Michael
967d3f6a11
Phase 6/6. Final polish layer on top of the OCR pipeline that ``extract_pages_auto`` has carried since commit 1. - **OCR status banner** at the top of the page next to the mode selector. Ready: a one-liner caption confirming OCR will run on scanned pages. Unavailable: a collapsed expander explaining the missing piece (``pytesseract`` binding vs. Tesseract binary) with install pointers for Windows, macOS, and Linux. The expander explicitly notes that modern text-based bank statements don't need OCR — most users will never expand it. - **"Use OCR for scanned pages" toggle** in Extract mode, defaulting to the runtime availability. Disabled (greyed out) when Tesseract isn't usable, so the user can't accidentally set themselves up for confusing warnings. Passes through as ``allow_ocr`` to ``extract_pages_auto``. - Build mode's sample-loading path continues to call ``extract_pages_auto(..., allow_ocr=True)`` — sample preview always uses OCR if available, since the user is actively diagnosing template fit. No schema change. OCR's structural support is in commits 1 + 3; this commit just makes it discoverable + opt-out. Rolling up the 6-commit feature:b8aff86Phase 1 — pure pdf_extract module + testsaea520dPhase 2 — template storage layer + tests2f349e8Phase 3 — Extract/Build/Manage page + nav + i18n5a8e2ecPhase 4 — batch polish (ZIP, sort, status block)b86828dPhase 5 — visual region picker (drawable canvas) THIS Phase 6 — OCR banner + toggle Each commit is independently revertable; rolling all the way back to ``c16e2a5`` is ``git revertb86828d5a8e2ec2f349e8aea520db8aff86<this>`` (or just ``git reset --hard c16e2a5`` on a clean branch). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
🌐 Language: English · Español
DataTools
Local CSV / Excel cleaning. CLI + browser GUI, no cloud, no install ceremony. GUI ships with English and Spanish language packs.
Tools
| # | Tool | Status |
|---|---|---|
| 01 | Find Duplicates — exact + fuzzy match, 5 normalizers, survivor rules, audit | Ready |
| 02 | Clean Text — whitespace, smart chars, BOM, line endings, case ops | Ready |
| 03 | Standardize Formats — dates, phones, emails, addresses, names, currencies, booleans | Ready |
| 04 | Fix Missing Values — disguised-null detection, profile, mean/median/mode/ffill/bfill/interpolate, drop strategies | Ready |
| 05 | Map Columns — fuzzy auto-rename, target schema with type coercion, required fields with defaults, drop/reorder | Ready |
| 06 | Find Unusual Values | Coming Soon |
| 07 | Combine Files | Coming Soon |
| 08 | Quality Check | Coming Soon |
| 09 | Automated Workflows — chain tools with recommended (not forced) order, save/load JSON, automate weekly cleanups | Ready |
Download (non-technical users)
Pre-built installers — no Python required:
| Platform | Download | First-launch note |
|---|---|---|
| macOS | DataTools-X.Y.Z-mac.dmg |
Drag DataTools.app into /Applications, then double-click. |
| Windows | DataTools-X.Y.Z-win-setup.exe |
Run the installer; launches from Start Menu. |
| Linux | DataTools-X.Y.Z-linux-x86_64.AppImage |
chmod +x the file, then double-click. |
Latest release: see GitHub Releases (or the Gumroad listing). The installers are ~150–200 MB; the launcher boots a local server at http://127.0.0.1:8501 and opens your browser. Nothing is sent to the cloud.
Install from source (developers)
pip install -r requirements.txt
Python 3.10+ required.
Run
GUI (recommended):
streamlit run src/gui/app.py
CLI — seven entry points:
python -m src.cli customers.csv [--apply] # dedup
python -m src.cli_text_clean messy.csv [--apply] # text clean
python -m src.cli_format intl.csv [--apply] # format standardize (auto-streams >100 MB)
python -m src.cli_missing holes.csv [--apply] # missing values
python -m src.cli_column_map vendor.csv [--apply] # column mapper
python -m src.cli_pipeline any_file.csv [--apply] # chain tools end-to-end
python -m src.cli_analyze any_file.csv [--json] # scan only
Every CLI runs preview-only by default; add --apply to write output.
Language
The GUI sidebar has a language picker. Packs ship for English and Español (src/i18n/packs/); the choice persists for the session. Adding a language: drop a <code>.json next to en.json mirroring its key tree, then list it in LANGUAGES. See Developer Guide §i18n.
Review & Normalize gate
Every uploaded file passes through a CSV-normalization gate before any tool sees it. The analyzer flags ~15 issue types (whitespace, NBSP / zero-width chars, BOM, encoding, smart punct, dirty headers, null sentinels, mojibake, …) tagged by confidence (high / medium / low) and fix action. The GUI shows each finding with Auto-fix / Skip / Customize, a live before/after preview, and an encoding-override picker. Tool pages refuse to load until the gate passes.
Output
Every run writes:
{input}_<tool>.csv— the cleaned data{input}_changes.csv(text cleaner) or{input}_match_groups.csv(dedup) — audit traillogs/<tool>_YYYYMMDD_HHMMSS.log— debug-level run log
Original input file is never modified.
Docs
- User Guide — install, GUI workflow, gate
- CLI Reference — every flag with recipes
- Requirements — file sizes, encodings, detectors, perf targets
- Technical — architecture, gate internals, fix registry
- Developer Guide — adding fixes / detectors / standardizers
Dependencies
pandas, openpyxl, rapidfuzz, phonenumbers, typer, loguru, charset-normalizer, streamlit. Optional: ftfy for mojibake repair.
License
Proprietary.