Michael
981a1a9cba
User reported downloads "do nothing on click" in tool pages and
"acts like it downloads but no file in the folder" in the PDF
tool. Two root causes, two fixes.
**Root cause #1 — wrong Downloads folder on Windows.**
``_downloads_dir()`` returned ``Path.home() / "Downloads"``
unconditionally. On Windows machines with OneDrive enabled
(very common for business users), the real Downloads folder
is redirected to ``C:\Users\<u>\OneDrive\Downloads``. Our
helper would write to ``C:\Users\<u>\Downloads`` instead —
a folder that may not even exist until ``mkdir`` creates it —
and the user, naturally opening their actual OneDrive
Downloads, sees no file and concludes nothing happened.
Now: on Windows, ``_downloads_dir`` queries the registry key
``Software\Microsoft\Windows\CurrentVersion\Explorer\User
Shell Folders`` for FOLDERID_Downloads (GUID
``{374DE290-123F-4565-9164-39C4925E467B}``). This entry returns
the redirected path when OneDrive is active, the original
``%USERPROFILE%\Downloads`` otherwise — exactly what the user's
File Explorer reads. ``%USERPROFILE%`` expansion is applied
via ``os.path.expandvars``. Any registry hiccup falls through
to ``Path.home() / "Downloads"`` so the helper never raises.
The sanity check (path exists OR parent exists) catches the
edge case where the registry points into a deleted OneDrive
mount.
**Root cause #2 — PDF page used st.download_button.**
Every other tool uses the project's ``html_download_button``
helper (which is ``local_download_button`` under the hood —
the rename happened in b9147f3). ``st.download_button`` has a
long-standing bug where the second-or-later instance in a
script pass silently fails to fire. The PDF tool predated the
rewrite that switched everyone over and was still using the
broken native widget. ``_Logs.py`` had the same problem in two
places.
Swapped all three call sites to ``html_download_button``. They
now save to ``~/Downloads/<filename>`` (correctly resolved per
fix #1) and show the saved path + "Open Downloads folder"
button below the click, matching every other tool in the suite.
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.