Categories

from __future__ import annotations – The Future of Python Type Hints

Explore how `from __future__ import annotations` enables lazy evaluation of Python type hints, its evolution from PEP 563 to PEP 649, and practical tips for handling circular references and large projects. Understand why it’s essential for Python 3.7‑3.10 and how it becomes default in 3.11+.

NumPy Basics for Deep Learning: +, -, *, /, **, Comparisons, sum/mean/max/min, and axis

A detailed guide to NumPy’s core operations—element‑wise arithmetic, comparisons, aggregation functions, and the `axis` concept—framed from a deep‑learning perspective. Learn how to apply these building blocks to compute loss, accuracy, and data statistics in PyTorch and NumPy with practical examples.

Anaconda? Miniconda? What Should You Start With? A Practical Guide to Managing conda Environments with Miniconda

When managing Python development environments with conda, this guide explains the differences between Anaconda and Miniconda and details step-by-step methods for creating, deleting, cloning, and migrating conda environments based on Miniconda. It introduces patterns for starting light and expanding as needed.

Confronting the Essence of Django - Why `HttpResponse` is the 'Fundamental'

Explore the core reasons and roles of HttpResponse in Django. This article explains how the HttpResponse object connects requests and responses and performs essential functions in web applications.

Understanding and Utilizing Python Wheel to Speed Up Docker Builds

This article presents how to significantly improve Docker build speeds using Python Wheel, step by step, including tips on Wheel creation, cache utilization, and multi-stage builds.

A Comprehensive Guide to Python's `urlparse()` - The Essential Tool for URL Analysis

This blog post explains how to parse and analyze URLs using Python's `urlparse()` function, covering components, parameter extraction, normalization, and security considerations with practical examples.

Why is the pop() Method Everywhere in Python?

The pop() method in Python is one of the most commonly used core functionalities found in lists and dictionaries. This post explores why pop() appears so frequently, in what situations it is useful, and important considerations to keep in mind with examples.

Understanding Python `@classmethod` Properly - When and Why Should We Use It?

This article explores the reasons and situations for utilizing the @classmethod decorator in Python. It compares class methods and instance methods, highlights the advantages of @classmethod, and provides practical tips on when to use it with real examples.

Mastering Text Manipulation in Django - 'django.utils.text'

This post summarizes the core text processing utilities provided by Django's django.utils.text module. It introduces key functions and usage examples, including slugify and get_valid_filename.

The Magic of Time Management in Django - A Complete Guide to 'django.utils.timezone'

A comprehensive guide on the core module for timezone management in Django, django.utils.timezone. It covers aspects like UTC storage, local conversion, differences between Naive and Aware times, and how to use make_aware with practical examples.

Django's HTTP Utility - 'django.utils.http'

This post introduces how to implement URL encoding, safe token transmission, and redirection security using Django's `django.utils.http` module.

Understanding Django's Time Solver 'dateparse'

A post summarizing the usage and advantages of the utility module `django.utils.dateparse` for converting ISO 8601 date/time strings to Python datetime objects in Django.

Proper Use of datetime and Timezone in Django

This guide outlines how to handle datetime and timezone safely in Django and Python, covering key concepts such as naive/aware, ISO8601, and timestamp with practical examples.

How to Use Django's get_valid_filename Function

Learn how to safely convert filenames using Django's get_valid_filename function along with practical examples.

3 Pythonic Moments That Turn Code into Art

In this post, we introduce three snippets that showcase the elegance and efficiency of Pythonic code, moving both beginners and experienced developers alike. By applying a Pythonic style, readability is enhanced, and maintainability becomes easier.

The Role and Use of Python __init__

A blog post summarizing the core role and ways to utilize Python's __init__.py file.

Python vs Node.js: CSS Compression Experiment Results Revealed!

Do you think CSS compression can only be done well with Node.js based tools? This post presents an experimental comparison of Python's csscompressor and clean-css-cli, exploring just how significant the performance difference really is.

The Most Pythonic Way to Retrieve Values that Meet Conditions: next()

`next()` is the most elegant way to find items that meet conditions from a list. Learn the essence of Pythonic code through examples!

Try Except Strategies for Python Beginners – Making Debugging Easy with Exception Handling!

A beginner's guide to exception handling in Python! Learn easily through real examples, from the try except structure to debugging tips and commonly used exception classes.

Mastering Python Standard Library 3 - pathlib

pathlib is a Python standard library that allows for object-oriented handling of file paths. This article explains the key features and usage examples of pathlib in a clear manner.

Mastering the Python Standard Library ② - collections.defaultdict

Master collections.defaultdict in Python's standard library. We'll explore the concept of defaultdict along with various examples and practical applications.

Mastering the Python Standard Library① - collections.Counter

Explore the depths of the Python standard library's collections.Counter and learn how to utilize it in real-world applications. This overview covers the core concepts and various examples.

Pythonic Ways to Handle Conditionals

As if and elif statements become more complex, they stray from Pythonic style. This article introduces various practical tips for writing conditionals more concisely and Pythonically.

Mastering the Basics of Python #1 — `None` and `""`: They Look Similar but Are Different

This post explains the difference between Python's None and the empty string "" from the perspective of conditional statements and boolean evaluation with practical code examples, addressing common points of confusion for beginners.

JavaScript, Python Dictionary, and C++'s std::map

Explore the nuances of dictionaries in Python and their counterparts in C++. Discover the significance of trailing commas and the differences between std::map and std::unordered_map in C++.

How to Extract Keys and Values from a Python Dictionary as Lists

Learn various methods to extract keys and values from a Python Dictionary as lists, enhancing your data processing efficiency.

A Complete Guide to Python @staticmethod

Easily understand the @staticmethod decorator in Python, learn its usage, compare it with @classmethod, and effectively utilize it through practical examples!

Various Ways to Handle Python Dictionaries

This guide details methods and use cases for accessing keys in Python Dictionaries. It covers basic key access, using the get method, checking key existence, loops, and exception handling, providing insights into safe and efficient Dictionary usage.

Understanding the Differences Between JSON Format and Python Dictionary

Explore the key differences and similarities between JSON format and Python Dictionary, including conversion methods and best practices.

Flexible Coding: Checking for Object Attribute Existence with Python `hasattr`

Explore the Python 'hasattr' function, learn its syntax, and view examples of how to check for the existence of object attributes in this comprehensive guide.

Introduction to Python Basics: Safe Coding with Error Handling (Try-Except)

Discover how to handle errors safely in Python using the try-except statement. This essential guide provides examples and tips for beginners to code confidently.

Introduction to Python Basics: The Power of Handling String Variables

Discover the power of Python in handling string variables easily. This post compares string manipulation in Python with other programming languages.

Using __(Double Underscore) in Django ORM: Leveraging Relational Fields and Queries

Explore the usage of double underscores in Django ORM for efficient relational field access and query building.