List Comprehension and Functions – Python Code Typing Test
Demonstrates Python's list comprehension, type hints, and function definitions with docstrings.
- Lines
- 38
- Chars
- 841
- At 40 WPM
- ≈ 4m 12s
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import math
from typing import List, Optional
def fibonacci(n: int) -> List[int]:
"""Generate fibonacci sequence up to n numbers"""
if n <= 0:
return []
elif n == 1:
return [0]
fib = [0, 1]
for i in range(2, n):
fib.append(fib[i-1] + fib[i-2])
return fib
def find_primes(limit: int) -> List[int]:
"""Find all prime numbers up to limit using sieve"""
primes = []
sieve = [True] * (limit + 1)
for i in range(2, int(math.sqrt(limit)) + 1):
if sieve[i]:
for j in range(i * i, limit + 1, i):
sieve[j] = False
return [i for i in range(2, limit + 1) if sieve[i]]
# Main execution
if __name__ == "__main__":
fib_sequence = fibonacci(10)
print(f"Fibonacci: {fib_sequence}")
primes = find_primes(30)
print(f"Primes up to 30: {primes}")
# List comprehension example
squares = [x**2 for x in range(1, 11) if x % 2 == 0]
print(f"Even squares: {squares}")Coding works best on desktop or with an external keyboard.
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✦This snippetList Comprehension and Functions — Python Code
Demonstrates Python's list comprehension, type hints, and function definitions with docstrings.
import math
from typing import List, Optional
def fibonacci(n: int) -> List[int]:
"""Generate fibonacci sequence up to n numbers"""
if n <= 0:
return []
elif n == 1:
return [0]
fib = [0, 1]
for i in range(2, n):
fib.append(fib[i-1] + fib[i-2])
return fib
def find_primes(limit: int) -> List[int]:
"""Find all prime numbers up to limit using sieve"""
primes = []
sieve = [True] * (limit + 1)
for i in range(2, int(math.sqrt(limit)) + 1):
if sieve[i]:
for j in range(i * i, limit + 1, i):
sieve[j] = False
return [i for i in range(2, limit + 1) if sieve[i]]
# Main execution
if __name__ == "__main__":
fib_sequence = fibonacci(10)
print(f"Fibonacci: {fib_sequence}")
primes = find_primes(30)
print(f"Primes up to 30: {primes}")
# List comprehension example
squares = [x**2 for x in range(1, 11) if x % 2 == 0]
print(f"Even squares: {squares}")✦Language file
Python Language Guide
Python is a high-level, dynamically typed, multi-paradigm programming language known for simplicity, readability, and massive ecosystem support. It powers web development, data science, machine learning, automation, scripting, backend systems, and more.
- Origin & Creator
- Created by Guido van Rossum in 1991, inspired by ABC language with a vision of a simple, readable language for everyday programming tasks.
- Industrial Note
- Python dominates in AI/ML research, automation-heavy engineering teams, fast MVP prototyping, data-driven industries, hybrid cloud pipelines, ETL scripting, scientific computing, and large-scale analytical workflows.
Primary Use Cases
- Backend web development
- Machine learning & AI
- Data analysis & visualization
- Automation & scripting
- API development
- Scientific computing
- DevOps tooling
- Cybersecurity scripting
Notable Features
- Simple, readable syntax
- Massive standard library
- Dynamically typed
- Extensive third-party ecosystem (PyPI)
- Cross-platform
- Strong scientific & ML libraries
Quick Explain
- Python emphasizes clean syntax and developer productivity.
- It supports procedural, object-oriented, and functional programming styles.
- Used across data science, AI, web development, automation, and scripting.
Core Features
- Object-oriented and functional support
- Garbage-collected memory management
- Interactive REPL
- Rich built-in data types
- Module/package system
- Asynchronous programming (async/await)
Learning Path
- Basics + syntax
- OOP + modules
- Web or data specialization
- Async + frameworks
- Advanced tooling
Practical Examples
- Data analysis script
- REST API with FastAPI
- Machine learning model
- Automation with Selenium
- File system utilities
Comparisons
- Easier than Java for beginners
- More flexible than C++
- Slower than Go/Rust
- Stronger ML ecosystem than JavaScript
Strengths
- Beginner-friendly
- Huge ecosystem
- Excellent for AI/ML
- Fast development cycle
- Great community support
Limitations
- Slower execution than compiled languages
- Weak mobile development ecosystem
- GIL limits multi-threaded CPU performance
- Runtime errors due to dynamic typing
When NOT to Use
- High-performance embedded systems
- Performance-critical computation
- Mobile app development
- Browser-based execution
Cheat Sheet
- List comprehension: [x for x in arr]
- Dictionary: {'a': 1}
- Lambda: lambda x: x + 1
- Async: async/await
- Import: from module import X
FAQ
- Is Python slow?
- Slower than compiled languages but fast enough with optimizations.
- Is Python good for ML?
- Yes-it's the top ML/AI language.
- Can Python run on web?
- Yes via backends, not directly in browser.
- Is Python good for beginners?
- It’s the most beginner-friendly mainstream language.
30-Day Skill Plan
- Week 1: Syntax & basics
- Week 2: OOP + functions
- Week 3: APIs + automation
- Week 4: Pick a specialization
Final Summary
- Python is a flexible, beginner-friendly language with a massive ecosystem.
- It dominates AI/ML, automation, and backend development.
- Its clarity, libraries, and community make it ideal for rapid development.
- Despite performance limitations, it’s among the most versatile languages ever built.
Project Structure
- src/ modules
- requirements.txt / pyproject.toml
- venv environment
- tests/ folder
- README + configs
Monetization
- Freelance automation scripts
- ML/AI engineering
- Backend development
- Data analysis consulting
Productivity Tips
- Use type hints
- Use virtualenv
- Use list comprehensions
- Profile code regularly
Basic Concepts
- Variables & dynamic typing
- Control flow
- Functions & classes
- Modules and packages
- Lists, tuples, dicts, sets
- Error handling
Official Docs
- Python Official Documentation
- PyPI Package Index
- Python PEP Index
More Python Typing Exercises
More Python typing tests →- 01Python Quick Sort Algorithm→
- 02Python Dictionary Comprehensions→
- 03Python Filter and Map→
- 04Python Lambda and Reduce→
- 05Python Set Comprehension→
- 06Python Nested List Comprehension→
- 07Python Function with Optional Argument→
- 08Python Zip Function→
- 09Python List Comprehension with Condition→
- 10Python Recursion Example→