Sample-Python-Telegram-Bot-AWS-Serverless-PTBv20.x

This is for PTB v20.x (and higher), which has made some async changes. For PTB v13.x, see this repo

This project contains source code and supporting files for a Python Telegram Bot v20.x serverless application, using Webhooks, that you can deploy with the AWS SAM CLI. Serverless is the best way to run a bot - with webhooks, there is no polling, and your bot only gets invoked when needed. You can run this for free - the AWS Lambda free tier includes one million free requests per month and 400,000 GB-seconds of compute time per month.

Versions

• Python 3.9
• python-telegram-bot 20.2 (pinned in requirements.txt)

Architecture

Requests come in via the Lambda Function URL endpoint, which get routed to a Lambda function. The Lambda function runs and posts back to Telegram. Logs are stored on CloudWatch. All of this is defined using AWS SAM, an IaC toolkit that simplifies building and running serverless applications on AWS.

It includes the following files and folders.

• ptb_lambda.py - Code for the bot's Lambda function. It echos back whatever text is sent to the bot.
• events - Invocation events that you can use to invoke the function.
• tests - Unit tests for the application code.
• template.yaml - A template that defines the application's AWS resources.
• requirements.txt - which pins the version of python-telegram-bot

The application uses several AWS resources, including a Lambda function and a Lambda Function URL HTTPS endpoint as a Telegram webhook. These resources are defined in the template.yaml file in this project. You can update the template to add AWS resources through the same deployment process that updates your application code.

If you prefer to use an integrated development environment (IDE) to build and test your application, you can use the AWS Toolkit.
The AWS Toolkit is an open source plug-in for popular IDEs that uses the SAM CLI to build and deploy serverless applications on AWS. The AWS Toolkit also adds a simplified step-through debugging experience for Lambda function code. See the following links to get started.

• CLion
• GoLand
• IntelliJ
• WebStorm
• Rider
• PhpStorm
• PyCharm
• RubyMine
• DataGrip
• VS Code
• Visual Studio

Deploy the sample application

• Create your bot using BotFather, and note the token, e.g. 12334342:ABCD124324234
• Update ptb_lambda.py with the token
• Install AWS CLI, and configure it

The Serverless Application Model Command Line Interface (SAM CLI) is an extension of the AWS CLI that adds functionality for building and testing Lambda applications.

To use the SAM CLI, you need the following tools.

• SAM CLI - Install the SAM CLI
• Python 3 installed

To build and deploy your application for the first time, run the following in your shell:

sam build
sam deploy --guided

The first command will build the source of your application. The second command will package and deploy your application to AWS, with a series of prompts:

• Stack Name: The name of the stack to deploy to CloudFormation. This should be unique to your account and region, and a good starting point would be something matching your project name.
• AWS Region: The AWS region you want to deploy your app to.
• Confirm changes before deploy: If set to yes, any change sets will be shown to you before execution for manual review. If set to no, the AWS SAM CLI will automatically deploy application changes.
• Allow SAM CLI IAM role creation: Many AWS SAM templates, including this example, create AWS IAM roles required for the AWS Lambda function(s) included to access AWS services. By default, these are scoped down to minimum required permissions. To deploy an AWS CloudFormation stack which creates or modifies IAM roles, the CAPABILITY_IAM value for capabilities must be provided. If permission isn't provided through this prompt, to deploy this example you must explicitly pass --capabilities CAPABILITY_IAM to the sam deploy command.
• Save arguments to samconfig.toml: If set to yes, your choices will be saved to a configuration file inside the project, so that in the future you can just re-run sam deploy without parameters to deploy changes to your application.

• You can find your Lambda Function URL Endpoint in the output values displayed after deployment. e.g. https://1fgfgfd56.lambda-url.eu-west-1.on.aws/
• Update your Telegram bot to change from polling to Webhook, by pasting this URL in your browser, or curl'ing it: https://api.telegram.org/bot12334342:ABCD124324234/setWebHook?url=https://1fgfgfd56.lambda-url.eu-west-1.on.aws/. Use your bot token and Lambda Function URL endpoint. You can check that it was set correctly by going to https://api.telegram.org/bot12334342:ABCD124324234/getWebhookInfo, which should include the url of your Lambda Function URL, as well as any errors Telegram is encounterting calling your bot on that API.

For future deploys, you can just run:

sam build && sam deploy

Use the SAM CLI to build and test locally

Build your application with the sam build --use-container command.

Sample-Python-Telegram-Bot-AWS-Serverless$ sam build --use-container

The SAM CLI installs dependencies defined in hello_world/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.

Test a single function by invoking it directly with a test event. An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.

Run functions locally and invoke them with the sam local invoke command.

Sample-Python-Telegram-Bot-AWS-Serverless$ sam local invoke HelloWorldFunction --event events/event.json

The SAM CLI can also emulate your application's API. Use the sam local start-api to run the API locally on port 3000.

Sample-Python-Telegram-Bot-AWS-Serverless$ sam local start-api
Sample-Python-Telegram-Bot-AWS-Serverless$ curl http://localhost:3000/

Add a resource to your application

The application template uses AWS Serverless Application Model (AWS SAM) to define application resources. AWS SAM is an extension of AWS CloudFormation with a simpler syntax for configuring common serverless application resources such as functions, triggers, and APIs. For resources not included in the SAM specification, you can use standard AWS CloudFormation resource types.

Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

Sample-Python-Telegram-Bot-AWS-Serverless$ sam logs -n HelloWorldFunction --stack-name Sample-Python-Telegram-Bot-AWS-Serverless --tail

You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.

Tests

Tests are defined in the tests folder in this project. Use PIP to install the test dependencies and run tests.

Sample-Python-Telegram-Bot-AWS-Serverless$ pip install -r tests/requirements.txt --user
# unit test
Sample-Python-Telegram-Bot-AWS-Serverless$ python -m pytest tests/unit -v
# integration test, requiring deploying the stack first.
# Create the env variable AWS_SAM_STACK_NAME with the name of the stack we are testing
Sample-Python-Telegram-Bot-AWS-Serverless$ AWS_SAM_STACK_NAME=<stack-name> python -m pytest tests/integration -v

Cleanup

To delete the sample application that you created, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:

sam delete

Resources

See the AWS SAM developer guide for an introduction to SAM specification, the SAM CLI, and serverless application concepts.

Next, you can use AWS Serverless Application Repository to deploy ready to use Apps that go beyond hello world samples and learn how authors developed their applications: AWS Serverless Application Repository main page

Whats Next?

• Instead of storing the Telegram token in your source code, use Lambda Environment Variables, or AWS SSM to securely store the token
• Want to store data in a serverless database? Try out Amazon DynamoDB
• High load, and what to respond async to Telegram? Try adding an SQS queue in front of the Lambda function
• Check out this fully featured Telegram Bot running on AWS Serverless