Metadata-Version: 2.1
Name: auto-profiler
Version: 1.4
Summary: A timer for profiling a Python function or snippet.
Home-page: https://github.com/modaresimr/auto_profiler
Author: modaresi mr
Author-email: modaresimr+git@gmail.com
License: MIT
Keywords: Profiling,Timer,Python,Auto prfiling,line profiler
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: monotonic (>=1.3)
Requires-Dist: six (>=1.10.0)
Requires-Dist: tree-format (==0.1.1)

# auto_profiler

A timer for profiling a Python function or snippet.

## Features
- Filtering external libraries profiling.
- Filtering very short time functions-> threshold
- Allow depth: you can easily find the time consuming function
- Allow loop or multiple function call
- Allow recursive function call
- Disable it globaly by Profiler.GlobalDisable=True to save time :)
## Installation

Release version:

```bash
$ pip install auto_profiler
```

Development version:

```bash
$ pip install -e git+https://github.com/modaresimr/auto_profiler.git#egg=auto_profiler
```


## Quick start

### Auto profiling
More commonly, chances are that we want to measure the execution time of an entry function and all its subfunctions. In this case, it's too tedious to do it manually, and we can leverage `Profiler` to inject all the timing points for us automatically:

```python
import time # line number 1
import random

from auto_profiler import Profiler, Tree

def f1():
    mysleep(.6+random.random())

def mysleep(t):
    time.sleep(t)

def fact(i):
    f1()
    if(i==1):
        return 1
    return i*fact(i-1)


def show(p):
    print('Time   [Hits * PerHit] Function name [Called from] [Function Location]\n'+\
          '-----------------------------------------------------------------------')
    print(Tree(p.root, threshold=0.5))

@Profiler(depth=4, on_disable=show)
def main():
    for i in range(5):
        f1()

    fact(3)


if __name__ == '__main__':
    main()

```

#### Example Output
```

Time   [Hits * PerHit] Function name [Called from] [function location]
-----------------------------------------------------------------------
8.974s [1 * 8.974]  main  [auto-profiler/profiler.py:267]  [/test/t2.py:30]
├── 5.954s [5 * 1.191]  f1  [/test/t2.py:34]  [/test/t2.py:14]
│   └── 5.954s [5 * 1.191]  mysleep  [/test/t2.py:15]  [/test/t2.py:17]
│       └── 5.954s [5 * 1.191]  <time.sleep>
|
|
|   # The rest is for the example recursive function call fact
└── 3.020s [1 * 3.020]  fact  [/test/t2.py:36]  [/test/t2.py:20]
    ├── 0.849s [1 * 0.849]  f1  [/test/t2.py:21]  [/test/t2.py:14]
    │   └── 0.849s [1 * 0.849]  mysleep  [/test/t2.py:15]  [/test/t2.py:17]
    │       └── 0.849s [1 * 0.849]  <time.sleep>
    └── 2.171s [1 * 2.171]  fact  [/test/t2.py:24]  [/test/t2.py:20]
        ├── 1.552s [1 * 1.552]  f1  [/test/t2.py:21]  [/test/t2.py:14]
        │   └── 1.552s [1 * 1.552]  mysleep  [/test/t2.py:15]  [/test/t2.py:17]
        └── 0.619s [1 * 0.619]  fact  [/test/t2.py:24]  [/test/t2.py:20]
            └── 0.619s [1 * 0.619]  f1  [/test/t2.py:21]  [/test/t2.py:14]
```

### Manual profiling

Sometimes, we only want to measure the execution time of partial snippets or a few functions, then we can inject all timing points into our code manually by leveraging `Timer`:

```python

# manual_example.py

import time

from auto_profiler import Timer, Tree


def main():
    t = Timer('sleep1', parent_name='main').start()
    time.sleep(1)
    t.stop()

    t = Timer('sleep2', parent_name='main').start()
    time.sleep(1.5)
    t.stop()

    print(Tree(Timer.root))


if __name__ == '__main__':
    main()
```

Run the example code:

```bash
$ python manual_example.py
```

and it will show you the profiling result:

```
2.503s  main
├── 1.001s  sleep1
└── 1.501s  sleep2

```

## Supported frameworks

While you can do profiling on normal Python code, as a web developer, chances are that you will usually do profiling on web service code.

Currently supported web frameworks:

- [Flask](http://flask.pocoo.org/)


## Examples

For profiling web service code (involving web requests), check out [examples](examples).


## License

[MIT](http://opensource.org/licenses/MIT)


