FargoImport/README.md

FargoImport extractor

This utility reads a HAR-style JSON file (for example posted.dat), scans:

• log.entries[*].response.content.text

It only processes text values that start with:

• /*WellFargoProprietary%

For each matching value, it extracts the JSON string between:

• start: /*WellFargoProprietary%
• end: %WellFargoProprietary*/

Then it parses that extracted string with Python json.loads and outputs the resulting Python objects.

Run

python .\main.py --input .\posted.dat

Optionally write extracted objects to a file:

python .\main.py --input .\posted.dat --output .\extracted.json

Show parse/skip errors while extracting:

python .\main.py --input .\posted.dat --show-errors

For HAR files where the payload is specifically at /log/entries/0/response/content/text, use:

python .\main.py --input .\checking.dat --entry0-only --output .\checking_extracted.json

Programmatic usage

from wf_debit_extractor import WellsFargoPayloadExtractor

extractor = WellsFargoPayloadExtractor()
objects = extractor.extract_from_file("posted.dat")

# For entry0-only HAR variants:
# objects = extractor.extract_from_file("checking.dat", entry0_only=True)

# Access converted Python objects.
print(len(objects))
print(extractor.get_objects()[0])

# Optional: review skipped/parse errors.
print(extractor.errors)

Legacy imports from main still work, but wf_debit_extractor is now the preferred module for programmatic use.

Transaction Processing

Once you've extracted WellsFargo payloads, use transaction_processor.py to extract and transform transaction data.

from transaction_processor import TransactionProcessor
from wf_debit_extractor import WellsFargoPayloadExtractor

# Extract payloads
extractor = WellsFargoPayloadExtractor()
payloads = extractor.extract_from_file("posted.dat")

# Process transactions
processor = TransactionProcessor()
transactions = processor.extract_transactions(payloads)

# Each transaction has:
#  - id (string)
#  - transaction_amount_cents (integer, e.g., 9.11 → 911)
#  - transaction_date_timestamp (milliseconds since epoch)
#  - transaction_date_datetime (Python datetime object)
#  - post_date_timestamp (milliseconds since epoch)
#  - post_date_datetime (Python datetime object)
#  - transaction_description (string)

for txn in transactions:
    print(txn["id"], txn["transaction_amount_cents"], txn["transaction_description"])

See example_usage.py for a working example that also saves all transactions to processed_transactions.json.

YNAB Integration

Use ynab_client.py to fetch transactions from your YNAB account. Configuration is loaded from ynab.yml which should contain your YNAB token, plan ID, and account IDs to track.

from ynab_client import YNABClient

# Initialize with config file
client = YNABClient("ynab.yml")

# Fetch transactions from past 30 days
transactions = client.get_transactions_for_days(days=30)

# Each transaction includes:
#  - id
#  - date (YYYY-MM-DD)
#  - payee_name
#  - category_name
#  - amount_milliCurrency (in milliCurrency units, divide by 1000 for dollars)
#  - memo
#  - account_id
#  - account_name
#  - cleared (cleared status)

for txn in transactions:
    print(f"{txn['date']} | {txn['payee_name']} | ${txn['amount_milliCurrency'] / 1000:.2f}")

# Get account balance
balance = client.get_account_balance("7282c2e6-0470-423d-9748-ec36e29f5698")
print(f"Balance: ${balance / 1000:.2f}")

See ynab_example.py for a complete example that also saves all transactions to ynab_transactions.json.

Export YNAB Transactions to CSV

Write transactions from the configured credit and debit accounts for the past 60 days:

python .\main.py --record-transactions

Set a different lookback (1–240 days) and output path:

python .\main.py --record-transactions=90 --transactions-csv .\exports\transactions.csv

The default output is transactions.csv. It contains only payee, category, inflow, and outflow columns. Split transactions are written as one row per subcategory, keeping the parent transaction's payee on each row. The misspelled --record-trasactions option is also accepted as an alias.

When importing bank transactions with --ynab-import, the importer uses transactions.csv and a reusable category_memory.json sidecar to suggest categories from similar payees, transaction direction, and amount. Confident suggestions are sent to YNAB; uncertain ones appear with a ? in the preview and remain uncategorized. Each explicit --record-transactions export merges new patterns into the sidecar, so they remain available after older rows leave the CSV. Keep or sync both files between machines; the sidecar contains normalized payee/category/amount patterns but no transaction dates or IDs.

ynab.yml Format

ynab:
  - token: "your_ynab_api_token_here"
    plan_id: "your_budget_id_here"
    accounts:
        - name: "Credit Card"
          id: "account_id_here"

Integration & Reconciliation

Use reconcile.py to fetch both WellsFargo and YNAB transactions side-by-side for reconciliation.

python .\reconcile.py

This will:

1. Extract WellsFargo transactions from posted.dat
2. Fetch YNAB transactions for past 30 days
3. Display summary comparison
4. Save combined report to reconciliation_report.json

Example Output

============================================================
RECONCILIATION SUMMARY
============================================================
WellsFargo transactions: 179
WellsFargo total: $5,432.15

YNAB transactions: 42
YNAB total: $3,210.50
============================================================

Note: Ensure your YNAB API token in ynab.yml is valid and has permission to access the budget/plan specified.