📦 Release v2.3.4 This release addresses critical issues in dynamic submodule resolution and implements a standardized, hierarchical console output system for improved user feedback. Summary of changes since 2.3.3: 🛠️ Critical fixes Lazy loading (#119): Fixed submodule resolution within _LazyModule. Submodules are now resolved dynamically, preventing attribute errors when accessing nested package components. This resolves the issue #118. 🚀 Output indentation refactor (#120) Adaptive hierarchy: Replaced hardcoded tab characters with a prepended indentation logic. Console outputs now follow a clear visual "Parent > Child > Grandchild" structure. Configurable indent parameter: Added indent support to the following modules: dbms: Standardized database operation logging. dirs: Improved delete_dir() with hierarchical verbose output. downloads: Enhanced download_file_from_url() to nest status messages beneath the progress bar. savers: Enhanced save_spreadsheets() to handle Excel sheet saving status message with multi-level indentation. 🔧 Improvements & maintenance Documentation updates: Overhauled Sphinx-style docstrings for normalize_pathname(), delete_dir() and download_file_from_url() to reflect new parameter logic. Test suite refinement: Updated tests for downloads, management and savers to validate the refactored indentation logic and ensure stable lazy-loading behavior. API standardization: Improved internal data flow between progress bar helpers and validation functions.

PyHelpers is an open-source Python package designed to streamline data (pre-)processing and manipulation tasks. It accommodates a wide range of functions and classes grounded in practical applications, making common data operations more accessible and efficient. This toolkit is particularly useful for Python learners, researchers and data scientists seeking to enhance their workflows. The package supports handling various data types, such as geographical and textual data, allowing for flexibility for diverse data processing needs. It also simplifies data input and output operations by offering functionalities for managing many different file-like objects. In addition, PyHelpers facilitates communication with relational databases, such as PostgreSQL and Microsoft SQL Server. This capability greatly smooths data integration with database systems through efficient data storage and retrieval. With its comprehensive suite of practical tools, PyHelpers simplifies complex data processing tasks and boosts productivity. It is ready to serve as an essential resource for effective data manipulation, management and analysis for anyone working with data in Python. For more information and detailed specifications, check out the PyHelpers 2.3.4 documentation.

Cite as: Fu, Q. (2020). PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks. Zenodo. https://doi.org/10.5281/zenodo.4017438 For specific version references, please see the list of all versions.