Michael fd9606c67b build: drop the local Python release method, return to CI-only installer builds
Removes the single-command Python packaging method (build/make_release.py
+ build/build_portable_zip.py + build/macos/build_zip.sh) and the portable
.zip artifacts it produced. Release builds go back to the original GitHub
Actions process: the CI matrix builds one installer per platform (.dmg /
.exe / .AppImage) on tag push and attaches them to a GitHub Release.

Tesseract OCR bundling is preserved: the fetch helpers the workflow depends
on (fetch_tessdata, fetch_tesseract_for_platform) are extracted into a
standalone build/tesseract.py, which build.yml now imports.

Docs (README, build/README, DEVELOPER, TECHNICAL, USER-GUIDE, vendor README,
es translations) updated to drop the portable-zip flavor and point at the
new module.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 17:47:36 +00:00

🌐 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

Every tool page has an in-tool Help popover (right of the title) with a compact When-to-use / Steps / Examples / Tip card. Copy lives in the language packs (tools.<id>.help_md).

Download (non-technical users)

Pre-built bundles — no Python install, no admin rights, no internet at runtime. Each release ships an installer per OS that wires up Desktop + Start Menu / Launchpad shortcuts.

Platform Installer
macOS DataTools-X.Y.Z-mac.dmg — open, drag DataTools.app into /Applications, launch from Launchpad.
Windows DataTools-X.Y.Z-win-setup.exe — run installer (per-user, no admin). Desktop shortcut + Start Menu entry created.
Linux DataTools-X.Y.Z-linux-x86_64.AppImagechmod +x, double-click. The AppImage is already portable.

Latest release: see GitHub Releases (or the Gumroad listing). Each bundle is ~300 MB unpacked; on first launch the app starts a local server at http://127.0.0.1:8501 and opens your default browser. Nothing leaves your machine.

Tesseract OCR is bundled. Scanned-PDF support in the PDF Extractor works out of the box on all three platforms — no separate Tesseract install required. License attribution: see LICENSE_TESSERACT.txt.

First-launch warnings (one-time):

  • macOS unsigned builds: right-click → Open → confirm. (Signed builds skip this.)
  • Windows SmartScreen: click More infoRun anyway.

Detailed install + troubleshooting walkthrough: User Guide §1.

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 trail
  • logs/<tool>_YYYYMMDD_HHMMSS.log — debug-level run log

Original input file is never modified.

Docs

Dependencies

pandas, openpyxl, rapidfuzz, phonenumbers, typer, loguru, charset-normalizer, streamlit. Optional: ftfy for mojibake repair.

License

Proprietary.

Description
Data tools development
Readme 7.7 MiB
Languages
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HTML 10%
CSS 1.8%
Shell 0.4%
JavaScript 0.2%
Other 0.2%