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Elevate your Python prowess in "30 Days of Advanced Programming." Unearth OOP, decorators, threading; excel in NumPy, pandas for data. Dive into AI/ML with TensorFlow, web dev with Flask, Django. Master complex problem-solving. Build robust apps, analyze data, and thrive in collaborative projects.

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Day 1: Decorators and Generators

  1. Explain the purpose of decorators in Python with an example.
  2. Write a decorator that Calculate Total Price Decorator.
  3. Write a decorator that authenticate the user username and password.
  4. Create a generator function that generates Fibonacci numbers.

Day 2: Context Managers and File Handling

  1. What are context managers in Python? Provide an example of using the with the statement.
  2. How can you implement a custom context manager using the contextlib module?
  3. Write code to read a large file line by line without loading the entire file into memory.

Day 3: Metaclasses and Reflection

  1. Explain what metaclasses are and how they are used in Python.
  2. Write a metaclass that automatically converts all attribute names to uppercase.
  3. How can you access the list of attributes and methods of an object using reflection?
  4. What is dataclasses with example?

Day 4: Threading and Multiprocessing

  1. Compare and contrast threading and multiprocessing in Python.
  2. Write code to create a multithreaded program that calculates the factorial of a number.
  3. Implement a multiprocessing pool to parallelize a time-consuming task.

Day 5: Memory Management and Garbage Collection

  1. Describe Python's memory management model and the role of reference counting.
  2. What is cyclic garbage collection? How does it prevent memory leaks?
  3. Write code that demonstrates circular reference and forces garbage collection.

Day 6: Decorators and Design Patterns

  1. Discuss the Singleton design pattern and provide a Python implementation.
  2. Implement a decorator that logs function calls along with their arguments.
  3. Explain the Observer design pattern and create a basic implementation.

Day 7: Unit Testing and Test Frameworks

  1. What is unit testing? How can you write unit tests in Python?
  2. Compare the built-in unittest framework and the third-party pytest framework.
  3. Write a test case for a function that checks if a given string is a palindrome.

Day 8: Regular Expressions and Parsing

  1. How do regular expressions work? Provide an example of using the re module.
  2. Write a regular expression to extract email addresses from a given text.
  3. Explain the concept of greedy and non-greedy matching in regular expressions.

Day 9: Networking and Web Services

  1. Describe the difference between TCP and UDP protocols.
  2. Write Python code to create a simple HTTP server using the http.server module.
  3. Utilize the requests library to make an API call and process the JSON response.

Day 10: Debugging and Profiling

  1. Discuss common debugging techniques and tools available in Python.
  2. How can you profile code performance using the cProfile module?
  3. Write a piece of code with a performance issue and use profiling to identify bottlenecks.
  4. Feel free to delve into these topics, research further, and experiment .
  5. with code examples to enhance your understanding of advanced Python concepts.

Day 11: Object-Oriented Programming

  1. Explain the concept of multiple inheritance and the Method Resolution Order (MRO) in Python.

Implement a custom exception class and demonstrate its usage in handling errors. Day 12: Decorators and Closures 33. Discuss the difference between decorators and closures in Python.

Create a closure that calculates the exponential of a given base.

Day 13: Data Serialization and Pickling

  1. What is data serialization? Describe how the pickle module is used for serialization.

Write code to serialize and deserialize a Python object using the pickle module.

Day 14: Asynchronous Programming

  1. Explain asynchronous programming and the role of the async and await keywords.

Develop an asynchronous function that fetches data from a web API using the aiohttp library.

Day 15: Design Patterns

  1. Discuss the Factory Method design pattern and provide a Python implementation.

Explain the Proxy design pattern and create a basic implementation.

Day 16: Functional Programming

  1. Describe the concepts of immutability and pure functions in functional programming.

Implement a higher-order function that returns a function to calculate the square of a number.

Day 17: Memory Optimization

  1. How can you reduce memory consumption using the sys.getsizeof function?

Write code that demonstrates the memory consumption difference between a list and a generator.

Day 18: Data Science Libraries

  1. Explain the differences between NumPy arrays and Python lists.

Use the pandas library to read a CSV file, manipulate data, and perform basic analysis.

Day 19: Machine Learning with scikit-learn

  1. Discuss the purpose of the scikit-learn library in machine learning.

Write code to create a simple linear regression model using scikit-learn.

Day 20: Web Development with Flask

  1. Describe the Flask micro web framework and its basic components.

Build a simple web application using Flask that displays a "Hello, World!" message. I hope these additional questions complete your 30-day challenge focused on advanced Python concepts. Feel free to explore each topic further and practice with code examples to deepen your understanding.

Day 21: Web Development with Django

  1. Explain the MVC (Model-View-Controller) architecture and how it's implemented in Django.

Create a Django project and app, and define a model for a basic database table.

Day 22: Data Visualization with Matplotlib

  1. Discuss the purpose of the Matplotlib library in data visualization.

Write code to create a line plot and a scatter plot using Matplotlib.

Day 23: Data Analysis with Pandas

  1. Explain the concept of a DataFrame in Pandas and its significance.

Perform basic data analysis tasks like filtering, grouping, and aggregation using Pandas.

Day 24: Web Scraping with Beautiful Soup

  1. Describe web scraping and its ethical considerations.

Use Beautiful Soup to scrape and extract information from a webpage.

Day 25: Natural Language Processing (NLP) with NLTK

  1. Discuss the role of the Natural Language Toolkit (NLTK) in NLP tasks.

Write code to tokenize and analyze the frequency distribution of words in a text using NLTK.

Day 26: Machine Learning with TensorFlow

  1. Explain the purpose of the TensorFlow library in machine learning.

Develop a simple neural network using TensorFlow to classify handwritten digits.

Day 27: Machine Learning with PyTorch

  1. Describe the key features of the PyTorch library for deep learning.

Create a convolutional neural network (CNN) using PyTorch for image classification.

Day 28: API Development with FastAPI

  1. Discuss FastAPI and its advantages over other web frameworks.

Build a RESTful API using FastAPI that performs CRUD operations on a resource.

Day 29: Data Serialization with JSON

  1. Explain the JSON (JavaScript Object Notation) format and its common use cases.

Convert a Python dictionary to JSON and vice versa using the json module.

Day 30: Concurrency with asyncio

  1. Introduce asyncio and its role in asynchronous programming.

Write code using asyncio to concurrently execute multiple tasks. I hope these questions provide a comprehensive and diverse set of advanced Python concepts to explore over your 30-day challenge. Feel free to research, experiment, and learn more about each topic to enhance your Python programming skills.

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Elevate your Python prowess in "30 Days of Advanced Programming." Unearth OOP, decorators, threading; excel in NumPy, pandas for data. Dive into AI/ML with TensorFlow, web dev with Flask, Django. Master complex problem-solving. Build robust apps, analyze data, and thrive in collaborative projects.

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