py-profiler 0.2.8

A library to measure your method, function execution time.

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:

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

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:

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:

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()

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.