alpayonal/flask-profiler

a flask profiler which watches endpoint calls and tries to make some analysis.

Flask-profiler

version: 1.4

Flask-profiler measures endpoints defined in your flask application; and provides you fine-grained report through a web interface.

It gives answers to these questions:

• Where are the bottlenecks in my application?
• Which endpoints are the slowest in my application?
• Which are the most frequently called endpoints?
• What causes my slow endpoints? In which context, with what args and kwargs are they slow?
• How much time did a specific request take?

In short, if you are curious about what your endpoints are doing and what requests they are receiving, give a try to flask-profiler.

With flask-profiler's web interface, you can monitor all your endpoints' performance and investigate endpoints and received requests by drilling down through filters.

Screenshots

Dashboard view displays a summary.

You can create filters to investigate certain type requests. 

You can see all the details of a request.

Quick Start

It is easy to understand flask-profiler going through an example. Let's dive in.

Install flask-profiler by pip.

pip install flask_profiler

Edit your code where you are creating Flask app.

# your app.py
from flask import Flask
import flask_profiler

app = Flask(__name__)
app.config["DEBUG"] = True

# You need to declare necessary configuration to initialize
# flask-profiler as follows:
app.config["flask_profiler"] = {
    "enabled": app.config["DEBUG"],
    "storage": {
        "engine": "sqlite"
    },
    "basicAuth":{
        "enabled": True,
        "username": "admin",
        "password": "admin"
    },
    "ignore": [
	    "^/static/.*"
	]
}


@app.route('/product/<id>', methods=['GET'])
def getProduct(id):
    return "product id is " + str(id)


@app.route('/product/<id>', methods=['PUT'])
def updateProduct(id):
    return "product {} is being updated".format(id)


@app.route('/products', methods=['GET'])
def listProducts():
    return "suppose I send you product list..."

@app.route('/static/something/', methods=['GET'])
def listProducts():
    return "this should not be tracked..."

# In order to active flask-profiler, you have to pass flask
# app as an argument to flask-profiler.
# All the endpoints declared so far will be tracked by flask-profiler.
flask_profiler.init_app(app)


# endpoint declarations after flask_profiler.init_app() will be
# hidden to flask_profiler.
@app.route('/doSomething', methods=['GET'])
def doSomething():
    return "flask-profiler will not measure this."


# But in case you want an endpoint to be measured by flask-profiler,
# you can specify this explicitly by using profile() decorator
@app.route('/doSomething', methods=['GET'])
@flask_profiler.profile()
def doSomethingImportant():
    return "flask-profiler will measure this request."

if __name__ == '__main__':
    app.run(host="127.0.0.1", port=5000)

Now run your app.py

python app.py

And make some requests like:

curl http://127.0.0.1:5000/products
curl http://127.0.0.1:5000/product/123
curl -X PUT -d arg1=val1 http://127.0.0.1:5000/product/123

If everything is okay, Flask-profiler will measure these requests. You can see the result heading to http://127.0.0.1:5000/flask-profiler/ or get results as JSON http://127.0.0.1:5000/flask-profiler/api/measurements?sort=elapsed,desc

Using with different database system

Currently, SQLite and MongoDB database systems are supported. However, it is easy to support other database systems. If you would like to have others, please go to contribution documentation. (It is really easy.)

SQLite

In order to use SQLite, just specify it as the value of storage.engine directive as follows.

app.config["flask_profiler"] = {
    "storage": {
        "engine": "sqlite",
    }
}

Below the other options are listed.

Filter key	Description	Default
storage.FILE	SQLite database file name	flask_profiler.sql
storage.TABLE	table name in which profiling data will reside	measurements

MongoDB

In order to use MongoDB, just specify it as the value of storage.engine directive as follows.

app.config["flask_profiler"] = {
    "storage": {
        "engine": "mongodb",
    }
}

Custom database engine

Specify engine as string module and class path.

app.config["flask_profiler"] = {
    "storage": {
        "engine": "custom.project.flask_profiler.mysql.MysqlStorage",
        "MYSQL": "mysql://user:password@localhost/flask_profiler"
    }
}

The other options are listed below.

Filter key	Description	Default
storage.MONGO_URL	mongodb connection string	mongodb://localhost
storage.DATABASE	database name	flask_profiler
storage.COLLECTION	collection name	measurements

Sampling

Control the number of samples taken by flask-profiler

You would want control over how many times should the flask profiler take samples while running in production mode. You can supply a function and control the sampling according to your business logic.

Example 1: Sample 1 in 100 times with random numbers

app.config["flask_profiler"] = {
    "sampling_function": lambda: True if random.sample(list(range(1, 101)), 1) == [42] else False
}

Example 2: Sample for specific users

app.config["flask_profiler"] = {
    "sampling_function": lambda: True if user is 'divyendu' else False
}

If sampling function is not present, all requests will be sampled.

Changing flask-profiler endpoint root

By default, we can access flask-profiler at /flask-profiler

app.config["flask_profiler"] = {
        "endpointRoot": "secret-flask-profiler"
}

Ignored endpoints

Flask-profiler will try to track every endpoint defined so far when init_app() is invoked. If you want to exclude some of the endpoints, you can define matching regex for them as follows:

app.config["flask_profiler"] = {
        "ignore": [
	        "^/static/.*",
	        "/api/users/\w+/password"
        ]
}

Contributing

Contributions are welcome!

Review the Contributing Guidelines for details on how to:

• Submit issues
• Add solutions to existing challenges
• Add new challenges

Authors

• Musafa Atik
• Fatih Sucu
• Safa Yasin Yildirim

License

MIT