pixel-client 1.2.3

Client library for Geodata Pixel

Geodata Pixel Client

A Python client library for interacting with the Geodata Pixel API. Geodata Pixel is a SaaS solution for efficient image management, providing a centralized platform for uploading, storing, and structuring image data with geospatial information. This makes it easy to find and manage images based on time and location.

This client library provides a convenient interface for working with Geodata Pixel, allowing users to create projects, manage data collections, and upload and process various types of geospatial imagery including survey photos, drone imagery, 360° images, and raster data.

Geodata Pixel er vår løsning for effektiv bildeforvaltning. Med Geodata Pixel får du et felles sted å laste opp, lagre og strukturere bildedata, noe som gjør det enkelt å finne bilder basert på tid og sted.

Features

• Dual API Support: Both synchronous and asynchronous interfaces
• Data Management: Create and manage projects and data collections
• Image Handling: Upload and process image data with geolocation
• Raster Data Handling: Support for various raster data types (RGB, DTM, DSM)
• ArcGIS Services: Create and manage ArcGIS Feature and Image services
• Harvest Services: Automated data harvesting from ArcGIS Feature services
• Authentication: Integrated Keycloak authentication
• Metadata Management: Flexible metadata handling for uploaded files
• Attachments: Add and manage file attachments to resources

Installation

Warning This package is not yet available on PyPI. You can install it from the source code repository instead.

pip install pixel-client

Requirements

• Python 3.11 or higher

Authentication

The Pixel client requires authentication through Keycloak. You can provide authentication details through environment variables, a .env file, or directly in code:

from pixel_client import get_client, PixelApiSettings

# Using environment variables
client = get_client()

# Using direct settings
settings = PixelApiSettings(
    PIXEL_TENANT="your_realm",
    PIXEL_USERNAME="your_username",
    PIXEL_PASSWORD="your_password"
)
client = get_client(settings=settings)

# Using a .env file
settings = PixelApiSettings.from_env_file("my_env_file.env")
client = get_client(settings=settings)

Quick Start

Synchronous Usage

from pixel_client import get_client
from geojson_pydantic import Polygon

# Initialize the client
client = get_client()

# Create a project
new_project = client.create_project(
    name="My New Project",
    description="A test project",
    area_of_interest=Polygon.model_validate({
        "type": "Polygon",
        "coordinates": [[[-10, 10], [-10, 20], [0, 20], [0, 10], [-10, 10]]]
    }),
    tags=["test", "example"]
)

# Create a data collection
data_collection = client.create_data_collection(
    project_id=new_project["id"],
    name="My Data Collection",
    description="An example data collection",
    data_collection_type="image",
    tags=["example", "images"]
)

Asynchronous Usage

import asyncio
from pixel_client import get_client
from geojson_pydantic import Polygon

async def main():
    # Initialize the async client
    client = get_client(async_=True)
    
    # Create a project
    new_project = await client.create_project(
        name="My Async Project",
        description="A test async project",
        area_of_interest=Polygon.model_validate({
            "type": "Polygon",
            "coordinates": [[[-10, 10], [-10, 20], [0, 20], [0, 10], [-10, 10]]]
        }),
        tags=["test", "async"]
    )
    
    # Create a data collection
    data_collection = await client.create_data_collection(
        project_id=new_project["id"],
        name="My Async Data Collection",
        description="An example async data collection",
        data_collection_type="image",
        tags=["example", "async"]
    )

asyncio.run(main())

Uploading Data

Image Data

from pixel_client import get_client, PixelUploadFile, MetadataObject, ImageMetadataFields
from pathlib import Path

client = get_client()

# Upload images to a data collection
image_files = [
    PixelUploadFile(
        file=Path("path/to/image.jpg"),
        metadata=MetadataObject(
            fields=ImageMetadataFields(name="my_image"),
            json_metadata={"custom_field": "value"}
        )
    )
]

images, errors = client.upload_multiple_images(
    project_id=project_id,
    data_collection_id=data_collection_id,
    files=image_files
)

Raster Data

The client supports various raster data types:

• raster: Generic raster data
• RGB: RGB raster data (3 or 4 bands, uint8)
• DTM: Digital Terrain Model data (single band, float32/float64)
• DSM: Digital Surface Model data (single band, float32/float64)

Project Structure

The project is organized as follows:

• src/: Source code for the Pixel client library
  • pixel_client/: Core client library code
    • __init__.py: Main entry point and exports
    • _base.py: Asynchronous client implementation
    • _sync.py: Synchronous client wrapper
    • auth.py: Authentication handling
    • models.py: Data models
    • settings.py: Configuration settings
    • exceptions.py: Custom exceptions
    • types.py: Type definitions
    • utils.py: Utility functions
• docs/: Documentation
  • usage/: User guides and tutorials
  • api/: API reference documentation
  • assets/: Static assets for documentation
  • code_snippets/: Example code snippets
• integration_tests/:
  • data: Sample data for integration tests
  • __init__.py: Initialization for integration tests
  • conftest.py: Configuration for pytest
  • constants.py: Constants used in tests
  • test_smoke.py: Smoketest for client functionality

Documentation

This project uses MkDocs with the Material theme for documentation. The documentation includes:

• Installation: How to install the library
• Getting Started: Getting started with the library
• Examples: Code examples for common tasks
• API Reference: Detailed API documentation

To build the documentation locally:

# Install dependencies with uv
uv sync --group docs --group dev

# Build and serve the documentation
uv run mkdocs serve

Development

Setting Up Development Environment

Requires uv package manager. To set up a development environment:

# Clone the repository
git clone "https://[e-mail]/geonett/Geodata%20Pixel%20-%20Geodata%20Pixel/_git/pixel-client"
cd pixel-client

# Install development dependencies
uv sync --group dev

# Install documentation dependencies
uv sync --group docs --group dev

Pre-commit Hooks

This project uses pre-commit hooks to ensure code quality. To set up pre-commit:

pre-commit install

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

When contributing, please:

1. Follow the existing code style
2. Add tests for new functionality
3. Update documentation as needed
4. Run pre-commit hooks before submitting changes

License

See LICENSE for details.