Python Concurrency and Parallelism

Python Concurrency and Parallelism - Important Points

A. Machine learning

B. GUI programming

C. Web scraping

D. Database programming

A. Concurrency refers to the ability to execute multiple tasks simultaneously, while parallelism refers to the ability to execute multiple tasks on multiple processors simultaneously.

B. Concurrency refers to the ability to execute multiple tasks on multiple processors simultaneously, while parallelism refers to the ability to execute multiple tasks simultaneously.

C. Concurrency refers to the ability to execute multiple tasks on a single processor simultaneously, while parallelism refers to the ability to execute multiple tasks on multiple processors simultaneously.

D. Concurrency and parallelism are the same thing.

A. A mechanism that ensures only one thread can execute Python bytecode at a time.

B. A mechanism that allows multiple threads to execute Python bytecode simultaneously.

C. A mechanism that allows multiple processes to execute Python bytecode simultaneously.

D. A mechanism that prevents Python code from being executed on more than one processor at a time.

A. A race condition

B. A deadlock

C. A livelock

D. A memory leak

A. PyCharm

B. Black

C. Flake8

D. Pyroscope