Files
multiarch-docker-images/automatic-pdf-renamer/scripts
72f8254e10 US0: Paperless-ngx Initial Import - Reusable Components + Import Script (#9)
* Add sidecar.py module for User Story 0 (Paperless-ngx import)

Implements the sidecar data model, schema validation, atomic writes,
and I/O helpers per PRD section 7.

- Sidecar and SidecarEvent dataclasses with full PRD schema
- SidecarStatus and EventType enums
- build_sidecar(), serialize(), deserialize() functions
- validate_sidecar() with type and required field checking
- get_sidecar_key() for .meta.json suffix generation
- write_atomic() for crash-safe temp-key + copy + delete pattern
- read_sidecar(), sidecar_exists(), matching_sha256() for storage I/O

This is a reusable component for both the import script and main service.

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Add storage/ module with S3 and File backends

Implements the storage layer abstraction for User Story 0.

- StorageBackend ABC: defines interface for all storage implementations
- S3Storage: boto3-based backend for Garage S3 (production)
- FileStorage: filesystem-based backend for testing
- get_storage_backend() factory function
- Atomic operations: put, get, delete, copy, exists, list, head

Both backends implement the same interface, allowing seamless
switching between production S3 and local testing.

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Add period.py, extractor.py, and config.py reusable modules

- period.py: Period parsing from filenames and computation from dates
  - parse_period_from_filename(): Extracts month-year, quarter, year, date patterns
  - compute_period_from_date(): Computes period per template rules (granularity + offset)
  - get_period(): Main entry point with filename fallback to rule-based computation
  - validate_period_consistency(): Checks period vs emission_date + rule
  - Supports French month names (août, janvier, etc.)

- extractor.py: PDF text extraction using PyMuPDF
  - extract_first_page_text(): Extracts text from first PDF page
  - extract_and_validate(): Extracts and checks minimum text length
  - TextExtractor class for dependency injection and mocking

- config.py: Configuration management
  - S3Config, PaperlessConfig, PollerConfig, ClassifierConfig dataclasses
  - AppConfig: Main application configuration from env vars
  - TemplateRegistry: Loads and manages template YAML configurations
  - load_config(), load_templates() helper functions

All modules are reusable by both import script and main service.

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Add import_paperless.py script for User Story 0

Implements the standalone import script that:
- Connects to Paperless-ngx REST API (PAPERLESS_URL + token from env)
- Connects to Garage S3 bucket via boto3 (S3_ENDPOINT_URL, credentials, bucket)
- Lists all documents from Paperless via paginated /api/documents/
- Fetches document metadata and maps to sidecar fields:
  - template: first path segment of storage_path
  - emission_date: document created field
  - emitting_company: correspondent name
  - document_type: document type name
  - period: parsed from filename tail, fallback to month-year from emission_date
  - extracted_text: first page text via PyMuPDF
  - optional_fields: from Paperless labels
- Downloads PDF via /api/documents/{id}/download/
- Stores PDF at files/{template}/{original filename}
- Writes sidecar {key}.meta.json with atomic temp-key + copy pattern
- Supports resumability (skip if PDF + sidecar exist with matching SHA256)
- Dry-run flag for testing
- Limit flag for trial runs
- Summary reporting at end
- Exit code: 0 if all succeed, 1 if any failures

Dependencies: requests, boto3, pymupdf, python-dateutil

Usage: python scripts/import_paperless.py [--dry-run] [--limit N] [--verbose]
Environment: PAPERLESS_URL, PAPERLESS_TOKEN, S3_ENDPOINT_URL, S3_ACCESS_KEY_ID, S3_SECRET_ACCESS_KEY, S3_BUCKET_NAME

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Add requirements.txt for import script dependencies

Lists all Python dependencies needed to run scripts/import_paperless.py:
- requests: Paperless-ngx API client
- boto3: Garage S3 client
- pymupdf: PDF text extraction
- python-dateutil: Date parsing
- PyYAML: YAML config parsing (optional)

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Update import script: add storage backend selection (s3/file)

- Added --storage-backend argument (choices: s3, file, default: s3)
- Added --file-base-dir argument for file storage
- Storage backend validation based on selection
- Updated help text and epilog with backend-specific env vars
- Importer class now accepts storage_backend and file_base_dir params
- _init_storage() method handles backend initialization
- Summary now shows which storage backend was used

Usage examples:
  # S3 storage (default)
  python scripts/import_paperless.py

  # File storage for testing
  python scripts/import_paperless.py --storage-backend file --file-base-dir ./test_storage

  # Explicit S3
  python scripts/import_paperless.py --storage-backend s3 --s3-endpoint ... --s3-bucket ...

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Add README.md for scripts directory

Comprehensive documentation for import_paperless.py script:
- Overview and features
- Requirements and installation
- Usage examples (env vars + CLI args)
- Storage backends (S3 vs file)
- Metadata mapping table
- Output structure
- Resumability notes
- Exit codes
- Example output
- Troubleshooting guide
- Development/testing notes
- Architecture overview

Helps users understand how to use the import script for User Story 0.

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Fix Paperless API field mapping

The Paperless-ngx API returns IDs for correspondent, document_type, and tags,
not the actual string values. This commit fixes the import script to:

- Use 'archived_file_name' instead of 'filename' for the actual filename
- Fetch correspondent name from /api/correspondents/{id}/ endpoint
- Fetch document type name from /api/document_types/{id}/ endpoint
- Fetch tag names from /api/tags/{id}/ endpoint
- Add caching for fetched entities to avoid duplicate API requests

This ensures the sidecar metadata contains actual human-readable strings
instead of numeric IDs.

Changes:
- PaperlessClient: Added get_correspondent_name(), get_document_type_name(), get_tag_name()
- PaperlessClient: Added caches for fetched entities
- get_all_documents(): Now resolves IDs to names for all fields
- Updated module docstring to document this behavior

Co-authored-by: napnap75 <napnap75@users.noreply.github.com>

* Refactor PaperlessClient: change labels to list, add storage path caching, and improve document fetching logic

---------

Co-authored-by: Vibe Nuage Agent <vibe@mistral.ai>
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
2026-10-03 10:05:49 +02:00
..

Scripts

Standalone Python scripts for the Automatic PDF Renamer project.

Available Scripts

Script Purpose Dependencies
import_paperless.py Import documents from Paperless-ngx to storage requests, boto3, pymupdf, python-dateutil

import_paperless.py - Paperless-ngx Initial Import

User Story 0: Standalone script that imports existing paperless-ngx documents into a Garage S3 bucket (or local filesystem) with their metadata as sidecars.

Features

  • ✅ Connects to Paperless-ngx REST API
  • ✅ Connects to Garage S3 or local filesystem
  • ✅ Lists all documents via paginated API
  • ✅ Maps Paperless metadata to sidecar fields
  • ✅ Downloads PDFs and extracts first-page text
  • ✅ Atomic sidecar writes (temp-key + copy pattern)
  • ✅ Resumability (skip if already imported with matching SHA256)
  • ✅ Dry-run mode for testing
  • ✅ Summary reporting
  • ✅ Proper exit codes

Requirements

Install dependencies:

pip install -r scripts/requirements.txt

Or individually:

pip install requests boto3 pymupdf python-dateutil PyYAML

Usage

Set these before running:

# Paperless-ngx
 export PAPERLESS_URL="http://paperless:8000"
 export PAPERLESS_TOKEN="your-api-token"

# S3 Storage (Garage)
 export S3_ENDPOINT_URL="http://garage:7777"
 export S3_ACCESS_KEY_ID="your-access-key"
 export S3_SECRET_ACCESS_KEY="your-secret-key"
 export S3_BUCKET_NAME="pdf-renamer"

# File Storage (for testing)
 export FILE_BASE_DIR="./import_storage"

Command Line

# S3 storage (default)
python scripts/import_paperless.py

# File storage for testing
python scripts/import_paperless.py \
    --storage-backend file \
    --file-base-dir ./test_storage

# Dry run (list what would be imported)
python scripts/import_paperless.py --dry-run

# Limited import (test with 5 documents)
python scripts/import_paperless.py --limit 5

# Verbose mode
python scripts/import_paperless.py --verbose

# Full options
python scripts/import_paperless.py \
    --paperless-url http://paperless:8000 \
    --paperless-token your-token \
    --storage-backend s3 \
    --s3-endpoint http://garage:7777 \
    --s3-access-key your-key \
    --s3-secret-key your-secret \
    --s3-bucket pdf-renamer \
    --dry-run \
    --limit 10 \
    --verbose

Storage Backends

The import script supports two storage backends:

Backend Description Use Case
s3 Garage S3 via boto3 Production
file Local filesystem Testing, development

S3 Backend

Requires:

  • --s3-endpoint or S3_ENDPOINT_URL
  • --s3-access-key or S3_ACCESS_KEY_ID
  • --s3-secret-key or S3_SECRET_ACCESS_KEY
  • --s3-bucket or S3_BUCKET_NAME

The script will refuse to run if the files/ prefix is not empty (to prevent accidental overwrites).

File Backend

Requires:

  • --file-base-dir or FILE_BASE_DIR (default: ./import_storage)

Creates a directory structure matching the S3 layout:

file_base_dir/
  files/
    Template1/
      document1.pdf
      document1.pdf.meta.json
    Template2/
      document2.pdf
      document2.pdf.meta.json
  tmp/
    (temporary files for atomic writes)

Metadata Mapping

Paperless-ngx fields are mapped to sidecar fields as follows:

Sidecar Field Paperless Source Notes
template_name storage_path (first segment) Document family
emission_date created Document date
emitting_company correspondent.name Correspondent
document_type document_type.name Document type
period Filename (parsed) or created (fallback) Month-year, quarter, year
extracted_text PDF first page Via PyMuPDF
optional_fields labels Each label becomes an optional field
sha256 PDF binary Computed from downloaded PDF
status Hardcoded validated
confidence Hardcoded 1.0

Output Structure

Documents are stored at:

files/{template}/{original_filename}
files/{template}/{original_filename}.meta.json

Example:

files/Banque/Relevé de compte août 2025.pdf
files/Banque/Relevé de compte août 2025.pdf.meta.json

Resumability

The script can be interrupted and rerun safely:

  • Documents already imported with matching SHA256 are skipped
  • Atomic sidecar writes ensure no partial/corrupted sidecars
  • Summary shows imported, skipped, and failed counts

Exit Codes

Code Meaning
0 Success (all documents imported)
1 Failure (one or more documents failed)
130 Interrupted by user (SIGINT)

Example Output

2026-10-02 12:00:00,000 - INFO - Starting Paperless-ngx import...
2026-10-02 12:00:00,001 - INFO - Using S3 storage backend: http://garage:7777/pdf-renamer
2026-10-02 12:00:00,002 - INFO - Fetching documents from Paperless...
2026-10-02 12:00:05,123 - INFO - Retrieved 150 documents from Paperless
2026-10-02 12:00:05,124 - INFO - Processing document 1: Relevé août 2025.pdf
2026-10-02 12:00:05,456 - INFO - Successfully imported document 1
2026-10-02 12:00:05,457 - INFO - Processing document 2: Facture Q3 2025.pdf
...

============================================================
IMPORT SUMMARY
============================================================
Storage backend: s3
Imported:   150
Skipped:    0
Failed:     0
Period fallbacks: 0

Per-template counts:
  Banque: 75
  Factures: 50
  Contrats: 25
============================================================

Troubleshooting

"Missing required values" error

Make sure all required environment variables are set or passed as CLI arguments:

# Check what's set
echo $PAPERLESS_URL
echo $S3_ENDPOINT_URL

"Bucket is not empty" error

The script refuses to run if files/ prefix already has objects. Options:

  1. Use a different bucket
  2. Use file storage for testing: --storage-backend file --file-base-dir ./test
  3. Empty the bucket first (if you're sure it's safe)

"PyMuPDF not available" warning

Text extraction will be skipped. Install it for full functionality:

pip install pymupdf

Connection errors

Check that:

  • Paperless-ngx is running and accessible
  • S3/Garage endpoint is correct
  • Credentials are valid
  • Network connectivity is available

Development / Testing

For testing without Paperless-ngx or S3:

# Use file storage
python scripts/import_paperless.py \
    --storage-backend file \
    --file-base-dir ./test_storage \
    --dry-run

# Or create a mock Paperless client (see tests/ directory)

Architecture

The import script uses the same reusable components as the main service:

  • app/sidecar.py - Sidecar data model and I/O
  • app/storage/ - Storage backend abstraction
  • app/period.py - Period parsing and computation
  • app/extractor.py - PDF text extraction
  • app/config.py - Configuration utilities

This ensures consistency between the import script and the main service.


License

Same as the main project. See ../LICENSE.