Spec and implementation plan for rasterizing PDF thumbnails with
pdftoppm+pikepdf+Pillow instead of ImageMagick's convert/gs delegate,
cutting subprocess calls and using narrower-scoped tools already
vendored in the image.
Adds the extensibility design that hoists the bulk-edit operation
definition (today smeared across serialisers.py, views.py, bulk_edit.py
and keyed three different ways) behind a BulkEditOperation registry +
PermissionRequirements value object, with per-operation OpenAPI examples.
Contract-preserving refactor; both docs reviewed across multiple passes
(permission matrix verified, both view call sites accounted for).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replace the search-error-shapes stub with a full design spec and a TDD
implementation plan for friendlier advanced-search error messages.
Empirically validated against a live Tantivy index: three error families
(UnknownFieldError, InvalidFieldValueError, MalformedQueryError),
proactive numeric validation plus a parse_query backstop, comparison
operators confirmed working, and a parse-based field drift guard.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* Feature: store barcode contents, list and search them
New setting PAPERLESS_CONSUMER_STORE_BARCODE_VALUES (off by default)
stores all barcodes found during consumption with the document: page,
type and content. They are listed on the metadata tab with a copy
button, returned by the documents API and searchable with barcodes:
in the advanced search. Versions keep their own barcodes, reprocessing
reads them again. Refs #9898
* Tests: cover the remaining barcode branches
Covers unchanged and failing barcode reads on reprocessing, unsupported files and DocumentBarcode.__str__, and uses toHaveLength in the barcode list spec as suggested by SonarCloud.
* Address review: keep barcodes when they can't be read, format choices
- Reprocessing and new versions keep the stored barcodes when the file
can't be scanned or the scan fails, and replace them atomically.
- Format is a TextChoices of the zxing-cpp formats, with a test.
- Shared scan code, latest_version helper, TypedDict, serializer reuse.
- Barcodes in the split manifest, export/import tests, pytest-style tests.
* Barcode tests: TIFF reprocess, format check both ways, fixtures
- Reprocessing a TIFF with TIFF support off keeps the stored barcodes.
- The format test also fails when zxing-cpp drops a format.
- Fixtures in place of the sample dir mixin, plugin-level disabled test.
- Format labels aren't translated, OpenAPI enum named BarcodeFormatEnum.
* Review: module-level zxing reader, shorter barcode docs
- read_barcodes_zxing is a module-level function used by scan_pdf.
- Drop the trivial __str__ test, mark it no cover.
- Shorten the barcode docs and remove the duplicate in configuration.md.
* Fix header
* Use utility class
* Return barcodes from the metadata endpoint only
Drop the barcodes field and its prefetches from the document serializer,
as agreed in the review. Also remove the now empty component stylesheet.
---------
Co-authored-by: shamoon <4887959+shamoon@users.noreply.github.com>
Enables pytest-randomly, which has sat commented out in pyproject.toml
since the Pytest 9 upgrade. Tests now run in a different order every
session, so a test cannot quietly depend on another having run first.
* Feature: match fuzzy terms in place inside the parsed query
Fuzzy matching was a separate clause OR'd in above the query: a flat bag
of the query's words, re-parsed through tantivy's own parser, blended
beside the exact clause. Nothing around a term reached it, so a fielded
term fuzzed across every default field, a filter did not constrain it, and
an exclusion had to be hoisted back over the whole blend to stop the
clause re-admitting what the query had just excluded.
Widen each leaf where it sits instead, through emit()'s rewrite_leaf hook,
so fielding, negation, AND, REQUIRE and positive filters constrain the
fuzzy match exactly as they constrain the exact one. Each of a leaf's
words becomes a Fuzzy leaf on the leaf's own field, boosted to 0.1, beside
the leaf and any CJK alternative it already had.
* Hello?
* Preprocesses classifier content with Tantivy instead of NLTK
Tokenizing and stemming now happen in one Rust call instead of NLTK's
Python tokenizer and per word stemming, which also removes the Redis
backed stem cache from every preprocessing call. The output matches the
NLTK pipeline closely; tokens containing digits are now stemmed, and the
English stop words follow Snowball's list.
Stemming and stop word removal apply whenever the OCR language is one of
the supported classifier languages, so PAPERLESS_ENABLE_NLTK and
PAPERLESS_NLTK_DIR are removed.
* Copies packages instead of hardlinking them in backend CI, some NLTK thing
* Adds a normalization to NFC to better fit what Tantivy expects
* docs(search): document the query grammar paperless actually supports
* docs(search): cover ?/bracket wildcards and the no-stemmer fallback
* Shorten things up, use tables and less wordy stuff. Fixes some test doc strings that referred to the documentation
* Silly sonarr
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