Format Dates and Times in Python
Learn how to use strftime and strptime to format dates as strings and parse date strings into Python datetime objects.
Learn Python programming from scratch
Learn how to use strftime and strptime to format dates as strings and parse date strings into Python datetime objects.
Learn how to use Python's base64 module to encode binary data as text and decode Base64 strings back to bytes.
Compare Python threading, multiprocessing, and asyncio side by side with benchmarks so you can choose the right concurrency model for your workload.
Identify the most common Python performance bottlenecks: slow loops, repeated attribute lookups, wrong data structures, excessive I/O, and the GIL.
Learn when to optimize Python code and when to leave it alone. Avoid premature optimization, recognize true bottlenecks, and time your effort for maximum impact.
A practical checklist of Python performance best practices: what to measure, which tools to use, when to stop, and how to keep optimized code maintainable.
Walk through a real Python optimization: profile a slow data processing script, find the bottlenecks, apply fixes, and measure the improvements step by step.
Learn how Python's object model works under the hood: what objects are, how names reference them, and why every value in Python is an object.
Learn how Python object identity works with `id()` and `is`, the difference between mutable and immutable types, and how mutability affects your programs.
Understand the Python data model: how protocols and magic methods let your objects work with built-in syntax like len(), +, in, and for loops.
Learn practical techniques for writing Python code that is easy to read, understand, and maintain, from function design to variable naming and control flow clarity.
Learn how to use the factory pattern in Python to encapsulate object creation, making your code more flexible and easier to extend.