Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/adriamontoto/developing-tools
The "Developing Tools" project is a Python 🐍 package designed to enhance the development process by providing a collection of tools/utilities ⚒️ aimed at improving debugging, performance measurement, error handling, ...
https://github.com/adriamontoto/developing-tools
decorator development python python3 python311 python312 python313 tools utilities
Last synced: 3 months ago
JSON representation
The "Developing Tools" project is a Python 🐍 package designed to enhance the development process by providing a collection of tools/utilities ⚒️ aimed at improving debugging, performance measurement, error handling, ...
- Host: GitHub
- URL: https://github.com/adriamontoto/developing-tools
- Owner: adriamontoto
- License: mit
- Created: 2024-06-22T08:12:55.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2024-11-13T08:19:28.000Z (3 months ago)
- Last Synced: 2024-11-13T09:24:46.727Z (3 months ago)
- Topics: decorator, development, python, python3, python311, python312, python313, tools, utilities
- Language: Python
- Homepage: https://pypi.org/project/developing-tools/
- Size: 68.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
- Security: SECURITY.md
Awesome Lists containing this project
README
# 🐣💻 Developing Tools
The "Developing Tools" project is a Python 🐍 package designed to enhance the development process by providing a collection of tools/utilities aimed at improving debugging, performance measurement, error handling, ...
These tools ⚒️ are intended to assist developers in identifying performance bottlenecks, handling transient errors, and gaining insights into function behavior during runtime. The package is easy to install and use, making it a good addition to any Python developer's toolkit 🚀.
## Table of Contents
- [📥 Installation](#installation)
- [💻 Utilization](#utilization)
- [🔑 License](#license)
## 📥 Installation
```bash
pip install developing-tools
```
## 💻 Utilization
### Execution Time
The `execution_time` decorator allows you to measure the execution time of a function. The decorator has one parameter:
- `output_decimals`: Number of decimal places to display in the output. Default is 10.
```python
from time import sleep
from developing_tools.functions import execution_time
@execution_time(output_decimals=2)
def too_slow_function() -> None:
sleep(2)
too_slow_function()
# >>> Function "too_slow_function" took 2.00 seconds to execute.
```
### Retry It
The `retryit` decorator allows you to retry a function multiple times in case of failure. The decorator has two parameters:
- `attempts`: The number of attempts to execute the function, if _None_ the function will be executed indefinitely. Default is _None_.
- `delay`: The delay between attempts in seconds, if a tuple is provided the delay will be randomized between the two values. Default is 5 seconds.
- `raise_exception`: If _True_ the decorator will raise the last caught exception if the function fails all attempts. Default is _True_.
- `valid_exceptions`: A tuple of exceptions that the decorator should catch and retry the function, if _None_ the decorator will catch all exceptions. Default is _None_.
```python
from developing_tools.functions import retryit
@retryit(attempts=3, delay=0.5, raise_exception=True, valid_exceptions=(ValueError,))
def failing_function() -> None:
raise ValueError('This function always fails!')
failing_function()
# >>> Function failed with error: "This function always fails!". Retrying in 0.50 seconds ...
# >>> Attempt [2/3] to execute function "failing_function".
# >>> Function failed with error: "This function always fails!". Retrying in 0.50 seconds ...
# >>> Attempt [3/3] to execute function "failing_function".
# >>> Function failed with error: "This function always fails!". No more attempts.
# Traceback (most recent call last):
# File "/main.py", line 7, in
# failing_function()
# File "/developing_tools/functions/retryit.py", line 132, in wrapper
# raise exception
# File "/developing_tools/functions/retryit.py", line 124, in wrapper
# return function(*args, **kwargs)
# ^^^^^^^^^^^^^^^^^^^^^^^^^
# File "/main.py", line 5, in failing_function
# raise ValueError('This function always fails!')
# ValueError: This function always fails!
```
### Print Parameters
The `print_parameters` decorator allows you to print the parameters of a function. The decorator has two parameters:
- `show_types`: If _True_ the decorator will print the types of the parameters. Default is _False_.
- `include_return`: If _True_ the decorator will print the return value of the function. Default is _True_.
```python
from developing_tools.functions import print_parameters
@print_parameters(show_types=True, include_return=True)
def normal_function(a: int, b: str, c: int, d) -> str:
return a
normal_function(1, 'Hello', c=3, d=4)
# >>> Positional arguments:
# >>> Argument 1: value "1", type int
# >>> Argument 2: value "Hello", type str
# >>>
# >>> Keyword arguments:
# >>> Argument c: value "3", supposed type int, real type int
# >>> Argument d: value "4", supposed type Any, real type int
# >>>
# >>> Return value:
# >>> "1", supposed type str, real type int
```
### Timeout
The `timeout` decorator allows you to set a maximum execution time for a function. The decorator has one parameter:
- `seconds`: The maximum number of seconds the function is allowed to execute before raising a _TimeoutError_. Default is 10 seconds.
```python
from time import sleep
from developing_tools.functions import timeout
@timeout(seconds=2)
def too_slow_function() -> None:
sleep(5)
too_slow_function()
# >>> TimeoutError: Function too_slow_function exceeded the 2 seconds timeout.
```
## 🔑 License
This project is licensed under the terms of the [MIT license](https://choosealicense.com/licenses/mit/).