# PY Profiler
A library to measure method, function or your restful api execution time.
## Install
- Run `pip install py-profiler` or `pip3 install py-profiler` to install this library
## Usage
It comes with a really easy api to use, you can add `profiler(name = None)` decorator to any method or function you want
to measure its execution time.
E.g:
```python
from py_profiler import profiler, profiling_service
@profiler('hello')
def hello():
print('hello')
class Foo:
@profiler('Food.some_thing')
def some_thing(self):
print('some_thing')
# By default, profiler name is f'{class_name}.{method_name}'
@profiler()
def method_2(self):
print('method_2')
```
## Access Profiler
There are 3 ways to access the profiler:
- View as a raw table in the console.
- View as a HTML page using a provided Flask blueprint.
- Integrate with your own RESTFul framework.
- Exec time is in milliseconds
1. **View as a table**
```python
from py_profiler import profiling_service
print(profiling_service.as_table())
```
| No | Name | Total Req | Pending Req | Total Exec Time | Last Exec Time | Highest Exec Time | Request Rate (req/sec) | Avg Time/Request (millis/req) |
|----|--------------------------------|--------|----------|------------|------------|------------|------------|------------|
| 1 | Foo.method_2 | 1 | 0 | 0.014 | 0.014 | 0.014 | 71428.571 | 0.014 |
| 2 | Food.some_thing | 1 | 0 | 0.011 | 0.011 | 0.011 | 90909.091 | 0.011 |
| 3 | hello | 1 | 0 | 0.031 | 0.031 | 0.031 | 32258.065 | 0.031 |
2. **Integrate with FastAPI**
- If you are using FastAPI to implement your Restful API. You can add `profiler_router` to your FastAPI app.
E.g:
```python
from fastapi import FastAPI
from py_profiler.fastapi_profiler_controller import profiler_router
app = FastAPI()
app.include_router(profiler_router)
```
Then you can access the profiler page at: `http://127.0.0.1:8080/profiler`
3. **Integrate with Flask**
- If you are using Flask to implement your Restful API. You can add `profiler_blueprint` to your Flash app.
E.g:
```python
from flask import Flask
from waitress import serve
from py_profiler.profiler_controller import profiler_blueprint
app = Flask(__name__)
app.register_blueprint(profiler_blueprint)
serve(
app,
host="0.0.0.0",
port=8080
)
```
Then you can access the profiler page at: `http://127.0.0.1:8080/profiler`
4. **Integrate with 3rd restful library**.
You can build your custom profiler viewer by using `as_html()`
```python
from py_profiler import profiling_service
html_page = profiling_service.as_html()
```
Then, you can implement a html page and return this `html_page` to your client to see profiler viewer.
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