https://github.com/dariusz-piekarz/pytools
Python tools (JSON, YML configs, metaclasses, decorators).
https://github.com/dariusz-piekarz/pytools
asynchronous-programming concurrency concurrent-programming configuration-files decorators httpx json-configuration metaclasses parallel-programming pyodbc python yaml-configuration
Last synced: about 1 month ago
JSON representation
Python tools (JSON, YML configs, metaclasses, decorators).
- Host: GitHub
- URL: https://github.com/dariusz-piekarz/pytools
- Owner: dariusz-piekarz
- Created: 2024-03-08T14:44:44.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2025-03-22T20:31:14.000Z (about 1 year ago)
- Last Synced: 2025-07-20T00:10:17.243Z (11 months ago)
- Topics: asynchronous-programming, concurrency, concurrent-programming, configuration-files, decorators, httpx, json-configuration, metaclasses, parallel-programming, pyodbc, python, yaml-configuration
- Language: Python
- Homepage:
- Size: 24.4 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
**pytools Module Overview**
The `pytools` module is a Python package currently under development (however is ready to be installed). It aims to provide a collection of useful functionalities for various purposes. Presently, it comprises seven main files:
1. **config**: This file contains tools related to the creation and management of configuration files. It offers functionality to handle both YAML and JSON file formats efficiently.
2. **vectorization**: The `vectorizations` file hosts decorators designed to generalize their actions from scalar values to different types of values. These decorators are versatile and can be applied to various data structures such as lists, pandas DataFrames, and more.
3. **metaclasses**: The `metaclass` file houses a set of metaclasses and decrators tailored to address specific scenarios. These include metaclasses for controlling instantiation, decorators for logging enhancements, method call ordering, and tracking method execution time.
4. **concurrency**: The `concurrency` module encompasses decorators and classes facilitating asynchronous, threading, and multiprocessing approaches for executing your code. One notable application is handling multiple CSV files, converting them into Pandas DataFrames, and saving DataFrames to CSV files.
5. **sqlserver**: The `sqlserver` file contains classes helping in connections to SQL Server and MS Access.
6. **postgres**: The `postgres` file has a connector class to PgAdmin4.
7. **apiconnector**: The `apiconnector` file has functions that help in serving POST, GET, PUT, PATCH and DELETE requests based on asynchonic client and optionally basic authentication.
Each of these files serves a distinct purpose and contributes to the overall functionality and utility of the `pytools` module. As development progresses, additional features and enhancements are expected to be incorporated into the module.