Skip to main content

Python SDK for Magic Hour API

Project description

Magic Hour Python SDK

PyPI - Version

The Magic Hour Python Library provides convenient access to the Magic Hour API. This library offers both synchronous and asynchronous clients powered by httpx.

Documentation

For full documentation of all APIs, please visit https://docs.magichour.ai

If you have any questions, please reach out to us via discord.

Install

pip install magic_hour

Synchronous Client Usage

from magic_hour import Client

# generate your API Key at https://magichour.ai/developer
client = Client(token="my api key")

response = client.v1.face_swap_photo.generate(
    assets={
        "face_swap_mode": "all-faces",
        "source_file_path": "/path/to/source/image.png",
        "source/image": "/path/to/target/image.png",
    },
    name="Face Swap image",
    wait_for_completion=True,
    download_outputs=True,
    download_directory="./outputs/",
)
print(f"Project ID: {response.id}")
print(f"Status: {response.status}")
print(f"Downloaded files: {response.downloaded_paths}")

Asynchronous Client Usage

from magic_hour import AsyncClient

# generate your API Key at https://magichour.ai/developer
client = AsyncClient(token="my api key")

response = await client.v1.face_swap_photo.generate(
    assets={
        "face_swap_mode": "all-faces",
        "source_file_path": "/path/to/source/image.png",
        "target_file_path": "/path/to/target/image.png",
    },
    name="Face Swap image",
    wait_for_completion=True,
    download_outputs=True,
    download_directory="./outputs/",
)
print(f"Project ID: {response.id}")
print(f"Status: {response.status}")
print(f"Downloaded files: {response.downloaded_paths}")

Client Functions

Most resources that generate media content support two methods:

  • generate() - A high-level convenience method that handles the entire workflow
  • create() - A low-level method that only initiates the generation process

Generate Function

The generate() function provides a complete end-to-end solution:

  • Uploads local file to Magic Hour storage
  • Calls the API to start generation
  • Automatically polls for completion
  • Downloads generated files to your local machine
  • Returns both API response data and local file paths

Additional Parameters:

  • wait_for_completion (bool, default True): Whether to wait for the project to complete.
  • download_outputs (bool, default True): Whether to download the generated files
  • download_directory (str, optional): Directory to save downloaded files (defaults to current directory)
# Generate function - handles everything automatically
response = client.v1.ai_image_generator.generate(
    style={"prompt": "A beautiful sunset over mountains"},
    name="Sunset Image",
    wait_for_completion=True,       # Wait for status to be complete/error/canceled
    download_outputs=True,          # Download files automatically
    download_directory="./outputs/" # Where to save files
)

# You get both the API response AND downloaded file paths
print(f"Project ID: {response.id}")
print(f"Status: {response.status}")
print(f"Downloaded files: {response.downloaded_paths}")

Create Function

The create() function provides granular control:

  • Only calls the API to start the generation process
  • Returns immediately with a project ID and amount of credits used
  • Requires manual status checking and file downloading
# Create function - only starts the process
create_response = client.v1.ai_image_generator.create(
    style={"prompt": "A beautiful sunset over mountains"},
    name="Sunset Image"
)

# You get just the project ID and initial response
project_id = create_response.id
print(f"Started project: {project_id}")

# You must handle the rest:
# 1. Poll for completion. We provide a helper function to handle polling for you
result = client.v1.image_projects.check_status(
    wait_for_completion=True,
    download_outputs=False,
)
# 2. Download files using the download URLs
download_urls = result.downloads
# download the files using your preferred way

Choosing Between Which Function to use

Use generate() when:

  • You want a simple, one-call solution
  • You're building a straightforward application
  • You don't need custom polling or download logic

Use create() when:

  • You need custom status checking logic
  • You're integrating with existing job processing systems
  • You want to separate generation initiation from completion handling
  • You need fine-grained control over the entire workflow

Module Documentation and Snippets

v1

v1.ai_clothes_changer

  • create - AI Clothes Changer
  • generate - AI Clothes Changer Generate Workflow

v1.ai_face_editor

v1.ai_gif_generator

v1.ai_headshot_generator

  • create - AI Headshots
  • generate - Ai Headshot Generator Generate Workflow

v1.ai_image_editor

  • create - AI Image Editor
  • generate - Ai Image Editor Generate Workflow

v1.ai_image_generator

v1.ai_image_upscaler

  • create - AI Image Upscaler
  • generate - Ai Image Upscaler Generate Workflow

v1.ai_meme_generator

  • create - AI Meme Generator
  • generate - Ai Meme Generator Generate Workflow

v1.ai_photo_editor

  • create - AI Photo Editor
  • generate - Ai Photo Editor Generate Workflow

v1.ai_qr_code_generator

  • create - AI QR Code
  • generate - Ai Qr Code Generator Generate Workflow

v1.ai_talking_photo

  • create - AI Talking Photo
  • generate - Ai Talking Photo Generate Workflow

v1.animation

v1.auto_subtitle_generator

  • create - Auto Subtitle Generator
  • generate - Auto Subtitle Generator Generate Workflow

v1.face_detection

  • create - Face Detection
  • generate - Face Detection Generate Workflow
  • get - Get face detection details

v1.face_swap

v1.face_swap_photo

  • create - Face Swap Photo
  • generate - Face Swap Photo Generate Workflow

v1.files

v1.files.upload_urls

  • create - Generate asset upload urls

v1.image_background_remover

  • create - Image Background Remover
  • generate - Image Background Remover Generate Workflow

v1.image_projects

v1.image_to_video

v1.lip_sync

v1.photo_colorizer

  • create - Photo Colorizer
  • generate - Photo Colorizer Generate Workflow

v1.text_to_video

v1.video_projects

v1.video_to_video

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

magic_hour-0.36.1.tar.gz (91.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

magic_hour-0.36.1-py3-none-any.whl (230.2 kB view details)

Uploaded Python 3

File details

Details for the file magic_hour-0.36.1.tar.gz.

File metadata

  • Download URL: magic_hour-0.36.1.tar.gz
  • Upload date:
  • Size: 91.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.5 CPython/3.8.18 Linux/6.11.0-1018-azure

File hashes

Hashes for magic_hour-0.36.1.tar.gz
Algorithm Hash digest
SHA256 093e2d9217a8b7a9cbf4ca71f5de7b3bf088b4c0e9a4c69f815571e2739aa507
MD5 12e98741129150003c4abea6055cca5a
BLAKE2b-256 ad72920f028945f4db655aba4c105c9b46e9351ce15419ec71c2ae1318434550

See more details on using hashes here.

File details

Details for the file magic_hour-0.36.1-py3-none-any.whl.

File metadata

  • Download URL: magic_hour-0.36.1-py3-none-any.whl
  • Upload date:
  • Size: 230.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.5 CPython/3.8.18 Linux/6.11.0-1018-azure

File hashes

Hashes for magic_hour-0.36.1-py3-none-any.whl
Algorithm Hash digest
SHA256 10e6e438102667bcea6d6cb053fe2a8c36dc89e56458b572007ad7aca7284474
MD5 3d05fbcdeef5a17b8802b6e7f3a4ad10
BLAKE2b-256 b20c9d0f66c053fd8b9481f9368ad0ca824bb5502ea07de990facf7eb63a6776

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page