IT Glossary & Dictionary

A powerful data analysis and manipulation library providing DataFrames and tools for working with structured data.

A modern Python module providing an object-oriented interface for filesystem paths, replacing os.path operations.

Python's built-in module for serializing and deserializing Python objects into a byte stream for storage or transmission.

The standard package installer for Python, used to install and manage third-party libraries from PyPI.

A text file listing Python package dependencies with version specifications for reproducible project installations.

A modern Python dependency management and packaging tool that handles virtual environments, locking, and publishing.

A data validation library that uses Python type annotations to validate and serialize data with automatic error reporting.

A testing framework for Python that simplifies writing and running tests with powerful features like fixtures and parametrize.

The Abstract Base Classes module that enables defining interfaces and abstract methods that subclasses must implement.

A variable that maintains separate values for each execution context, enabling implicit state passing in async code without global variables.

A function defined with async def that can be paused and resumed, enabling concurrent execution without threads.

Objects that define __get__, __set__, or __delete__ methods, controlling how attribute access works on other objects.

The program that reads and executes Python code, translating it into machine instructions at runtime.

The interface requiring __iter__() and __next__() methods, enabling objects to be used in for loops and other iteration contexts.

Structured approaches to implementing logging in Python applications using the built-in logging module for debugging and monitoring.

A class whose instances are classes themselves — the class of a class that controls how classes are created and behaved.

A directory containing Python modules and an __init__.py file, providing a way to organize and distribute reusable code.

A modern dependency management and packaging tool for Python that simplifies project setup, versioning, and publishing.

Measuring where Python code spends time and memory to identify performance bottlenecks and optimization opportunities.

A built-in decorator that lets you define methods that behave like attributes, enabling controlled access to instance data.

A standard library module providing type hints for function signatures and variables, enabling static analysis without runtime enforcement.

A built distribution format (.whl) that allows faster installation of Python packages by avoiding the need for compilation.