Four issues batched together since they all touch the GUI shell:
- ``stMainBlockContainer``'s ``padding-bottom`` bumped from 0.75rem
→ 4rem (~one button-height of free space above the fixed Help/Close
footer). The last line of content on a page that fills the viewport
was previously sitting flush against the footer's top border.
- Farewell overlay's "Close this window" button removed per UX
request. The auto-dismiss path is now the only flow: try
programmatic close (works in Chrome/Edge ``--app`` windows);
failing that, surface the hint and redirect the parent window to
``about:blank`` after a short timeout. Previously the user had to
click the button to get the same fallback. The
``quit.close_window_button`` i18n key is retained as a no-op for
now in case the button comes back; nothing references it.
- Sidebar collapse → expand was broken: clicking « collapsed the
sidebar but the » expand-back affordance was invisible. Two causes
pulled apart:
1. ``.dt-brand { flex: 1 }`` was eating the entire
``stSidebarHeader`` width, squeezing Streamlit's
``stSidebarCollapseButton`` off the right edge. Changed to
``margin: 0 auto 0 0`` so the brand keeps its natural width
and the chevron has room to live next to it.
2. The "hide Streamlit chrome" toolbar block was listing
``stToolbar`` and ``stToolbarActions`` for ``display: none``
— but the post-collapse re-open button
(``stExpandSidebarButton``) lives inside ``stToolbar``, so
hiding the container killed the button too. Dropped both
container testids from the hide list and kept the per-icon
rules for ``stMainMenu`` / ``stAppDeployButton`` /
``stStatusWidget`` / ``stDecoration``.
- Loguru's stderr sink quieted in GUI mode. ``src/gui/app.py`` now
runs ``logger.remove()`` + ``logger.add(sys.stderr, level="ERROR",
…)`` at the top so internal ``logger.debug`` / ``logger.warning``
breadcrumbs (e.g.
``standardize_dataframe: 7/31 cells were unparseable``) no longer
print to the terminal when the user runs ``python -m src.gui``.
CLI entry points already do the same configuration per-script.
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.