Learn Python Coding

🔰 Comprehensions in python with example

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✨ Unpacking the remaining elements 🧩 Sometimes you need to extract the first and last elements from a list, while grouping everything in the middle separately. Instead of struggling with slicing ([1:-1]), use the asterisk (*). ⭐️

data = ["CEO", "Middle Python Dev", "Junior Dev", "QA", "HR"]

# The asterisk automatically collects everything "extra" into a separate list.
boss, *team, hr = data

print(boss)    # CEO
print(team)    # ['Middle Python Dev', 'Junior Dev', 'QA']
print(hr)      # HR

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Python has a built-in topological dependency sorter!🚀 If you're working with tasks that have dependencies — for example, in build systems, CI/CD pipelines, or workflow orchestration — the order of execution often has to be determined manually. Usually through graphs, DFS,, or custom execution order logic. But Python's standard library already has graphlib.TopologicalSorter.

ts = TopologicalSorter()
ts.add("deploy", "test")
ts.add("test", "build")

After preparation, the sorter returns the correct execution order.

tuple(ts.static_order())

Result:

("build", "test", "deploy")

Especially useful for workflow management systems, dependency resolution, orchestration systems, and any tasks with a dependency graph. 🔥 TopologicalSorter allows you to solve dependency problems using Python's built-in tools without having to implement graph algorithms manually. #Python #DependencyResolution #WorkflowOrchestration #CICD #BuildSystems #TopologicalSort ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

💡 Replacing if-else with Match-Case Starting with Python 3.10, we have a powerful tool: Structural Pattern Matching (match-case). This is not just an analog of switch-case from other languages; it's much more flexible. 🚀 Imagine you're writing a command handler for a bot. 🤖 ❌ How NOT to do it:

def handle_command(command):
    if command == "start":
        return "Hello! I'm a bot."
    elif command == "help":
        return "Here's a list of available commands..."
    elif command == "stop":
        return "Goodbye!"
    else:
        return "Unknown command."

⚡ How to do it properly:

def handle_command(command):
    match command:
        case "start":
            return "Hello! I'm a bot."
        case "help":
            return "Here's a list of available commands..."
        case "stop":
            return "Goodbye!"
        case _:  # The underscore symbol catches everything else (default)
            return "Unknown command."

The code looks like a clear table, and your eye doesn't get caught up in a bunch of elif statements. 🧐 You can pass data structures in the case statements and check their structure and content on the fly. 🔍 It's easy to combine cases. 🧩 #Python #Programming #MatchCase #CodingTips #Python310 #Developer ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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What's the difference between is and == in Python? The == operator checks whether the values of two objects are equal. In contrast, is determines whether variables refer to same object in memory. That is, == compares the content, while is checks the identity of the objects 🐍🔍 #Python #Programming #Coding #Developer #Tech #Learning ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

📌 How to make code cleaner with any() and all() 🐍 Do you often have to check lists for compliance with conditions? Forget about cumbersome loops! 🚫🔄 any() — returns True if at least one element is true. ✅ all() — returns True only if all elements are true. 🔒 # Example: checking if there are negative numbers numbers = [1, 5, -3, 7] # Bad: through a loop has_negative = False for num in numbers:      if num < 0:          has_negative = True # Beautiful: has_negative = any(num < 0 for num in numbers) # True ✨ #python #coding #pythonprogramming #learnpython #codeoptimization #programmingtips ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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collections.Counter — counting elements in a single line. 📊 Counting elements without loops with Counter 🔄 Do you need to count how many times each word appears in a text or how many duplicates there are in a list? Don't reinvent the wheel with for loops and dictionaries. The built-in collections module will do everything for you. 🚀 🛠 Code:

from collections import Counter

words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
word_counts = Counter(words)

print(word_counts)
# Output: Counter({'apple': 3, 'banana': 2, 'cherry': 1})

# Bonus: the top 2 most frequent elements
print(word_counts.most_common(2))
# Output: [('apple', 3), ('banana', 2)]

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