🔩 Efficient Queues and Stacks in Python: A Quick Summary 📚
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Learn how to use the powerful
• Use
• Internally uses a doubly linked list, making end operations O(1) while random indexing O(n). ⏱️
understand when to use
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Learn how to use the powerful
deque data structure in Python, perfect for efficient queue and stack operations under heavy workloads! 🔄• Use
deque for both append and pop at both ends, ideal for implementing queues and stacks. 🔗• Internally uses a doubly linked list, making end operations O(1) while random indexing O(n). ⏱️
understand when to use
deque over lists and how to build efficient FIFO queues! 👉❤2
📚 How to Build a Personal Python Learning Roadmap 📊
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Are you looking for a structured approach to learning Python? A personalized roadmap can help you stay on track and achieve your goals. Here's how to create one:
Benefits of a Personalized Learning Roadmap
Set clear targets and milestones
Track progress and adjust course as needed
Stay accountable and motivated
Focus on skills development, not just theory
Key Components of a Personalized Python Learning Roadmap
What you want to achieve: Identify your short-term and long-term goals
Current level of proficiency: Assess your current skills and knowledge
Skill gaps: Determine areas where you need improvement
Learning plan: Create an action plan with specific tasks and deadlines
How to Build a Personalized Python Learning Roadmap
1. Take online courses or tutorials to fill skill gaps
2. Read books, articles, and blogs on Python topics
3. Join online communities, forums, or social media groups for support
4. Practice coding exercises and projects
5. Review and adjust your roadmap regularly
By following these steps, you'll be well on your way to creating a personalized Python learning roadmap that helps you achieve your goals.
======================================================
Are you looking for a structured approach to learning Python? A personalized roadmap can help you stay on track and achieve your goals. Here's how to create one:
Benefits of a Personalized Learning Roadmap
Set clear targets and milestones
Track progress and adjust course as needed
Stay accountable and motivated
Focus on skills development, not just theory
Key Components of a Personalized Python Learning Roadmap
What you want to achieve: Identify your short-term and long-term goals
Current level of proficiency: Assess your current skills and knowledge
Skill gaps: Determine areas where you need improvement
Learning plan: Create an action plan with specific tasks and deadlines
How to Build a Personalized Python Learning Roadmap
1. Take online courses or tutorials to fill skill gaps
2. Read books, articles, and blogs on Python topics
3. Join online communities, forums, or social media groups for support
4. Practice coding exercises and projects
5. Review and adjust your roadmap regularly
By following these steps, you'll be well on your way to creating a personalized Python learning roadmap that helps you achieve your goals.
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📊 Python News Digest
Summary:
🔗 A new Python extension for VS Code has gained popularity, allowing authors to track search rankings. This feature provides valuable insights into how users discover and utilize the extension.
Key Takeaways:
• Tracks search rankings in VS Code
• Provides valuable data for extension development
Learn more about this feature:
Check it out
Summary:
🔗 A new Python extension for VS Code has gained popularity, allowing authors to track search rankings. This feature provides valuable insights into how users discover and utilize the extension.
Key Takeaways:
• Tracks search rankings in VS Code
• Provides valuable data for extension development
Learn more about this feature:
Check it out
❤3
🔬 New Python Tutorial: Mastering Pandas Data Structures 🤯
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Stay ahead in data science with our new tutorial!
Learn the basics of Pandas, a powerful library for data manipulation and analysis. This tutorial covers:
Creating and modifying DataFrames
Handling missing values and outliers
Filtering and sorting data
Merging and joining datasets
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Stay ahead in data science with our new tutorial!
Learn the basics of Pandas, a powerful library for data manipulation and analysis. This tutorial covers:
Creating and modifying DataFrames
Handling missing values and outliers
Filtering and sorting data
Merging and joining datasets
❤1
🖥️ Image Style Transfer with AI: A Beginner's Guide 🚀
Learn how to effortlessly style images using AI-powered tools. This online platform, Img2img.net, allows you to convert your photos into artistic styles like fashion, portrait, and more. In this article, we'll cover the basics of image style transfer and provide a step-by-step guide on how to use it.
Key Features:
🎨 Easy-to-use interface: No prior experience with AI required
💻 Fast results: Achieve stunning images in minutes
📸 High-quality output: Perfect for social media, art, or personal projects
How it works:
1. Upload your photo and select the style you want to achieve.
2. Adjust settings to fine-tune the result.
3. Click "Transform" to see your artistic masterpiece.
Benefits:
💡 Save time: Automate image editing tasks
📈 Enhance creativity: Experiment with new styles and techniques
Try Image Style Transfer today and take your photography skills to the next level!👏
Learn how to effortlessly style images using AI-powered tools. This online platform, Img2img.net, allows you to convert your photos into artistic styles like fashion, portrait, and more. In this article, we'll cover the basics of image style transfer and provide a step-by-step guide on how to use it.
Key Features:
🎨 Easy-to-use interface: No prior experience with AI required
💻 Fast results: Achieve stunning images in minutes
📸 High-quality output: Perfect for social media, art, or personal projects
How it works:
1. Upload your photo and select the style you want to achieve.
2. Adjust settings to fine-tune the result.
3. Click "Transform" to see your artistic masterpiece.
Benefits:
💡 Save time: Automate image editing tasks
📈 Enhance creativity: Experiment with new styles and techniques
Try Image Style Transfer today and take your photography skills to the next level!👏
❤1
🌞 Python Weather Forecasting with OpenWeatherMap 👉
Get ready to explore the world of Python weather forecasting with OpenWeatherMap! 🌪️
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This project builds upon the success of Xweather Live, a public demo of our weather APIs and mapping stack. 🚀
By leveraging OpenWeatherMap's API, we've created an interactive visualizer that allows developers to explore and validate our weather data and visualization tools.
Key features:
• Real-time global weather maps rendered with WebGL
• Explore and validate our weather forecasting models
• Learn from expert advice on building robust APIs and data visualizations
Keep exploring!💻
Get ready to explore the world of Python weather forecasting with OpenWeatherMap! 🌪️
---------------------------------------------
This project builds upon the success of Xweather Live, a public demo of our weather APIs and mapping stack. 🚀
By leveraging OpenWeatherMap's API, we've created an interactive visualizer that allows developers to explore and validate our weather data and visualization tools.
Key features:
• Real-time global weather maps rendered with WebGL
• Explore and validate our weather forecasting models
• Learn from expert advice on building robust APIs and data visualizations
Keep exploring!💻
❤4
Forwarded from Code With Python
Python Cheat sheet
#python #oop #interview #coding #programming #datastructures
https://t.iss.one/DataScience4
#python #oop #interview #coding #programming #datastructures
https://t.iss.one/DataScience4
❤3
📚 "Python Project Setup: A Quick Guide"
In this article, you'll learn how to create and set up a new Django project. Follow along with our quiz to reinforce your understanding of creating a virtual environment, installing Django, and setting up dependencies. You'll also see how isolating dependencies helps others reproduce the setup.
Read more about creating a Django project: How to Set Up a Django Project
In this article, you'll learn how to create and set up a new Django project. Follow along with our quiz to reinforce your understanding of creating a virtual environment, installing Django, and setting up dependencies. You'll also see how isolating dependencies helps others reproduce the setup.
Read more about creating a Django project: How to Set Up a Django Project
Realpython
How to Set Up a Django Project – Real Python
In this course, you'll learn the necessary steps you'll need to take to set up a new Django project. You'll learn the basic setup for any new Django project that needs to happen before programming the specific functionality of your project.
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"🚀 OOP 101: Understanding Object-Oriented Programming in Python 📚
===================================================================="
• Definition: Object-oriented programming (OOP) is a programming paradigm that revolves around the concept of objects and classes.
• Key concepts: Classes, inheritance, polymorphism, encapsulation, and abstraction. These are essential components of OOP and will help you write maintainable code in Python.
• Benefits: Improved code readability, reusability, and scalability. By understanding OOP, you'll be able to create more efficient and effective software solutions.
• Practical application: Learn how to define custom types using classes, instantiate objects, and use inheritance to achieve common programming tasks.
Summary:
Learn the basics of object-oriented programming in Python and elevate your skills to write maintainable code. Understand key concepts like classes, inheritance, polymorphism, encapsulation, and abstraction for a deeper understanding of OOP.
===================================================================="
• Definition: Object-oriented programming (OOP) is a programming paradigm that revolves around the concept of objects and classes.
• Key concepts: Classes, inheritance, polymorphism, encapsulation, and abstraction. These are essential components of OOP and will help you write maintainable code in Python.
• Benefits: Improved code readability, reusability, and scalability. By understanding OOP, you'll be able to create more efficient and effective software solutions.
• Practical application: Learn how to define custom types using classes, instantiate objects, and use inheritance to achieve common programming tasks.
Summary:
Learn the basics of object-oriented programming in Python and elevate your skills to write maintainable code. Understand key concepts like classes, inheritance, polymorphism, encapsulation, and abstraction for a deeper understanding of OOP.
❤1
🤔 Did you know? You can use Python's <code>deque</code> for efficient appends and pops at both ends of a sequence-like data type. This is especially useful when implementing queue and stack data structures that operate efficiently under heavy workloads. 💪
# 📊 Speed Up Your Python App with DiskCache
A cloud SSD is sitting idle, waiting for its purpose. Today, we're putting it to work with DiskCache, a simple cache built on SQLite that can speed up your Python app without spinning up Redis or extra services.
### What is DiskCache?
DiskCache is a lightweight, practical cache that stores frequently accessed data in memory. It's built on top of SQLite and doesn't require any additional setup or dependencies.
### Benefits
🚀 Faster application response times: By storing frequently accessed data in memory, your Python app can respond faster to user input.
⏱️ Improved scalability: DiskCache can handle increased load without performance drops due to disk I/O.
💻 Reduced database queries: Your Python app won't need to query the database as often, freeing up resources and reducing latency.
### Example Use Case
### Get Started
Start using DiskCache in your Python applications to boost performance and reduce latency. Check out the official documentation for more information: <https://grantjenks.com/docs/diskcache/?featuredon=talkpython>
A cloud SSD is sitting idle, waiting for its purpose. Today, we're putting it to work with DiskCache, a simple cache built on SQLite that can speed up your Python app without spinning up Redis or extra services.
### What is DiskCache?
DiskCache is a lightweight, practical cache that stores frequently accessed data in memory. It's built on top of SQLite and doesn't require any additional setup or dependencies.
### Benefits
🚀 Faster application response times: By storing frequently accessed data in memory, your Python app can respond faster to user input.
⏱️ Improved scalability: DiskCache can handle increased load without performance drops due to disk I/O.
💻 Reduced database queries: Your Python app won't need to query the database as often, freeing up resources and reducing latency.
### Example Use Case
import sqlite3
from diskcache importDiskCache
# Create a connection to our SQLite database
conn = sqlite3.connect('example.db')
# Create a cache instance
cache = DiskCache(dbname='example', debug=False)
# Initialize the cache with some data
data = {'key': 'value'}
# Access the cached data without querying the database
print(cache.get(data['key']))
### Get Started
Start using DiskCache in your Python applications to boost performance and reduce latency. Check out the official documentation for more information: <https://grantjenks.com/docs/diskcache/?featuredon=talkpython>
🎁❗️TODAY FREE❗️🎁
Entry to our VIP channel is completely free today. Tomorrow it will cost $500! 🔥
JOIN 👇
https://t.iss.one/+DBdNGbxImzgxMDBi
https://t.iss.one/+DBdNGbxImzgxMDBi
https://t.iss.one/+DBdNGbxImzgxMDBi
Entry to our VIP channel is completely free today. Tomorrow it will cost $500! 🔥
JOIN 👇
https://t.iss.one/+DBdNGbxImzgxMDBi
https://t.iss.one/+DBdNGbxImzgxMDBi
https://t.iss.one/+DBdNGbxImzgxMDBi
❤2
What will happen if in the
try block you call return, and in the finally block you also call return?Answer:
This happens because finally always executes after try and catch, but before the actual return of the value. If there is a return in finally, it definitively determines the result of the method.
tags: #interview
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❤3
If you're testing forms, mockups, or just want to play with data, there's Mimesis — a generator of fake data. Names, emails, addresses, and phone numbers. There's a location setting that allows you to select a country, and the data will be generated accordingly.
from typing import Dict
from mimesis.enums import Gender
from mimesis import Person
def generate_fake_user(locale: str = "es", gender: Gender = Gender.MALE) -> Dict[str, str]:
"""
Generates fake user data based on the locale and gender.
:param locale: The locale (for example, 'ru', 'en', 'es')
:param gender: The gender (Gender.MALE or Gender.FEMALE)
:return: A dictionary with the fake user data
"""
person = Person(locale)
user_data = {
"name": person.full_name(gender=gender),
"height": person.height(),
"phone": person.telephone(),
"occupation": person.occupation(),
}
return user_data
if __name__ == "__main__":
fake_user = generate_fake_user(locale="es", gender=Gender.MALE)
print(fake_user)
{
'name': 'Carlos Herrera',
'height': '1.84',
'phone': '912 475 289',
'occupation': 'Arquitecto'
)ru, 🇺🇸 en, 🇪🇸 es, etc.) Save it, it'll come in handy
#python #github #interview
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How to manage caching in HTTP?
Answer:
These mechanisms reduce the network load and speed up reloads.
tags: #interview
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Forwarded from Machine Learning with Python
Beautiful Soup — a library for extracting data from HTML and XML files, ideal for web scraping.
pip install beautifulsoup4
from bs4 import BeautifulSoup
import requests
html_doc = "<html><body><p class='text'>Hello, world!</p></body></html>"
soup = BeautifulSoup(html_doc, 'html.parser') # or 'lxml', 'html5lib'
print(soup.p.text) # Hello, world!
# First found element
first_p = soup.find('p')
# Search by class or attribute
text_elem = soup.find('p', class_='text')
text_elem = soup.find('p', {'class': 'text'})
# All elements
all_p = soup.find_all('p')
all_text_class = soup.find_all(class_='text')
a_tag = soup.find('a')
print(a_tag['href']) # value of the href attribute
print(a_tag.get_text()) # text inside the tag
print(a_tag.text) # alternative# Moving to parent, children, siblings
parent = soup.p.parent
children = soup.ul.children
next_sibling = soup.p.next_sibling
# Finding the previous/next element
prev_elem = soup.find_previous('p')
next_elem = soup.find_next('div')
response = requests.get('https://example.com')
soup = BeautifulSoup(response.text, 'html. parser')
title = soup.title.text
links = [a['href'] for a in soup.find_all('a', href=True)]# More powerful and concise search
items = soup.select('div.content > p.text')
first_item = soup.select_one('a.button')
🟢 Web scraping and data collection🟢 Processing HTML/XML reports🟢 Automating data extraction from websites🟢 Preparing data for analysis and machine learning
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