a.institution, a.holder_name + FROM transactions t + LEFT JOIN accounts a ON a.id = t.account_id + WHERE t.status='active' + AND t.id<>? + AND COALESCE(t.account_id, '')<>COALESCE(?, '') + AND t.amount=? + AND t.transaction_date BETWEEN ? AND ? + ORDER BY t.transaction_date, t.transaction_datetime, t.created_at + """, + ( + transaction_id, + source.get("account_id", ""), + int(source.get("amount") or 0), + date.fromordinal(window_start).isoformat(), + date.fromordinal(window_end).isoformat(), + ), + ).fetchall() + + candidates: list[dict[str, Any]] = [] + for row in candidate_rows: + candidate = row_to_dict(row) + direction_score = _self_transfer_direction_score(str(source.get("type", "")), str(candidate.get("type", ""))) + if direction_score == 0: + continue + + candidate_dt = _parse_tx_datetime(candidate.get("transaction_datetime")) + day_delta = abs((date.fromisoformat(candidate.get("transaction_date", source_date)) - date.fromisoformat(source_date)).days) + time_delta_seconds = abs(int((candidate_dt - source_dt).total_seconds())) if candidate_dt and source_dt else None + same_owner = bool(source_holder and source_holder == _normalize_counterparty_for_match(candidate.get("holder_name", ""))) + party_score = max( + _party_match_score(str(source.get("counterparty", "")), str(candidate.get("counterparty", ""))), + _party_match_score(str(source.get("counterparty", "")), str(candidate.get("holder_name", ""))), + _party_match_score(str(source.get("merchant", "")), str(candidate.get("counterparty", ""))), + _party_match_score(str(source.get("merchant", "")), str(candidate.get("holder_name", ""))), + ) + source_gap_score = 1 if source.get("source") != candidate.get("source") else 0 + day_score = 3 if day_delta == 0 else 1 + time_score = 0 + if time_delta_seconds is not None: + if time_delta_seconds <= 120: + time_score = 3 + elif time_delta_seconds <= 3600: + time_score = 2 + elif time_delta_seconds <= 86400: + time_score = 1 + score = direction_score + party_score + source_gap_score + day_score + time_score + (3 if same_owner else 0) + reason_bits = [ + f"direction={direction_score}", + f"party={party_score}", + f"same_owner={int(same_owner)}", + f"same_source={int(source.get('source') == candidate.get('source'))}", + f"day_delta={day_delta}", + ] + if time_delta_seconds is not None: + reason_bits.append(f"time_delta={time_delta_seconds}s") + candidates.append( + { + "id": candidate.get("id"), + "transaction_date": candidate.get("transaction_date"), + "transaction_datetime": candidate.get("transaction_datetime"), + "source": candidate.get("source"), + "type": candidate.get("type"), + "amount": candidate.get("amount"), + "category": candidate.get("category"), + "subcategory": candidate.get("subcategory"), + "merchant": candidate.get("merchant"), + "counterparty": candidate.get("counterparty"), + "account_id": candidate.get("account_id"), + "account_name": candidate.get("account_name"), + "institution": candidate.get("institution"), + "holder_name": candidate.get("holder_name"), + "memo": candidate.get("memo"), + "score": score, + "same_owner": same_owner, + "day_delta": day_delta, + "time_delta_seconds": time_delta_seconds, + "reason": ", ".join(reason_bits), + } + ) + + candidates.sort(key=lambda item: (-int(item.get("score", 0)), int(item.get("day_delta", 99)), int(item.get("time_delta_seconds") or 999999), str(item.get("transaction_datetime") or ""))) + return ok(source_tx=source, count=len(candidates[:limit]), candidates=candidates[:limit], source="self_transfer_candidate_search") + + +def link_self_transfer_pair(source_transaction_id: str, candidate_transaction_id: str, db_path: str | None = None) -> dict[str, Any]: + if not source_transaction_id or not candidate_transaction_id: + return fail("validation_error", "both transaction ids are required") + if source_transaction_id == candidate_transaction_id: + return fail("validation_error", "source and candidate transaction must differ") + + preview = find_self_transfer_candidates(source_transaction_id, limit=50, db_path=db_path) + if not preview.get("success"): + return preview + candidates = preview.get("candidates") or [] + candidate = next((item for item in candidates if item.get("id") == candidate_transaction_id), None) + if candidate is None: + return fail("candidate_not_found", f"candidate not found for source transaction: {candidate_transaction_id}") + + link_tag = f"manual_self_transfer_link:{source_transaction_id}|{candidate_transaction_id}" + ts = now_iso() + with db(db_path) as conn: + source_row = conn.execute("SELECT * FROM transactions WHERE id=?", (source_transaction_id,)).fetchone() + candidate_row = conn.execute("SELECT * FROM transactions WHERE id=?", (candidate_transaction_id,)).fetchone() + if not source_row or not candidate_row: + return fail("not_found", "source or candidate transaction not found") + source_memo = _append_memo_tag(source_row["memo"], link_tag) + candidate_memo = _append_memo_tag(candidate_row["memo"], link_tag) + conn.execute( + "UPDATE transactions SET category='이체', subcategory='본인계좌이동', memo=?, updated_at=? WHERE id=?", + (source_memo, ts, source_transaction_id), + ) + conn.execute( + "UPDATE transactions SET category='이체', subcategory='본인계좌이동', memo=?, updated_at=? WHERE id=?", + (candidate_memo, ts, candidate_transaction_id), + ) + updated_source = conn.execute("SELECT * FROM transactions WHERE id=?", (source_transaction_id,)).fetchone() + updated_candidate = conn.execute("SELECT * FROM transactions WHERE id=?", (candidate_transaction_id,)).fetchone() + + return ok( + source_transaction=row_to_dict(updated_source), + candidate_transaction=row_to_dict(updated_candidate), + link_tag=link_tag, + score=candidate.get("score"), + reason=candidate.get("reason"), + source="manual_self_transfer_link", + ) + + +def link_cancel_to_original(cancel_transaction_id: str, original_transaction_id: str, db_path: str | None = None) -> dict[str, Any]: + if not cancel_transaction_id or not original_transaction_id: + return fail("validation_error", "both transaction ids are required") + if cancel_transaction_id == original_transaction_id: + return fail("validation_error", "cancel and original transaction must differ") + + preview = find_cancel_original_candidates(cancel_transaction_id, limit=50, db_path=db_path) + if not preview.get("success"): + return preview + candidates = preview.get("candidates") or [] + original = next((item for item in candidates if item.get("id") == original_transaction_id), None) + if original is None: + return fail("candidate_not_found", f"original transaction candidate not found: {original_transaction_id}") + + link_tag = f"manual_cancel_link:cancel={cancel_transaction_id}|original={original_transaction_id}" + ts = now_iso() + with db(db_path) as conn: + cancel_row = conn.execute("SELECT * FROM transactions WHERE id=?", (cancel_transaction_id,)).fetchone() + original_row = conn.execute("SELECT * FROM transactions WHERE id=?", (original_transaction_id,)).fetchone() + if not cancel_row or not original_row: + return fail("not_found", "cancel or original transaction not found") + + cancel_memo = _append_memo_tag(cancel_row["memo"], link_tag) + original_memo = _append_memo_tag(original_row["memo"], link_tag) + original_category = original_row["category"] or "수입" + original_subcategory = original_row["subcategory"] or "환급" + original_person = original_row["person"] or "" + conn.execute( + "UPDATE transactions SET type='refund', category=?, subcategory=?, person=?, memo=?, updated_at=? WHERE id=?", + (original_category, original_subcategory, original_person, cancel_memo, ts, cancel_transaction_id), + ) + conn.execute( + "UPDATE transactions SET memo=?, updated_at=? WHERE id=?", + (original_memo, ts, original_transaction_id), + ) + updated_cancel = conn.execute("SELECT * FROM transactions WHERE id=?", (cancel_transaction_id,)).fetchone() + updated_original = conn.execute("SELECT * FROM transactions WHERE id=?", (original_transaction_id,)).fetchone() + + return ok( + cancel_transaction=row_to_dict(updated_cancel), + original_transaction=row_to_dict(updated_original), + link_tag=link_tag, + score=original.get("score"), + reason=original.get("reason"), + source="manual_cancel_link", + ) + + +def _tag_memos(conn: Any, tx_id: str, tag: str) -> None: + existing = conn.execute("SELECT memo FROM transactions WHERE id=?", (tx_id,)).fetchone() + if not existing: + return + memo = _append_memo_tag(existing["memo"], tag) + conn.execute("UPDATE transactions SET memo=?, updated_at=? WHERE id=?", (memo, now_iso(), tx_id)) + + +def _run_cross_account_transfer_match(limit: int = 500, dry_run: bool = True, db_path: str | None = None) -> dict[str, Any]: + limit = max(1, min(int(limit), 1000)) + matched_pairs: list[dict[str, Any]] = [] + review_items: list[dict[str, Any]] = [] + matched_tx_ids: set[str] = set() + + with db(db_path) as conn: + kb_rows = _fetch_transfer_candidates(conn, "kb_bank_pdf") + toss_rows = _fetch_transfer_candidates(conn, "toss_bank_pdf") + toss_index = _build_cross_transfer_index(toss_rows) + + for kb in kb_rows: + if kb["status"] != "active": + continue + if _memo_has_tag(kb.get("memo", ""), CROSS_TRANSFER_MATCH_TAG): + continue + required_type = "income" if kb["type"] == "expense" else "expense" + candidates = [ + t + for t in toss_index.get((kb["transaction_date"], int(kb["amount"]), required_type), []) + if t.get("status") == "active" and not _memo_has_tag(t.get("memo", ""), CROSS_TRANSFER_MATCH_TAG) + ] + + if not candidates: + review_items.append( + { + "source_tx_id": kb["id"], + "source": "kb_bank_pdf", + "target_tx_id": "", + "reason": "no_candidate_found", + "type": kb["type"], + "amount": kb["amount"], + "transaction_date": kb["transaction_date"], + "counterparty": kb["counterparty"], + } + ) + continue + + scored = [] + for candidate in candidates: + score = _party_match_score(kb.get("counterparty", ""), candidate.get("counterparty", "")) + scored.append((score, candidate["transaction_datetime"], candidate)) + scored.sort(key=lambda item: (item[0], item[1]), reverse=True) + best_score = scored[0][0] + top = [c for c in scored if c[0] == best_score] + + if best_score == 0 or len(top) != 1: + review_items.append( + { + "source_tx_id": kb["id"], + "source": "kb_bank_pdf", + "target_tx_id": "", + "reason": "ambiguous_or_name_mismatch", + "candidate_count": len(candidates), + "best_name_score": best_score, + "type": kb["type"], + "amount": kb["amount"], + "transaction_date": kb["transaction_date"], + "counterparty": kb["counterparty"], + } + ) + continue + + toss = top[0][2] + if toss["id"] in matched_tx_ids: + review_items.append( + { + "source_tx_id": kb["id"], + "source": "kb_bank_pdf", + "target_tx_id": toss["id"], + "reason": "target_already_matched", + "type": kb["type"], + "amount": kb["amount"], + "transaction_date": kb["transaction_date"], + "counterparty": kb["counterparty"], + } + ) + continue + + kb_party = _normalize_counterparty_for_match(kb.get("counterparty", "")) + toss_party = _normalize_counterparty_for_match(toss.get("counterparty", "")) + owner_candidates = { + _normalize_counterparty_for_match(kb.get("holder_name", "")), + _normalize_counterparty_for_match(toss.get("holder_name", "")), + } + if (kb_party and kb_party in owner_candidates) or (toss_party and toss_party in owner_candidates): + subcategory = "투자이동" + else: + subcategory = "확인필요" + + matched_pairs.append( + { + "kb_tx_id": kb["id"], + "toss_tx_id": toss["id"], + "transaction_date": kb["transaction_date"], + "amount": kb["amount"], + "counterparty_kb": kb["counterparty"], + "counterparty_toss": toss["counterparty"], + "subcategory": subcategory, + "name_score": best_score, + "reason": "paired_by_date_amount_party", + } + ) + if not dry_run: + review_tag = f"{CROSS_TRANSFER_MATCH_TAG}kb={kb['id']}|toss={toss['id']}" + conn.execute( + "UPDATE transactions SET category='이체', subcategory=?, memo=?, updated_at=? WHERE id=?", + (subcategory, _append_memo_tag(kb.get("memo", ""), review_tag), now_iso(), kb["id"]), + ) + conn.execute( + "UPDATE transactions SET category='이체', subcategory=?, memo=?, updated_at=? WHERE id=?", + (subcategory, _append_memo_tag(toss.get("memo", ""), review_tag), now_iso(), toss["id"]), + ) + + if not dry_run: + _tag_memos(conn, kb["id"], f"{CROSS_TRANSFER_REVIEW_TAG}paired") + _tag_memos(conn, toss["id"], f"{CROSS_TRANSFER_REVIEW_TAG}paired") + matched_tx_ids.add(kb["id"]) + matched_tx_ids.add(toss["id"]) + + if len(matched_pairs) >= limit: + break + + for review in review_items: + if review["source_tx_id"] in matched_tx_ids: + continue + if not dry_run: + _tag_memos(conn, review["source_tx_id"], f"{CROSS_TRANSFER_REVIEW_TAG}{review['reason']}") + + + return ok( + dry_run=dry_run, + matched_count=len(matched_pairs), + review_count=len(review_items), + matched_pairs=matched_pairs[:limit], + review_items=review_items[:limit], + source="kb_toss_cross_transfer_match", + ) + + +def preview_cross_account_transfers(limit: int = 500, db_path: str | None = None) -> dict[str, Any]: + return _run_cross_account_transfer_match(limit=limit, dry_run=True, db_path=db_path) + + +def run_cross_account_transfer_match(limit: int = 500, db_path: str | None = None) -> dict[str, Any]: + return _run_cross_account_transfer_match(limit=limit, dry_run=False, db_path=db_path) + + +def list_cross_transfer_review_queue(limit: int = 300, db_path: str | None = None) -> dict[str, Any]: + clauses = ["t.status='active'", "t.source IN ('kb_bank_pdf','toss_bank_pdf')"] + clauses.append("t.memo LIKE '%cross_transfer_review:%'") + where = " WHERE " + " AND ".join(clauses) + with db(db_path) as conn: + rows = conn.execute( + f"SELECT * FROM transactions t{where} ORDER BY t.transaction_date DESC, t.created_at DESC LIMIT ?", + (max(1, min(int(limit), 1000)),), + ).fetchall() + return ok(transactions=[row_to_dict(r) for r in rows], count=len(rows), source="cross_transfer_review_queue") + + +def preview_seoulpay_xlsx_import(file_path: str, password: str = "", preview_limit: int = 20, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_seoulpay_xlsx(file_path, password=password) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("xlsx_parse_error", str(e)) + except Exception as e: + return fail("xlsx_parse_error", str(e)) + + transactions = parsed["transactions"] + source_hash = parsed["source_hash"] + duplicate_count = 0 + by_category: dict[str, dict[str, int]] = {} + with db(db_path) as conn: + linked_account_id = "" + metadata = parsed["metadata"] + holder_name = metadata.get("holder_name") or "" + if holder_name: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND name=? AND active=1 ORDER BY created_at LIMIT 1", + ("서울페이", f"서울페이 이용내역 {holder_name}".strip()), + ).fetchone() + linked_account_id = row["id"] if row else "" + for tx in transactions: + category, subcategory, _, _ = _classify_seoulpay_transaction(tx) + key = f"{category}/{subcategory}" + item = by_category.setdefault(key, {"count": 0, "amount": 0}) + item["count"] += 1 + item["amount"] += int(tx.amount) + merchant = f"서울페이 {tx.merchant}".strip() + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, tx.external_id(source_hash)) + found = conn.execute("SELECT 1 FROM transactions WHERE dedupe_key=?", (dedupe_key,)).fetchone() + duplicate_count += 1 if found else 0 + + preview = [seoulpay_transaction_preview(tx, source_hash) for tx in transactions[: max(1, min(int(preview_limit), 100))]] + return ok( + source="seoulpay_xlsx", + file_path=parsed["file_path"], + source_hash=source_hash, + sheet_name=parsed["sheet_name"], + metadata=parsed["metadata"], + row_count=len(transactions), + duplicate_count=duplicate_count, + validation=parsed["validation"], + by_category=by_category, + preview=preview, + ) + + +def import_seoulpay_xlsx(file_path: str, password: str = "", account_id: str = "", skip_duplicates: bool = True, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_seoulpay_xlsx(file_path, password=password) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("xlsx_parse_error", str(e)) + except Exception as e: + return fail("xlsx_parse_error", str(e)) + + transactions = parsed["transactions"] + validation = parsed["validation"] + if not validation.get("ok"): + return fail("xlsx_parse_error", "SeoulPay XLSX parsing produced invalid transactions", validation=validation) + + source_hash = parsed["source_hash"] + metadata = parsed["metadata"] + ts = now_iso() + batch_id = new_id("imp") + inserted = 0 + skipped_duplicates = 0 + inserted_ids: list[str] = [] + + try: + with db(db_path) as conn: + linked_account_id = _find_or_create_seoulpay_account(conn, metadata, account_id) + conn.execute( + """INSERT INTO import_batches(id,source,filename,imported_at,row_count,status,memo) + VALUES(?,?,?,?,?,?,?)""", + ( + batch_id, + "seoulpay_xlsx", + parsed["file_path"], + ts, + 0, + "active", + json.dumps( + { + "source_hash": source_hash, + "sheet_name": parsed["sheet_name"], + "metadata": metadata, + "validation": validation, + "parsed_row_count": len(transactions), + }, + ensure_ascii=False, + ), + ), + ) + for tx in transactions: + tx_id = new_id("tx") + external_id = tx.external_id(source_hash) + merchant = f"서울페이 {tx.merchant}".strip() + category, subcategory, person, is_fixed = _classify_seoulpay_transaction(tx) + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, external_id) + description = f"서울페이 XLSX import; 거래유형={tx.transaction_kind}; 결제구분={tx.payment_kind}; 거래번호={tx.transaction_no}; 가맹점ID={tx.merchant_id}" + try: + conn.execute( + """INSERT INTO transactions(id,transaction_date,posted_date,type,amount,currency,category,subcategory,merchant,description,account_id,payment_method,person,project,tags,is_fixed,source,import_batch_id,external_id,dedupe_key,memo,transaction_datetime,counterparty,balance_after,branch,raw_summary,raw_payload,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + tx_id, + tx.transaction_date, + "", + tx.type, + tx.amount, + "KRW", + category, + subcategory, + merchant, + description, + linked_account_id, + tx.payment_kind, + person, + "", + normalize_tags(["seoulpay_xlsx", tx.channel, tx.payment_kind, tx.transaction_kind]), + int(is_fixed), + "seoulpay_xlsx", + batch_id, + external_id, + dedupe_key, + tx.payment_kind, + tx.transaction_datetime, + tx.merchant, + None, + tx.channel, + tx.transaction_kind, + tx.raw_payload(), + ts, + ts, + ), + ) + inserted += 1 + inserted_ids.append(tx_id) + except Exception as e: + if "UNIQUE constraint failed" in str(e) and skip_duplicates: + skipped_duplicates += 1 + continue + raise + conn.execute("UPDATE import_batches SET row_count=? WHERE id=?", (inserted, batch_id)) + except ValueError as e: + return fail("validation_error", str(e)) + except Exception as e: + return fail("db_error", str(e)) + + return ok( + import_batch_id=batch_id, + account_id=linked_account_id, + source="seoulpay_xlsx", + parsed_row_count=len(transactions), + inserted_count=inserted, + skipped_duplicate_count=skipped_duplicates, + inserted_transaction_ids=inserted_ids[:20], + validation=validation, + metadata=metadata, + ) + + +def preview_toss_bank_pdf_import(file_path: str, preview_limit: int = 20, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_toss_bank_pdf(file_path) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_parse_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + + transactions = parsed["transactions"] + source_hash = parsed["source_hash"] + duplicate_count = 0 + with db(db_path) as conn: + metadata = parsed["metadata"] + account_number_masked = metadata.get("account_number_masked") or "" + linked_account_id = "" + if account_number_masked: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND account_number_masked=? AND active=1 ORDER BY created_at LIMIT 1", + ("토스뱅크", account_number_masked), + ).fetchone() + linked_account_id = row["id"] if row else "" + for tx in transactions: + merchant = f"토스뱅크 {tx.action}" + (f" {tx.counterparty}" if tx.counterparty else "") + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, tx.external_id(source_hash)) + found = conn.execute("SELECT 1 FROM transactions WHERE dedupe_key=?", (dedupe_key,)).fetchone() + duplicate_count += 1 if found else 0 + + preview = [toss_bank_transaction_preview(tx, source_hash) for tx in transactions[: max(1, min(int(preview_limit), 100))]] + by_action: dict[str, dict[str, int]] = {} + for tx in transactions: + item = by_action.setdefault(tx.action, {"count": 0, "amount": 0}) + item["count"] += 1 + item["amount"] += int(tx.amount) + return ok( + source="toss_bank_pdf", + file_path=parsed["file_path"], + source_hash=source_hash, + page_count=parsed["page_count"], + metadata=parsed["metadata"], + row_count=len(transactions), + duplicate_count=duplicate_count, + validation=parsed["validation"], + by_action=by_action, + preview=preview, + ) + + +def import_toss_bank_pdf(file_path: str, account_id: str = "", skip_duplicates: bool = True, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_toss_bank_pdf(file_path) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_parse_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + + transactions = parsed["transactions"] + validation = parsed["validation"] + if not validation.get("ok"): + return fail("pdf_parse_error", "Toss Bank PDF parsing produced no valid transactions", validation=validation) + + source_hash = parsed["source_hash"] + metadata = parsed["metadata"] + ts = now_iso() + batch_id = new_id("imp") + inserted = 0 + skipped_duplicates = 0 + inserted_ids: list[str] = [] + + try: + with db(db_path) as conn: + linked_account_id = _find_or_create_toss_bank_account(conn, metadata, account_id) + conn.execute( + """INSERT INTO import_batches(id,source,filename,imported_at,row_count,status,memo) + VALUES(?,?,?,?,?,?,?)""", + ( + batch_id, + "toss_bank_pdf", + parsed["file_path"], + ts, + 0, + "active", + json.dumps( + { + "source_hash": source_hash, + "page_count": parsed["page_count"], + "metadata": metadata, + "validation": validation, + "parsed_row_count": len(transactions), + }, + ensure_ascii=False, + ), + ), + ) + for tx in transactions: + tx_id = new_id("tx") + external_id = tx.external_id(source_hash) + merchant = f"토스뱅크 {tx.action}" + (f" {tx.counterparty}" if tx.counterparty else "") + category, subcategory, person, is_fixed = _classify_toss_bank_transaction(tx, metadata.get("holder_name") or "") + if category == "이체": + tx_type = "transfer" + else: + tx_type = tx.type + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, external_id) + description = f"토스뱅크 PDF import; 구분={tx.action}; 상대={tx.counterparty}; 잔액={tx.balance_after}" + payload = tx.raw_payload() + try: + conn.execute( + """INSERT INTO transactions(id,transaction_date,posted_date,type,amount,currency,category,subcategory,merchant,description,account_id,payment_method,person,project,tags,is_fixed,source,import_batch_id,external_id,dedupe_key,memo,transaction_datetime,counterparty,balance_after,branch,raw_summary,raw_payload,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + tx_id, + tx.transaction_date, + "", + tx_type, + tx.amount, + "KRW", + category, + subcategory, + merchant, + description, + linked_account_id, + tx.action, + person, + "", + normalize_tags(["toss_bank_pdf", tx.action] + ([tx.counterparty] if tx.counterparty else [])), + int(is_fixed), + "toss_bank_pdf", + batch_id, + external_id, + dedupe_key, + tx.action, + tx.transaction_datetime, + tx.counterparty, + tx.balance_after, + "토스뱅크", + tx.raw_summary, + payload, + ts, + ts, + ), + ) + inserted += 1 + inserted_ids.append(tx_id) + except Exception as e: + if "UNIQUE constraint failed" in str(e) and skip_duplicates: + skipped_duplicates += 1 + continue + raise + conn.execute("UPDATE import_batches SET row_count=? WHERE id=?", (inserted, batch_id)) + if transactions: + conn.execute( + "UPDATE accounts SET last_balance=?, last_synced_at=?, updated_at=? WHERE id=?", + (transactions[-1].balance_after, ts, ts, linked_account_id), + ) + except ValueError as e: + return fail("validation_error", str(e)) + except Exception as e: + return fail("db_error", str(e)) + + return ok( + import_batch_id=batch_id, + account_id=linked_account_id, + source="toss_bank_pdf", + parsed_row_count=len(transactions), + inserted_count=inserted, + skipped_duplicate_count=skipped_duplicates, + inserted_transaction_ids=inserted_ids[:20], + validation=validation, + metadata=metadata, + ) + + +def _find_or_create_toss_securities_account(conn: Any, metadata: dict[str, Any], account_id: str = "") -> str: + if account_id: + row = conn.execute("SELECT id FROM accounts WHERE id=?", (account_id,)).fetchone() + if row: + return account_id + raise ValueError(f"account_id not found: {account_id}") + account_number_masked = metadata.get("account_number_masked") or "" + row = None + if account_number_masked: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND account_number_masked=? AND active=1 ORDER BY created_at LIMIT 1", + ("토스증권", account_number_masked), + ).fetchone() + if row: + return row["id"] + ts = now_iso() + new_account_id = new_id("acct") + display_name = f"토스증권 {metadata.get('account_name') or '계좌'} {account_number_masked}".strip() + conn.execute( + """INSERT INTO accounts(id,name,type,institution,currency,active,memo,account_number_masked,holder_name,last_balance,last_synced_at,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + new_account_id, + display_name, + "investment", + "토스증권", + "KRW", + 1, + "토스증권 거래내역 PDF import로 자동 생성", + account_number_masked, + metadata.get("holder_name") or "", + None, + ts, + ts, + ts, + ), + ) + return new_account_id + + +def _classify_toss_transaction(tx: Any, owner_name: str = "") -> tuple[str, str, str, bool]: + action = tx.action + counterparty = (tx.name or "").strip() + owner_name = (owner_name or "").strip() + if "배당" in action: + return "수입", "배당", counterparty, False + if "이자" in action: + return "수입", "이자", counterparty, False + if "환급" in action: + return "수입", "환급", counterparty, False + if "이체" in action: + # 토스증권 입출금에서 상대가 계좌 소유자와 다르면 본인 투자 이동으로 확정하지 않는다. + # 예: 이체출금(국민은행) 조상문 -> 외부/타인 송금 가능성이 있어 확인필요. + if counterparty and owner_name and counterparty != owner_name: + return "이체", "확인필요", counterparty, False + return "이체", "투자이동", counterparty, False + return "이체", "투자이동", counterparty, False + + +def preview_toss_securities_pdf_import(file_path: str, preview_limit: int = 20, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_toss_securities_pdf(file_path) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_parse_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + transactions = parsed["transactions"] + source_hash = parsed["source_hash"] + duplicate_count = 0 + with db(db_path) as conn: + metadata = parsed["metadata"] + account_number_masked = metadata.get("account_number_masked") or "" + linked_account_id = "" + if account_number_masked: + row = conn.execute( + "SELECT id FROM accounts WHERE institution=? AND account_number_masked=? AND active=1 ORDER BY created_at LIMIT 1", + ("토스증권", account_number_masked), + ).fetchone() + linked_account_id = row["id"] if row else "" + for tx in transactions: + merchant = f"토스증권 {tx.action}" + (f" {tx.name}" if tx.name else "") + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, tx.external_id(source_hash)) + found = conn.execute("SELECT 1 FROM transactions WHERE dedupe_key=?", (dedupe_key,)).fetchone() + duplicate_count += 1 if found else 0 + preview = [toss_transaction_preview(tx, source_hash) for tx in transactions[: max(1, min(int(preview_limit), 100))]] + by_action: dict[str, dict[str, int]] = {} + for tx in transactions: + item = by_action.setdefault(tx.action, {"count": 0, "amount": 0}) + item["count"] += 1 + item["amount"] += int(tx.amount) + return ok( + source="toss_securities_pdf", + file_path=parsed["file_path"], + source_hash=source_hash, + page_count=parsed["page_count"], + metadata=parsed["metadata"], + row_count=len(transactions), + duplicate_count=duplicate_count, + validation=parsed["validation"], + by_action=by_action, + preview=preview, + ) + + +def import_toss_securities_pdf(file_path: str, account_id: str = "", skip_duplicates: bool = True, db_path: str | None = None) -> dict[str, Any]: + try: + parsed = parse_toss_securities_pdf(file_path) + except FileNotFoundError as e: + return fail("not_found", str(e)) + except ValueError as e: + return fail("pdf_parse_error", str(e)) + except Exception as e: + return fail("pdf_parse_error", str(e)) + transactions = parsed["transactions"] + validation = parsed["validation"] + if not validation.get("ok"): + return fail("pdf_parse_error", "Toss Securities PDF parsing produced no valid transactions", validation=validation) + source_hash = parsed["source_hash"] + metadata = parsed["metadata"] + ts = now_iso() + batch_id = new_id("imp") + inserted = 0 + skipped_duplicates = 0 + inserted_ids: list[str] = [] + try: + with db(db_path) as conn: + linked_account_id = _find_or_create_toss_securities_account(conn, metadata, account_id) + conn.execute( + """INSERT INTO import_batches(id,source,filename,imported_at,row_count,status,memo) + VALUES(?,?,?,?,?,?,?)""", + ( + batch_id, + "toss_securities_pdf", + parsed["file_path"], + ts, + 0, + "active", + json.dumps( + { + "source_hash": source_hash, + "page_count": parsed["page_count"], + "metadata": metadata, + "validation": validation, + "parsed_row_count": len(transactions), + }, + ensure_ascii=False, + ), + ), + ) + for tx in transactions: + tx_id = new_id("tx") + external_id = tx.external_id(source_hash) + merchant = f"토스증권 {tx.action}" + (f" {tx.name}" if tx.name else "") + category, subcategory, person, is_fixed = _classify_toss_transaction(tx, metadata.get("holder_name") or "") + dedupe_key = make_dedupe_key(tx.transaction_date, tx.amount, merchant, linked_account_id, external_id) + description = f"토스증권 PDF import; 구분={tx.action}; 종목/상대={tx.name}; 수량={tx.quantity}; 단가={tx.unit_price}; 수수료={tx.fee}; 세금={tx.tax}; 잔액={tx.balance_after}" + try: + conn.execute( + """INSERT INTO transactions(id,transaction_date,posted_date,type,amount,currency,category,subcategory,merchant,description,account_id,payment_method,person,project,tags,is_fixed,source,import_batch_id,external_id,dedupe_key,memo,transaction_datetime,counterparty,balance_after,branch,raw_summary,raw_payload,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""", + ( + tx_id, + tx.transaction_date, + "", + tx.type, + tx.amount, + "KRW", + category, + subcategory, + merchant, + description, + linked_account_id, + tx.action, + person, + "", + normalize_tags(["toss_securities_pdf", tx.section, tx.action, tx.code] if tx.code else ["toss_securities_pdf", tx.section, tx.action]), + int(is_fixed), + "toss_securities_pdf", + batch_id, + external_id, + dedupe_key, + tx.code, + tx.transaction_date, + tx.name, + tx.balance_after, + "토스증권", + tx.action, + tx.raw_payload(), + ts, + ts, + ), + ) + inserted += 1 + inserted_ids.append(tx_id) + except Exception as e: + if "UNIQUE constraint failed" in str(e) and skip_duplicates: + skipped_duplicates += 1 + continue + raise + conn.execute("UPDATE import_batches SET row_count=? WHERE id=?", (inserted, batch_id)) + if transactions: + conn.execute( + "UPDATE accounts SET last_balance=?, last_synced_at=?, updated_at=? WHERE id=?", + (transactions[-1].balance_after, ts, ts, linked_account_id), + ) + except ValueError as e: + return fail("validation_error", str(e)) + except Exception as e: + return fail("db_error", str(e)) + return ok( + import_batch_id=batch_id, + account_id=linked_account_id, + source="toss_securities_pdf", + parsed_row_count=len(transactions), + inserted_count=inserted, + skipped_duplicate_count=skipped_duplicates, + inserted_transaction_ids=inserted_ids[:20], + validation=validation, + metadata=metadata, + ) + + +def list_ledger_import_batches(source: str = "", include_rolled_back: bool = True, limit: int = 50, db_path: str | None = None) -> dict[str, Any]: + clauses=[]; params=[] + if source: + clauses.append("source=?"); params.append(source) + if not include_rolled_back: + clauses.append("status='active'") + where = " WHERE " + " AND ".join(clauses) if clauses else "" + params.append(max(1, min(int(limit), 500))) + with db(db_path) as conn: + rows=conn.execute(f"SELECT * FROM import_batches{where} ORDER BY imported_at DESC LIMIT ?", params).fetchall() + return ok(import_batches=[row_to_dict(r) for r in rows], count=len(rows)) + + +def rollback_ledger_import_batch(import_batch_id: str, hard_delete: bool = False, db_path: str | None = None) -> dict[str, Any]: + with db(db_path) as conn: + batch = conn.execute("SELECT * FROM import_batches WHERE id=?", (import_batch_id,)).fetchone() + if not batch: + return fail("not_found", "import batch not found") + if hard_delete: + cur = conn.execute("DELETE FROM transactions WHERE import_batch_id=?", (import_batch_id,)) + else: + cur = conn.execute("UPDATE transactions SET status='deleted', updated_at=? WHERE import_batch_id=? AND status='active'", (now_iso(), import_batch_id)) + conn.execute("UPDATE import_batches SET status='rolled_back' WHERE id=?", (import_batch_id,)) + return ok(import_batch_id=import_batch_id, affected_transactions=cur.rowcount, hard_delete=hard_delete) + + +RULE_FIELDS = {"merchant", "counterparty", "description", "payment_method", "raw_summary", "branch", "memo"} +RULE_MATCH_TYPES = {"contains", "equals", "regex", "starts_with", "ends_with"} + +DEFAULT_CATEGORY_RULES: list[dict[str, Any]] = [ + {"priority": 10, "match_field": "merchant", "pattern": "급여", "transaction_type": "income", "category": "수입", "subcategory": "급여"}, + {"priority": 10, "match_field": "merchant", "pattern": "이자", "transaction_type": "income", "category": "수입", "subcategory": "이자"}, + {"priority": 10, "match_field": "merchant", "pattern": "환급", "transaction_type": "income", "category": "수입", "subcategory": "환급"}, + {"priority": 20, "match_field": "raw_summary", "match_type": "equals", "pattern": "국민카드", "transaction_type": "expense", "category": "금융", "subcategory": "카드대금", "is_fixed": 1}, + {"priority": 20, "match_field": "merchant", "pattern": "KB카드출금", "transaction_type": "expense", "category": "금융", "subcategory": "카드대금", "is_fixed": 1}, + {"priority": 30, "match_field": "merchant", "pattern": "SK텔레콤", "transaction_type": "expense", "category": "통신", "subcategory": "휴대폰", "is_fixed": 1}, + {"priority": 30, "match_field": "merchant", "pattern": "KT통신", "transaction_type": "expense", "category": "통신", "subcategory": "통신요금", "is_fixed": 1}, + {"priority": 40, "match_field": "merchant", "pattern": "학원", "transaction_type": "expense", "category": "교육", "subcategory": "학원"}, + {"priority": 40, "match_field": "merchant", "pattern": "교습소", "transaction_type": "expense", "category": "교육", "subcategory": "예체능"}, + {"priority": 40, "match_field": "merchant", "pattern": "연세대학교", "transaction_type": "expense", "category": "의료", "subcategory": "병원"}, + {"priority": 40, "match_field": "merchant", "pattern": "병원", "transaction_type": "expense", "category": "의료", "subcategory": "병원"}, + {"priority": 40, "match_field": "merchant", "pattern": "의원", "transaction_type": "expense", "category": "의료", "subcategory": "병원"}, + {"priority": 40, "match_field": "merchant", "pattern": "치과", "transaction_type": "expense", "category": "의료", "subcategory": "치과"}, + {"priority": 40, "match_field": "merchant", "pattern": "약국", "transaction_type": "expense", "category": "의료", "subcategory": "약국"}, + {"priority": 50, "match_field": "merchant", "pattern": "이마트", "transaction_type": "expense", "category": "식비", "subcategory": "마트"}, + {"priority": 50, "match_field": "merchant", "pattern": "오아시스마켓", "transaction_type": "expense", "category": "식비", "subcategory": "마트"}, + {"priority": 50, "match_field": "merchant", "pattern": "생협", "transaction_type": "expense", "category": "식비", "subcategory": "마트"}, + {"priority": 50, "match_field": "merchant", "pattern": "스타벅스", "transaction_type": "expense", "category": "식비", "subcategory": "카페"}, + {"priority": 50, "match_field": "merchant", "pattern": "메가MGC", "transaction_type": "expense", "category": "식비", "subcategory": "카페"}, + {"priority": 50, "match_field": "merchant", "pattern": "매머드", "transaction_type": "expense", "category": "식비", "subcategory": "카페"}, + {"priority": 50, "match_field": "merchant", "pattern": "커피", "transaction_type": "expense", "category": "식비", "subcategory": "카페"}, + {"priority": 60, "match_field": "merchant", "pattern": "KFC", "transaction_type": "expense", "category": "식비", "subcategory": "외식"}, + {"priority": 60, "match_field": "merchant", "pattern": "스시", "transaction_type": "expense", "category": "식비", "subcategory": "외식"}, + {"priority": 60, "match_field": "merchant", "pattern": "쌀국수", "transaction_type": "expense", "category": "식비", "subcategory": "외식"}, + {"priority": 60, "match_field": "merchant", "pattern": "짜장", "transaction_type": "expense", "category": "식비", "subcategory": "외식"}, + {"priority": 80, "match_field": "raw_summary", "match_type": "equals", "pattern": "스마트출금", "category": "이체", "subcategory": "현금/계좌이동"}, + {"priority": 80, "match_field": "raw_summary", "match_type": "equals", "pattern": "ATM입금", "category": "이체", "subcategory": "현금/계좌이동"}, +] + + +def _rule_matches(rule: dict[str, Any], tx: dict[str, Any]) -> bool: + if rule.get("transaction_type") and rule.get("transaction_type") != tx.get("type", ""): + return False + amount = int(tx.get("amount") or 0) + if rule.get("amount_min") is not None and amount < int(rule["amount_min"]): + return False + if rule.get("amount_max") is not None and amount > int(rule["amount_max"]): + return False + if rule.get("day_of_month") is not None: + tx_date = tx.get("transaction_datetime") or tx.get("transaction_date") or "" + try: + if datetime.fromisoformat(str(tx_date)[:10]).day != int(rule["day_of_month"]): + return False + except ValueError: + return False + value = str(tx.get(rule["match_field"], "") or "") + pattern = str(rule.get("pattern", "")) + match_type = rule.get("match_type") or "contains" + if match_type == "contains": + return pattern.lower() in value.lower() + if match_type == "equals": + return value == pattern + if match_type == "starts_with": + return value.startswith(pattern) + if match_type == "ends_with": + return value.endswith(pattern) + if match_type == "regex": + return re.search(pattern, value) is not None + return False + + +def create_category_rule(match_field: str, pattern: str, category: str, subcategory: str = "", transaction_type: str = "", match_type: str = "contains", priority: int = 100, person: str = "", is_fixed: bool | None = None, confidence: float = 1.0, memo: str = "", amount_min: int | None = None, amount_max: int | None = None, day_of_month: int | None = None, db_path: str | None = None) -> dict[str, Any]: + if match_field not in RULE_FIELDS: + return fail("validation_error", f"match_field must be one of {sorted(RULE_FIELDS)}") + if match_type not in RULE_MATCH_TYPES: + return fail("validation_error", f"match_type must be one of {sorted(RULE_MATCH_TYPES)}") + if transaction_type and transaction_type not in VALID_TRANSACTION_TYPES: + return fail("validation_error", f"transaction_type must be empty or one of {sorted(VALID_TRANSACTION_TYPES)}") + if day_of_month is not None and not 1 <= int(day_of_month) <= 31: + return fail("validation_error", "day_of_month must be between 1 and 31") + if amount_min is not None and amount_max is not None and int(amount_min) > int(amount_max): + return fail("validation_error", "amount_min must be <= amount_max") + if not pattern or not category: + return fail("validation_error", "pattern and category are required") + ts=now_iso(); rule_id=new_id("rule") + with db(db_path) as conn: + conn.execute("""INSERT INTO category_rules(id,priority,match_field,match_type,pattern,amount_min,amount_max,day_of_month,transaction_type,category,subcategory,person,is_fixed,confidence,active,memo,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?) + ON CONFLICT(match_field,match_type,pattern,transaction_type,category,subcategory,person) DO UPDATE SET priority=excluded.priority,amount_min=excluded.amount_min,amount_max=excluded.amount_max,day_of_month=excluded.day_of_month,is_fixed=excluded.is_fixed,confidence=excluded.confidence,active=1,memo=excluded.memo,updated_at=excluded.updated_at""", + (rule_id, int(priority), match_field, match_type, pattern, None if amount_min is None else int(amount_min), None if amount_max is None else int(amount_max), None if day_of_month is None else int(day_of_month), transaction_type, category, subcategory, person, None if is_fixed is None else int(is_fixed), float(confidence), 1, memo, ts, ts)) + row=conn.execute("SELECT * FROM category_rules WHERE match_field=? AND match_type=? AND pattern=? AND transaction_type=? AND category=? AND subcategory=? AND person=?", (match_field, match_type, pattern, transaction_type, category, subcategory, person)).fetchone() + return ok(rule=row_to_dict(row)) + + +def seed_default_category_rules(overwrite: bool = False, db_path: str | None = None) -> dict[str, Any]: + created=0; skipped=0 + with db(db_path) as conn: + if overwrite: + conn.execute("UPDATE category_rules SET active=0 WHERE memo LIKE 'default:%'") + for rule in DEFAULT_CATEGORY_RULES: + memo = "default: initial Jarca ledger categorization" + res=create_category_rule(memo=memo, db_path=db_path, **rule) + if res.get("success"): + created += 1 + else: + skipped += 1 + return ok(created_or_updated=created, skipped=skipped) + + +def list_category_rules(active_only: bool = True, db_path: str | None = None) -> dict[str, Any]: + sql="SELECT * FROM category_rules" + (" WHERE active=1" if active_only else "") + " ORDER BY priority, id" + with db(db_path) as conn: + rows=conn.execute(sql).fetchall() + return ok(rules=[row_to_dict(r) for r in rows], count=len(rows)) + + +def update_category_rule(rule_id: str, match_field: str, pattern: str, category: str, subcategory: str = "", transaction_type: str = "", match_type: str = "contains", priority: int = 100, person: str = "", is_fixed: bool | None = None, confidence: float = 1.0, memo: str = "", amount_min: int | None = None, amount_max: int | None = None, day_of_month: int | None = None, active: bool = True, db_path: str | None = None) -> dict[str, Any]: + if match_field not in RULE_FIELDS: + return fail("validation_error", f"match_field must be one of {sorted(RULE_FIELDS)}") + if match_type not in RULE_MATCH_TYPES: + return fail("validation_error", f"match_type must be one of {sorted(RULE_MATCH_TYPES)}") + if transaction_type and transaction_type not in VALID_TRANSACTION_TYPES: + return fail("validation_error", f"transaction_type must be empty or one of {sorted(VALID_TRANSACTION_TYPES)}") + if day_of_month is not None and not 1 <= int(day_of_month) <= 31: + return fail("validation_error", "day_of_month must be between 1 and 31") + if amount_min is not None and amount_max is not None and int(amount_min) > int(amount_max): + return fail("validation_error", "amount_min must be <= amount_max") + if not pattern or not category: + return fail("validation_error", "pattern and category are required") + ts = now_iso() + with db(db_path) as conn: + existing = conn.execute("SELECT * FROM category_rules WHERE id=?", (rule_id,)).fetchone() + if not existing: + return fail("not_found", f"category rule not found: {rule_id}") + duplicate = conn.execute( + "SELECT id FROM category_rules WHERE match_field=? AND match_type=? AND pattern=? AND transaction_type=? AND category=? AND subcategory=? AND person=? AND id<>?", + (match_field, match_type, pattern, transaction_type, category, subcategory, person, rule_id), + ).fetchone() + if duplicate: + return fail("conflict", f"another rule already exists with the same unique fields: {duplicate['id']}") + conn.execute( + """UPDATE category_rules + SET priority=?, match_field=?, match_type=?, pattern=?, amount_min=?, amount_max=?, day_of_month=?, + transaction_type=?, category=?, subcategory=?, person=?, is_fixed=?, confidence=?, active=?, memo=?, updated_at=? + WHERE id=?""", + ( + int(priority), match_field, match_type, pattern, + None if amount_min is None else int(amount_min), + None if amount_max is None else int(amount_max), + None if day_of_month is None else int(day_of_month), + transaction_type, category, subcategory, person, + None if is_fixed is None else int(is_fixed), + float(confidence), int(bool(active)), memo, ts, rule_id, + ), + ) + row = conn.execute("SELECT * FROM category_rules WHERE id=?", (rule_id,)).fetchone() + return ok(rule=row_to_dict(row)) + + +def delete_category_rule(rule_id: str, db_path: str | None = None) -> dict[str, Any]: + if not rule_id: + return fail("validation_error", "rule_id is required") + with db(db_path) as conn: + existing = conn.execute("SELECT * FROM category_rules WHERE id=?", (rule_id,)).fetchone() + if not existing: + return fail("not_found", f"category rule not found: {rule_id}") + conn.execute("DELETE FROM category_rules WHERE id=?", (rule_id,)) + return ok(deleted_rule_id=rule_id) + + +def _load_active_rules(conn: Any) -> list[dict[str, Any]]: + return [row_to_dict(r) for r in conn.execute("SELECT * FROM category_rules WHERE active=1 ORDER BY priority, id").fetchall()] + + +def _categorization_preview_data(limit: int = 1000, only_uncategorized: bool = True, db_path: str | None = None) -> dict[str, Any]: + with db(db_path) as conn: + rules = _load_active_rules(conn) + where = "WHERE status='active'" + (" AND category=''" if only_uncategorized else "") + rows = [row_to_dict(r) for r in conn.execute( + f"SELECT * FROM transactions {where} ORDER BY transaction_datetime, transaction_date LIMIT ?", + (max(1, min(int(limit), 5000)),), + ).fetchall()] + matches = [] + unmatched = [] + for tx in rows: + match = next((r for r in rules if _rule_matches(r, tx)), None) + if match: + matches.append({ + "transaction_id": tx["id"], + "merchant": tx["merchant"], + "type": tx["type"], + "amount": tx["amount"], + "transaction_datetime": tx.get("transaction_datetime", ""), + "category": match["category"], + "subcategory": match["subcategory"], + "person": match["person"], + "is_fixed": match["is_fixed"], + "rule_id": match["id"], + "rule_pattern": match["pattern"], + }) + else: + unmatched.append({ + "transaction_id": tx["id"], + "merchant": tx["merchant"], + "raw_summary": tx.get("raw_summary", ""), + "type": tx["type"], + "amount": tx["amount"], + "transaction_datetime": tx.get("transaction_datetime", ""), + }) + by_category = {} + for m in matches: + key = f"{m['category']}/{m['subcategory']}" if m['subcategory'] else m['category'] + by_category.setdefault(key, {"count": 0, "amount": 0}) + by_category[key]["count"] += 1 + by_category[key]["amount"] += int(m["amount"]) + return { + "rows": rows, + "matches": matches, + "unmatched": unmatched, + "by_category": by_category, + } + + +def preview_categorization(limit: int = 1000, only_uncategorized: bool = True, db_path: str | None = None) -> dict[str, Any]: + data = _categorization_preview_data(limit, only_uncategorized, db_path) + return ok( + scanned=len(data["rows"]), + matched_count=len(data["matches"]), + unmatched_count=len(data["unmatched"]), + by_category=data["by_category"], + matches=data["matches"][:100], + unmatched=data["unmatched"][:100], + ) + + +def apply_categorization_rules(limit: int = 1000, only_uncategorized: bool = True, db_path: str | None = None) -> dict[str, Any]: + data = _categorization_preview_data(limit, only_uncategorized, db_path) + preview = ok( + scanned=len(data["rows"]), + matched_count=len(data["matches"]), + unmatched_count=len(data["unmatched"]), + by_category=data["by_category"], + matches=data["matches"][:100], + unmatched=data["unmatched"][:100], + ) + applied = 0 + ts = now_iso() + with db(db_path) as conn: + for m in data["matches"]: + conn.execute("UPDATE transactions SET category=?, subcategory=?, person=CASE WHEN ?<>'' THEN ? ELSE person END, is_fixed=CASE WHEN ? IS NULL THEN is_fixed ELSE ? END, updated_at=? WHERE id=?", (m["category"], m["subcategory"], m["person"], m["person"], m["is_fixed"], m["is_fixed"], ts, m["transaction_id"])) + applied += 1 + return ok(applied_count=applied, preview=preview) + + +def list_uncategorized_transactions(limit: int = 100, min_amount: int = 0, db_path: str | None = None) -> dict[str, Any]: + with db(db_path) as conn: + rows=conn.execute("""SELECT * FROM transactions WHERE status='active' AND category='' AND amount>=? ORDER BY amount DESC, transaction_datetime DESC LIMIT ?""", (int(min_amount), max(1,min(int(limit),1000)))).fetchall() + return ok(transactions=[row_to_dict(r) for r in rows], count=len(rows)) + + +def get_uncategorized_merchant_summary(limit: int = 50, db_path: str | None = None) -> dict[str, Any]: + with db(db_path) as conn: + rows=conn.execute("""SELECT merchant, raw_summary, type, COUNT(*) count, SUM(amount) total_amount, MAX(amount) max_amount + FROM transactions WHERE status='active' AND category='' + GROUP BY merchant, raw_summary, type ORDER BY total_amount DESC LIMIT ?""", (max(1,min(int(limit),500)),)).fetchall() + return ok(items=[row_to_dict(r) for r in rows], count=len(rows)) + + +DEFAULT_LEDGER_CATEGORIES: list[dict[str, Any]] = [ + {"category": "수입", "subcategory": "급여", "sort_order": 10}, + {"category": "수입", "subcategory": "이자", "sort_order": 11}, + {"category": "수입", "subcategory": "환급", "sort_order": 12}, + {"category": "수입", "subcategory": "배당", "sort_order": 13}, + {"category": "수입", "subcategory": "기타수입", "sort_order": 19}, + {"category": "이체", "subcategory": "본인계좌이동", "sort_order": 20}, + {"category": "이체", "subcategory": "현금입출금", "sort_order": 21}, + {"category": "이체", "subcategory": "가족송금", "sort_order": 22}, + {"category": "이체", "subcategory": "투자이동", "sort_order": 23}, + {"category": "이체", "subcategory": "확인필요", "sort_order": 29}, + {"category": "식비", "subcategory": "마트", "sort_order": 30}, + {"category": "식비", "subcategory": "외식", "sort_order": 31}, + {"category": "식비", "subcategory": "카페", "sort_order": 32}, + {"category": "식비", "subcategory": "배달", "sort_order": 33}, + {"category": "주거", "subcategory": "관리비", "sort_order": 40}, + {"category": "주거", "subcategory": "전기", "sort_order": 41}, + {"category": "주거", "subcategory": "가스", "sort_order": 42}, + {"category": "주거", "subcategory": "수도", "sort_order": 43}, + {"category": "주거", "subcategory": "인터넷", "sort_order": 44}, + {"category": "통신", "subcategory": "휴대폰", "sort_order": 50}, + {"category": "통신", "subcategory": "인터넷", "sort_order": 51}, + {"category": "통신", "subcategory": "통신요금", "sort_order": 52}, + {"category": "교통", "subcategory": "대중교통", "sort_order": 60}, + {"category": "교통", "subcategory": "택시", "sort_order": 61}, + {"category": "교통", "subcategory": "주유", "sort_order": 62}, + {"category": "교통", "subcategory": "주차", "sort_order": 63}, + {"category": "교통", "subcategory": "차량정비", "sort_order": 64}, + {"category": "교육", "subcategory": "학원", "sort_order": 70}, + {"category": "교육", "subcategory": "교재", "sort_order": 71}, + {"category": "교육", "subcategory": "학교", "sort_order": 72}, + {"category": "교육", "subcategory": "예체능", "sort_order": 73}, + {"category": "의료", "subcategory": "병원", "sort_order": 80}, + {"category": "의료", "subcategory": "약국", "sort_order": 81}, + {"category": "의료", "subcategory": "치과", "sort_order": 82}, + {"category": "의료", "subcategory": "보험", "sort_order": 83}, + {"category": "생활", "subcategory": "생필품", "sort_order": 90}, + {"category": "생활", "subcategory": "의류", "sort_order": 91}, + {"category": "생활", "subcategory": "미용", "sort_order": 92}, + {"category": "생활", "subcategory": "세탁", "sort_order": 93}, + {"category": "문화/여가", "subcategory": "여행", "sort_order": 100}, + {"category": "문화/여가", "subcategory": "숙박", "sort_order": 101}, + {"category": "문화/여가", "subcategory": "공연", "sort_order": 102}, + {"category": "문화/여가", "subcategory": "취미", "sort_order": 103}, + {"category": "문화/여가", "subcategory": "스포츠", "sort_order": 104}, + {"category": "금융", "subcategory": "카드대금", "sort_order": 110}, + {"category": "금융", "subcategory": "대출상환", "sort_order": 111}, + {"category": "금융", "subcategory": "수수료", "sort_order": 112}, + {"category": "금융", "subcategory": "보험료", "sort_order": 113}, + {"category": "가족/용돈", "subcategory": "부모님", "sort_order": 120}, + {"category": "가족/용돈", "subcategory": "자녀", "sort_order": 121}, + {"category": "가족/용돈", "subcategory": "가족송금", "sort_order": 122}, + {"category": "미분류", "subcategory": "확인필요", "sort_order": 999}, +] + + +def infer_cashflow_kind(category: str, subcategory: str = "") -> str: + if category == "수입": + return "income" + if category == "이체": + if subcategory == "투자이동": + return "investment" + return "transfer" + if category == "금융": + if subcategory == "대출상환": + return "debt_payment" + if subcategory in {"카드대금", "수수료"}: + return "exclude" + return "exclude" + if category == "미분류": + return "unknown" + return "expense" + + +def create_ledger_category(category: str, subcategory: str = "", sort_order: int = 100, memo: str = "", cashflow_kind: str = "", db_path: str | None = None) -> dict[str, Any]: + category = (category or "").strip() + subcategory = (subcategory or "").strip() + cashflow_kind = (cashflow_kind or infer_cashflow_kind(category, subcategory)).strip() + if not category: + return fail("validation_error", "category is required") + if cashflow_kind not in VALID_CASHFLOW_KINDS: + return fail("validation_error", f"cashflow_kind must be one of {sorted(VALID_CASHFLOW_KINDS)}") + ts = now_iso(); category_id = new_id("cat") + with db(db_path) as conn: + conn.execute("""INSERT INTO ledger_categories(id,category,subcategory,cashflow_kind,active,sort_order,memo,created_at,updated_at) + VALUES(?,?,?,?,?,?,?,?,?) + ON CONFLICT(category, subcategory) DO UPDATE SET active=1, cashflow_kind=excluded.cashflow_kind, sort_order=excluded.sort_order, memo=excluded.memo, updated_at=excluded.updated_at""", + (category_id, category, subcategory, cashflow_kind, 1, int(sort_order), memo, ts, ts)) + row = conn.execute("SELECT * FROM ledger_categories WHERE category=? AND subcategory=?", (category, subcategory)).fetchone() + return ok(category=row_to_dict(row)) + + +def seed_default_ledger_categories(overwrite: bool = False, db_path: str | None = None) -> dict[str, Any]: + if overwrite: + with db(db_path) as conn: + conn.execute("UPDATE ledger_categories SET active=0 WHERE memo LIKE 'default:%'") + created = 0 + for item in DEFAULT_LEDGER_CATEGORIES: + res = create_ledger_category(memo="default: Jarca initial category", db_path=db_path, **item) + if res.get("success"): + created += 1 + return ok(created_or_updated=created) + + +def list_ledger_categories(active_only: bool = True, include_usage: bool = True, db_path: str | None = None) -> dict[str, Any]: + clauses = [] + if active_only: + clauses.append("active=1") + where = " WHERE " + " AND ".join(clauses) if clauses else "" + with db(db_path) as conn: + rows = conn.execute(f"SELECT * FROM ledger_categories{where} ORDER BY sort_order, category, subcategory").fetchall() + items = [row_to_dict(r) for r in rows] + if include_usage: + usage_rows = conn.execute("""SELECT category, subcategory, COUNT(*) AS transaction_count, SUM(amount) AS total_amount + FROM transactions WHERE status='active' + GROUP BY category, subcategory""").fetchall() + usage = {(r["category"], r["subcategory"]): {"transaction_count": int(r["transaction_count"] or 0), "total_amount": int(r["total_amount"] or 0)} for r in usage_rows} + for item in items: + item.update(usage.get((item["category"], item["subcategory"]), {"transaction_count": 0, "total_amount": 0})) + grouped: dict[str, list[str]] = {} + for item in items: + grouped.setdefault(item["category"], []) + if item["subcategory"] and item["subcategory"] not in grouped[item["category"]]: + grouped[item["category"]].append(item["subcategory"]) + return ok(categories=items, grouped=grouped, count=len(items)) + + +def delete_ledger_category(category: str, subcategory: str = "", hard_delete: bool = False, force: bool = False, db_path: str | None = None) -> dict[str, Any]: + category = (category or "").strip() + subcategory = (subcategory or "").strip() + if not category: + return fail("validation_error", "category is required") + with db(db_path) as conn: + row = conn.execute("SELECT * FROM ledger_categories WHERE category=? AND subcategory=?", (category, subcategory)).fetchone() + if not row: + return fail("not_found", "category not found") + tx_count = conn.execute("SELECT COUNT(*) FROM transactions WHERE status='active' AND category=? AND subcategory=?", (category, subcategory)).fetchone()[0] + budget_count = conn.execute("SELECT COUNT(*) FROM budgets WHERE category=? AND subcategory=?", (category, subcategory)).fetchone()[0] + rule_count = conn.execute("SELECT COUNT(*) FROM category_rules WHERE active=1 AND category=? AND subcategory=?", (category, subcategory)).fetchone()[0] + in_use = int(tx_count or 0) + int(budget_count or 0) + int(rule_count or 0) + if in_use and hard_delete and not force: + return fail("category_in_use", "category is referenced; use soft delete or force=true", transaction_count=tx_count, budget_count=budget_count, rule_count=rule_count) + if hard_delete: + conn.execute("DELETE FROM ledger_categories WHERE id=?", (row["id"],)) + else: + conn.execute("UPDATE ledger_categories SET active=0, updated_at=? WHERE id=?", (now_iso(), row["id"])) + return ok(category=category, subcategory=subcategory, deleted=True, hard_delete=hard_delete, transaction_count=tx_count, budget_count=budget_count, rule_count=rule_count) diff --git a/jarca_ledger_mcp/toss_bank_pdf.py b/jarca_ledger_mcp/toss_bank_pdf.py new file mode 100644 index 0000000..f178a37 --- /dev/null +++ b/jarca_ledger_mcp/toss_bank_pdf.py @@ -0,0 +1,227 @@ +from __future__ import annotations + +import hashlib +import json +import re +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +import fitz + + +DATETIME_RE = re.compile(r"^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}$") +AMOUNT_RE = re.compile(r"^[+-]?\d{1,3}(?:,\d{3})*$") +ACCOUNT_NUMBER_RE = re.compile(r"\d{3,}-\d{4}-\d{4}") + + +@dataclass +class TossBankTransaction: + row_index: int + transaction_datetime: str + transaction_date: str + action: str + counterparty: str + amount: int + type: str + balance_after: int + raw_summary: str + raw_lines: list[str] + + def external_id(self, source_hash: str) -> str: + return f"toss_bank_pdf:{source_hash}:{self.row_index}:{self.transaction_datetime}:{self.amount}" + + def raw_payload(self) -> str: + return json.dumps( + { + "row_index": self.row_index, + "transaction_datetime": self.transaction_datetime, + "action": self.action, + "counterparty": self.counterparty, + "amount": self.amount, + "type": self.type, + "balance_after": self.balance_after, + "raw_summary": self.raw_summary, + "raw_lines": self.raw_lines, + }, + ensure_ascii=False, + ) + + +def _normalize_lines(text: str) -> list[str]: + lines: list[str] = [] + for line in text.splitlines(): + line = re.sub(r"\s+", " ", line).strip() + if not line: + continue + # Toss statements include page markers like '1 / 70' + if re.fullmatch(r"\d+\s*/\s*\d+", line): + continue + lines.append(line) + return lines + + +def _parse_amount_token(text: str) -> int | None: + token = text.strip() + if not AMOUNT_RE.fullmatch(token): + return None + try: + return int(token.replace(",", "")) + except ValueError: + return None + + +def _extract_metadata(text: str) -> dict[str, str]: + lines = _normalize_lines(text) + holder_name = "" + account_name = "" + account_number_masked = "" + period = "" + + for idx, line in enumerate(lines): + if line.endswith("님의 계좌 거래내역을"): + holder_name = line.replace("님의 계좌 거래내역을", "").strip() + if line == "예금주" and idx + 1 < len(lines): + if not holder_name: + holder_name = lines[idx + 1] + continue + if line == "계좌번호" and idx + 1 < len(lines): + next_line = lines[idx + 1] + if ACCOUNT_NUMBER_RE.search(next_line): + account_number_masked = next_line + continue + if line == "예금명" and idx + 1 < len(lines): + if not account_name: + account_name = lines[idx + 1] + continue + if line == "계좌종류" and idx + 1 < len(lines): + if not account_name: + account_name = lines[idx + 1] + continue + if line == "조회기간" and idx + 1 < len(lines): + period = lines[idx + 1] + + if not account_name: + account_name = "토스뱅크 통장" + + return { + "holder_name": holder_name, + "account_name": account_name, + "account_number_masked": account_number_masked, + "period": period, + "institution": "토스뱅크", + "source": "toss_bank_pdf", + } + + +def _transaction_from_rows(row_index: int, lines: list[str]) -> TossBankTransaction | None: + if len(lines) < 4: + return None + transaction_datetime = lines[0].strip() + if not DATETIME_RE.match(transaction_datetime): + return None + + action = lines[1].strip() if len(lines) > 1 else "" + amount = None + balance_after = None + memo_lines: list[str] = [] + + for item in lines[2:]: + value = item.strip() + parsed_amount = _parse_amount_token(value) + if amount is None and parsed_amount is not None: + amount = parsed_amount + continue + if balance_after is None and parsed_amount is not None: + balance_after = parsed_amount + continue + memo_lines.append(value) + + if amount is None or balance_after is None: + return None + + counterparty = " ".join(memo_lines).strip() + tx_type = "expense" if amount < 0 else "income" + + return TossBankTransaction( + row_index=row_index, + transaction_datetime=transaction_datetime, + transaction_date=transaction_datetime[:10], + action=action, + counterparty=counterparty, + amount=abs(amount), + type=tx_type, + balance_after=balance_after, + raw_summary=counterparty, + raw_lines=lines, + ) + + +def _parse_rows(lines: list[str]) -> list[TossBankTransaction]: + rows: list[list[str]] = [] + current: list[str] = [] + + for line in lines: + if DATETIME_RE.match(line): + if current: + rows.append(current) + current = [line] + elif current: + current.append(line) + + if current: + rows.append(current) + + parsed: list[TossBankTransaction] = [] + for idx, row_lines in enumerate(rows, start=1): + tx = _transaction_from_rows(idx, row_lines) + if tx is not None: + parsed.append(tx) + return parsed + + +def parse_toss_bank_pdf(file_path: str) -> dict[str, Any]: + path = Path(file_path).expanduser() + if not path.exists(): + raise FileNotFoundError(f"Toss Bank PDF not found: {path}") + + data = path.read_bytes() + source_hash = hashlib.sha256(data).hexdigest() + doc = fitz.open(stream=data, filetype="pdf") + if doc.is_encrypted: + raise ValueError("encrypted Toss Bank PDF is not supported yet") + + lines: list[str] = [] + for page in doc: + lines.extend(_normalize_lines(page.get_text("text"))) + all_text = "\n".join(lines) + metadata = _extract_metadata(all_text) + + transactions = _parse_rows(lines) + validation = { + "ok": bool(transactions), + "parsed_rows": len(transactions), + "errors": [] if transactions else ["no valid rows parsed"], + } + return { + "file_path": str(path), + "source_hash": source_hash, + "page_count": doc.page_count, + "metadata": metadata, + "transactions": transactions, + "validation": validation, + } + + +def transaction_preview(tx: TossBankTransaction, source_hash: str) -> dict[str, Any]: + return { + "transaction_datetime": tx.transaction_datetime, + "transaction_date": tx.transaction_date, + "type": tx.type, + "action": tx.action, + "counterparty": tx.counterparty, + "amount": tx.amount, + "balance_after": tx.balance_after, + "raw_summary": tx.raw_summary, + "external_id": tx.external_id(source_hash), + } diff --git a/jarca_ledger_mcp/toss_securities_pdf.py b/jarca_ledger_mcp/toss_securities_pdf.py new file mode 100644 index 0000000..0339bca --- /dev/null +++ b/jarca_ledger_mcp/toss_securities_pdf.py @@ -0,0 +1,293 @@ +from __future__ import annotations + +import hashlib +import json +import re +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +import fitz + +DATE_RE = re.compile(r"^\d{4}\.\d{2}\.\d{2}$") +FOOTER_RE = re.compile(r"^\d+\s*/\s*\d+$") +NUM_RE = re.compile(r"^-?\d{1,3}(?:,\d{3})*(?:\.\d+)?$|^-?\d+(?:\.\d+)?$") +DOLLAR_RE = re.compile(r"^\(\$\s*-?\d+(?:,\d{3})*(?:\.\d+)?\)$") +HEADER_LINES = { + "거래일자", + "거래구분", + "종목명(종목코드)", + "환율", + "거래수량", + "거래대금", + "정산금액", + "단가", + "수수료", + "거래세", + "제세금", + "변제/연체합", + "잔고", + "잔액", +} + + +def _clean(text: str) -> str: + return re.sub(r"\s+", " ", text.replace("\u00a0", " ")).strip() + + +def _parse_number(value: str) -> float: + cleaned = _clean(value).replace(",", "") + if cleaned.startswith("($") and cleaned.endswith(")"): + cleaned = cleaned[2:-1].strip() + return float(cleaned) + + +def _parse_int(value: str) -> int: + return int(round(_parse_number(value))) + + +def _is_num(value: str) -> bool: + value = _clean(value) + return bool(NUM_RE.match(value) or DOLLAR_RE.match(value)) + + +def _split_numeric_line(line: str) -> list[str]: + line = _clean(line) + parts = line.split() + if len(parts) > 1 and all(NUM_RE.match(p) for p in parts): + return parts + return [line] + + +def _normalize_lines(text: str) -> list[str]: + lines: list[str] = [] + for raw in text.splitlines(): + line = _clean(raw) + if not line or FOOTER_RE.match(line) or line in HEADER_LINES: + continue + if line.startswith("수량단위") or line.startswith("금액단위") or line.startswith("발급기준"): + continue + lines.append(line) + return lines + + +@dataclass(frozen=True) +class TossSecuritiesTransaction: + row_index: int + section: str + transaction_date: str + action: str + name: str + code: str + amount: int + type: str + quantity: float | None + unit_price: float | None + fee: int + tax: int + balance_after: int | None + raw_numbers: list[str] + raw_block: list[str] + + def external_id(self, source_hash: str) -> str: + raw = "|".join( + [ + source_hash, + str(self.row_index), + self.section, + self.transaction_date, + self.action, + self.name, + str(self.amount), + json.dumps(self.raw_numbers, ensure_ascii=False), + ] + ) + return "tosssec:" + hashlib.sha256(raw.encode("utf-8")).hexdigest() + + def raw_payload(self) -> str: + return json.dumps( + { + "row_index": self.row_index, + "section": self.section, + "transaction_date": self.transaction_date, + "action": self.action, + "name": self.name, + "code": self.code, + "amount": self.amount, + "type": self.type, + "quantity": self.quantity, + "unit_price": self.unit_price, + "fee": self.fee, + "tax": self.tax, + "balance_after": self.balance_after, + "raw_numbers": self.raw_numbers, + "raw_block": self.raw_block, + }, + ensure_ascii=False, + ) + + +def _extract_metadata(text: str) -> dict[str, Any]: + compact = _clean(text) + holder = "" + account = "" + date_range = "" + issue_no = "" + m = re.search(r"성명\s+([^\s]+)", compact) + if m: + holder = m.group(1) + m = re.search(r"계좌 번호\s+([0-9\-]+)", compact) + if m: + account = m.group(1) + m = re.search(r"조회 기간\s+(\d{4}년\s+\d{1,2}월\s+\d{1,2}일\s+~\s+\d{4}년\s+\d{1,2}월\s+\d{1,2}일)", compact) + if m: + date_range = m.group(1) + m = re.search(r"거래내역서\s+([0-9A-Z\-]+)\s+발급번호", compact) + if m: + issue_no = m.group(1) + return { + "holder_name": holder, + "account_number_masked": account, + "date_range": date_range, + "issue_no": issue_no, + "account_name": "토스증권 계좌", + } + + +def _blocks_from_lines(lines: list[str]) -> list[tuple[str, list[str]]]: + blocks: list[tuple[str, list[str]]] = [] + section = "KRW" + current: list[str] | None = None + current_section = section + for line in lines: + if line == "원화 거래내역": + section = "KRW" + continue + if line == "달러 거래내역": + section = "USD" + continue + if DATE_RE.match(line): + if current: + blocks.append((current_section, current)) + current = [line] + current_section = section + elif current is not None: + current.append(line) + if current: + blocks.append((current_section, current)) + return blocks + + +def _parse_block(row_index: int, section: str, block: list[str]) -> TossSecuritiesTransaction | None: + if len(block) < 3: + return None + date_iso = block[0].replace(".", "-") + action = block[1] + body_start = 2 + if "(" in action and ")" not in action and len(block) > 2: + action = f"{action} {block[2]}" + body_start = 3 + action = action.replace("케 이뱅크", "케이뱅크") + name_parts: list[str] = [] + numeric_cells: list[str] = [] + numeric_started = False + for line in block[body_start:]: + pieces = _split_numeric_line(line) + if not numeric_started and all(_is_num(p) for p in pieces): + numeric_started = True + if numeric_started: + numeric_cells.extend(p for p in pieces if _is_num(p)) + else: + name_parts.append(line) + name = " ".join(name_parts).strip() + code = "" + code_match = re.search(r"\(([A-Z0-9]+)\)", name) + if code_match: + code = code_match.group(1) + krw_numbers = [n for n in numeric_cells if not _clean(n).startswith("($")] + if len(krw_numbers) < 2: + return None + has_exchange = section == "USD" or action.startswith("환전") or action.startswith("외화") + amount_idx = 3 if has_exchange and len(krw_numbers) > 3 else 2 if len(krw_numbers) > 2 else 1 + amount = abs(_parse_int(krw_numbers[amount_idx])) + quantity_idx = 1 if has_exchange and len(krw_numbers) > 1 else 0 + quantity = _parse_number(krw_numbers[quantity_idx]) if len(krw_numbers) > quantity_idx else None + price_idx = 4 if has_exchange else 3 + unit_price = _parse_number(krw_numbers[price_idx]) if len(krw_numbers) > price_idx else None + fee_idx = 5 if has_exchange else 4 + fee = abs(_parse_int(krw_numbers[fee_idx])) if len(krw_numbers) > fee_idx else 0 + tax_start = 6 if has_exchange else 5 + tax = sum(abs(_parse_int(x)) for x in krw_numbers[tax_start : min(tax_start + 2, len(krw_numbers))]) + balance_after = _parse_int(krw_numbers[-1]) if krw_numbers else None + tx_type = "income" if any(k in action for k in ["입금", "판매", "환급"]) else "expense" + if any(k in action for k in ["출금", "구매"]): + tx_type = "expense" + return TossSecuritiesTransaction( + row_index=row_index, + section=section, + transaction_date=date_iso, + action=action, + name=name, + code=code, + amount=amount, + type=tx_type, + quantity=quantity, + unit_price=unit_price, + fee=fee, + tax=tax, + balance_after=balance_after, + raw_numbers=numeric_cells, + raw_block=block, + ) + + +def parse_toss_securities_pdf(file_path: str) -> dict[str, Any]: + path = Path(file_path).expanduser() + if not path.exists(): + raise FileNotFoundError(f"Toss Securities PDF not found: {path}") + data = path.read_bytes() + source_hash = hashlib.sha256(data).hexdigest() + doc = fitz.open(stream=data, filetype="pdf") + if doc.is_encrypted: + raise ValueError("encrypted Toss Securities PDF is not supported yet") + all_text = "\n".join(page.get_text("text") for page in doc) + metadata = _extract_metadata(all_text) + lines: list[str] = [] + for page in doc: + lines.extend(_normalize_lines(page.get_text("text"))) + transactions: list[TossSecuritiesTransaction] = [] + for idx, (section, block) in enumerate(_blocks_from_lines(lines), start=1): + tx = _parse_block(idx, section, block) + if tx and tx.amount > 0: + transactions.append(tx) + validation = { + "ok": bool(transactions), + "parsed_rows": len(transactions), + "errors": [] if transactions else ["no transactions parsed"], + } + return { + "file_path": str(path), + "source_hash": source_hash, + "page_count": doc.page_count, + "metadata": metadata, + "transactions": transactions, + "validation": validation, + } + + +def transaction_preview(tx: TossSecuritiesTransaction, source_hash: str) -> dict[str, Any]: + return { + "transaction_date": tx.transaction_date, + "type": tx.type, + "amount": tx.amount, + "action": tx.action, + "name": tx.name, + "code": tx.code, + "section": tx.section, + "quantity": tx.quantity, + "unit_price": tx.unit_price, + "fee": tx.fee, + "tax": tx.tax, + "balance_after": tx.balance_after, + "external_id": tx.external_id(source_hash), + } diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..f943e96 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,36 @@ +[build-system] +requires = ["setuptools>=68", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "jarca-ledger-mcp" +version = "0.1.0" +description = "Jarca household ledger MCP server for transactions, accounts, budgets, cashflow, and investable cashflow analysis" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "mcp>=1.0.0", + "pymupdf>=1.24.0", + "python-dotenv>=1.0.0", + "openpyxl>=3.1.0", + "msoffcrypto-tool>=5.4.0", +] + +[project.optional-dependencies] +dev = ["pytest>=8.0.0"] +dashboard = [ + "pandas>=2.0.0", + "plotly>=5.0.0", + "streamlit>=1.30.0", +] + +[project.scripts] +jarca-ledger-mcp = "jarca_ledger_mcp.server:main" + +[tool.pytest.ini_options] +addopts = "-q" +testpaths = ["tests"] + +[tool.setuptools.packages.find] +include = ["jarca_ledger_mcp*"] +exclude = ["dashboard*"] diff --git a/tests/test_categorization.py b/tests/test_categorization.py new file mode 100644 index 0000000..2ec41f8 --- /dev/null +++ b/tests/test_categorization.py @@ -0,0 +1,51 @@ +from __future__ import annotations + +from jarca_ledger_mcp import service + + +def test_category_rules_preview_apply(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.create_ledger_transaction("2026-06-01", "expense", 10_000, merchant="이마트에브리데이", raw_summary="체크카드", db_path=db_path) + service.create_ledger_transaction("2026-06-02", "expense", 5_000, merchant="알수없음", raw_summary="체크카드", db_path=db_path) + seeded = service.seed_default_category_rules(db_path=db_path) + assert seeded["success"] is True + rules = service.list_category_rules(db_path=db_path) + assert rules["count"] > 0 + + preview = service.preview_categorization(db_path=db_path) + assert preview["matched_count"] == 1 + assert preview["unmatched_count"] == 1 + assert preview["matches"][0]["category"] == "식비" + assert preview["matches"][0]["subcategory"] == "마트" + + applied = service.apply_categorization_rules(db_path=db_path) + assert applied["success"] is True + assert applied["applied_count"] == 1 + categorized = service.list_ledger_transactions(category="식비", db_path=db_path) + assert categorized["count"] == 1 + uncategorized = service.list_uncategorized_transactions(db_path=db_path) + assert uncategorized["count"] == 1 + + +def test_apply_categorization_rules_applies_all_matches_not_just_preview_sample(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.seed_default_category_rules(db_path=db_path) + for idx in range(150): + service.create_ledger_transaction( + transaction_date=f"2026-06-{(idx % 28) + 1:02d}", + type="expense", + amount=10_000 + idx, + merchant=f"이마트에브리데이 {idx}", + raw_summary="체크카드", + db_path=db_path, + ) + + preview = service.preview_categorization(limit=5000, db_path=db_path) + assert preview["matched_count"] == 150 + assert len(preview["matches"]) == 100 + + applied = service.apply_categorization_rules(limit=5000, db_path=db_path) + assert applied["success"] is True + assert applied["applied_count"] == 150 + uncategorized = service.list_uncategorized_transactions(limit=200, db_path=db_path) + assert uncategorized["count"] == 0 diff --git a/tests/test_category_rule_filters.py b/tests/test_category_rule_filters.py new file mode 100644 index 0000000..44cac04 --- /dev/null +++ b/tests/test_category_rule_filters.py @@ -0,0 +1,105 @@ +from __future__ import annotations + +from jarca_ledger_mcp import service + + +def test_category_rule_amount_and_day_filters(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.health_check(db_path) + rule = service.create_category_rule( + match_field="counterparty", + match_type="equals", + pattern="고근수", + transaction_type="expense", + category="금융", + subcategory="대출상환", + is_fixed=True, + amount_min=1200000, + amount_max=1200000, + day_of_month=5, + db_path=db_path, + ) + assert rule["success"] is True + assert rule["rule"]["amount_min"] == 1200000 + assert rule["rule"]["day_of_month"] == 5 + + matching = service.create_ledger_transaction( + transaction_date="2026-04-05", + type="expense", + amount=1200000, + merchant="고근수", + description="test", + db_path=db_path, + ) + non_matching_amount = service.create_ledger_transaction( + transaction_date="2026-04-05", + type="expense", + amount=1000000, + merchant="고근수", + db_path=db_path, + ) + non_matching_day = service.create_ledger_transaction( + transaction_date="2026-04-06", + type="expense", + amount=1200000, + merchant="고근수", + db_path=db_path, + ) + # Manual transaction helper maps merchant, not counterparty, so set counterparty directly for this importer-specific rule. + from jarca_ledger_mcp.db import db + with db(db_path) as conn: + for tx in [matching, non_matching_amount, non_matching_day]: + conn.execute("UPDATE transactions SET counterparty=? WHERE id=?", ("고근수", tx["transaction"]["id"])) + + preview = service.preview_categorization(limit=100, db_path=db_path) + assert preview["matched_count"] == 1 + assert preview["matches"][0]["transaction_id"] == matching["transaction"]["id"] + assert preview["matches"][0]["category"] == "금융" + assert preview["matches"][0]["subcategory"] == "대출상환" + + +def test_update_category_rule_allows_condition_edits(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.health_check(db_path) + created = service.create_category_rule( + match_field="merchant", + match_type="contains", + pattern="학원", + transaction_type="expense", + category="교육", + subcategory="학원", + amount_min=100000, + db_path=db_path, + ) + assert created["success"] is True + + updated = service.update_category_rule( + created["rule"]["id"], + match_field="merchant", + match_type="equals", + pattern="대치학원", + transaction_type="expense", + category="교육", + subcategory="학원비", + priority=40, + person="고재성", + is_fixed=True, + memo="dashboard edit", + amount_min=120000, + amount_max=150000, + day_of_month=10, + active=False, + db_path=db_path, + ) + assert updated["success"] is True + rule = updated["rule"] + assert rule["match_type"] == "equals" + assert rule["pattern"] == "대치학원" + assert rule["subcategory"] == "학원비" + assert rule["priority"] == 40 + assert rule["person"] == "고재성" + assert rule["is_fixed"] is True + assert rule["amount_min"] == 120000 + assert rule["amount_max"] == 150000 + assert rule["day_of_month"] == 10 + assert rule["active"] is False diff --git a/tests/test_cross_account_transfer_matching.py b/tests/test_cross_account_transfer_matching.py new file mode 100644 index 0000000..73cf1b0 --- /dev/null +++ b/tests/test_cross_account_transfer_matching.py @@ -0,0 +1,127 @@ +from __future__ import annotations + +from jarca_ledger_mcp import service + + +def _find_tx(rows: list[dict], tx_id: str) -> dict: + for row in rows: + if row["id"] == tx_id: + return row + raise AssertionError(f"tx {tx_id} not found") + + +def test_run_cross_transfer_match_marks_ownership_transfer_as_investment(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + kb_account = service.create_ledger_account("KB 본인", "bank", institution="국민", holder_name="고진환", db_path=db_path) + toss_account = service.create_ledger_account("토스증권/뱅크", "bank", institution="토스", holder_name="고진환", db_path=db_path) + + kb_tx = service.create_ledger_transaction( + transaction_date="2026-06-17", + type="expense", + amount=63_000, + category="이체", + subcategory="입금", + merchant="출금", + counterparty="고진환", + account_id=kb_account["account"]["id"], + source="kb_bank_pdf", + db_path=db_path, + ) + toss_tx = service.create_ledger_transaction( + transaction_date="2026-06-17", + type="income", + amount=63_000, + category="이체", + subcategory="입금", + merchant="입금", + counterparty="고진환", + account_id=toss_account["account"]["id"], + source="toss_bank_pdf", + db_path=db_path, + ) + + assert kb_tx["success"] is True + assert toss_tx["success"] is True + + result = service.run_cross_account_transfer_match(db_path=db_path) + assert result["success"] is True + assert result["matched_count"] >= 1 + transactions = service.list_ledger_transactions(limit=20, db_path=db_path)["transactions"] + kb = _find_tx(transactions, kb_tx["transaction"]["id"]) + toss = _find_tx(transactions, toss_tx["transaction"]["id"]) + + assert kb["category"] == "이체" + assert kb["subcategory"] == "투자이동" + assert toss["category"] == "이체" + assert toss["subcategory"] == "투자이동" + + +def test_run_cross_transfer_match_marks_foreign_name_as_review_needed(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + kb_account = service.create_ledger_account("KB 본인", "bank", institution="국민", holder_name="고진환", db_path=db_path) + toss_account = service.create_ledger_account("토스뱅크", "bank", institution="토스", holder_name="고진환", db_path=db_path) + + kb_tx = service.create_ledger_transaction( + transaction_date="2026-06-20", + type="expense", + amount=5_000_000, + category="이체", + subcategory="출금", + merchant="출금", + counterparty="최진선", + account_id=kb_account["account"]["id"], + source="kb_bank_pdf", + db_path=db_path, + ) + toss_tx = service.create_ledger_transaction( + transaction_date="2026-06-20", + type="income", + amount=5_000_000, + category="이체", + subcategory="입금", + merchant="입금", + counterparty="최진선", + account_id=toss_account["account"]["id"], + source="toss_bank_pdf", + db_path=db_path, + ) + + assert kb_tx["success"] is True + assert toss_tx["success"] is True + + result = service.run_cross_account_transfer_match(db_path=db_path) + assert result["success"] is True + + transactions = service.list_ledger_transactions(limit=20, db_path=db_path)["transactions"] + kb = _find_tx(transactions, kb_tx["transaction"]["id"]) + toss = _find_tx(transactions, toss_tx["transaction"]["id"]) + assert kb["subcategory"] == "확인필요" + assert toss["subcategory"] == "확인필요" + + +def test_preview_cross_transfer_marks_unmatched_as_review_item(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + kb_account = service.create_ledger_account("KB 본인", "bank", institution="국민", holder_name="고진환", db_path=db_path) + + kb_tx = service.create_ledger_transaction( + transaction_date="2026-06-22", + type="expense", + amount=12_000, + category="이체", + subcategory="출금", + merchant="출금", + counterparty="고진환", + account_id=kb_account["account"]["id"], + source="kb_bank_pdf", + db_path=db_path, + ) + + assert kb_tx["success"] is True + + result = service.run_cross_account_transfer_match(limit=100, db_path=db_path) + assert result["success"] is True + assert result["review_count"] >= 1 + + rows = service.list_cross_transfer_review_queue(db_path=db_path)["transactions"] + row = _find_tx(rows, kb_tx["transaction"]["id"]) + assert row["memo"].find("cross_transfer_review") != -1 diff --git a/tests/test_kb_bank_pdf.py b/tests/test_kb_bank_pdf.py new file mode 100644 index 0000000..5412d54 --- /dev/null +++ b/tests/test_kb_bank_pdf.py @@ -0,0 +1,66 @@ +from __future__ import annotations + +from pathlib import Path +import os + +import pytest + +from jarca_ledger_mcp import service + +PDF_PATH = Path("/root/.hermes/cache/documents/doc_5a12af727ae0_KB거래내역조회_5704_2606171043.pdf") +PDF_PASSWORD = os.environ.get("KB_BANK_PDF_TEST_PASSWORD", "") +SAMPLE_AVAILABLE = PDF_PATH.exists() and bool(PDF_PASSWORD) + + +@pytest.mark.skipif(not SAMPLE_AVAILABLE, reason="sample KB Bank PDF/password is not available") +def test_preview_kb_bank_pdf_import_real_sample(tmp_path): + result = service.preview_kb_bank_pdf_import(str(PDF_PATH), PDF_PASSWORD, preview_limit=3, db_path=str(tmp_path / "ledger.sqlite3")) + assert result["success"] is True + assert result["row_count"] == 499 + assert result["page_count"] == 20 + assert result["metadata"]["account_number_masked"] == "****5704" + assert result["metadata"]["final_balance"] == 3_041_678 + assert result["validation"]["ok"] is True + assert result["validation"]["total_deposit"] == 125_730_389 + assert result["validation"]["total_withdrawal"] == 123_565_861 + assert result["preview"][0]["transaction_datetime"] == "2026-01-03T09:05:10" + assert result["preview"][0]["type"] == "expense" + assert result["preview"][0]["amount"] == 200 + + +@pytest.mark.skipif(not SAMPLE_AVAILABLE, reason="sample KB Bank PDF/password is not available") +def test_import_kb_bank_pdf_real_sample_and_rollback(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + result = service.import_kb_bank_pdf(str(PDF_PATH), PDF_PASSWORD, db_path=db_path) + assert result["success"] is True + assert result["parsed_row_count"] == 499 + assert result["inserted_count"] == 499 + assert result["skipped_duplicate_count"] == 0 + assert result["metadata"]["account_number_masked"] == "****5704" + + duplicated = service.import_kb_bank_pdf(str(PDF_PATH), PDF_PASSWORD, db_path=db_path) + assert duplicated["success"] is True + assert duplicated["inserted_count"] == 0 + assert duplicated["skipped_duplicate_count"] == 499 + + listed = service.list_ledger_transactions(start_date="2026-01-01", end_date="2026-06-17", limit=1000, db_path=db_path) + assert listed["success"] is True + assert listed["count"] == 499 + sample = next(tx for tx in listed["transactions"] if tx["transaction_datetime"] == "2026-06-15T16:50:50") + assert sample["merchant"] == "오아시스마켓" + assert sample["balance_after"] == 3_041_678 + assert sample["branch"] == "KB카드" + + accounts = service.list_ledger_accounts(db_path=db_path) + assert accounts["count"] == 1 + assert accounts["accounts"][0]["institution"] == "KB국민은행" + assert accounts["accounts"][0]["last_balance"] == 3_041_678 + + batches = service.list_ledger_import_batches(source="kb_bank_pdf", db_path=db_path) + assert batches["count"] == 2 + + rollback = service.rollback_ledger_import_batch(result["import_batch_id"], db_path=db_path) + assert rollback["success"] is True + assert rollback["affected_transactions"] == 499 + after = service.list_ledger_transactions(start_date="2026-01-01", end_date="2026-06-17", limit=1000, db_path=db_path) + assert after["count"] == 0 diff --git a/tests/test_ledger_categories.py b/tests/test_ledger_categories.py new file mode 100644 index 0000000..013437c --- /dev/null +++ b/tests/test_ledger_categories.py @@ -0,0 +1,57 @@ +from __future__ import annotations + +from jarca_ledger_mcp import service + + +def test_ledger_category_create_list_delete_reactivate(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + health = service.health_check(db_path) + assert health["schema_version"] == "6" + + created = service.create_ledger_category("반려동물", "사료", sort_order=250, memo="test", db_path=db_path) + assert created["success"] is True + assert created["category"]["category"] == "반려동물" + assert created["category"]["subcategory"] == "사료" + assert created["category"]["cashflow_kind"] == "expense" + assert created["category"]["active"] is True + + listed = service.list_ledger_categories(db_path=db_path) + assert listed["count"] == 1 + assert listed["grouped"] == {"반려동물": ["사료"]} + + deleted = service.delete_ledger_category("반려동물", "사료", db_path=db_path) + assert deleted["success"] is True + assert service.list_ledger_categories(db_path=db_path)["count"] == 0 + assert service.list_ledger_categories(active_only=False, db_path=db_path)["categories"][0]["active"] is False + + reactivated = service.create_ledger_category("반려동물", "사료", sort_order=260, db_path=db_path) + assert reactivated["success"] is True + assert reactivated["category"]["active"] is True + assert reactivated["category"]["sort_order"] == 260 + + +def test_ledger_category_cashflow_kind(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + income = service.create_ledger_category("기타수입", "상금", cashflow_kind="income", db_path=db_path) + assert income["success"] is True + assert income["category"]["cashflow_kind"] == "income" + invalid = service.create_ledger_category("테스트", "", cashflow_kind="bad", db_path=db_path) + assert invalid["success"] is False + assert invalid["error_code"] == "validation_error" + + +def test_ledger_category_hard_delete_requires_force_when_in_use(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.create_ledger_category("식비", "마트", db_path=db_path) + service.create_ledger_transaction("2026-06-01", "expense", 10000, category="식비", subcategory="마트", merchant="테스트마트", db_path=db_path) + + blocked = service.delete_ledger_category("식비", "마트", hard_delete=True, db_path=db_path) + assert blocked["success"] is False + assert blocked["error_code"] == "category_in_use" + + soft = service.delete_ledger_category("식비", "마트", db_path=db_path) + assert soft["success"] is True + assert soft["transaction_count"] == 1 + + txs = service.list_ledger_transactions(category="식비", db_path=db_path) + assert txs["count"] == 1 diff --git a/tests/test_seoulpay_xlsx.py b/tests/test_seoulpay_xlsx.py new file mode 100644 index 0000000..db780b1 --- /dev/null +++ b/tests/test_seoulpay_xlsx.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +from pathlib import Path + +from jarca_ledger_mcp import service +from jarca_ledger_mcp.seoulpay_xlsx import parse_seoulpay_xlsx + + +def _write_sample_seoulpay_xlsx(path: Path) -> None: + import openpyxl + + wb = openpyxl.Workbook() + ws = wb.active + ws.title = "결제내역" + ws.append(["성명", "최진선"]) + ws.append(["생년월일", "19791010"]) + ws.append(["조회기간", "20260601~20260620"]) + ws.append([]) + ws.append([]) + ws.append(["결제채널", "거래번호", "결제일", "가맹점", "사업자번호", "가맹점ID", "거래유형", "결제구분", "거래금액", "공급가액", "봉사료", "부가세", "과세여부"]) + ws.append(["서울페이", "260618ZP00534273", "2026-06-18 18:27:46", "땡겨요", "2028102637", "AF2402815444", "온라인 결제 ", "결제", 42000, 38182, 0, 3818, "과세"]) + ws.append(["서울페이", "ABP0123761927", "2026-06-10 15:14:05", "리엘바이올린음악교습소", "8259301583", "AF2402827183", "비대면 결제 ", "결제", 260000, 260000, 0, 0, "면세"]) + wb.save(path) + + +def test_parse_seoulpay_xlsx_plain_file(tmp_path): + file_path = tmp_path / "서울페이.xlsx" + _write_sample_seoulpay_xlsx(file_path) + + parsed = parse_seoulpay_xlsx(str(file_path)) + + assert parsed["metadata"]["holder_name"] == "최진선" + assert parsed["metadata"]["period"] == "20260601~20260620" + assert parsed["validation"]["ok"] is True + assert len(parsed["transactions"]) == 2 + first = parsed["transactions"][0] + assert first.transaction_date == "2026-06-18" + assert first.merchant == "땡겨요" + assert first.amount == 42000 + assert first.type == "expense" + + +def test_import_seoulpay_xlsx_creates_account_and_expenses(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + file_path = tmp_path / "서울페이.xlsx" + _write_sample_seoulpay_xlsx(file_path) + + preview = service.preview_seoulpay_xlsx_import(str(file_path), preview_limit=10, db_path=db_path) + assert preview["success"] is True + assert preview["row_count"] == 2 + assert preview["duplicate_count"] == 0 + assert preview["by_category"]["식비/배달"]["amount"] == 42000 + assert preview["by_category"]["교육/학원"]["amount"] == 260000 + + imported = service.import_seoulpay_xlsx(str(file_path), db_path=db_path) + assert imported["success"] is True + assert imported["inserted_count"] == 2 + assert imported["skipped_duplicate_count"] == 0 + + duplicate = service.import_seoulpay_xlsx(str(file_path), db_path=db_path) + assert duplicate["success"] is True + assert duplicate["inserted_count"] == 0 + assert duplicate["skipped_duplicate_count"] == 2 + + cashflow = service.get_monthly_cashflow_report("2026-06", db_path) + assert cashflow["expenses"] == 302000 + categories = service.get_category_spending_report(month="2026-06", db_path=db_path) + assert categories["total_expense"] == 302000 + assert categories["items"][0]["category"] == "교육" diff --git a/tests/test_service.py b/tests/test_service.py new file mode 100644 index 0000000..210ebdc --- /dev/null +++ b/tests/test_service.py @@ -0,0 +1,137 @@ +from __future__ import annotations + +from jarca_ledger_mcp import service + + +def test_health_check_initializes_db(tmp_path): + db_path = tmp_path / "ledger.sqlite3" + result = service.health_check(str(db_path)) + assert result["success"] is True + assert result["schema_version"] == "6" + assert db_path.exists() + + +def test_account_transaction_cashflow_and_category_reports(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + acct = service.create_ledger_account("신한카드", type="card", institution="신한", db_path=db_path) + assert acct["success"] is True + account_id = acct["account"]["id"] + + income = service.create_ledger_transaction( + "2026-06-01", + "income", + 8_000_000, + category="수입", + merchant="회사", + account_id=account_id, + db_path=db_path, + ) + assert income["success"] is True + + expense = service.create_ledger_transaction( + "2026-06-03", + "expense", + 120_000, + category="식비", + subcategory="마트", + merchant="이마트", + account_id=account_id, + person="공통", + tags=["장보기"], + db_path=db_path, + ) + assert expense["success"] is True + + fixed = service.create_ledger_transaction( + "2026-06-05", + "expense", + 900_000, + category="교육", + subcategory="학원", + merchant="물리학원", + person="고재성", + is_fixed=True, + db_path=db_path, + ) + assert fixed["success"] is True + + investment_in = service.create_ledger_transaction( + "2026-06-06", + "income", + 5_000_000, + category="이체", + subcategory="투자이동", + merchant="토스증권 매도/이체입금", + db_path=db_path, + ) + assert investment_in["success"] is True + + investment_out = service.create_ledger_transaction( + "2026-06-07", + "expense", + 3_000_000, + category="이체", + subcategory="투자이동", + merchant="토스증권 매수/이체출금", + is_fixed=True, + db_path=db_path, + ) + assert investment_out["success"] is True + + cashflow = service.get_monthly_cashflow_report("2026-06", db_path) + assert cashflow["success"] is True + assert cashflow["income"] == 8_000_000 + assert cashflow["expenses"] == 1_020_000 + assert cashflow["net_cashflow"] == 6_980_000 + assert cashflow["by_type"]["income"] == 13_000_000 + assert cashflow["by_type"]["expense"] == 4_020_000 + assert cashflow["by_cashflow_kind"]["investment"] == 8_000_000 + + categories = service.get_category_spending_report(month="2026-06", db_path=db_path) + assert categories["total_expense"] == 1_020_000 + assert categories["items"][0]["category"] == "교육" + + fixed_report = service.get_fixed_cost_report("2026-06", db_path) + assert fixed_report["total_fixed_cost"] == 900_000 + assert fixed_report["count"] == 1 + + +def test_budget_vs_actual_and_investable_cashflow(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + service.create_ledger_budget("2026-06", "식비", 500_000, db_path=db_path) + service.create_ledger_budget("2026-06", "교육", 800_000, person="고재준", db_path=db_path) + service.create_ledger_transaction("2026-06-01", "income", 4_000_000, category="수입", db_path=db_path) + service.create_ledger_transaction("2026-06-02", "expense", 550_000, category="식비", db_path=db_path) + service.create_ledger_transaction("2026-06-03", "expense", 700_000, category="교육", person="고재준", db_path=db_path) + service.create_ledger_transaction("2026-06-04", "expense", 2_000_000, category="이체", subcategory="투자이동", db_path=db_path) + service.create_ledger_transaction("2026-06-05", "income", 1_000_000, category="이체", subcategory="투자이동", db_path=db_path) + + report = service.get_budget_vs_actual_report("2026-06", db_path) + assert report["success"] is True + food = next(i for i in report["items"] if i["category"] == "식비") + edu = next(i for i in report["items"] if i["category"] == "교육") + assert food["status"] == "over" + assert food["remaining"] == -50_000 + assert edu["status"] == "ok" + assert edu["remaining"] == 100_000 + + investable = service.get_investable_cashflow_report("2026-06", minimum_cash_buffer=1_000_000, planned_extra_expense=500_000, db_path=db_path) + assert investable["investable_cashflow"] == 1_250_000 + + +def test_duplicate_detection_and_soft_delete(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + first = service.create_ledger_transaction("2026-06-10", "expense", 10_000, merchant="카페", account_id="card1", db_path=db_path) + second = service.create_ledger_transaction("2026-06-10", "expense", 10_000, merchant="카페", account_id="card1", db_path=db_path) + assert first["success"] is True + assert second["success"] is False + assert second["error_code"] == "duplicate_transaction" + + tx_id = first["transaction"]["id"] + deleted = service.delete_ledger_transaction(tx_id, db_path=db_path) + assert deleted["success"] is True + listed = service.list_ledger_transactions(include_deleted=False, db_path=db_path) + assert listed["count"] == 0 + listed_all = service.list_ledger_transactions(include_deleted=True, db_path=db_path) + assert listed_all["count"] == 1 + assert listed_all["transactions"][0]["status"] == "deleted" diff --git a/tests/test_toss_securities_pdf.py b/tests/test_toss_securities_pdf.py new file mode 100644 index 0000000..618b057 --- /dev/null +++ b/tests/test_toss_securities_pdf.py @@ -0,0 +1,54 @@ +from __future__ import annotations + +from pathlib import Path + +import pytest + +from jarca_ledger_mcp import service +from jarca_ledger_mcp.toss_securities_pdf import parse_toss_securities_pdf + +SAMPLE = Path("/root/.hermes/cache/documents/doc_f4cfe8e0221f_거래내역서_20250618_20260617_1.pdf") + + +@pytest.mark.skipif(not SAMPLE.exists(), reason="sample Toss Securities PDF is not available") +def test_parse_toss_securities_pdf_sample(): + parsed = parse_toss_securities_pdf(str(SAMPLE)) + assert parsed["metadata"]["holder_name"] == "고진환" + assert parsed["metadata"]["account_number_masked"] == "123-01-048829" + assert parsed["page_count"] == 15 + assert len(parsed["transactions"]) == 207 + assert any(tx.action == "구매" and tx.code == "A012510" for tx in parsed["transactions"]) + assert any(tx.action == "이체입금(주식회사 케이뱅크)" for tx in parsed["transactions"]) + assert any(tx.section == "USD" and tx.action == "외화증권배당금입금" for tx in parsed["transactions"]) + + +@pytest.mark.skipif(not SAMPLE.exists(), reason="sample Toss Securities PDF is not available") +def test_preview_and_import_toss_securities_pdf_sample(tmp_path): + db_path = str(tmp_path / "ledger.sqlite3") + preview = service.preview_toss_securities_pdf_import(str(SAMPLE), db_path=db_path) + assert preview["success"] is True + assert preview["row_count"] == 207 + assert preview["duplicate_count"] == 0 + + imported = service.import_toss_securities_pdf(str(SAMPLE), db_path=db_path) + assert imported["success"] is True + assert imported["inserted_count"] == 207 + assert imported["skipped_duplicate_count"] == 0 + + imported_again = service.import_toss_securities_pdf(str(SAMPLE), db_path=db_path) + assert imported_again["success"] is True + assert imported_again["inserted_count"] == 0 + assert imported_again["skipped_duplicate_count"] == 207 + + txs = service.list_ledger_transactions(account_id=imported["account_id"], limit=300, db_path=db_path) + assert txs["count"] == 207 + assert any(t["category"] == "수입" and t["subcategory"] == "배당" for t in txs["transactions"]) + assert any(t["category"] == "이체" and t["subcategory"] == "투자이동" for t in txs["transactions"]) + assert any( + t["merchant"] == "토스증권 이체출금(국민은행) 조상문" and t["category"] == "이체" and t["subcategory"] == "확인필요" + for t in txs["transactions"] + ) + assert any( + t["merchant"] == "토스증권 이체입금(국민은행) 고진환" and t["category"] == "이체" and t["subcategory"] == "투자이동" + for t in txs["transactions"] + ) diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..bc1f7b6 --- /dev/null +++ b/uv.lock @@ -0,0 +1,1612 @@ +version = 1 +revision = 3 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.14' and sys_platform == 'win32'", + "python_full_version >= '3.14' and sys_platform != 'win32'", + "python_full_version < '3.14' and sys_platform == 'win32'", + 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