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Python learning resources Beginner to advanced Python guides, cheatsheets, books and projects. For data science, backend and automation. Join πŸ‘‰ https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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Kanal postlari
πŸ“– Reading Python Error Messages Suppose you see this.
TypeError: can only concatenate str (not "int") to str
Instead of panicking, read it from left to right. TypeError β†’ The operation uses the wrong data type. str β†’ Python found a string. int β†’ It also found an integer. πŸ‘‰ You're trying to combine two incompatible types.

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πŸ“š 10 Python Modules You Probably Didn't Know Existed 1. textwrap - Format long blocks of text. 2. difflib - Compare files or strings. 3. fractions - Work with exact fractions. 4. decimal - High precision decimal arithmetic. 5. calendar - Generate calendars programmatically. 6. uuid - Generate unique IDs. 7. secrets - Create cryptographically secure tokens. 8. pprint - Print nested data structures beautifully. 9. platform - Detect operating system information. 10. getpass - Securely read passwords from the terminal.
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What does the Python slice list[::-1] do?
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⚑️ append() vs extend() These two methods look similar, but they do completely different things. numbers = [1, 2, 3] numbers.append([4, 5]) print(numbers) Output: [1, 2, 3, [4, 5]] Now compare it with: numbers = [1, 2, 3] numbers.extend([4, 5]) print(numbers) Output: [1, 2, 3, 4, 5] πŸ‘‰ append() adds one object. πŸ‘‰ extend() adds every element. This small difference causes countless beginner bugs.
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πŸ“¦ What Should You Learn After Python Basics? βœ… Functions & Modules ⬇️ βœ… Object-Oriented Programming ⬇️ βœ… File Handling ⬇️ βœ… Exception Handling ⬇️ βœ… Virtual Environments ⬇️ βœ… Git & GitHub ⬇️ βœ… Choose a Path: β€’ Web Development β€’ Automation β€’ Data Science β€’ Machine Learning β€’ Cybersecurity β€’ Backend APIs Python is just the language. Your specialization is what turns it into a career.
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Python Script to Retrieve Saved Wi-Fi Passwords (Windows) Someone requested this… We thought it might help. import subprocess def get_wifi_passwords(): # To get list of all saved Wi-Fi profiles profiles_data = subprocess.check_output(['netsh', 'wlan', 'show', 'profiles']).decode('utf-8', errors="ignore").split('\n') profiles = [line.split(":")[1].strip() for line in profiles_data if "All User Profile" in line] print("\nSaved Wi-Fi Networks & Passwords:\n" + "-"*40) for profile in profiles: try: # To get password for each profile profile_info = subprocess.check_output( ['netsh', 'wlan', 'show', 'profile', profile, 'key=clear'] ).decode('utf-8', errors="ignore").split('\n') password = [line.split(":")[1].strip() for line in profile_info if "Key Content" in line] print(f"Network : {profile}") print(f"Password: {password[0] if password else 'None / Open Network'}\n") except: print(f"Network : {profile}") print("Password: Unable to retrieve\n") if __name__ == "__main__": get_wifi_passwords() πŸ’» How to use the above code: 1. Open any text editor (Notepad, VS Code, etc.) 2. Copy and paste the code above 3. Save the file as wifi_passwords.py 4. Open Command Prompt or PowerShell as Administrator 5. Navigate to the folder where you saved the file 6. Run the command: python wifi_passwords.py βœ… The script will list all the Wi-Fi networks that are saved on your computer along with their passwords. ⚠️ This only works for networks that are already saved on your Windows PC. It cannot crack or find passwords of networks you have never connected to.
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+1
Python Notes for AI was requested by one of you. And here it is... You can drop any future resource requests here.
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🧠 Think Like Python Suppose you want to know if a username exists. πŸ”» Many beginners write: found = False for user in users: if user == "Alex": found = True break 🟒 Python gives you a simpler solution. found = "Alex" in users Less code. More readable. Usually faster to understand. Whenever Python has a built-in way to express an idea, prefer it.
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What exception does Python raise when you divide by zero?
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Python Machine Learning Workbook.pdf
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πŸ” 10 Useful String Methods in Python 1. split() β†’ Break text into pieces. 2. join() β†’ Combine multiple strings. 3. replace() β†’ Replace part of a string. 4. strip() β†’ Remove extra spaces. 5. startswith() β†’ Check prefixes. 6. endswith() β†’ Check suffixes. 7. find() β†’ Locate text. 8. count() β†’ Count occurrences. 9. upper() / lower() β†’ Change case. 10. capitalize() β†’ Capitalize the first letter. These methods appear in almost every real-world Python project.
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One of our members asked for a Python Book This book, Think Python, is an introduction to Python programming for beginners. It starts with basic concepts of programming; it is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression.
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πŸš€ Python Time Complexity Cheat Sheet βœ… List β€’ Access by index β†’ O(1) β€’ Append β†’ O(1) β€’ Insert at beginning β†’ O(n) β€’ Delete from middle β†’ O(n) β€’ Search (in) β†’ O(n) Best for: Ordered collections where fast indexing matters. βœ… Dictionary (dict) β€’ Lookup β†’ O(1) β€’ Insert β†’ O(1) β€’ Update β†’ O(1) β€’ Delete β†’ O(1) Best for: Fast lookups using keys. βœ… Set β€’ Add β†’ O(1) β€’ Remove β†’ O(1) β€’ Membership test β†’ O(1) Best for: Removing duplicates and fast membership checks. βœ… Tuple β€’ Access β†’ O(1) β€’ Search β†’ O(n) Best for: Read-only collections that shouldn't change.
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πŸ“– Reading Python Error Messages Suppose you see this. TypeError: 'NoneType' object is not iterable Instead of guessing, break it down. TypeError β†’ You're performing an operation on an incompatible type. NoneType β†’ The value is None. not iterable β†’ Python expected something it could loop over, like a list or tuple. A common cause: def get_users(): print("Loading users...") for user in get_users(): print(user) get_users() doesn't return anything, so it returns None by default. Python can't loop over None. When you see this error, ask yourself: "Which variable was supposed to contain a list but ended up being None?"
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🐍 15 Python Built-in Functions Every Developer Should Know You don't always need another library. Python already ships with powerful built-in functions that can make your code cleaner, shorter, and faster. 1. enumerate() - Loop through items while automatically keeping track of their index. 2. zip() - Combine multiple lists together element by element. 3. map() - Apply the same function to every item in an iterable. 4. filter() - Keep only the elements that satisfy a condition. 5. sorted() - Return a new sorted list without changing the original. 6. any() - Returns True if at least one item is truthy. 7. all() - Returns True only if every item is truthy. 8. sum() - Quickly calculate the total of numeric values. 9. min() / max() - Find the smallest or largest value instantly. 10. len() - Count the number of items in any iterable. 11. set() - Remove duplicate values while creating a collection of unique items. 12. isinstance() - Check whether an object belongs to a specific type. 13. range() - Generate sequences of numbers efficiently. 14. reversed() - Iterate over data in reverse order without modifying it. 15. help() - Open the built-in documentation for almost any Python object. Learning these built-ins will make your code look much more "Pythonic" and save you from writing unnecessary loops.
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What is the biggest advantage of using a set instead of a list when checking whether an item exists?
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A Japanese AI company called Preferred Networks has a mature open-source library for NumPy/SciPy calculations on GPUs. It's c
A Japanese AI company called Preferred Networks has a mature open-source library for NumPy/SciPy calculations on GPUs. It's called CuPy πŸš€. For massive datasets, it is often enough to replace a single line: import cupy as cp The same array operations can run on CUDA up to 100 times faster. What it can do: πŸ›  Highly compatible with existing NumPy and SciPy code πŸ“ Dramatically reduces the need to rewrite code or learn new syntax πŸ’» Supports not only NVIDIA CUDA but also AMD ROCm architectures Keep in mind: β†’ Only faster for massive arrays; small datasets will run slower due to CPU-to-GPU data transfer lag β†’ Strictly bound by your physical GPU VRAM limits (can cause out-of-memory errors). β†’ Covers most major math functions, but does not replicate 100% of NumPy/SciPy modules. The project is completely open-source and battle-tested since 2015 πŸ“‚: https://github.com/cupy/cupy
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100+ Python Problems with Solutions.pdf
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πŸ“˜ Biopython: Tutorial and Cookbook ✍️ Authors: Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon,
πŸ“˜ Biopython: Tutorial and Cookbook ✍️ Authors: Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich, Bartek WilczyΕ„ski πŸ”— Read Online #Python ──────────────────── πŸ‘‰ @free_programming_books_bds πŸ‘ˆ
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The Unofficial Python Graph Gallery If you work with data, you already know the pain of making charts look decent in Python. You spend 5 minutes writing the logic to process your data, and then 45 minutes wrestling with matplotlib or seaborn trying to figure out why your labels are overlapping, how to change a specific hex color, or how to remove those ugly default borders. This repository completely solves that. Instead of just listing libraries, it is a massive, beautifully organized collection of hundreds of data visualization examples. πŸ”— Link
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