Python SDK

This page provides an in-depth introduction to the Python SDK.

Overview

Cloudinary's Python SDK provides simple, yet comprehensive image and video upload, transformation, optimization, and delivery capabilities that you can implement using code that integrates seamlessly with your existing Python application.

Quick example: Transformations

Take a look at the following transformation code and the image it delivers:

This relatively simple code performs all of the following on the original front_face.jpg image before delivering it:

• Crop to a 150x150 thumbnail using face-detection gravity to automatically determine the location for the crop
• Round the corners with a 20 pixel radius
• Apply a sepia effect
• Overlay the Cloudinary logo on the southeast corner of the image (with a slight offset). The logo is scaled down to a 50 pixel width, with increased brightness and partial transparency (opacity = 60%)
• Rotate the resulting image (including the overlay) by 10 degrees
• Convert and deliver the image in PNG format (the originally uploaded image was a JPG)

And here's the URL that would be included in the image tag that's automatically generated from the above code:

In a similar way, you can transform a video.

Quick example: File upload

The following Python code uploads the dog.mp4 video to the sub-folder path, myfolder/mysubfolder. The resulting public_id will be myfolder/mysubfolder/dog. The video will overwrite the existing video if a video with that public_id already exists. When the video upload is complete, the specified notification URL will receive details about the uploaded media asset.

Python Library features

• Build URLs for image and video transformation
• API wrappers: file upload, administration, sprite generation and more
• Server-side file upload + direct unsigned file upload from the browser using the jQuery plugin
• Django form and model integration classes
• Django template tags for embedding and transforming resources

Installation

Cloudinary's Python integration library is available as open-source Python code.

1. Install Cloudinary's module using either easy_install or pip package management tools:

2. Add cloudinary to the list of INSTALLED_APPS in settings.py.

3. Include Cloudinary's Python classes in your code:

Configuration

To use the Cloudinary Python library, you have to configure at least your cloud_name. Your api_key and api_secret are also needed for secure API calls to Cloudinary (e.g., image and video uploads). You can find your product environment configuration credentials in the Dashboard page of the Cloudinary Console.

In addition to the required configuration parameters, you can define a number of optional configuration parameters if relevant.

Setting the configuration parameters can be done globally, using either an environment variable or the config method, or programmatically in each call to a Cloudinary method. Parameters set in a call to a Cloudinary method override globally set parameters.

Setting the CLOUDINARY_URL environment variable

You can configure the required cloud_name, api_key, and api_secret by defining the CLOUDINARY_URL environment variable. The CLOUDINARY_URL value is available in the Dashboard page of the Cloudinary Console. When using Cloudinary through a PaaS add-on (e.g., Heroku or AppFog), this environment variable is automatically defined in your deployment environment. For example:

Set additional parameters, for example upload_prefix and cname, to the environment variable:

Setting configuration parameters globally

Here's an example of setting configuration parameters globally in your Python application:

Python capitalization and data type guidelines

When using the Python SDK, keep these guidelines in mind:

• Parameter names: snake_case. For example: public_id
• Classes: PascalCase. For example: CloudinaryField
• Methods: snake_case. For example: add_tag
• Pass parameter data as: dict or named arguments

Full app demo and code sandbox

This demo uses Cloudinary's auto-tagging feature to recommend product images based on the images you select. Try out the demo and then check out the code behind it.

This code is also available in GitHub.

Jupyter notebook

This Jupyter notebook focuses on uploading images to your product environment. It walks you through:

• Installing and configuring Cloudinary.
• Creating an upload preset.
• Applying the preset to assets being uploaded.
• Uploading assets with incoming transformations.

To run the code snippets in the Jupyter notebook, you'll need to enter your credentials as part of configuration. Find your credentials in the Dashboard page of your Cloudinary Console.

Sample projects

For additional useful code samples and learn how to integrate Cloudinary with your Python applications, take a look at our Sample Projects.

• Basic python sample: Uploading local and remote images to Cloudinary and generating various transformation URLs.
• Django Photo Album: A fully working web application that allows you to upload photos, maintain a database with references, list images with their metadata, and display them using various cloud-based transformations. Image uploading is performed both from the server side and directly from the browser using a jQuery plugin.