Build a corpus of 35 deliberately-broken files (empty bytes, NUL
bytes, mojibake, UTF-16 without BOM, mismatched columns, unescaped
quotes, corrupt zip, etc.) and pin the analyzer's stability contract
against them.
Files land in ``test-cases/junk-corpus/test_data/``. The generator
``make_junk_corpus.py`` produces them deterministically (one random
sample uses ``secrets.token_bytes`` — committed bytes are stable
across regenerations because the byte stream is captured at commit
time). README documents the categories and how to add new shapes.
``tests/test_junk_corpus.py`` parametrizes over every file in the
corpus and asserts:
1. ``_run_analysis_on_upload`` never raises — exceptions must be
caught and surfaced as a synthetic ``Finding`` with
severity="error". This was the user-reported crash for
13_non_latin_scripts.csv that the previous fix in ae9d4a2
defensively wrapped; the corpus now stops the regression
from re-landing on a different shape.
2. Every Finding in the result list is well-formed (string id,
valid severity, non-empty description).
3. A high-risk subset (empty.csv, only_bom.csv, only_nul.csv,
corrupt_xlsx.xlsx) MUST surface at least one error-level
Finding — otherwise the GUI would render "no issues found"
for a structurally broken file.
4. Error-level Finding descriptions are at least 20 chars so the
UI banner gives the user something to act on.
Also exclude ``junk-corpus`` from ``tests/test_fixtures_sweep.py``
since that sweep is happy-path (round-trip the text cleaner) and
fights with files designed to break it. The contract is enforced
by the dedicated junk-corpus test, not the sweep.
Runtime: 12 s for the junk-corpus tests, 30 s for the full
project suite (was 19 s without these). 2118 tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds src/core/format_standardize.py — a per-cell standardizer for dates,
phones, emails, addresses, names, currencies, booleans — wired through
StandardizeOptions / standardize_dataframe with FieldType registry.
Includes:
- Date parser handles ISO/US/EU/longform/excel-serial/unix-timestamp/
partial-precision/quarter notation; opt-in French/German/Spanish month
dictionaries via month_locales.
- Phone via libphonenumber with extension preservation (;ext=N), 001
international prefix handling, error sentinels for placeholders /
multi-number cells.
- Email lowercase/trim/mailto/angle-bracket strip with optional
--gmail-canonical mode.
- Address USPS abbreviation expansion or compression (expand=False per
corpus § 6.3), state-name → 2-letter conversion, multi-line collapse,
PO Box normalization, state-code preservation regardless of input case.
- Name handler: Mc/Mac/O'/D' inner caps, hyphen segments, particle
lowercasing (von/van/de/da), comma-format reversal, period stripping
for titles/suffixes/initials, PhD/MD acronym preservation, conservative
mode for mixed-case input.
- Currency: auto-detect EU vs US separators, space-thousands, Swiss
apostrophe, accounting parens, optional ISO code preservation, error
sentinels for percentages/ranges/word-values/ambiguous separators.
- Per-domain error_policy ("passthrough" | "sentinel") for surfacing
malformed values as <error: reason> per corpus § 0.3.
Test corpus from Business/DataTools/test-cases-format-cleaner copied to
test-cases/format-cleaner-corpus/ — 7 fixtures plus FORMATS-CASES.md.
tests/test_format_standardize_corpus.py drives all 199 rows through the
per-cell standardizers; 0 xfailed.
Wires the GUI page (3_Format_Standardizer.py) to "Ready" status.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds a Review & Normalize page that sits between upload and every tool
page. The analyzer now tags each finding with confidence (high/medium/low)
and a fix_action; the gate auto-applies high-confidence fixes, surfaces
medium/low ones for user review, and blocks tool pages on error-level
findings until resolved or waived.
Core (src/core/):
- analyze.py: Finding gains confidence, fix_action, pre_applied; new
detectors for encoding_uncertain, encoding_decode_failed; new top-
level encoding_override parameter.
- fixes.py: registry of fix algorithms keyed by fix_action id.
- normalize.py: auto_fix(), apply_decisions(), is_normalized(), and
the NormalizationResult / Decision dataclasses the gate consumes.
- io.py: detect_encoding tries strict UTF-8 first; repair_bytes now
transcodes UTF-16/32 to UTF-8 before NUL-strip (fixes UTF-16 corruption)
and normalizes line endings (fixes bare-CR parser crash); empty file
handled gracefully instead of EmptyDataError traceback.
GUI (src/gui/):
- pages/0_Review.py: gate page with per-finding decision controls,
encoding override picker (16 codepages + custom), and Advanced output
options (encoding, delimiter, line terminator) on the download.
- components.py: require_normalization_gate() helper.
- pages/1-9: gate guard wired on every tool page.
Test corpora:
- test-cases/encodings-corpus/: 31 encoded CSV fixtures + 9 reference
UTF-8 files + manifest, synced from Business/DataTools.
- test-cases/text-cleaner-corpus/test_data/17: synced malformed input
(unquoted $1,500.00) for the unquoted-delimiter detector.
Tests (94 new):
- test_normalize.py (48): finding fields, fix registry, auto_fix scope,
decision paths, gate idempotency, output-options helper.
- test_encodings_corpus.py (90, 16 xfailed): parametric detection +
decode + analyzer-no-crash sweep against the manifest.
- test_analyze.py: encoding override + encoding_uncertain detectors.
- test_corpus.py: pre-parse repair in the strict reader.
run_tests.py: new aliases --tool normalize, --tool encodings, --tool gate;
encodings corpus added to --fixtures category.
Docs: USER-GUIDE §3.3 covers the gate workflow, encoding override, and
output options; TECHNICAL §10.2.1-10.2.4 documents the analyzer schema,
gate API, Review page, and pre-parse repair pipeline; CLI-REFERENCE adds
the analyzer JSON schema with the new fields; README links to all of it.
Suite: 765 passed, 17 xfailed (was 458 passed).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The 21-fixture corpus (test-cases/text-cleaner-corpus/) exercises the cleaner
end-to-end against the spec in TEST-CASES.md. Closing the failing cases drove
five small cleaner fixes plus two fixture-generation fixes:
- _SMART_CHARS: add prime, double prime, guillemets (case 03)
- _ZERO_WIDTH: add soft hyphen U+00AD (case 05)
- clean_dataframe: clean column headers via the same pipeline (cases 16/19/20),
with a clean_headers toggle on CleanOptions
- smart_title_case: title-case full-shout strings ("ALICE SMITH" -> "Alice
Smith") while still preserving embedded acronyms; preserve uppercase after
apostrophe in names ("O'CONNOR" -> "O'Connor", "o'neil" -> "O'neil")
- test_corpus.py reader: pre-strip NUL bytes (C parser truncates at NUL,
python engine is too strict about embedded literal "), per spec case 06
- generate_test_data.py: properly CSV-escape literal-quote cells in case 03
expected; quote the rogue-comma price field in case 17 input
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Rewrite README.md with project overview, quick-start, and CLI summary
- Add docs/CLI-REFERENCE.md with full flag reference and 8 recipe sections
- Add docs/DEVELOPER.md with architecture, data flow, and extension guides
- Rewrite src/core/__init__.py with public API exports and module docstring
- Add Streamlit GUI (src/gui/) with file upload, advanced options, interactive
match group review with side-by-side diff, and download buttons
- Add .gitignore, requirements.txt, all source code, tests, and sample data
- Add streamlit to requirements.txt
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
