Metadata-Version: 2.4
Name: privacyforms.pdf
Version: 0.2.0
Summary: Python library to extract and fill PDF forms using pypdf
Author-email: Andreas Jung <info@zopyx.com>
License: MIT
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click>=8
Requires-Dist: pluggy>=1
Requires-Dist: pydantic>=2
Requires-Dist: pypdf>=6.10.2
Requires-Dist: rich>=13
Provides-Extra: labels
Requires-Dist: pymupdf>=1.24.0; extra == "labels"
Dynamic: license-file

# privacyforms-pdf

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Python library for parsing and filling PDF forms using [pypdf](https://pypdf.readthedocs.io/).

## Features

- Parse fillable PDFs into a canonical `PDFRepresentation` schema
- Fill PDF forms from simple JSON key/value data
- Extract layout hints and visual row groupings
- Validate representation JSON against the schema
- Verify sample data keys against parsed field IDs
- Extend the CLI through `pluggy` command entry points

## Requirements

- Python `3.12+`
- `pypdf >= 5`

## Installation

```bash
git clone <repo-url>
cd privacyforms.pdf
uv sync
```

## CLI Quick Start

### Parse A PDF

```bash
pdf-forms parse form.pdf -o representation.json
```

This writes a compact `PDFRepresentation` JSON document.

### Verify A Representation JSON File

```bash
pdf-forms verify-json representation.json
```

### Verify Sample Data Keys Against Parsed Field IDs

```bash
pdf-forms verify-data --form-json representation.json --data-json sample-data.json
```

Preferred format:

- use field IDs such as `f-0` for canonical machine-facing data
- field names such as `Candidate Name` remain supported for convenience

Compatibility modes:

- `fill-form` accepts `--field-keys name|id|auto`
- `verify-data` accepts `--key-mode name|id|auto`
- `auto` accepts a mixture of field IDs and field names

### Fill A PDF Form

```bash
pdf-forms fill-form form.pdf data.json -o filled.pdf
pdf-forms fill-form form.pdf data.json -o filled.pdf --no-validate
pdf-forms fill-form form.pdf data.json -o filled.pdf --strict
pdf-forms fill-form form.pdf data.json -o filled.pdf --field-keys id
```

Recommended `fill-form` payloads are keyed by field IDs:

```json
{
  "f-0": "John Smith",
  "f-1": "Software Engineer",
  "f-2": "2025-06-01",
  "f-3": true
}
```

Field names and mixed key styles are still supported through `--field-keys name` and `--field-keys auto`.

### Check Whether A PDF Contains A Form

```bash
pdf-forms info form.pdf
```

## Python API

The package currently exposes two main API layers:

- read/parse APIs via `parse_pdf()` and `extract_pdf_form()`
- higher-level read/fill/validate APIs via `PDFFormService`

### Parse A PDF Into `PDFRepresentation`

```python
from privacyforms_pdf import extract_pdf_form

representation = extract_pdf_form("form.pdf")

print(representation.spec_version)
print(representation.source)
print(len(representation.fields))
print(len(representation.rows))

for field in representation.fields:
    print(field.id, field.name, field.type, field.value)
```

### Extract Labels And Nearby Text

Install the optional `labels` dependency (requires **PyMuPDF**):

```bash
pip install privacyforms.pdf[labels]
```

CLI:

```bash
pdf-forms parse form.pdf --labels -o representation.json
```

Python API:

```python
from privacyforms_pdf import PDFFormService

service = PDFFormService()
representation = service.extract("form.pdf", extract_labels=True)

for field in representation.fields:
    print(field.title)  # best inferred label
    for block in field.text_blocks:
        print(block.role, block.direction, block.text)
```

You can also call `parse_pdf()` directly:

```python
from privacyforms_pdf import parse_pdf

representation = parse_pdf("form.pdf")
json_text = representation.to_compact_json()
```

### Fill And Validate Forms

```python
from privacyforms_pdf import PDFFormService

service = PDFFormService()

has_form = service.has_form("form.pdf")

form_data = {
    "f-0": "John Smith",
    "f-3": True,
}

errors = service.validate_form_data("form.pdf", form_data, key_mode="id")
if errors:
    print(errors)
else:
    service.fill_form("form.pdf", form_data, "filled.pdf", key_mode="id")
```

You can also fill from a JSON file:

```python
from privacyforms_pdf import PDFFormService

service = PDFFormService()
service.fill_form_from_json("form.pdf", "data.json", "filled.pdf", key_mode="id")
```

The class also exposes read helpers:

```python
from privacyforms_pdf import PDFFormService

service = PDFFormService()
representation = service.extract("form.pdf")
fields = service.list_fields("form.pdf")
field = service.get_field_by_id("form.pdf", "f-0")
value = service.get_field_value("form.pdf", "Candidate Name")
service.extract_to_json("form.pdf", "representation.json")
```

## Public Objects

Primary exports from `privacyforms_pdf`:

- `PDFFormService`
- `FormFiller`
- `parse_pdf`
- `extract_pdf_form`
- `PDFRepresentation`
- `PDFField`
- `FieldFlags`
- `FieldLayout`
- `FieldTextBlock`
- `FieldTextRole`
- `FieldTextDirection`
- `ChoiceOption`
- `RowGroup`
- `PDFFormError`
- `PDFFormNotFoundError`
- `FormValidationError`
- `FieldNotFoundError`

## `PDFRepresentation` Schema

Top-level fields:

- `spec_version: str`
- `source: str | None`
- `fields: list[PDFField]`
- `rows: list[RowGroup]`

### `PDFField`

Main fields:

- `name: str`
- `title: str | None`
- `id: str`
- `type: PDFFieldType`
- `field_flags: FieldFlags | None`
- `layout: FieldLayout | None`
- `default_value: str | bool | list[str] | None`
- `value: str | bool | list[str] | None`
- `choices: list[ChoiceOption]`
- `text_blocks: list[FieldTextBlock]` — nearby labels, descriptions, helpers
- `format: str | None`
- `max_length: int | None`
- `textarea_rows: int | None`
- `textarea_cols: int | None`

Supported field types:

- `textfield`
- `textarea`
- `datefield`
- `checkbox`
- `radiobuttongroup`
- `combobox`
- `listbox`
- `signature`

### `FieldLayout`

Layout hints are stored in integer PDF coordinates:

- `page: int | None`
- `x: int | None`
- `y: int | None`
- `width: int | None`
- `height: int | None`

### `FieldTextBlock`

Nearby text associated with a field (populated when `extract_labels=True`):

- `text: str`
- `role: "label" | "description" | "helper" | "instruction" | "unknown"`
- `direction: "left" | "right" | "above" | "below" | "inside" | "unknown"`
- `layout: FieldLayout | None`
- `distance: float | None`

### `RowGroup`

Visual rows derived from layout analysis:

- `fields: list[PDFField | str]`
- `page_index: int`

When serialized, row fields are emitted as field IDs.

## JSON Shape

Example parsed representation:

```json
{
  "source": "form.pdf",
  "fields": [
    {
      "name": "Candidate Name",
      "id": "f-0",
      "type": "textfield",
      "layout": {
        "page": 1,
        "x": 53,
        "y": 1077,
        "width": 361,
        "height": 27
      }
    }
  ],
  "rows": [
    {
      "fields": ["f-0"],
      "page_index": 1
    }
  ]
}
```

Notes:

- omitted fields are intentionally excluded by compact serialization
- `field_flags` only serializes flags set to `true`
- `rows` reference fields by ID in JSON

## Exceptions

- `PDFFormError`: base exception for form-related failures
- `PDFFormNotFoundError`: raised when a PDF does not contain a form
- `FormValidationError`: raised when fill-time validation fails
- `FieldNotFoundError`: exported for compatibility and field lookup failures

## Ratings

| Aspect | Score | Notes |
|--------|------:|-------|
| **Overall** | **9/10** | Production-grade library with excellent engineering discipline |
| Security | 9/10 | Input validation, symlink rejection, size limits, Bandit clean |
| Architecture | 9/10 | Clean layers, canonical schema, pluggy extensibility |
| API Design | 8/10 | Dual function/class layers, type-safe, minor wrapper leakage |
| Functionality | 9/10 | All form types handled, cross-generator radio support, graceful fallback |
| Code Quality | 9/10 | 100% coverage, strict ruff/ty, complete type hints |
| Documentation | 8/10 | Excellent project docs; PDF internals could use more inline depth |

## Security

- Symlinks are rejected for both reads and writes to prevent path-traversal issues
- PDF files are validated via magic-byte header check (`%PDF`) before parsing
- Input size limits guard against oversized PDFs (> 50 MB) and JSON (> 10 MB)
- JSON depth limits prevent stack exhaustion from malicious payloads

## Architecture

- Clean separation of concerns: `schema` → `parser` → `filler` → `extractor` → `cli`
- Canonical `PDFRepresentation` schema (Pydantic v2) is the single source of truth
- CLI commands are loaded dynamically via `pluggy` entry points — easy to extend
- Low-level PDF writer (`FormFiller`) is decoupled from the high-level service (`PDFFormService`)

## API Design

- Two complementary layers: function-based (`parse_pdf`, `extract_pdf_form`) and class-based (`PDFFormService`)
- Field IDs are the canonical key format; field names remain supported for convenience
- `key_mode="auto"` accepts mixed payloads of IDs and names
- All public methods have complete type hints and Google-style docstrings

## Functionality

- Handles all common PDF form types: text, textarea, date, checkbox, radio, combo, listbox, signature
- Radio button state resolution works across different PDF generators
- Listbox filling includes custom appearance streams so selections are visible in viewers
- Graceful fallback when pypdf's appearance-stream generation hits edge cases

## Code Quality

- **100% test coverage** (426 tests) with pytest and `pytest-cov`
- **Ruff** enforces strict linting (E, W, F, I, N, D, UP, B, C4, SIM, TCH)
- **ty** type checker runs in strict mode — complete type hints throughout
- **Bandit** security scanner integrated; no high or medium severity issues

## Development

### Quality Checks

```bash
make check
make test
make test-cov
```

### Project Structure

```text
privacyforms.pdf/
├── privacyforms_pdf/
│   ├── __init__.py
│   ├── schema.py
│   ├── schema_layout.py
│   ├── parser.py
│   ├── extractor.py
│   ├── filler.py
│   ├── hooks.py
│   ├── cli.py
│   └── commands/
├── tests/
├── samples/
├── demo/
├── docs/
├── pyproject.toml
└── README.md
```

## License

MIT
