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v1.0.0
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‎.github/workflows/ci.yml‎

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name: CI
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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check:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.9", "3.12", "3.13"]
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- run: pip install -e ".[dev]"
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- run: ruff check .
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- run: ruff format --check .
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- run: mypy iterationlayer
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- run: pytest

‎.github/workflows/publish.yml‎

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name: Publish
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on:
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push:
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tags:
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- "v*"
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jobs:
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publish:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: "3.13"
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- run: pip install build twine
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- run: python -m build
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- run: twine upload dist/*
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}

‎README.md‎

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# Iteration Layer Python SDK
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Official Python SDK for the [Iteration Layer API](https://iterationlayer.com).
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## Installation
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```sh
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pip install iterationlayer
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```
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## Usage
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```python
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from iterationlayer import IterationLayer
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client = IterationLayer(api_key="il_your_api_key")
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```
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### Document Extraction
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Extract structured data from documents using AI.
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```python
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result = client.extract(
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files=[{"type": "url", "name": "invoice.pdf", "url": "https://example.com/invoice.pdf"}],
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schema={
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"fields": [
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{"type": "TEXT", "name": "company_name", "description": "The company name"},
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{"type": "CURRENCY_AMOUNT", "name": "total", "description": "The invoice total"},
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]
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},
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)
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print(result["company_name"]["value"]) # "Acme Corp"
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print(result["company_name"]["confidence"]) # 0.95
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```
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### Image Transformation
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Resize, crop, convert, and apply effects to images.
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```python
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result = client.transform(
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file={"type": "url", "name": "photo.jpg", "url": "https://example.com/photo.jpg"},
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operations=[
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{"type": "resize", "width_in_px": 800, "height_in_px": 600, "fit": "cover"},
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{"type": "convert", "format": "webp", "quality": 85},
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],
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)
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import base64
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image_bytes = base64.b64decode(result["buffer"])
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```
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### Image Generation
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Compose images from layer definitions.
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```python
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result = client.generate_image(
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dimensions={"width_in_px": 1200, "height_in_px": 630},
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layers=[
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{"type": "solid-color-background", "index": 0, "hex_color": "#1a1a2e"},
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{
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"type": "text",
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"index": 1,
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"text": "Hello World",
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"font_name": "Inter",
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"font_size_in_px": 48,
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"text_color": "#ffffff",
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"position": {"x_in_px": 50, "y_in_px": 50},
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"dimensions": {"width_in_px": 1100, "height_in_px": 530},
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},
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],
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output_format="png",
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)
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import base64
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image_bytes = base64.b64decode(result["buffer"])
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```
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### Document Generation
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Generate PDF, DOCX, EPUB, or PPTX from structured data.
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```python
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result = client.generate_document(
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format="pdf",
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document={
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"metadata": {"title": "Invoice #123"},
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"page": {
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"size": {"preset": "A4"},
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"margins": {"top_in_pt": 36, "bottom_in_pt": 36, "left_in_pt": 36, "right_in_pt": 36},
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},
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"styles": {
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"text": {"font_family": "Helvetica", "font_size_in_pt": 12, "line_height": 1.5, "color": "#000000"},
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"headline": {"font_family": "Helvetica", "font_size_in_pt": 24, "color": "#000000", "spacing_before_in_pt": 12, "spacing_after_in_pt": 6},
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"link": {"color": "#0066cc"},
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"list": {"indent_in_pt": 18, "spacing_between_items_in_pt": 4},
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"table": {
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"header": {"background_color": "#f0f0f0", "font_family": "Helvetica", "font_size_in_pt": 12, "color": "#000000", "padding_in_pt": 6},
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"body": {"font_family": "Helvetica", "font_size_in_pt": 12, "color": "#000000", "padding_in_pt": 6},
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},
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"grid": {"gap_in_pt": 12},
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"separator": {"color": "#cccccc", "thickness_in_pt": 1, "margin_top_in_pt": 12, "margin_bottom_in_pt": 12},
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"image": {"alignment": "center", "margin_top_in_pt": 8, "margin_bottom_in_pt": 8},
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},
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"content": [
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{"type": "headline", "level": "h1", "text": "Invoice #123"},
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{"type": "paragraph", "markdown": "Thank you for your business."},
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],
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},
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)
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import base64
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pdf_bytes = base64.b64decode(result["buffer"])
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```
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### Webhooks (Async)
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Use the `*_async` methods to receive results via webhook instead of waiting for the response.
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```python
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result = client.extract_async(
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files=[{"type": "url", "name": "invoice.pdf", "url": "https://example.com/invoice.pdf"}],
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schema={
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"fields": [
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{"type": "CURRENCY_AMOUNT", "name": "total", "description": "The invoice total"},
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]
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},
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webhook_url="https://your-app.com/webhooks/extraction",
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)
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```
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### Context Manager
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The client can be used as a context manager to ensure the underlying HTTP connection is closed.
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```python
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with IterationLayer(api_key="il_your_api_key") as client:
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result = client.extract(...)
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```
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### Error Handling
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```python
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from iterationlayer import IterationLayerError
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try:
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result = client.extract(...)
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except IterationLayerError as e:
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print(e.status_code) # 422
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print(e.error_message) # "Validation error: ..."
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```
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## Documentation
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Full documentation is available at [https://iterationlayer.com/docs](https://iterationlayer.com/docs).
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## Issues & Feedback
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Please report bugs and request features in the [issues repository](https://github.com/iterationlayer/issues).

‎iterationlayer/__init__.py‎

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from iterationlayer.client import (
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IterationLayer,
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IterationLayerError,
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)
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from iterationlayer.types import * # noqa: F401, F403
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__all__ = [
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"IterationLayer",
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"IterationLayerError",
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]

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