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Learn Python Coding

Learn Python Coding

@pythonre

Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills.

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Post #9759 2.31K
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Post #9758 1.85K
httptap

This is a command-line tool that breaks down an HTTP request into individual stages: DNS resolution, TCP connection, TLS handshake, and data transfer.

It generates a detailed waterfall timeline, which allows you to quickly identify which stage of the request is causing the delay.

📁 Language: #Python 99%

⭐️ Stars: 526

More: https://github.com/ozeranskii/httptap
  • ❤ 2
Post #9757 776

Forwarded from Machine Learning with Python

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Post #9755 1.49K

Forwarded from Machine Learning with Python

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Post #9752 3.05K
Function

pprint()
pprint()

is designed for pretty-printed, formatted output in Python. 🐍

It automatically formats complex data structures, such as nested lists, dictionaries, and tuples, by adding indentation and line breaks for improved readability. ✨

Features:
• Supports customization of the output width for convenient formatting.
• Includes depth and compact parameters to control the level of nesting and display compactness.
• Available through the standard pprint module in the Python library. 💻

#Python #Programming #Code #Developer #Tech #Scripting

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Post #9749 2.84K
collections.ChainMap — a built-in Python class that combines multiple dictionaries or other mappings into a single, updatable view. 🧠

Instead of merging dictionaries and creating new data structures in memory, it links them by reference, allowing you to search and manage them as a single entity. 🔗

# Example usage of collections.ChainMap
from collections import ChainMap

dict1 = {'a': 1, 'b': 2}
dict2 = {'b': 3, 'c': 4}
combined = ChainMap(dict1, dict2)
print(combined['b'])  # Output: 2

#Python #Coding #DataStructures #Programming #Tech #DevTools

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Post #9737 2.18K
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Post #9734 2.27K
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Post #9733 2.27K
Python allows you to create enumerations that are also regular strings!

Previously, when working with APIs, JSON, and configurations, it was often necessary to manually extract the value from an Enum.

For example:
class Status(Enum):
    ACTIVE = "active"

When serializing, you would get an enumeration object:
Status.ACTIVE

rather than a regular string:
"active"

In Python 3.11, StrEnum was introduced to solve this problem.
from enum import StrEnum

class Status(StrEnum):
    ACTIVE = "active"
    BLOCKED = "blocked"

Now, the value can be used wherever a string is expected:
json.dumps({"status": Status.ACTIVE})

The result:
{"status": "active"}

At the same time, the advantages of enumerations are preserved:
Status.ACTIVE
Status.BLOCKED

You cannot accidentally pass an incorrect value:
Status("unknown")

will result in an error.

🔥 StrEnum allows you to combine the strict typing of enumerations with the convenience of regular strings, without manual conversion when working with APIs, JSON, and configurations.

#Python #Coding #StrEnum #DevTips #Programming #Python311

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