Learn Python Coding

✨ wildcard import | Python Glossary ✨ 📖 An import uses the star syntax to pull many names into your current namespace at once. 🏷️ #Python

⚠ Message was hidden by channel owner

✨ transitive dependency | Python Glossary ✨ 📖 An indirect requirement of your project. 🏷️ #Python

⚠ Message was hidden by channel owner

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

✨ GeoPandas Basics: Maps, Projections, and Spatial Joins ✨ 📖 Dive into GeoPandas with this tutorial covering data loading, mapping, CRS concepts, projections, and spatial joins for intuitive analysis. 🏷️ #intermediate #data-science

⚠ Message was hidden by channel owner

✨ relative import | Python Glossary ✨ 📖 Import modules from the same package or parent packages using leading dots. 🏷️ #Python

Python Clean Code: Stop Writing Bad Code — Lessons from Uncle Bob Are you tired of writing messy and unorganized code that leads to frustration and bugs? You can transform your code from a confusing mess into something crystal clear with a few simple changes. In this article, we'll explore key principles from the book "Clean Code" by Robert C. Martin, also known as Uncle Bob, and apply them to Python. Whether you're a web developer, software engineer, data analyst, or data scientist, these principles will help you write clean, readable, and maintainable Python code. Read: https://habr.com/en/articles/841820/ https://t.me/CodeProgrammer 🧠

⚠ Message was hidden by channel owner

Working with f-strings: more possibilities than it seems! f-strings often replace .format() in everyday code, but their capabilities are not always fully utilized. They support formatting, function calls, working with data structures, and convenient debugging (from 3.8+). f-strings are convenient for aligning columns without additional tools. This makes the output readable in the CLI and logs:

rows = [
    ("id", "name", "role"),
    (1, "Ivan", "admin"),
    (2, "Olga", "editor"),
]

for r in rows:
    print(f"{r[0]:<5} {r[1]:<10} {r[2]:<10}")

Debug expressions (Python 3.8+): {x=> displays the name and value of the variable, which speeds up debugging. Supports formatting of calculations:

x = 12
y = 7
print(f"{x=} {y=} {x*y=} x/y={x/y:.3f}")

Specifiers !r, !a: !r - repr(), !a - ascii() for unambiguous logs. Eliminates ambiguities in the output of objects:

path = "/var/data/config.yaml"
print(f"{path!r} {path!a}")  # repr and ascii()

Specifiers support width and padding, for example 08d for zeros. This is convenient for reports and IDs:

n = 42
print(f"{n:08d}")  # → #00000042

You can access dictionaries and immediately calculate metrics, for example len():

data = {"user": "Ivan", "items": [1, 2, 3]}
print(f"{data['user&#39]}=», items={data['items&#39]}")
print(f"len(data['items&#39])={len(data['items&#39])}")

🔥 f-strings are a cool tool for formatting, logging, and debugging, if you apply them taking into account the version of Python and the context of the output. 🚪 @DataScience4

🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t.me/+0-w7MQwkOs02MmJi You can join at this link! 👆👇 https://t.me/+0-w7MQwkOs02MmJi

✨ Quiz: How to Integrate Local LLMs With Ollama and Python ✨ 📖 Check your understanding of using Ollama with Python to run local LLMs, generate text, chat, and call tools for private, offline apps. 🏷️ #intermediate #ai #tools

⚠ Message was hidden by channel owner

✨ unpacking | Python Glossary ✨ 📖 Passing multiple values at once by expanding an iterable. 🏷️ #Python

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

✨ Anaconda Navigator | Python Tools ✨ 📖 A desktop graphical interface included with the Anaconda Distribution. 🏷️ #Python

✨ Quiz: How to Integrate ChatGPT's API With Python Projects ✨ 📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz. 🏷️ #intermediate #ai #api