Stouputils is a collection of utility modules designed to simplify and enhance the development process. It includes a range of tools for tasks such as execution of doctests, display utilities, decorators, as well as context managers, and many more.
Project description
๐ ๏ธ Project Badges
๐ Project Overview
Stouputils is a collection of utility modules designed to simplify and enhance the development process.
It includes a range of tools for tasks such as execution of doctests, display utilities, decorators, as well as context managers.
๐ง Installation
pip install stouputils
โจ Enable Tab Completion on Linux (Optional)
For a better CLI experience, enable bash tab completion:
# Option 1: Using argcomplete's global activation
activate-global-python-argcomplete --user
# Option 2: Manual setup for bash
register-python-argcomplete stouputils >> ~/.bashrc
source ~/.bashrc
After enabling completion, you can use <TAB> to autocomplete commands:
stouputils <TAB> # Shows: --version, -v, all_doctests, backup
stouputils all_<TAB> # Completes to: all_doctests
Note: Tab completion works best in bash, zsh, Git Bash, or WSL on Windows.
๐ Project File Tree
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stouputils/ โโโ print.py # ๐จ๏ธ Utility functions for printing (info, debug, warning, error, whatisit, breakpoint, colored_for_loop, ...) โโโ decorators.py # ๐ฏ Decorators (measure_time, handle_error, timeout, retry, simple_cache, abstract, deprecated, silent) โโโ ctx.py # ๐ Context managers (LogToFile, MeasureTime, Muffle, DoNothing, SetMPStartMethod) โโโ io.py # ๐พ Utilities for file management (json_dump, json_load, csv_dump, csv_load, read_file, super_copy, super_open, clean_path, ...) โโโ parallel.py # ๐ Utility functions for parallel processing (multiprocessing, multithreading, run_in_subprocess) โโโ image.py # ๐ผ๏ธ Little utilities for image processing (image_resize, auto_crop, numpy_to_gif, numpy_to_obj) โโโ collections.py # ๐งฐ Utilities for collection manipulation (unique_list, sort_dict_keys, upsert_in_dataframe, array_to_disk) โโโ all_doctests.py # โ Run all doctests for all modules in a given directory (launch_tests, test_module_with_progress) โโโ backup.py # ๐พ Utilities for backup management (delta backup, consolidate) โโโ archive.py # ๐ฆ Functions for creating and managing archives โ โโโ applications/ โ โโโ automatic_docs.py # ๐ Documentation generation utilities (used to create this documentation) โ โโโ upscaler/ # ๐ Image & Video upscaler (configurable) โ โโโ ... โ โโโ continuous_delivery/ โ โโโ cd_utils.py # ๐ง Utilities for continuous delivery โ โโโ github.py # ๐ฆ Utilities for continuous delivery on GitHub (upload_to_github) โ โโโ pypi.py # ๐ฆ Utilities for PyPI (pypi_full_routine) โ โโโ pyproject.py # ๐ Utilities for reading, writing and managing pyproject.toml files โ โโโ stubs.py # ๐ Utilities for generating stub files using stubgen โ โโโ ... โ โโโ data_science/ โ โโโ config/ # โ๏ธ Configuration utilities for data science โ โโโ dataset/ # ๐ Dataset handling (dataset, dataset_loader, grouping_strategy) โ โโโ data_processing/ # ๐ Data processing utilities (image augmentation, preprocessing) โ โ โโโ image/ # ๐ผ๏ธ Image processing techniques โ โ โโโ ... โ โโโ models/ # ๐ง ML/DL model interfaces and implementations โ โ โโโ keras/ # ๐ค Keras model implementations โ โ โโโ keras_utils/ # ๐ ๏ธ Keras utilities (callbacks, losses, visualizations) โ โ โโโ ... โ โโโ scripts/ # ๐ Data science scripts (augment, preprocess, routine) โ โโโ metric_utils.py # ๐ Static methods for calculating various ML metrics โ โโโ mlflow_utils.py # ๐ Utility functions for working with MLflow โ โโโ ... โ โโโ installer/ โ โโโ common.py # ๐ง Common functions used by the Linux and Windows installers modules โ โโโ downloader.py # โฌ๏ธ Functions for downloading and installing programs from URLs โ โโโ linux.py # ๐ง Linux/macOS specific implementations for installation โ โโโ main.py # ๐ Core installation functions for installing programs from zip files or URLs โ โโโ windows.py # ๐ป Windows specific implementations for installation โ โโโ ... โโโ ...
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