acroforge 0.1.1

Turn flat PDFs into real, fillable AcroForms - permissive, deterministic, zero-copyleft.

acroforge

Turn flat PDFs into real, fillable AcroForms. Permissive (Apache-2.0), deterministic, zero-copyleft.

Left: a flat PDF - just printed lines and an empty box. Right: the same PDF after acroforge - real, fillable form fields, filled and rendered correctly. No Adobe, no cloud, no AGPL.

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What it does

acroforge takes any PDF - vector or scanned - and injects real AcroForm fields at positions you specify. The result is a standards-compliant fillable PDF that renders correctly in Chrome's pdfium and Firefox's pdf.js.

Three operations:

Operation	What it does
build	Inject interactive AcroForm fields into a flat PDF
fill	Set field values by name on a fillable PDF
flatten	Bake field appearances into page content; remove interactive fields

All three functions accept and return plain bytes, making them easy to compose in any pipeline.

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Install

pip install acroforge

Or from source:

git clone https://github.com/san64777/acroforge
cd acroforge
pip install -e .   # or: uv pip install -e .

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Python usage

import io
from reportlab.pdfgen import canvas  # any PDF source works
import acroforge as af
from acroforge import FieldSpec, FieldType

# --- Step 0: obtain a flat PDF (bytes) any way you like ---
buf = io.BytesIO()
c = canvas.Canvas(buf, pagesize=(612, 792))
c.drawString(72, 720, "Name:")
c.drawString(72, 680, "Agree to terms:")
c.save()
flat_pdf: bytes = buf.getvalue()

# --- Step 1: describe the fields you want ---
fields = [
    FieldSpec(
        type=FieldType.TEXT,
        page=0,
        rect=(200, 700, 450, 730),  # (x0, y0, x1, y1) in PDF points
        name="full_name",
    ),
    FieldSpec(
        type=FieldType.CHECKBOX,
        page=0,
        rect=(200, 660, 220, 680),
        name="agree",
        export_value="Yes",
    ),
]

# --- Step 2: inject the fields ---
fillable: bytes = af.build(flat_pdf, fields)

# --- Step 3: fill values ---
filled: bytes = af.fill(fillable, {"full_name": "Jane Doe", "agree": True})

# --- Step 4: flatten (optional - locks the form) ---
final: bytes = af.flatten(filled)

# Write to disk
with open("output.pdf", "wb") as f:
    f.write(final)

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CLI usage

# 1. Inject fields described in a JSON manifest
acroforge build in.pdf manifest.json fillable.pdf

# 2. Fill fields from a JSON object {name: value}
acroforge fill fillable.pdf data.json filled.pdf

# 3. Flatten (bake and lock)
acroforge flatten filled.pdf final.pdf

Example manifest.json:

[
  {
    "type": "text",
    "page": 0,
    "rect": [200, 700, 450, 730],
    "name": "full_name"
  },
  {
    "type": "checkbox",
    "page": 0,
    "rect": [200, 660, 220, 680],
    "name": "agree",
    "export_value": "Yes"
  },
  {
    "type": "radio",
    "page": 0,
    "rect": [200, 620, 220, 640],
    "name": "plan",
    "options": ["basic", "pro", "enterprise"],
    "export_value": "pro"
  }
]

Example data.json:

{"full_name": "Jane Doe", "agree": true, "plan": "pro"}

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Field types

Type	FieldType	Notes
Single-line text	FieldType.TEXT	Optional maxlen to cap character count
Multi-cell comb	FieldType.COMB	maxlen sets the number of cells (e.g. SSN = 9)
Checkbox	FieldType.CHECKBOX	export_value is the on-state value (default "Yes")
Radio button	FieldType.RADIO	One FieldSpec per button; share name, set export_value per button
Signature	FieldType.SIGNATURE	Placeholder widget - renders a blank sig box

FieldSpec reference

class FieldSpec(BaseModel):
    type: FieldType
    page: int                                    # 0-indexed
    rect: tuple[float, float, float, float]      # (x0, y0, x1, y1) in PDF points
    name: str                                    # AcroForm field name
    options: list[str] | None = None             # radio group member labels
    maxlen: int | None = None                    # TEXT cap / COMB cell count
    export_value: str | None = None              # radio/checkbox on-value
    confidence: float = 1.0                      # 1.0 = explicit; <1.0 = best-effort guess

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Detection (best-effort)

In addition to the deterministic engine, acroforge ships an optional, best-effort detector that guesses where fields belong on a flat vector PDF by reading its vector geometry and nearby text labels. It handles both common form archetypes:

• Underline forms - write-on rules become text fields.
• Table/grid forms - bordered table cells become text fields (label-aware: the field is placed in the writable area below the label, multi-column cells are split, and section-header rows are skipped).
• Checkboxes - both vector squares and font glyphs (☐ / ☑ / ☒).

import acroforge as af

pdf = open("form.pdf", "rb").read()

# Inspect candidate fields (a FormManifest); every field has confidence < 1.0
manifest = af.detect(pdf)
for f in manifest.fields:
    print(f.type, f.name, f.rect, f.confidence)

# Or go straight to a fillable PDF (detect() then build())
fillable: bytes = af.make_fillable(pdf)

CLI:

# Print the detected manifest as JSON (review it!)
acroforge detect form.pdf

# Detect and write a fillable PDF in one step
acroforge make-fillable form.pdf fillable.pdf

Read this before relying on it:

• Heuristic. Detection guesses from vector shapes and text proximity. It will miss fields and invent spurious ones.
• Vector-only. It reads the PDF's vector content stream. Scanned (image-only) PDFs are refused with ScannedPDFError - there is no OCR.
• Confidence-scored. Every detected FieldSpec carries confidence < 1.0 to flag it as a guess. Explicitly authored specs use confidence = 1.0.
• Meant to be reviewed. Treat the output of detect() / make-fillable as a draft manifest to inspect and correct, not a finished form.
• No accuracy claims. We make no promise about detection precision or recall on any form. Quality varies wildly by document.
• No AI. There are no models, no inference, no network calls - just deterministic geometry heuristics over the PDF's own vectors.

Scope and honest limits

The reliable part is the deterministic build / fill / flatten engine. You supply field positions via FieldSpecs - acroforge injects, fills, and flattens them reliably at exactly the coordinates you give it, on any PDF (vector or scanned).

detect() / make_fillable() are the best-effort layer described above: use them to bootstrap a manifest, then review and hand off the corrected specs to the engine.

There is no AI in this package, and no copyrighted form templates are bundled - bring your own PDFs.

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Engine and dependencies

Runtime dependencies are strictly permissive:

Package	License	Role
reportlab	BSD	Field widget rendering
pypdf	BSD-3-Clause	PDF read / merge / flatten
pdfplumber	MIT	PDF geometry utilities
PyPDFForm	MIT	Fill helpers
pydantic	MIT	FieldSpec / FormManifest validation

Optional extras:

• [fallback] - adds pikepdf (MPL-2.0) as a fallback PDF writer; not required for the default engine path.
• [harness] - adds pypdfium2 + Pillow for cross-viewer visual regression tests.

No GPL, AGPL, LGPL, or SSPL in the runtime tree. CI enforces this on every push via pip-licenses --fail-on='GPL;AGPL;LGPL;SSPL'.

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License

Apache-2.0. See LICENSE.

No copyrighted form templates are included or bundled. Bring your own PDFs.