flask_profiler 1.7

API endpoint profiler for Flask framework

# Flask-profiler


**version: 1.7** [](https://travis-ci.org/muatik/flask-profiler)

##### 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.
```sh
pip install flask_profiler
```


Edit your code where you are creating Flask app.
```python
# 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('/doSomethingImportant', 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:
```sh
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

If you like to initialize your extensions in other files or use factory apps pattern, you can also create a instance of the `Profiler` class, this will register all your endpoints once you app run by first time. E.g:

```python
from flask import Flask
from flask_profiler import Profiler

profiler = 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/.*"
]
}

profiler = Profiler() # You can have this in another module
profiler.init_app(app)
# Or just Profiler(app)

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

```

## Using with different database system
You can use flaskprofiler with **SqlLite**, **MongoDB**, **Postgresql**, **Mysql** or **MongoDB** database systems. 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.

```json
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.

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

### SQLAchemy
In order to use SQLAchemy, just specify it as the value of `storage.engine` directive as follows.
Also first create an empty database with the name "flask_profiler".

```python
app.config["flask_profiler"] = {
"storage": {
"engine": "sqlalchemy",
"db_url": "postgresql://user:pass@localhost:5432/flask_profiler" # optional, if no db_url specified then sqlite will be used.
}
}
```

### Custom database engine
Specify engine as string module and class path.

```json
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
```python
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
```python
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 <your-app>/flask-profiler

```python
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:

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


## Contributing

Contributions are welcome!

Review the [Contributing Guidelines](https://github.com/muatik/flask-profiler/wiki/Development) for details on how to:

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

## Authors
* [Musafa Atik](https://www.linkedin.com/in/muatik)
* Fatih Sucu
* [Safa Yasin Yildirim](https://www.linkedin.com/in/safayasinyildirim)

## License
MIT