Michael 10015c40e1 fix(pdf): shim image_to_url for drawable-canvas on modern Streamlit
User hit ``AttributeError: module 'streamlit.elements.image' has
no attribute 'image_to_url'`` on first PDF import. Root cause:
``streamlit-drawable-canvas`` 0.9.3 (last upstream release 2023)
calls a Streamlit internal that was relocated in Streamlit
~1.30+. The function moved from ``streamlit.elements.image`` to
``streamlit.elements.lib.image_utils`` AND its signature
changed — the second positional argument is now a
``LayoutConfig`` dataclass instead of a plain ``int`` width.

Three remedies considered:

1. Downgrade Streamlit. Reverses unrelated improvements +
   security fixes; not on the table.
2. Fork drawable-canvas. The maintenance hit isn't worth it for a
   one-line internal API change.
3. **Ship a compatibility shim.** Re-attach a wrapper at the old
   import path that adapts the old call shape to the new
   function. This is the standard workaround the wider Streamlit
   community has converged on for this exact regression.

``src/gui/_drawable_canvas_compat.py`` does (3). The ``install()``
helper is idempotent, opt-in (not auto-run at module import — a
grep for ``_install_canvas_compat`` shows every call site), and
no-ops if Streamlit hasn't moved the function OR if the new
function isn't where we expect (lets the canvas surface a real
error rather than papering over a different bug). The page calls
``_install_canvas_compat()`` once at module top before any
``st_canvas`` invocation; Streamlit's script-rerun model means
this fires every page load but the ``_PATCHED`` guard makes
re-runs free.

The shim wraps the old ``width=int`` arg into a default-constructed
``LayoutConfig()`` — the old ``width=-1`` sentinel meant "use
the image's natural width", which is also what an unconfigured
LayoutConfig produces. Confirmed by inspecting Streamlit 1.57.0's
``image_utils.py``.

4 new tests pin the shim contract:

- ``install()`` attaches ``image_to_url`` to the old path on modern
  Streamlit
- Idempotent — calling twice doesn't double-wrap
- Doesn't clobber a future Streamlit that restores the original
  at the old path
- Translates ``(image, -1, False, "RGB", "PNG", "id")`` into a
  proper call to the new function with a ``LayoutConfig`` instance

If a future Streamlit upgrade moves ``image_to_url`` AGAIN, the
shim's silent-no-op fallback means the canvas error surfaces
again and points at where to look. The shim doesn't paper over
mysteries; it only patches the one specific relocation we know
about.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 23:29:20 +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

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 ~150200 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 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.

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