Changeset - 54d11f24377e
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Child rev.
[Not reviewed]
0 2 0
Ben Sturmfels (bsturmfels) - 3 years ago 2022-02-24 11:43:37
ben@sturm.com.au
reconcile: Add further typing info; update tests.
2 files changed with 75 insertions and 41 deletions:
conservancy_beancount/reconcile/statement_reconciler.py
72
38
tests/test_reconcile.py
3
3
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conservancy_beancount/reconcile/statement_reconciler.py
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@@ -53,17 +53,17 @@ import itertools
 
import logging
 
import os
 
import re
 
import sys
 
from typing import Callable, Dict, List, Tuple, TextIO
 

			




	
	
	
		
 
from beancount import loader


			




	
	
	
		
 
from beancount.query.query import run_query


			




	
	
	
		
 
from colorama import Fore, Style


			




	
	
	
		
 
from colorama import Fore, Style  # type: ignore


			




	
	
	
		
 

			




	
	
	
		
 
if not sys.warnoptions:


			




	
	
	
		
 
    import warnings


			




	
	
	
		
 
    # Disable annoying warning from thefuzz prompting for a C extension. The


			




	
	
	
		
 
    # current pure-Python implementation isn't a bottleneck for us.


			




	
	
	
		
 
    warnings.filterwarnings('ignore', category=UserWarning, module='thefuzz.fuzz')


			




	
	
	
		
 
from thefuzz import fuzz  # type: ignore


			




	
	
	
		
 

			




	...
	
		
 
@@ -91,17 +91,17 @@ JUNK_WORDS = [


			




	
	
	
		
 
    'online',


			




	
	
	
		
 
    'donation',


			




	
	
	
		
 
    'usd',


			




	
	
	
		
 
    'inc',


			




	
	
	
		
 
]


			




	
	
	
		
 
JUNK_WORDS_RES = [re.compile(word, re.IGNORECASE) for word in JUNK_WORDS]


			




	
	
	
		
 
ZERO_RE = re.compile('^0+')


			




	
	
	
		
 

			




	
	
	
		
 
def remove_duplicate_words(text):


			




	
	
	
		
 
def remove_duplicate_words(text: str) -> str:


			




	
	
	
		
 
    unique_words = []


			




	
	
	
		
 
    known_words = set()


			




	
	
	
		
 
    for word in text.split():


			




	
	
	
		
 
        if word.lower() not in known_words:


			




	
	
	
		
 
            unique_words.append(word)


			




	
	
	
		
 
            known_words.add(word.lower())


			




	
	
	
		
 
    return ' '.join(unique_words)


			




	
	
	
		
 

			




	...
	
		
 
@@ -118,41 +118,56 @@ def remove_payee_junk(payee: str) -> str:


			




	
	
	
		
 
    payee = re.sub(re.escape('.net'), ' ', payee, flags=re.IGNORECASE)


			




	
	
	
		
 
    payee = payee.replace('*', ' ')


			




	
	
	
		
 
    payee = ' '.join([i for i in payee.split(' ') if len(i) > 2])


			




	
	
	
		
 
    payee = payee.replace('-', ' ')


			




	
	
	
		
 
    payee = remove_duplicate_words(payee)


			




	
	
	
		
 
    payee.strip()


			




	
	
	
		
 
    return payee


			




	
	
	
		
 

			




	
	
	
		
 
# NOTE: Statement doesn't seem to give us a running balance or a final total.


			




	
	
	
		
 

			




	
	
	
		
 
def read_transactions_from_csv(f: TextIO, standardize_statement_record: Callable) -> list:


			




	
	
	
		
 
    reader = csv.DictReader(f)


			




	
	
	
		
 
    return sort_records([standardize_statement_record(row, reader.line_num) for row in reader])


			




	
	
	
		
 
    # The reader.line_num is the source line number, not the spreadsheet row


			




	
	
	
		
 
    # number due to multi-line records.


			




	
	
	
		
 
    return sort_records([standardize_statement_record(row, i) for i, row in enumerate(reader, 2)])


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
# Does the account you entered match the CSV?


			




	
	
	
		
 
# Is the CSV in the format we expect? (ie. did they download through the right interface?)


			




	
	
	
		
 
# Logical CSV line numbers


			




	
	
	
		
 
# CSV reconciliation report


			




	
	
	
		
 
# NOTE: Statement doesn't seem to give us a running balance or a final total.


			




	
	
	
		
 
# CSV reconciliation report.


			




	
	
	
		
 
# Merge helper script.


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def standardize_amex_record(row: Dict, line: int) -> Dict:


			




	
	
	
		
 
    """Turn an AMEX CSV row into a standard dict format representing a transaction."""


			




	
	
	
		
 
    return {


			




	
	
	
		
 
        'date': datetime.datetime.strptime(row['Date'], '%m/%d/%Y').date(),


			




	
	
	
		
 
        'amount': -1 * decimal.Decimal(row['Amount']),


			




	
	
	
		
 
        # Descriptions have too much noise, so taking just the start


			




	
	
	
		
 
        # significantly assists the fuzzy matching.


			




	
	
	
		
 
        'payee': remove_payee_junk(row['Description'] or '')[:20],


			




	
	
	
		
 
        'check_id': '',


			




	
	
	
		
 
        'line': line,


			




	
	
	
		
 
    }


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def validate_amex_csv(sample: str, account: str) -> None:


			




	
	
	
		
 
    required_cols = {'Date', 'Amount', 'Description', 'Card Member'}


			




	
	
	
		
 
    reader = csv.DictReader(io.StringIO(sample))


			




	
	
	
		
 
    if reader.fieldnames and not required_cols.issubset(reader.fieldnames):


			




	
	
	
		
 
        sys.exit(f"This CSV doesn't seem to have the columns we're expecting, including: {', '.join(required_cols)}")


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def validate_fr_csv(sample: str, account: str) -> None:


			




	
	
	
		
 
    required_cols = {'Date', 'Amount', 'Detail', 'Serial Num'}


			




	
	
	
		
 
    reader = csv.DictReader(io.StringIO(sample))


			




	
	
	
		
 
    if reader.fieldnames and not required_cols.issubset(reader.fieldnames):


			




	
	
	
		
 
        sys.exit(f"This CSV doesn't seem to have the columns we're expecting, including: {', '.join(required_cols)}")


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def standardize_fr_record(row: Dict, line: int) -> Dict:


			




	
	
	
		
 
    return {


			




	
	
	
		
 
        'date': datetime.datetime.strptime(row['Date'], '%m/%d/%Y').date(),


			




	
	
	
		
 
        'amount': decimal.Decimal(row['Amount']),


			




	
	
	
		
 
        'payee': remove_payee_junk(row['Detail'] or '')[:20],


			




	
	
	
		
 
        'check_id': row['Serial Num'].lstrip('0'),


			




	
	
	
		
 
        'line': line,


			




	
	
	
		
 
    }


			




	...
	
		
 
@@ -176,46 +191,49 @@ def format_record(record: dict) -> str:


			




	
	
	
		
 
        output = f"{record['date'].isoformat()}: {record['amount']:11,.2f} {record['payee'][:25]} #{record['check_id']}".ljust(59)


			




	
	
	
		
 
    elif record['payee']:


			




	
	
	
		
 
        output = f"{record['date'].isoformat()}: {record['amount']:11,.2f} {record['payee'][:35]}".ljust(59)


			




	
	
	
		
 
    else:


			




	
	
	
		
 
        output = f"{record['date'].isoformat()}: {record['amount']:11,.2f} #{record['check_id']}".ljust(59)


			




	
	
	
		
 
    return output


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def format_multirecord(r1s, r2s, note):


			




	
	
	
		
 
def format_multirecord(r1s: list[dict], r2s: list[dict], note: str) -> list[list]:


			




	
	
	
		
 
    total = sum(x['amount'] for x in r2s)


			




	
	
	
		
 
    assert len(r1s) == 1


			




	
	
	
		
 
    assert len(r2s) > 1


			




	
	
	
		
 
    match_output = []


			




	
	
	
		
 
    match_output.append([r1s[0]['date'], f'{format_record(r1s[0])}  →  {format_record(r2s[0])}  ✓ Matched{note}'])


			




	
	
	
		
 
    for r2 in r2s[1:]:


			




	
	
	
		
 
        match_output.append([r1s[0]['date'], f'{r1s[0]["date"].isoformat()}:             ↳                                    →  {format_record(r2)}  ✓ Matched{note}'])


			




	
	
	
		
 
    return match_output


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def sort_records(records: List) -> List:


			




	
	
	
		
 
    return sorted(records, key=lambda x: (x['date'], x['amount']))


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def first_word_exact_match(a, b):


			




	
	
	
		
 
def first_word_exact_match(a: str, b: str) -> float:


			




	
	
	
		
 
    if len(a) == 0 or len(b) == 0:


			




	
	
	
		
 
        return 0


			




	
	
	
		
 
        return 0.0


			




	
	
	
		
 
    first_a = a.split()[0].strip()


			




	
	
	
		
 
    first_b = b.split()[0].strip()


			




	
	
	
		
 
    if first_a.casefold() == first_b.casefold():


			




	
	
	
		
 
        return min(1.0, 0.2 * len(first_a))


			




	
	
	
		
 
    else:


			




	
	
	
		
 
        return 0;


			




	
	
	
		
 
        return 0.0;


			




	
	
	
		
 

			




	
	
	
		
 
def payee_match(a, b):


			




	
	
	
		
 
    fuzzy_match = fuzz.token_set_ratio(a, b) / 100.00


			




	
	
	
		
 

			




	
	
	
		
 
def payee_match(a: str, b: str) -> float:


			




	
	
	
		
 
    fuzzy_match = float(fuzz.token_set_ratio(a, b) / 100.00)


			




	
	
	
		
 
    first_word_match = first_word_exact_match(a, b)


			




	
	
	
		
 
    return max(fuzzy_match, first_word_match)


			




	
	
	
		
 

			




	
	
	
		
 
def records_match(r1: Dict, r2: Dict) -> Tuple[bool, str]:


			




	
	
	
		
 

			




	
	
	
		
 
def records_match(r1: Dict, r2: Dict) -> Tuple[float, List[str]]:


			




	
	
	
		
 
    """Do these records represent the same transaction?"""


			




	
	
	
		
 

			




	
	
	
		
 
    date_score = date_proximity(r1['date'], r2['date'])


			




	
	
	
		
 
    if r1['date'] == r2['date']:


			




	
	
	
		
 
        date_message = ''


			




	
	
	
		
 
    elif date_score > 0.0:


			




	
	
	
		
 
        diff = abs((r1['date'] - r2['date']).days)


			




	
	
	
		
 
        date_message = f'+/- {diff} days'


			




	...
	
		
 
@@ -249,51 +267,54 @@ def records_match(r1: Dict, r2: Dict) -> Tuple[bool, str]:


			




	
	
	
		
 
        else:


			




	
	
	
		
 
            payee_message = 'payee mismatch'


			




	
	
	
		
 

			




	
	
	
		
 
    overall_score = (date_score + amount_score + check_score + payee_score) / 4


			




	
	
	
		
 
    overall_message = [m for m in [date_message, amount_message, check_message, payee_message] if m]


			




	
	
	
		
 
    return overall_score, overall_message


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def match_statement_and_books(statement_trans: list, books_trans: list):


			




	
	
	
		
 
def match_statement_and_books(statement_trans: List[Dict], books_trans: List[Dict]) -> Tuple[List[Tuple[List, List, List]], List[Dict], List[Dict]]:


			




	
	
	
		
 
    """


			




	
	
	
		
 
    Runs through all the statement transactions to find a matching transaction


			




	
	
	
		
 
    in the books. If found, the books transaction is marked off so that it can


			




	
	
	
		
 
    only be matched once. Some transactions will be matched, some will be on the


			




	
	
	
		
 
    statement but not the books and some on the books but not the statement.


			




	
	
	
		
 
    """


			




	
	
	
		
 
    matches = []


			




	
	
	
		
 
    remaining_books_trans = []


			




	
	
	
		
 
    remaining_statement_trans = []


			




	
	
	
		
 

			




	
	
	
		
 
    for r1 in statement_trans:


			




	
	
	
		
 
        best_match_score = 0


			




	
	
	
		
 
        best_match_score = 0.0


			




	
	
	
		
 
        best_match_index = None


			




	
	
	
		
 
        best_match_note = ''


			




	
	
	
		
 
        best_match_note = []


			




	
	
	
		
 
        matches_found = 0


			




	
	
	
		
 
        for i, r2 in enumerate(books_trans):


			




	
	
	
		
 
            score, note = records_match(r1, r2)


			




	
	
	
		
 
            if score >= 0.5 and score >= best_match_score:


			




	
	
	
		
 
                matches_found += 1


			




	
	
	
		
 
                best_match_score = score


			




	
	
	
		
 
                best_match_index = i


			




	
	
	
		
 
                best_match_note = note


			




	
	
	
		
 
        if best_match_score > 0.5 and matches_found == 1 and 'check-id mismatch' not in best_match_note or best_match_score > 0.8:


			




	
	
	
		
 
            matches.append(([r1], [books_trans[best_match_index]], best_match_note))


			




	
	
	
		
 
            # Don't try to make a second match against this books entry.


			




	
	
	
		
 
            del books_trans[best_match_index]


			




	
	
	
		
 
            if best_match_index is not None:


			




	
	
	
		
 
                del books_trans[best_match_index]


			




	
	
	
		
 
        else:


			




	
	
	
		
 
            remaining_statement_trans.append(r1)


			




	
	
	
		
 
    for r2 in books_trans:


			




	
	
	
		
 
        remaining_books_trans.append(r2)


			




	
	
	
		
 
    return matches, remaining_statement_trans, remaining_books_trans


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def format_matches(matches, csv_statement: str, show_reconciled_matches):


			




	
	
	
		
 
# TODO: Return list of tuples (instead of list of lists).


			




	
	
	
		
 

			




	
	
	
		
 
def format_matches(matches: List, csv_statement: str, show_reconciled_matches: bool) -> List[List]:


			




	
	
	
		
 
    match_output = []


			




	
	
	
		
 
    for r1s, r2s, note in matches:


			




	
	
	
		
 
        note = ', '.join(note)


			




	
	
	
		
 
        note = ': ' + note if note else note


			




	
	
	
		
 
        if r1s and r2s:


			




	
	
	
		
 
            if show_reconciled_matches or not all(x['bank_statement'] for x in r2s):


			




	
	
	
		
 
                if len(r2s) == 1:


			




	
	
	
		
 
                    match_output.append([r1s[0]['date'], f'{format_record(r1s[0])}  →  {format_record(r2s[0])}  ✓ Matched{note}'])


			




	...
	
		
 
@@ -301,24 +322,25 @@ def format_matches(matches, csv_statement: str, show_reconciled_matches):


			




	
	
	
		
 
                    match_output.extend(format_multirecord(r1s, r2s, note))


			




	
	
	
		
 
        elif r1s:


			




	
	
	
		
 
            match_output.append([r1s[0]['date'], Fore.RED + Style.BRIGHT + f'{format_record(r1s[0])}  →  {" ":^59}  ✗ NOT IN BOOKS ({os.path.basename(csv_statement)}:{r1s[0]["line"]})' + Style.RESET_ALL])


			




	
	
	
		
 
        else:


			




	
	
	
		
 
            match_output.append([r2s[0]['date'], Fore.RED + Style.BRIGHT + f'{" ":^59}  →  {format_record(r2s[0])}  ✗ NOT ON STATEMENT ({os.path.basename(r2s[0]["filename"])}:{r2s[0]["line"]})' + Style.RESET_ALL])


			




	
	
	
		
 
    return match_output


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def date_proximity(d1, d2):


			




	
	
	
		
 
    diff = abs((d1 - d2).days)


			




	
	
	
		
 
def date_proximity(d1: datetime.date, d2: datetime.date) -> float:


			




	
	
	
		
 
    diff = abs(int((d1 - d2).days))


			




	
	
	
		
 
    if diff > 60:


			




	
	
	
		
 
        return 0


			




	
	
	
		
 
        return 0.0


			




	
	
	
		
 
    else:


			




	
	
	
		
 
        return 1.0 - (diff / 60.0)


			




	
	
	
		
 

			




	
	
	
		
 
def metadata_for_match(match, statement_filename, csv_filename):


			




	
	
	
		
 

			




	
	
	
		
 
def metadata_for_match(match: Tuple[List, List, List], statement_filename: str, csv_filename: str) -> List[Tuple[str, int, str]]:


			




	
	
	
		
 
    # Can we really ever have multiple statement entries? Probably not.


			




	
	
	
		
 
    statement_filename = get_repo_relative_path(statement_filename)


			




	
	
	
		
 
    csv_filename = get_repo_relative_path(csv_filename)


			




	
	
	
		
 
    metadata = []


			




	
	
	
		
 
    statement_entries, books_entries, _ = match


			




	
	
	
		
 
    for books_entry in books_entries:


			




	
	
	
		
 
        for statement_entry in statement_entries:


			




	
	
	
		
 
            if not books_entry['bank_statement']:


			




	...
	
		
 
@@ -356,117 +378,129 @@ def write_metadata_to_books(metadata_to_apply: List[Tuple[str, int, str]]) -> No


			




	
	
	
		
 
        file_contents[filename].insert(line + file_offsets[filename], metadata.rstrip() + '\n')


			




	
	
	
		
 
        file_offsets[filename] += 1


			




	
	
	
		
 
    # Writes each updated file back to disk.


			




	
	
	
		
 
    for filename, contents in file_contents.items():


			




	
	
	
		
 
        with open(filename, 'w') as f:


			




	
	
	
		
 
            f.writelines(contents)


			




	
	
	
		
 
            print(f'Wrote {filename}.')


			




	
	
	
		
 

			




	
	
	
		
 
def get_repo_relative_path(path):


			




	
	
	
		
 

			




	
	
	
		
 
def get_repo_relative_path(path: str) -> str:


			




	
	
	
		
 
    return os.path.relpath(path, start=os.getenv('CONSERVANCY_REPOSITORY'))


			




	
	
	
		
 

			




	
	
	
		
 
def parse_path(path):


			




	
	
	
		
 

			




	
	
	
		
 
def parse_path(path: str) -> str:


			




	
	
	
		
 
    if not os.path.exists(path):


			




	
	
	
		
 
        raise argparse.ArgumentTypeError(f'File {path} does not exist.')


			




	
	
	
		
 
    return path


			




	
	
	
		
 

			




	
	
	
		
 
def parse_repo_relative_path(path):


			




	
	
	
		
 

			




	
	
	
		
 
def parse_repo_relative_path(path: str) -> str:


			




	
	
	
		
 
    if not os.path.exists(path):


			




	
	
	
		
 
        raise argparse.ArgumentTypeError(f'File {path} does not exist.')


			




	
	
	
		
 
    repo = os.getenv('CONSERVANCY_REPOSITORY')


			




	
	
	
		
 
    if not repo:


			




	
	
	
		
 
        raise argparse.ArgumentTypeError(f'$CONSERVANCY_REPOSITORY is not set.')


			




	
	
	
		
 
    if not path.startswith(repo):


			




	
	
	
		
 
        raise argparse.ArgumentTypeError(f'File {path} does not share a common prefix with $CONSERVANCY_REPOSITORY {repo}.')


			




	
	
	
		
 
    return path


			




	
	
	
		
 

			




	
	
	
		
 
def parse_args(argv):


			




	
	
	
		
 

			




	
	
	
		
 
def parse_args(argv: List[str]) -> argparse.Namespace:


			




	
	
	
		
 
    parser = argparse.ArgumentParser(description='Reconciliation helper')


			




	
	
	
		
 
    parser.add_argument('--beancount-file', required=True, type=parse_path)


			




	
	
	
		
 
    parser.add_argument('--csv-statement', required=True, type=parse_repo_relative_path)


			




	
	
	
		
 
    parser.add_argument('--bank-statement', required=True, type=parse_repo_relative_path)


			




	
	
	
		
 
    parser.add_argument('--account', required=True, help='eg. Liabilities:CreditCard:AMEX')


			




	
	
	
		
 
    parser.add_argument('--grep-output-filename')


			




	
	
	
		
 
    # parser.add_argument('--report-group-regex')


			




	
	
	
		
 
    parser.add_argument('--show-reconciled-matches', action='store_true')


			




	
	
	
		
 
    parser.add_argument('--statement-balance', type=decimal.Decimal, required=True, help="A.K.A \"cleared balance\" taken from the end of the period on the PDF statement. Required because CSV statements don't include final or running totals")


			




	
	
	
		
 
    parser.add_argument('--non-interactive', action='store_true', help="Don't prompt to write to the books")


			




	
	
	
		
 
    return parser.parse_args(args=argv[1:])


			




	
	
	
		
 

			




	
	
	
		
 
def totals(matches):


			




	
	
	
		
 

			




	
	
	
		
 
def totals(matches: List[Tuple[List, List, List]]) -> Tuple[decimal.Decimal, decimal.Decimal, decimal.Decimal]:


			




	
	
	
		
 
    total_matched = decimal.Decimal(0)


			




	
	
	
		
 
    total_missing_from_books = decimal.Decimal(0)


			




	
	
	
		
 
    total_missing_from_statement = decimal.Decimal(0)


			




	
	
	
		
 
    for statement_entries, books_entries, _ in matches:


			




	
	
	
		
 
        if statement_entries and books_entries:


			




	
	
	
		
 
            total_matched += sum(c['amount'] for c in statement_entries)


			




	
	
	
		
 
        elif statement_entries:


			




	
	
	
		
 
            total_missing_from_books += sum(c['amount'] for c in statement_entries)


			




	
	
	
		
 
        else:


			




	
	
	
		
 
            total_missing_from_statement += sum(c['amount'] for c in books_entries)


			




	
	
	
		
 
    return total_matched, total_missing_from_books, total_missing_from_statement


			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def subset_match(statement_trans, books_trans):


			




	
	
	
		
 
def subset_match(statement_trans: List[dict], books_trans: List[dict]) ->  Tuple[List[Tuple[List, List, List]], List[Dict], List[Dict]]:


			




	
	
	
		
 
    matches = []


			




	
	
	
		
 
    remaining_books_trans = []


			




	
	
	
		
 
    remaining_statement_trans = []


			




	
	
	
		
 

			




	
	
	
		
 
    groups = itertools.groupby(books_trans, key=lambda x: (x['date'], x['payee']))


			




	
	
	
		
 
    for k, group in groups:


			




	
	
	
		
 
        best_match_score = 0


			




	
	
	
		
 
        best_match_score = 0.0


			




	
	
	
		
 
        best_match_index = None


			




	
	
	
		
 
        best_match_note = ''


			




	
	
	
		
 
        best_match_note = []


			




	
	
	
		
 
        matches_found = 0


			




	
	
	
		
 

			




	
	
	
		
 
        group_items = list(group)


			




	
	
	
		
 
        total = sum(x['amount'] for x in group_items)


			




	
	
	
		
 
        r2 = copy.copy(group_items[0])


			




	
	
	
		
 
        r2['amount'] = total


			




	
	
	
		
 
        for i, r1 in enumerate(statement_trans):


			




	
	
	
		
 
            score, note = records_match(r1, r2)


			




	
	
	
		
 
            if score >= 0.5 and score >= best_match_score:


			




	
	
	
		
 
                matches_found += 1


			




	
	
	
		
 
                best_match_score = score


			




	
	
	
		
 
                best_match_index = i


			




	
	
	
		
 
                best_match_note = note


			




	
	
	
		
 
        if best_match_score > 0.5 and matches_found == 1 and 'check-id mismatch' not in best_match_note or best_match_score > 0.8:


			




	
	
	
		
 
            if best_match_score <= 0.8:


			




	
	
	
		
 
                best_match_note.append('only one decent match')


			




	
	
	
		
 
            matches.append(([statement_trans[best_match_index]], group_items, best_match_note))


			




	
	
	
		
 
            del statement_trans[best_match_index]


			




	
	
	
		
 
            if best_match_index is not None:


			




	
	
	
		
 
                del statement_trans[best_match_index]


			




	
	
	
		
 
            for item in group_items:


			




	
	
	
		
 
                # TODO: Why?


			




	
	
	
		
 
                books_trans.remove(item)


			




	
	
	
		
 
        else:


			




	
	
	
		
 
            remaining_books_trans.append(r2)


			




	
	
	
		
 
    for r1 in statement_trans:


			




	
	
	
		
 
         remaining_statement_trans.append(r1)


			




	
	
	
		
 
    return matches, remaining_statement_trans, remaining_books_trans


			




	
	
	
		
 

			




	
	
	
		
 
def process_unmatched(statement_trans, books_trans):


			




	
	
	
		
 
    matches = []


			




	
	
	
		
 

			




	
	
	
		
 
def process_unmatched(statement_trans: List[dict], books_trans: List[dict]) -> List[Tuple[List, List, List]]:


			




	
	
	
		
 
    matches: List[Tuple[List, List, List]] = []


			




	
	
	
		
 
    for r1 in statement_trans:


			




	
	
	
		
 
        matches.append(([r1], [], ['no match']))


			




	
	
	
		
 
    for r2 in books_trans:


			




	
	
	
		
 
        matches.append(([], [r2], ['no match']))


			




	
	
	
		
 
    return matches


			




	
	
	
		
 

			




	
	
	
		
 
def main(args):


			




	
	
	
		
 

			




	
	
	
		
 
def main(args: argparse.Namespace) -> None:


			




	
	
	
		
 
    # TODO: Should put in a sanity check to make sure the statement you're feeding


			




	
	
	
		
 
    # in matches the account you've provided.


			




	
	
	
		
 

			




	
	
	
		
 
    # TODO: Can we open the files first, then pass the streams on to the rest of the program?


			




	
	
	
		
 

			




	
	
	
		
 
    if 'AMEX' in args.account:


			




	
	
	
		
 
        validate_csv = validate_amex_csv


			




	
	
	
		
 
        standardize_statement_record = standardize_amex_record


			




	
	
	
		
 
    else:


			




	
	
	
		
 
        validate_csv = validate_fr_csv


			




	
	
	
		
 
        standardize_statement_record = standardize_fr_record


			




	
	
	
		
 

			




	
	
	
		
 
    with open(args.csv_statement) as f:


			




	
	
	
		
 
        sample = f.read(200)


			




	
	
	
		
 
        validate_csv(sample, args.account)


			




	
	
	
		
 
        f.seek(0)


			




	
	
	
		
 
        statement_trans = read_transactions_from_csv(f, standardize_statement_record)


			




	
	
	
		
 

			




	
	
	
		
 
    begin_date = statement_trans[0]['date']


			




	
	
	
		
 
    end_date = statement_trans[-1]['date']


			




	
	
	
		
 

			




	
	
	
		
 
    # Do we traverse and filter the in-memory entries list and filter that, or do we


			




	
	
	
		
 
    # use Beancount Query Language (BQL) to get a list of transactions? Currently


			




	
	
	
		
 
    # using BQL.


			




        

    


    
    

    

        

                

                    tests/test_reconcile.py
                

                

                  
                      
                        

                      ➞

                      
                        
                  

                  
                      
                  
                      
                  
                      
                  
                      
                  
                  
                

                

                    Show inline comments
                    
                

        

        

            



	...
	
		
 
@@ -213,17 +213,17 @@ def test_incorrect_amount_does_not_match():


			




	
	
	
		
 
        [S3],


			




	
	
	
		
 
        [B3_mismatch_amount],


			




	
	
	
		
 
    )


			




	
	
	
		
 

			




	
	
	
		
 
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'])],


			




	
	
	
		
 
        [([S3], [B3_payee_mismatch_1], ['payee mismatch'])],


			




	
	
	
		
 
        [],


			




	
	
	
		
 
        [],


			




	
	
	
		
 
    )


			




	
	
	
		
 

			




	
	
	
		
 
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)


			




	...
	
		
 
@@ -250,18 +250,18 @@ def test_remove_duplicate_words():


			




	
	
	
		
 

			




	
	
	
		
 
def test_payee_matches_when_first_word_matches():


			




	
	
	
		
 
    assert payee_match('Gandi San Francisco', 'Gandi example.com renewal 1234567') == 1.0


			




	
	
	
		
 
    assert payee_match('USPS 123456789 Portland', 'USPS John Brown') == 0.8


			




	
	
	
		
 

			




	
	
	
		
 
def test_metadata_for_match(monkeypatch):


			




	
	
	
		
 
    monkeypatch.setenv('CONSERVANCY_REPOSITORY', '.')


			




	
	
	
		
 
    assert metadata_for_match(([S1], [B1], []), 'statement.pdf', 'statement.csv') == [


			




	
	
	
		
 
        ('2022/imports.beancount', 777, '    bank-statement: statement.pdf'),


			




	
	
	
		
 
        ('2022/imports.beancount', 777, '    bank-statement-csv: statement.csv:222'),


			




	
	
	
		
 
        ('2022/imports.beancount', 777, '    bank-statement: "statement.pdf"'),


			




	
	
	
		
 
        ('2022/imports.beancount', 777, '    bank-statement-csv: "statement.csv:222"'),


			




	
	
	
		
 
    ]


			




	
	
	
		
 

			




	
	
	
		
 
def test_no_metadata_if_no_matches():


			




	
	
	
		
 
    assert metadata_for_match(([S1], [], ['no match']), 'statement.pdf', 'statement.csv') == []


			




	
	
	
		
 
    assert metadata_for_match(([], [B1], ['no match']), 'statement.pdf', 'statement.csv') == []


			




	
	
	
		
 
    assert metadata_for_match(([S1], [B2], ['no match']), 'statement.pdf', 'statement.csv') == []


			




	
	
	
		
 

			




	
	
	
		
 
def test_write_to_books():


			




        

    



    


    



    



      

      





    
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