semvec/pypi-packages huggingface dataset:
commanderbot-ext 0.15.0
A collection of cogs and extensions for discord.py bots.
License: MIT
Requires Python: >=3.8,<4.0
Keywords: discord,bot

# CommanderBot Ext

A collection of cogs and extensions for discord.py bots.

[![package-badge]](https://pypi.python.org/pypi/commanderbot-ext/)
[![version-badge]](https://pypi.python.org/pypi/commanderbot-ext/)

[package-badge]: https://img.shields.io/pypi/v/commanderbot-ext.svg
[version-badge]: https://img.shields.io/pypi/pyversions/commanderbot-ext.svg
profile-decorator 0.1.0
A simple decorator to profile memory usage in production apps
License: MIT
Requires Python: >=3.6.2,<4

# profile-decorator

## Problem/Motivation

Find memory leaks in Python code quickly without significant code changes in a quickly digestible manner such that the root cause can be easily diagnosed.

Until open-telemetry [Adds metrics API](https://github.com/open-telemetry/opentelemetry-python/pull/1887), I want a quick and dirty decorator that will give me the  memory usage of the process in scope before and after a function is run.

## Usage

```python
# example.py
from profile_decorator import profile_decorator

profile_decorator.init()


@profile_decorator.profile_memory
def my_func():
    print("hello, world")


if __name__ == "__main__":
    my_func()
```

```zsh
$ poetry run python example.py
hello, world
{
  "start_time": "2021-08-29T13:20:31.435036",
  "uss_memory_before": 6852608,
  "end_time": "2021-08-29T13:20:31.435892",
  "uss_memory_after": 6995968,
  "lines": [
    {
      "filename": "/home/harry/projects/GitHub/hkiang01/profile-decorator/example.py",
      "lineno": 7,
      "size": 752,
      "size_diff": 0
    },
    {
      "filename": "/home/harry/projects/GitHub/hkiang01/profile-decorator/example.py",
      "lineno": 12,
      "size": 560,
      "size_diff": 0
    }
  ]
}
```

## Design

The decorator will collect the following information:
- name of function
- filepath
- line number
- memory usage before function is run
- timestamp when function is called
- timestamp when function is finished
- memory usage after function is run

It will expose this in json or other easily digestble format for reporting purposes.