reconcile: Improve reconciler matching and add test cases.
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commit
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2 changed files with 337 additions and 58 deletions
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@ -44,11 +44,14 @@ TODO/ISSUES:
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"""
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import argparse
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import collections
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import copy
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import csv
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import datetime
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import decimal
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import io
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import logging
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import os
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import re
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import sys
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from typing import Callable, Dict, List, Tuple, TextIO
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@ -62,6 +65,49 @@ if not sys.warnoptions:
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warnings.filterwarnings('ignore', category=UserWarning, module='thefuzz.fuzz')
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from thefuzz import fuzz # type: ignore
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logger = logging.getLogger()
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logger.setLevel(logging.DEBUG)
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# Console logging.
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logger.addHandler(logging.StreamHandler())
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JUNK_WORDS = [
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'software',
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'freedom',
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'conservancy',
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'conse',
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'payment',
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'echeck',
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'bill',
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'debit',
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'wire',
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'credit',
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"int'l",
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"in.l",
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'llc',
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'online',
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'donation',
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]
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JUNK_WORDS_RES = [re.compile(word, re.IGNORECASE) for word in JUNK_WORDS]
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ZERO_RE = re.compile('^0+')
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def remove_payee_junk(payee):
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for r in JUNK_WORDS_RES:
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payee = r.sub('', payee)
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payee = ZERO_RE.sub('', payee)
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payee = payee.replace(' - ', ' ')
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payee = re.sub(r'\.0\.\d+', ' ', payee)
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payee = payee.replace('.0', ' ')
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payee = payee.replace('/', ' ')
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payee = re.sub(re.escape('.com'), ' ', payee, flags=re.IGNORECASE)
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payee = re.sub(re.escape('.net'), ' ', payee, flags=re.IGNORECASE)
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payee = payee.replace('*', ' ')
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payee = ' '.join([i for i in payee.split(' ') if len(i) > 3])
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payee = payee.replace('-', ' ')
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payee.strip()
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return payee
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# NOTE: Statement doesn't seem to give us a running balance or a final total.
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def read_transactions_from_csv(f: TextIO, standardize_statement_record: Callable) -> list:
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@ -74,8 +120,10 @@ def standardize_amex_record(row: Dict, line: int) -> Dict:
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return {
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'date': datetime.datetime.strptime(row['Date'], '%m/%d/%Y').date(),
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'amount': -1 * decimal.Decimal(row['Amount']),
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# Descriptions have too much noise, so taking just the start
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# significantly assists the fuzzy matching.
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'payee': remove_payee_junk(row['Description'] or '')[:25],
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'line': line,
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'payee': row['Description'] or '',
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}
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@ -83,39 +131,46 @@ def standardize_fr_record(row: Dict, line: int) -> Dict:
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return {
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'date': datetime.datetime.strptime(row['Date'], '%m/%d/%Y').date(),
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'amount': decimal.Decimal(row['Amount']),
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'payee': row['Detail'] or row['Description'],
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'payee': remove_payee_junk(row['Detail'] or row['Serial Num'])[:20],
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'line': line,
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}
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def standardize_beancount_record(row) -> Dict: # type: ignore[no-untyped-def]
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"""Turn a Beancount query result row into a standard dict representing a transaction."""
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# if '0000000362' in row.narration:
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# import pdb; pdb.set_trace()
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return {
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'date': row.date,
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'amount': row.number_cost_position,
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'payee': row.payee if row.payee else row.narration,
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'payee': remove_payee_junk(row.payee or row.narration)[:30],
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'entity': row.entity,
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'check_id': row.check_id,
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'filename': row.filename,
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'line': row.posting_line,
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'statement': row.posting_statement,
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'line': row.line,
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'bank_statement': row.bank_statement,
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}
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def format_record(record: Dict) -> str:
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return f"{record['date'].isoformat()}: {record['amount']:12,.2f} {record['payee'][:20]:<20}"
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def format_record(records: list[dict]) -> str:
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if len(records) == 1:
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record = records[0]
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return f"{record['date'].isoformat()}: {record['amount']:12,.2f} {record['payee'][:25]:<25}"
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else:
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raise NotImplementedError
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def sort_records(records: List) -> List:
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return sorted(records, key=lambda x: (x['date'], x['amount']))
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def match_statement_and_books(statement_trans: list, books_trans: list, show_reconciled_matches: bool, csv_statement: str) -> tuple[list, list, decimal.Decimal]:
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def match_statement_and_books2(statement_trans: list, books_trans: list):
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matches = []
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metadata_to_apply = []
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total_matched = decimal.Decimal(0)
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total_missing_from_books = decimal.Decimal(0)
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total_missing_from_statement = decimal.Decimal(0)
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# We need a realised list and should be a copy so we can safely delete
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# items.
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books_trans = list(books_trans)
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# Run through all the statement transactions to find a matching transaction in
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# run through all the statement transactions to find a matching transaction in
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# the books. If found, the books transaction is marked off so that it can only
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# be matched once. Some transactions will be matched, some will be on the
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# statement but not the books and some on the books but not the statement.
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@ -125,49 +180,96 @@ def match_statement_and_books(statement_trans: list, books_trans: list, show_rec
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# the books transactions to find an closely matching payee, then do another pass
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# disregarding payee.
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# TODO: What if th
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for r1 in statement_trans:
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for r2 in books_trans:
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match, note = records_match(r1, r2)
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if match:
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if not r2['statement'] or show_reconciled_matches:
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matches.append([r2['date'], f'{format_record(r1)} → {format_record(r2)} ✓ {note}'])
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total_matched += r2['amount']
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if not r2['statement']:
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metadata_to_apply.append((r2['filename'], r2['line'], f' bank-statement: "{os.path.basename(csv_statement)}:{r2["line"]}"\n'))
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books_trans.remove(r2)
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break
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best_match_score = 0
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best_match_index = None
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best_match_note = ''
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matches_found = 0
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for i, r2 in enumerate(books_trans):
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score, note = records_match2(r1, r2)
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if score >= 0.5 and score >= best_match_score:
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matches_found += 1
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best_match_score = score
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best_match_index = i
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best_match_note = note
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# if note == 'payee mismatch':
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# payee_only_mismatches += 1
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if best_match_score > 0.5 and matches_found == 1 and 'payee_mismatch' not in best_match_note or best_match_score > 0.8:
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if best_match_score <= 0.8:
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best_match_note.append('only one decent match')
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matches.append(([r1], [books_trans[best_match_index]], best_match_note))
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del books_trans[best_match_index]
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else:
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matches.append([r1['date'], f'{format_record(r1)} → {" ":^45} ✗ Not in books ({os.path.basename(csv_statement)}:{r1["line"]})'])
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total_missing_from_books += r1['amount']
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matches.append(([r1], [], ['no match']))
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for r2 in books_trans:
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matches.append([r2['date'], f'{" ":^45} → {format_record(r2)} ✗ Not on statement ({os.path.basename(r2["filename"])}:{r2["line"]})'])
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total_missing_from_statement += r2['amount']
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return matches, metadata_to_apply, total_matched, total_missing_from_books, total_missing_from_statement
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matches.append(([], [r2], ['no match']))
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return matches
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def format_matches(statement_trans, books_trans, show_reconciled_matches: bool, csv_statement: str):
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match_output = []
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metadata_to_apply = []
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total_matched = decimal.Decimal(0)
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total_missing_from_books = decimal.Decimal(0)
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total_missing_from_statement = decimal.Decimal(0)
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matches = match_statement_and_books2(statement_trans, books_trans)
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for r1, r2, note in matches:
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note = ', '.join(note)
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note = ': ' + note if note else note
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if r1 and r2:
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match_output.append([r1[0]['date'], f'{format_record(r1)} → {format_record(r2)} ✓ Matched{note}'])
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elif r1:
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match_output.append([r1[0]['date'], f'{format_record(r1)} → {" ":^50} ✗ Not in books ({os.path.basename(csv_statement)}:{r1[0]["line"]})'])
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else:
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match_output.append([r2[0]['date'], f'{" ":^50} → {format_record(r2)} ✗ Not on statement ({os.path.basename(r2[0]["filename"])}:{r2[0]["line"]})'])
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return match_output, metadata_to_apply, total_matched, total_missing_from_books, total_missing_from_statement
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# TODO: Time for some test cases I think.
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# TODO: Could potentially return a score so that we can find the best match from
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# a pool of candidates. How would be then remove that candidate from the global
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# pool?
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def records_match(r1: Dict, r2: Dict) -> Tuple[bool, str]:
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"""Do these records represent the same transaction?"""
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date_matches_exactly = r1['date'] == r2['date']
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date_matches_loosly = r1['date'] >= r2['date'] - datetime.timedelta(days=3) and r1['date'] <= r2['date'] + datetime.timedelta(days=3)
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amount_matches = r1['amount'] == r2['amount']
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payee_match_quality = fuzz.token_set_ratio(r1['payee'], r2['payee'])
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payee_matches = payee_match_quality > 50
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if date_matches_exactly and amount_matches and payee_matches:
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return True, 'Matched'
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elif date_matches_loosly and amount_matches and payee_matches:
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return True, 'Matched +/- 3 days'
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elif date_matches_exactly and amount_matches:
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return True, f'Matched ignoring payee'
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elif date_matches_loosly and amount_matches:
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return True, f'Matched +/- 3 days, ignoring payee'
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def date_proximity(d1, d2):
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diff = abs((d1 - d2).days)
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if diff > 60:
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return 0
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else:
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return False, ''
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return 1.0 - (diff / 60.0)
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def records_match2(r1: Dict, r2: Dict) -> Tuple[bool, str]:
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"""Do these records represent the same transaction?"""
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date_score = date_proximity(r1['date'], r2['date'])
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if r1['date'] == r2['date']:
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date_message = ''
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elif date_score > 0.0:
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diff = abs((r1['date'] - r2['date']).days)
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date_message = f'+/- {diff} days'
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else:
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date_message = 'date mismatch'
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if r1['amount'] == r2['amount']:
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amount_score, amount_message = 2.0, ''
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else:
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amount_score, amount_message = 0.0, 'amount mismatch'
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if r2['check_id']:
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payee_score = 1.0 if r1['payee'] == str(r2['check_id']) else 0
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payee_message = 'check # matched'
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else:
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payee_match_quality_payee = fuzz.token_set_ratio(r1['payee'], r2['payee'])
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payee_match_quality_entity = fuzz.token_set_ratio(r1['payee'], r2['entity'])
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payee_score = max(payee_match_quality_payee, payee_match_quality_entity) / 100.0
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if payee_score > 0.8:
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payee_message = ''
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elif payee_score > 0.5:
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payee_message = 'partial payee match'
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else:
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payee_message = 'payee mismatch'
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overall_score = (date_score + amount_score + payee_score) / 4
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overall_message = [m for m in [date_message, amount_message, payee_message] if m]
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return overall_score, overall_message
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# TODO: Is there a way to pull the side-effecting code out of this function?
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@ -221,6 +323,9 @@ def parse_args(argv):
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def main(args):
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# TODO: Should put in a sanity check to make sure the statement you're feeding
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# in matches the account you've provided.
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# TODO: Can we open the files first, then pass the streams on to the rest of the program?
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if 'AMEX' in args.account:
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standardize_statement_record = standardize_amex_record
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else:
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@ -253,14 +358,16 @@ def main(args):
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# String concatenation looks bad, but there's no SQL injection possible here
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# because BQL can't write back to the Beancount files. I hope!
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query = f"SELECT filename, META('lineno') AS posting_line, META('bank-statement') AS posting_statement, date, number(cost(position)), payee, narration where account = '{args.account}' and date >= {begin_date} and date <= {end_date}"
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query = f"SELECT id, filename, META('lineno') AS line, META('bank-statement') AS bank_statement, date, number(cost(position)), payee, ANY_META('entity') as entity, ANY_META('check-id') as check_id, narration where account = '{args.account}' and date >= {begin_date} and date <= {end_date}"
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result_types, result_rows = run_query(entries, options, query)
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books_trans = sort_records([standardize_beancount_record(row) for row in result_rows])
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matches, metadata_to_apply, total_matched, total_missing_from_books, total_missing_from_statement = match_statement_and_books(
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matches, metadata_to_apply, total_matched, total_missing_from_books, total_missing_from_statement = format_matches(
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statement_trans, books_trans, args.show_reconciled_matches, args.csv_statement)
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# assert books_balance == books_balance_reconciled + total_matched + total_missing_from_statement
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out = io.StringIO()
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print('-' * 155)
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print(f'{"Statement transaction":<38} {"Books transaction":<44} Notes')
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@ -268,17 +375,14 @@ def main(args):
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for _, output in sorted(matches):
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print(output)
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print('-' * 155)
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print(f'Period: {begin_date} to {end_date}')
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print(f'Statement period: {begin_date} to {end_date}')
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print(f'Statement/cleared balance: {args.statement_balance:12,.2f} (as provided by you)')
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print(f'Books balance (all): {books_balance:12,.2f} (all transactions, includes unreconciled)')
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print(f'Books balance (reconciled): {books_balance_reconciled:12,.2f} (transactions with "bank-statement" tag only)')
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print(f'Matched above: {total_matched:12,.2f} ("bank-statement" tag yet to be applied)')
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print(f'On statement only: {total_missing_from_books:12,.2f} (no match in books)')
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print(f'On books only: {total_missing_from_statement:12,.2f} (no match on statement)')
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print(f'Unmatched on books: {total_missing_from_statement:12,.2f}')
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print(f'Unmatched statement: {total_missing_from_books:12,.2f}')
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print('-' * 155)
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# print(f'Remaning to reconcile: {books_balance - books_balance_reconciled - total_matched:12,.2f}')
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# print(f'Total reconciled inc. above: {books_balance_reconciled + total_matched:12,.2f}')
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# print('-' * 155)
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# Write statement metadata back to books
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if metadata_to_apply and not args.non_interactive:
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175
tests/test_reconcile.py
Normal file
175
tests/test_reconcile.py
Normal file
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@ -0,0 +1,175 @@
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import datetime
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import decimal
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from conservancy_beancount.reconcile.prototype_amex_reconciler import match_statement_and_books2 as match_statement_and_books, remove_payee_junk, date_proximity
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S1 = {
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'date': datetime.date(2022, 1, 1),
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'amount': decimal.Decimal('10.00'),
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'payee': 'Patreon / Patreon / 123456/ ST-A1B2C3D4G5H6 /',
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'line': 222,
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}
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S2 = {
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'date': datetime.date(2022, 1, 2),
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'amount': decimal.Decimal('20.00'),
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'payee': 'BT*LINODE PHILADELPHIA P',
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'line': 333,
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}
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S3 = {
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'date': datetime.date(2022, 1, 3),
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'amount': decimal.Decimal('30.00'),
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'payee': 'USPS PO 4067540039 0PORTLAND OR',
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'line': 444,
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}
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B1 = {
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'date': datetime.date(2022, 1, 1),
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'amount': decimal.Decimal('10.00'),
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'payee': 'Patreon',
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'entity': '',
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'check_id': None,
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'filename': '2022/imports.beancount',
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'line': 777,
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'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
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}
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B2 = {
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'date': datetime.date(2022, 1, 2),
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'amount': decimal.Decimal('20.00'),
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'payee': 'Linode',
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'entity': '',
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'check_id': None,
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'filename': '2022/main.beancount',
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'line': 888,
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'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
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}
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B3_next_day = {
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'date': datetime.date(2022, 1, 4),
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'amount': decimal.Decimal('30.00'),
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'payee': 'USPS',
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'entity': '',
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'check_id': None,
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'filename': '2022/main.beancount',
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'line': 999,
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'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
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}
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B3_next_week = {
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'date': datetime.date(2022, 1, 10),
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'amount': decimal.Decimal('30.00'),
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'payee': 'USPS',
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'entity': '',
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'check_id': None,
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'filename': '2022/main.beancount',
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'line': 999,
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'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
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}
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B3_mismatch_amount = {
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'date': datetime.date(2022, 1, 3),
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'amount': decimal.Decimal('31.00'),
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'payee': 'USPS',
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'entity': '',
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'check_id': None,
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'filename': '2022/main.beancount',
|
||||
'line': 999,
|
||||
'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
|
||||
}
|
||||
B3_payee_mismatch_1 = {
|
||||
'date': datetime.date(2022, 1, 3),
|
||||
'amount': decimal.Decimal('30.00'),
|
||||
'payee': 'Credit X',
|
||||
'entity': '',
|
||||
'check_id': None,
|
||||
'filename': '2022/main.beancount',
|
||||
'line': 999,
|
||||
'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
|
||||
}
|
||||
B3_payee_mismatch_2 = {
|
||||
'date': datetime.date(2022, 1, 3),
|
||||
'amount': decimal.Decimal('30.00'),
|
||||
'payee': 'Credit Y',
|
||||
'entity': '',
|
||||
'check_id': None,
|
||||
'filename': '2022/main.beancount',
|
||||
'line': 999,
|
||||
'bank_statement': "Financial/Bank-Statements/AMEX/2022-01-12_AMEX_statement.pdf"
|
||||
}
|
||||
|
||||
|
||||
def test_one_exact_match():
|
||||
statement = [S1]
|
||||
books = [B1]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S1], [B1], []),
|
||||
]
|
||||
|
||||
def test_multiple_exact_matches():
|
||||
statement = [S1, S2]
|
||||
books = [B1, B2]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S1], [B1], []),
|
||||
([S2], [B2], []),
|
||||
]
|
||||
|
||||
def test_one_mismatch():
|
||||
statement = [S1]
|
||||
books = []
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S1], [], ['no match']),
|
||||
]
|
||||
|
||||
def test_multiple_mismatches():
|
||||
statement = [S1]
|
||||
books = [B2]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S1], [], ['no match']),
|
||||
([], [B2], ['no match']),
|
||||
]
|
||||
|
||||
def test_next_day_matches():
|
||||
statement = [S3]
|
||||
books = [B3_next_day]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S3], [B3_next_day], ['+/- 1 days']),
|
||||
]
|
||||
|
||||
def test_next_week_matches():
|
||||
statement = [S3]
|
||||
books = [B3_next_week]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S3], [B3_next_week], ['+/- 7 days']),
|
||||
]
|
||||
|
||||
def test_incorrect_amount_does_not_match():
|
||||
statement = [S3]
|
||||
books = [B3_mismatch_amount]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S3], [], ['no match']),
|
||||
([], [B3_mismatch_amount], ['no match']),
|
||||
]
|
||||
|
||||
def test_payee_mismatch_ok_when_only_one_that_amount_and_date():
|
||||
statement = [S3]
|
||||
books = [B3_payee_mismatch_1]
|
||||
assert match_statement_and_books(statement, books) == [
|
||||
([S3], [B3_payee_mismatch_1], ['payee mismatch', 'only one decent match']),
|
||||
]
|
||||
|
||||
def test_payee_mismatch_not_ok_when_multiple_that_amount_and_date():
|
||||
statement = [S3]
|
||||
books = [B3_payee_mismatch_1, B3_payee_mismatch_2]
|
||||
match = match_statement_and_books(statement, books)
|
||||
assert match == [
|
||||
([S3], [], ['no match']),
|
||||
([], [B3_payee_mismatch_1], ['no match']),
|
||||
([], [B3_payee_mismatch_2], ['no match']),
|
||||
]
|
||||
|
||||
# def test_subset_sum_with_same_date_and_payee():
|
||||
|
||||
def test_remove_payee_junk():
|
||||
assert remove_payee_junk('WIDGETSRUS INC PAYMENT 1') == 'WIDGETSRUS'
|
||||
assert remove_payee_junk('0000010017') == '10017'
|
||||
|
||||
def test_date_proximity():
|
||||
assert date_proximity(datetime.date(2021, 8, 23), datetime.date(2021, 8, 23)) == 1.0
|
||||
assert date_proximity(datetime.date(2021, 8, 23), datetime.date(2021, 8, 23) - datetime.timedelta(days=30)) == 0.5
|
||||
assert date_proximity(datetime.date(2021, 8, 23), datetime.date(2021, 8, 23) - datetime.timedelta(days=60)) == 0.0
|
Loading…
Reference in a new issue