Concurrency Basics
Concurrency, in the context of computer science, refers to the ability of a system to execute multiple tasks simultaneously. This is a crucial concept in modern software development, especially as applications become more complex and require handling multiple operations at once.
Key Concepts
- Parallelism: The execution of two or more tasks at the same time.
- Concurrency: The execution of two or more tasks by a single processor in interleaved fashion.
- Thread: A thread of execution within a process.
- Lock: A synchronization mechanism used to ensure that only one thread can access a resource at a time.
Types of Concurrency
- CPU-bound: Tasks that are limited by the processing power of the CPU.
- IO-bound: Tasks that are limited by the speed of input/output operations.
Benefits of Concurrency
- Improved performance: By executing tasks concurrently, the system can make better use of available resources.
- Better responsiveness: Applications can remain responsive even when performing time-consuming tasks.
Challenges
- Complexity: Concurrency introduces complexity into the system, making it harder to design and maintain.
- Race conditions: When two or more threads access the same resource concurrently, it can lead to race conditions, where the outcome depends on the order of execution.
Example
Here is a simple example of a concurrent program in Python:
import threading
def print_numbers():
for i in range(1, 6):
print(i)
thread1 = threading.Thread(target=print_numbers)
thread2 = threading.Thread(target=print_numbers)
thread1.start()
thread2.start()
thread1.join()
thread2.join()
Further Reading
For more information on concurrency, you might want to check out our Concurrency Deep Dive guide.
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