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Converting a video to a GIF in Python

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Updated at July 24, 2024

You will create a video converter using FFmpeg and Yandex Message Queue. This guide is intended for Linux and macOS users.

To create an application:

  1. Prepare your cloud.
  2. Create resources.
  3. Create an API function.
  4. Create a converter function.
  5. Create a trigger.
  6. Test the application.

If you no longer need the resources you created, delete them.

Prepare your cloud

Sign up for Yandex Cloud and create a billing account:

  1. Go to the management console and log in to Yandex Cloud or create an account if you do not have one yet.
  2. On the Yandex Cloud Billing page, make sure you have a billing account linked and it has the ACTIVE or TRIAL_ACTIVE status. If you do not have a billing account, create one.

If you have an active billing account, you can go to the cloud page to create or select a folder for your infrastructure to operate in.

Learn more about clouds and folders.

The infrastructure support cost includes:

Create resources

  1. Download the archive with the files required to create a video converter.

  2. Create a service account named ffmpeg-sa and assign it the following roles:

    • ymq.reader
    • ymq.writer
    • lockbox.payloadViewer
    • storage.viewer
    • storage.uploader
    • ydb.admin
    • functions.functionInvoker

  3. Create a static key for the service account. Save the Key ID and Your secret key.

  4. Create a secret named ffmpeg-sa-secret in Yandex Lockbox. Under Version, specify:

    • ACCESS_KEY_ID as the key and Key ID from the previous step as the value.
    • SECRET_ACCESS_KEY as the key and Your secret key from the previous step as the value.

    Save the secret ID from the Information about secret section.

  5. Create a message queue named converter-queue in Yandex Message Queue. Save the queue URL from the General information section.

  6. Create a YDB database in Serverless mode. Save the Endpoint from the Document API endpoint section.

  7. Create a table in the database:

  1. Create a bucket with restricted access in Yandex Object Storage.

Create an API function

The function implements an API which you can use to perform the following actions:

  • convert: Transfer a video to convert. The function writes the task to the tasks table using the Document API.
  • get_task_status: Get the task status. The function checks whether the task is completed and returns a link to a GIF file.

  1. Create a function named ffmpeg-api.

  2. Create a function version:

    1. Create a file named requirements.txt and specify the following library in it:

      boto3

    2. Create a file named index.py and paste the contents of ffmpeg-api.py from the archive into it.

    3. Specify the following parameters:

      • Runtime environment: python37
      • Entry point: index.handle_api
      • Timeout, sec: 5
      • Service account: ffmpeg-sa

    4. Add environment variables:

      • DOCAPI_ENDPOINT: Endpoint from the database configuration.
      • SECRET_ID: Yandex Lockbox secret ID.
      • YMQ_QUEUE_URL: Message Queue queue URL.

Create a converter function

A converter function is run by a trigger. It performs video processing and registers the execution result in the tasks table.

Video conversion is done using the FFmpeg utility. The FFmpeg executable file is larger than 70 MB. To upload it along with the function code, create a ZIP archive and upload it via Object Storage. Learn more about code upload formats.

  1. Create a function named ffmpeg-converter.

  2. Create an src.zip archive with the following files:

    • The requirements.txt file:

      boto3
requests

    • The index.py file with the contents of ffmpeg-converter.py from the archive.

    • The FFmpeg executable file. Go to the FFmpeg official website, navigate to the Linux Static Builds section, download the archive with the 64-bit FFmpeg version, and make the file executable by running the chmod +x ffmpeg command.

  3. Upload src.zip to the previously created bucket.

  4. Create a function version:

    1. Specify the following parameters:

      • Runtime environment: python37
      • Method: Object Storage upload method
      • Bucket: Name of the previously created bucket
      • Object: src.zip
      • Entry point: index.handle_process_event
      • Timeout, sec: 600
      • Memory: 2048 MB
      • Service account: ffmpeg-sa

    2. Add environment variables:

      • DOCAPI_ENDPOINT: Endpoint from the database configuration
      • SECRET_ID: Yandex Lockbox secret ID
      • YMQ_QUEUE_URL: Message Queue queue URL
      • S3_BUCKET: Name of the previously created bucket

Create a trigger

A message queue is handled using a trigger for Message Queue. It invokes the converter function when messages arrive in converter-queue.

  1. In the management console, select the folder where you want to create a trigger.
  2. Select Cloud Functions.
  3. Go to the Triggers tab.
  4. Click Create trigger.
  5. Under Basic settings:
    • Name the trigger ffmpeg-trigger.
    • In the Type field, select Message Queue.
  6. Under Message Queue message settings, select converter-queue and the ffmpeg-sa service account with the permissions to read messages from the queue.
  7. Under Function settings:
    • Select the function to be invoked by the trigger: ffmpeg-converter.
    • Specify the function version tag: $latest.
    • Specify the service account to be used to invoke the function: ffmpeg-sa.
  8. Click Create trigger.

Test the application

Create a task

  1. In the management console, select the folder with the ffmpeg-api function.

  2. Select Cloud Functions.

  3. Select ffmpeg-api.

  4. Go to the Testing tab.

  5. In the Payload field, enter:

    {"action":"convert", "src_url":"<link_to_video>"}

    Where <link_to_video> is a link to an MP4 video file saved to Yandex Disk.

  6. Click Run test.

  7. You will see the task ID in the Function output field:

    { "task_id": "c4269ceb-8d3a-40fe-95f0-84cf********" }

View the queue statistics

After the task is created, the number of messages in the queue increases by one and a trigger fires. Make sure that messages arrive in the queue and are handled. To do this, view the queue statistics.

  1. In the management console, select the folder with converter-queue.
  2. Select Message Queue.
  3. Select converter-queue.
  4. Under General information, you can see the number of enqueued messages and those being handled.
  5. Go to Monitoring. View the Overall queue stats charts.

View the function logs

The trigger should invoke the converter function for each message in the queue. To make sure the function is invoked, check its logs.

  1. In the management console, select the folder with the ffmpeg-converter function.
  2. Select Cloud Functions.
  3. Select ffmpeg-converter.
  4. Go to the Logs tab and specify the period to view them for.

  1. In the management console, select the folder with the ffmpeg-api function.

  2. Select Cloud Functions.

  3. Select ffmpeg-api.

  4. Go to the Testing tab.

  5. In the Payload field, enter the following request:

    {"action":"get_task_status", "task_id":"<job_ID>"}

  6. Click Run test.

  7. If video conversion to GIF is not completed, the Function output field returns:

    {
    "ready": false
}

    Otherwise, you will get a link to the GIF file:

    {
    "ready": true,
    "gif_url": "https://storage.yandexcloud.net/<bucket_name>/1b4db1a6-f2b2-4b1c-b662-37f7********.gif?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=qxLftbbZ91U695ysemyZ%2F202********ru-central1%2Fs3%2Faws4_request&X-Amz-Date=20210831T110351Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=f4a5fe7848274a09be5b221fbf8a9f6f2b385708cfa351861a4e69df********"
}

How to delete the resources you created

To shut down the infrastructure and stop paying for the resources you created:

  1. Delete the converter-queue.
  2. Delete the database.
  3. Delete all objects from the bucket.
  4. Delete the bucket.
  5. Delete the ffmpeg-api and ffmpeg-converter functions.
  6. Delete the ffmpeg-trigger.
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