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Python Advanced: Code That Scales Past Your Own Laptop
Check Yourself: Doing More Than One Thing at a Time
Five scenario questions on threads, processes and asyncio. If you miss more than one, go back to the two lessons.
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Functions That Wrap Functions
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Python Closures: Functions That Remember
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Python Decorators in Real Code: Timing, Retry and Logging
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Data That Doesn't Fit in Memory
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Python Iterators: What a for Loop Actually Does
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Python Generators and yield: One Piece at a Time
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Python Context Managers: Clean Up Even When Things Fail
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Catch Bugs Before You Run the Code
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Python Type Hints Beyond the Basics: Optional, Union, Generics
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Checking Types With mypy in a Real Project
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Doing More Than One Thing at a Time
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Python Concurrency Basics: Threads, Processes or asyncio?
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Python asyncio: Wait for Many Things Without Waiting Longer
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Ship It, Then Make It Fast
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Packaging a Python Project With pyproject.toml
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Profiling Python Code: Measure Before You Optimize
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- Final Check: Python Advanced
1.
A script makes 50 slow network requests one after another. Which tool is the simplest way to speed it up with normal blocking libraries?
2.
You used 8 threads for a pure-Python calculation, and it takes the same time as one thread. Why?
3.
Your async function calls time.sleep(1) and requests.get(). What happens to the other tasks?
4.
You start 5,000 requests with asyncio.gather and the supplier starts refusing connections. What should you add?
5.
Your ProcessPoolExecutor script starts a flood of processes on Windows. What is missing?
About
Five scenario questions on threads, processes and asyncio. If you miss more than one, go back to the two lessons.
- Duration
- 5 min
- Last update
- 09/06/2026
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