Python Threading with Examples | Guide to Your Python Journey
Python threading allows you to run many parts of your program at the same time, which simplifies your design. Python threading is ideal for I/O operations like web scraping and applicable even the Python can’t be used for parallel CPU computations. To speed up your knowledge of Python programming, then prep yourself with Python threading with examples.
What is Python Threading?
Python threading is useful for making a responsive user interface and for processing several brief web requests where I/O is the bottleneck rather than Python code. Python threading allows you to run several threads (tasks, function calls) at once. This does not imply that they are executed on separate CPUs. Python threads will not speed up your program if it already consumes 100% of the CPU (wikibooks.com).
Python threads are utilized when a task’s execution necessitates some waiting. Interaction with a service hosted on another computer, such as a webserver, is one example. The threading mechanism allows Python to run other code while waiting for something to happen; the sleep() method can be used to simulate this.
Python Threading Examples
Time needed: 10 minutes.
Here are some examples of Threading in Python that will discuss the different uses of python threading.
- Python Threading Example – Join()
Join is a synchronization technique that blocks the calling thread (the one that calls the method) until the thread called the Join method has finished. To ensure that a thread has been killed, use this technique. If the thread does not end, the caller will stall indefinitely. This method stops the caller thread until the thread whose join() method is called terminates, either properly or due to an unhandled error.
The function join() makes the main thread wait for your thread to finish. Otherwise, your thread will run on its own. So think of join() as a “hold” on the main thread: it de-threads your thread and executes sequentially in the main thread before it can continue.
Example Syntax: <
object_name.join() OR object_name.join(timeout) where timeout argument is the timeout value.>
- Python Threading Example – Pool()
The Python thread pool is primarily used to manage worker threads and keep the number of application threads to a minimum. It is to establish a large number of threads at the start of a process and place them in a pool where they will sit and wait for work. A thread pool has the advantage of limiting the number of threads that can be created.
A thread pool in Python is a collection of idle threads that have been pre-instantiated and are waiting for a task. For new threads, you can either create new threads or use the Python Thread Pool. However, the Python Thread Pool is recommended over the former option when the number of jobs is extremely large.
- Python Threading Example – Timer()
In Python Timer(), threading begins with the delay specified as an argument. As a result, the Timer class calls itself, delaying the next operation by the same amount of time given.
Python’s Timer class is a subclass of the Thread class. It starts by explicitly using the start() function that corresponds to the timer. After the interval seconds have passed, create a timer that will run the function with arguments args and keyword arguments kwargs.
- Python Threading Example – Sleep()
Python threading sleep() suspends the thread and process execution in single-threaded programs. In multithreaded systems, however, the function suspends a thread rather than the entire process.
The sleep() function can be used to suspend the current thread’s execution for a specified amount of time in milliseconds. The milliseconds’ parameter value cannot be negative; otherwise, an IllegalArgumentException will be thrown.
- Python Threading Example – Stop()
Python threading stop() function is used to break or finish the thread. You can kill or stop the thread using several different methods.
• Raising exceptions
• Set and reset the stop flag
• Using traces
• Using the multiprocessing module
• Setting the Python thread as a daemon
• Using the _stop function (hidden function())
- Python Threading Example – Lock()
Locking ensures that one thread does not enter a critical section of code while another is already there in Python threading. When a thread tries to access a locked function, it will wait (block) until the object is released.
Locks are a synchronization technique included in Python’s threading module. When one thread tries to edit a shared resource at the same time as another thread, the result is jumbled output, which is why threads must be synchronized.
Python threads are referred to as lightweight processes. Communication between threads has a low operational cost, which is a benefit because threads share a similar address space as other processes and threads within the process.
Learning the definition and use of python threading will help you become more productive at python programming. Knowing the examples and classification of Python threading can give you more confidence in doing your program and projects in python.
There you have it, fellas. May this article about Python Threading and Multi-threading tutorial help you as you go through your python journey.
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