# Build brief — a focused alternative to BlackLine

> **Verdict:** Not faithfully · **Buildability:** 13/100 · **Category:** Finance Accounting
> **Source:** https://www.canitbevibecoded.com/blackline
> Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from BlackLine. Verify current pricing and capabilities before acting.

## Context

**BlackLine** — Enterprise accounting automation for the financial close: account reconciliations, journal entries, matching, and audit trails on top of your ERP.

You can absolutely build a transaction matcher: read two CSVs, fuzzy match on amount and date, flag the leftovers. That is maybe five percent of what BlackLine is being paid for. The rest is certified reconciliations with named preparers and reviewers, immutable audit trails an external auditor will accept, SOX control evidence, multi-entity intercompany elimination, and live connectors into SAP, Oracle and NetSuite that survive a chart-of-accounts change. A personal replacement is a category error here: nobody buys this for themselves, a controller buys it so the audit does not become a quarter-long forensic exercise. If you are a solo operator reconciling one bank account against one ledger, you never needed it anyway.

This brief describes a focused, single-operator replacement for the part of BlackLine that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.

## What you are building

Ingest a bank CSV and a ledger CSV, auto-match on amount plus date tolerance plus reference fuzz, and produce a reconciliation report listing matched pairs, unmatched items on each side, and a running difference.

- Model a narrow bookkeeping workflow with explicit review and export steps.
- A responsive interface with real empty, loading, success, and error states.

## Requirements

### Functional

- Python 3.11 and a local terminal.
- CSV exports from your bank and your accounting system.
- Willingness to hand-tune matching rules for your own transaction descriptions.
- No auditor who needs to sign off on the result.

### Non-functional

- Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
- Security: server-side secrets, validated input, and no credentials in the client bundle.
- Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
- Portability: the operator can export their data and leave without losing it.

## Implementation brief

Build a local, single-user bank reconciliation tool. No accounts, no cloud, no telemetry, no hosted anything.

Stack, non-negotiable:
- Python 3.11
- Typer for the CLI
- pandas for CSV handling
- SQLite via sqlite3 for persistence (file: recon.db)
- Jinja2 to render a static HTML report
- pytest for tests
No web server, no auth, no Docker, no external API calls.

What it does:
1. `recon import --side bank --file path.csv` and `--side ledger` ingest CSVs into SQLite. Support column mapping via a mapping.yml so the user can point date/amount/description/reference at their own headers. Store a stable row hash so re-importing the same file does not duplicate rows.
2. `recon match --period 2026-07` runs matching in passes, most confident first: (a) exact amount + exact reference, (b) exact amount within a configurable date window (default 3 days), (c) exact amount + fuzzy description via difflib ratio above a threshold, (d) many-to-one sums where several ledger lines total one bank line, capped at 4 lines to keep it tractable. Every match records the pass that made it and a confidence score.
3. `recon review --period 2026-07` interactive CLI: step through low-confidence and unmatched items, accept, reject, or tag as a known timing difference or fee. Decisions persist so re-running match does not undo human calls.
4. `recon report --period 2026-07 --out report.html` renders: opening balance, matched total, unmatched bank items, unmatched ledger items, tagged differences, and the closing difference that must reconcile to zero. Include a plain-text summary printed to stdout.
5. `recon rules` reads rules.yml for auto-tagging patterns (regex on description to category), applied during match.

Explicitly out of scope: multi-entity consolidation, FX revaluation, journal entry posting, approval workflows, ERP connectors, anything claiming to be audit evidence.

Deliverables: README with a worked example using two generated sample CSVs, mapping.yml and rules.yml examples, tests covering each matching pass plus the many-to-one case, and a Makefile with install/test/demo targets. Config paths and thresholds in .env or config.yml, never hardcoded. Print a one-line disclaimer in the report footer: this is a personal tool, not audit evidence.

## Delivery standard

- Inspect the repository first, then write a short implementation plan before writing code.
- Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
- Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
- Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
- Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
- Add structured logs around every external call and return actionable errors without leaking sensitive details.
- Write unit tests for the core logic and one automated test of the main user journey.
- Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.

## Acceptance criteria

- [ ] A clean install starts the app using only the README and .env.example.
- [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
- [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
- [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
- [ ] Tests, type checking, linting, and a production build all pass with no ignored failures.
- [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.

## Non-goals

Do not build these, and do not claim to have replaced them:

- Audit-defensible evidence: preparer/reviewer sign-off, timestamps, locked periods, nothing editable after certification.
- SOX and internal-control reporting that auditors already know how to read.
- Live ERP integrations (SAP, Oracle, NetSuite, Dynamics) instead of manual CSV exports.
- Multi-entity and intercompany handling, FX, and consolidation-scale volumes.
- Someone accountable when the numbers are wrong at year end.

## What you still own after launch

- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.
- Maintain every third-party integration as APIs and OAuth rules change.

## Risk

**High consequence.** Use this as a prototype or personal aid. Keep a qualified human and an established provider in the loop for consequential decisions.

Editorial confidence in this assessment: medium. No reviewed project implementation is linked yet.

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Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/blackline