base-project: Basic Project Environment for Python Development

This project aims to build a Python project environment based on various useful tools.

1. Development Environment

To provide a consistent development experience across different platforms, I have set up the following environment:

• Dev Container: Utilizes Visual Studio Code's Dev Containers to provide a consistent development environment.
  • Configuration file: .devcontainer/devcontainer.json
• Docker: Supports containerization for deployment and testing.
  • Configuration file: Dockerfile
• Python:
  • Project configuration: pyproject.toml
  • Dependency management: requirements.txt

2. Core Utilities

The src/core/ directory includes several utility modules to enhance development productivity.

2.1 Timer

Provides functionality to measure code execution time.

1. Context manager

   from src.core import Timer
   
   with Timer("Task 1"):
       # Here is code snippet
       sleep(1)

   Output:

   * Task 1    | 1.00s (0.02m)
   

2. Decorator

   from src.core import Timer, T
   
   @Timer("Task 1")
   def fn1():
       sleep(1)
   
   @T
   def fn2():
       sleep(1)
   
   fn1()
   fn2()

   Output:

   * Task 1     | 1.00s (0.02m)
   * fn2()      | 1.00s (0.02m)
   

2.2 Depth logging

Provides functionality to visualize the function call stack and measure execution time.

from src.core import D

@D
def main():
    main1()
    main2()

@D
def main1():
    main11()
    main12()

@D
def main11():
    return

@D
def main12():
    return

@D
def main2():
    main21()

@D
def main21():
    return

main()

Output:

  1            | main()
  1.1          | main1()
  1.1.1        | main11()
* 1.1.1        | 0.00s (0.00m)
  1.1.2        | main12()
* 1.1.2        | 0.00s (0.00m)
* 1.1          | 0.00s (0.00m)
  1.2          | main2()
  1.2.1        | main21()
* 1.2.1        | 0.00s (0.00m)
* 1.2          | 0.00s (0.00m)
* 1            | 0.00s (0.00m)

2.3 Logging

Records logs to both console and file.
Logs are saved in the logs/YYYY-MM-DD.log file for easy tracking and debugging.
Utility functions allow for easy use.

from src.core import slog, log_info, log_success, log_error, log_warning, log_api
from src.core.logger import STYLES

log_info("This is an info message.")
log_success("This is a success message.")
log_error("This is an error message.")
log_warning("This is a warning message.")
log_api("This is an API message.")
for style in STYLES:
    slog(f"This is a {style} message.", style=style)

2.4 Safe HTTP requests

Allows for safe HTTP requests (requests.post) including error handling and logging.

from src.core import safe_post

url = "https://httpbin.org/post"
json = {"key": "value"}
response = safe_post(url, json)

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I hope this project helps improve your Python development experience!