# Amazon CodeGuru Profiler Python Demo Flask Web Application

![CodeGuru Profiler Console Screenshot](resources/CodeGuruProfilerPythonScreenshotDemoFlask.png)

### Code

The code for the Flask web application is based on the [Flask official tutorial](https://flask.palletsprojects.com/en/1.1.x/tutorial/), with modifications to make some network operations.

## Setup

Here is the summary of the steps that follow.

1. Make sure you have installed the latest version of [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-welcome.html).
Use an IAM entity for the AWS CLI that has permissions to access CodeGuru Profiler, S3 and SQS to create all the required components for the demo application to run.
2. Create a profiling group in CodeGuru Profiler, named `PythonDemoFlaskApplication`.
3. Create a S3 bucket, e.g. `s3://python-demo-application-test-bucket`. Note, the bucket name must be unique across all of Amazon S3.
See [here](https://docs.aws.amazon.com/cli/latest/reference/s3/mb.html) for more details.
5. Create virtual environment with venv, e.g. `python3 -m venv ./venv`.
6. Activate the virtual environment, e.g. `source venv/bin/activate`.
7. Install the needed dependencies that are used for the demo application through `pip` using the `requirements.txt` file.

Here are the commands to run on your machine.

```bash
aws configure # Set up your AWS credentials and region as usual.
```

```bash
aws codeguruprofiler create-profiling-group --profiling-group-name PythonDemoFlaskApplication

# It is required to set the DEMO_APP_BUCKET_NAME environment applications for later running the demo application.

# Make sure you update `YOUR-BUCKET-NAME-REPLACE-ME`with a bucket name that is unique across all of Amazon S3.
export DEMO_APP_BUCKET_NAME=YOUR-BUCKET-NAME-REPLACE-ME
aws s3 mb s3://${DEMO_APP_BUCKET_NAME}
```

```bash
python3 -m venv ./venv
source venv/bin/activate
pip install -r requirements.txt
```

## How to run

The main entry point is in `sample-demo-flask-app/flaskr/__init__.py` that initializes applications, like the main one from `sample-demo-flask-app/flaskr/blog.py`.

* The configuration for gunicorn is in `gunicorn_conf.py`.

* There in the `gunicorn_conf.py` you can find the configuration for CodeGuru Profiler to start and to log.

### Initialize the local db

After the following command, there will now be a `flaskr.sqlite` file in the `instance/` folder in your project.
````bash
flask init-db
````

### Run the service.

Start the service using the gunicorn configuration.
```bash
# Start the service using a gunicorn server and 5 workers.
gunicorn "flaskr:create_app()" -c gunicorn_conf.py --log-level DEBUG --workers=5
```

Note that the agent currently does NOT work with -k option for gevent workers.

### Generate traffic

Generate traffic by running the following script that will make thousands of requests to the local server started at `http://127.0.0.1:8000`.
```bash
./generate-traffic.sh
```

## How to see the results

Go to the [AWS CodeGuru Profiler console](https://console.aws.amazon.com/codeguru/profiler) to check the results. Choose the region you picked and your profiling group.

The attached screenshot was captured by hiding the `gunicorn.workers.sync:SyncWorker:wait` frame because it covered more than half of the time.
```