{"id":31629,"date":"2024-11-01T09:01:06","date_gmt":"2024-11-01T09:01:06","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=31629"},"modified":"2024-11-01T11:48:52","modified_gmt":"2024-11-01T11:48:52","slug":"python-multithreading","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/31629\/","title":{"rendered":"Python Multithreading"},"content":{"rendered":"\n<h1 class=\"wp-block-heading\">Multithreading in Python<\/h1>\n\n\n\n<p>This document covers the basics of multithreading in the Python programming language.&nbsp;<a href=\"https:\/\/www.geeksforgeeks.org\/multiprocessing-python-set-1\/\">Multiprocessing<\/a>&nbsp;as well as&nbsp;multithreading is a method to achieve multitasking. In multithreading, the concept of a&nbsp;<strong>thread<\/strong>&nbsp;is used. First, let\u2019s understand the concept of a&nbsp;<strong>thread<\/strong>&nbsp;in computer architecture.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What is a Process in Python?<\/strong><\/h2>\n\n\n\n<p>In computing, a&nbsp;<a href=\"https:\/\/www.geeksforgeeks.org\/introduction-of-process-management\/\"><strong>process<\/strong><\/a>&nbsp;is an instance of a running computer program. Every process has three basic components.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>An executable program.<\/li>\n\n\n\n<li>Relevant data required by the program (variables, workspace, buffers, etc.)<\/li>\n\n\n\n<li>The execution context of the program (process state)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Introduction to Python Threading<\/strong><\/h2>\n\n\n\n<p>A thread&nbsp;<strong>is<\/strong>&nbsp;an entity within a process that can be scheduled for execution. It is also the smallest unit of processing that can be executed by the OS (operating system). Simply put, a thread is a sequence of instructions within a program that can be executed independently from other code. For simplification, a thread can be considered simply a subset of a process. Threads contain all this information in a&nbsp;<a href=\"https:\/\/www.geeksforgeeks.org\/thread-control-block-in-operating-system\/\"><strong>Thread Control Block<\/strong><\/a><strong>&nbsp;(TCB)<\/strong>.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Thread Identifier:<\/strong>&nbsp;A unique ID (TID) is assigned to each new thread.<\/li>\n\n\n\n<li><strong>Stack Pointer:<\/strong>&nbsp;Points to the thread stack of the process. The stack contains local variables defined within the thread&#8217;s scope.<\/li>\n\n\n\n<li><strong>Program Counter:<\/strong>&nbsp;A register that holds the address of the instruction currently being executed by the thread.<\/li>\n\n\n\n<li><strong>Thread State:<\/strong>&nbsp;Can be running, ready, waiting, starting, or completed.<\/li>\n\n\n\n<li><strong>Set of Registers for the Thread:<\/strong>&nbsp;Registers assigned to the thread for computation.<\/li>\n\n\n\n<li><strong>Pointer to Parent Process:<\/strong>&nbsp;A pointer to the process control block (PCB) of the process that the thread belongs to.<\/li>\n<\/ul>\n\n\n\n<p>Understanding how to implement multithreading can significantly enhance the performance of I\/O-bound and certain types of network applications. However, mastering this concept requires a clear understanding of some advanced features of Python. For those looking to advance these skills further, a&nbsp;<a href=\"https:\/\/www.geeksforgeeks.org\/courses\/python-course-certification-free\"><strong>free Python course includes<\/strong><\/a>&nbsp;a dedicated module on multithreading.<\/p>\n\n\n\n<p>To understand the relationship between processes and threads, consider the diagram below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"631\" height=\"802\" src=\"http:\/\/thelivesmart.com\/w\/wp-content\/uploads\/2024\/10\/img-1.png\" alt=\"\" class=\"wp-image-24046\" srcset=\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img-1.png 631w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img-1-236x300.png 236w\" sizes=\"auto, (max-width: 709px) 85vw, (max-width: 909px) 67vw, (max-width: 984px) 61vw, (max-width: 1362px) 45vw, 600px\" \/><\/figure>\n\n\n\n<p>Relationship Between Processes and Threads<\/p>\n\n\n\n<p>There can be multiple threads within a single process in the following cases:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Each thread includes its own<strong>set of registers<\/strong>&nbsp;and<strong>local variables (stored on the stack)<\/strong>.<\/li>\n\n\n\n<li>All threads in a process share<strong>global variables (stored in the heap)<\/strong>&nbsp;and<strong>program code<\/strong>.<\/li>\n<\/ul>\n\n\n\n<p>To understand how multiple threads exist in memory, consider the diagram below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"712\" height=\"391\" src=\"http:\/\/thelivesmart.com\/w\/wp-content\/uploads\/2024\/10\/img_1.png\" alt=\"\" class=\"wp-image-24045\" srcset=\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_1.png 712w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_1-300x165.png 300w\" sizes=\"auto, (max-width: 709px) 85vw, (max-width: 909px) 67vw, (max-width: 984px) 61vw, (max-width: 1362px) 45vw, 600px\" \/><\/figure>\n\n\n\n<p>Multiple Threads in Memory<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Introduction to Python Threading<\/h2>\n\n\n\n<p><strong>Multithreading is<\/strong>&nbsp;defined as the ability of a processor to execute multiple threads simultaneously. In a simple single-core CPU, this is achieved using frequent context switching between threads. This is called<strong>context switching<\/strong>. In context switching, the state of a thread is saved each time an interrupt (due to I\/O or manual setup) occurs, and the state of another thread is loaded. The context switching happens so frequently that it appears as if all threads are running in parallel (this is referred to as<strong>multitasking<\/strong>).<\/p>\n\n\n\n<p>Look at the diagram below that contains two active threads in a process.&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"412\" height=\"370\" src=\"http:\/\/thelivesmart.com\/w\/wp-content\/uploads\/2024\/10\/img_2.png\" alt=\"\" class=\"wp-image-24044\" srcset=\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_2.png 412w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_2-300x269.png 300w\" sizes=\"auto, (max-width: 412px) 85vw, 412px\" \/><\/figure>\n\n\n\n<p>Multithreading<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Multithreading in Python<\/strong><\/h3>\n\n\n\n<p>The threading module in <a href=\"https:\/\/www.geeksforgeeks.org\/python-programming-language\/\">Python<\/a>&nbsp;provides a very simple and intuitive API for creating multiple threads in a program. Let\u2019s understand multithreading code step by step.<\/p>\n\n\n\n<p><strong>Step 1:<\/strong>&nbsp;Import the module<\/p>\n\n\n\n<p>First, import the threading module.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import threading<\/code><\/pre>\n\n\n\n<p><strong>Step 2:<\/strong>&nbsp;Create Threads<\/p>\n\n\n\n<p>To create a new thread, create an object of the Thread class. Use &#8216;target&#8217; and &#8216;args&#8217; as parameters. The target&nbsp;<strong>is<\/strong>&nbsp;the function that will be executed by the thread, and args are the arguments that will be passed to the target function&nbsp;<strong>.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>t1 = threading.Thread(target, args)\nt2 = threading.Thread(target, args)<\/code><\/pre>\n\n\n\n<p><strong>Step 3:<\/strong>&nbsp;Start the Thread<\/p>\n\n\n\n<p>To start a thread, use the<strong>start() method of the Thread class.<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>t1.start()\nt2.start()<\/code><\/pre>\n\n\n\n<p><strong>Step 4:<\/strong>&nbsp;End Thread Execution<\/p>\n\n\n\n<p>Once the threads are started, the current program (think of it as the main thread) continues to execute as well. To stop the execution of the current program until the threads complete, use the<strong>join()<\/strong>&nbsp;method.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>t1.join()\nt2.join()<\/code><\/pre>\n\n\n\n<p>As a result, the current program waits for<strong>t1<\/strong>&nbsp;to finish first, and then waits for<strong>t2<\/strong>&nbsp;to complete. Once the tasks are done, the remaining statements of the current program are executed.<\/p>\n\n\n\n<p><strong>Example:<\/strong><\/p>\n\n\n\n<p>Let\u2019s look at a simple example using the threading module.<\/p>\n\n\n\n<p>This code demonstrates how to calculate the square and cube of a number simultaneously using Python&#8217;s threading module. Two threads&nbsp;are created to perform these calculations. The results are printed in parallel before the program prints &#8220;Done!&#8221; after both threads have completed. Threading is used to achieve parallelism when handling computation-intensive tasks and enhance program performance.<strong>&nbsp;<\/strong><strong>t1<\/strong><strong>&nbsp;<\/strong><strong>t2<\/strong><\/p>\n\n\n\n<p>Python<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import threading\n\n\ndef print_cube(num):\n    print(\"Cube: {}\" .format(num * num * num))\n\n\ndef print_square(num):\n    print(\"Square: {}\" .format(num * num))\n\n\nif __name__ ==\"__main__\":\n    t1 = threading.Thread(target=print_square, args=(10,))\n    t2 = threading.Thread(target=print_cube, args=(10,))\n\n    t1.start()\n    t2.start()\n\n    t1.join()\n    t2.join()\n\n    print(\"Done!\")\n<\/code><\/pre>\n\n\n\n<p><strong>Output<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Square: 100\nCube: 1000\nDone!<\/code><\/pre>\n\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Square: 100\nCube: 1000\nDone!<\/code><\/pre>\n\n\n\n<p>To better understand how the above program works, consider the diagram below.&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"282\" height=\"422\" src=\"http:\/\/thelivesmart.com\/w\/wp-content\/uploads\/2024\/10\/img_3.png\" alt=\"\" class=\"wp-image-24043\" srcset=\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_3.png 282w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_3-200x300.png 200w\" sizes=\"auto, (max-width: 282px) 85vw, 282px\" \/><\/figure>\n\n\n\n<p>Multithreading<\/p>\n\n\n\n<p><strong>Example:<\/strong><\/p>\n\n\n\n<p>This example uses the<strong>os.getpid()<\/strong>&nbsp;function to get the ID of the current process. The<strong>threading.main_thread()<\/strong>&nbsp;function is used to retrieve the main thread object. Under normal conditions, the main thread is the thread in which the Python interpreter was started. The<strong>name<\/strong>&nbsp;attribute of the thread object is used to obtain the thread&#8217;s name. Then, the<strong>threading.current_thread()<\/strong>&nbsp;function is used to retrieve the current thread object.<\/p>\n\n\n\n<p>Consider the following Python program that prints the thread name and its associated process for each task.&nbsp;<\/p>\n\n\n\n<p>This code demonstrates how to run two tasks simultaneously using Python&#8217;s threading module. The main program starts two threads, each executing a specific task. The threads run in parallel, and the code provides information about the process ID and thread name. The module is used to access process IDs, and the<strong>&#8216;<\/strong>&nbsp;module is used to manage threads and thread execution.<strong>&nbsp;<\/strong><strong>t1<\/strong><strong>&nbsp;<\/strong><strong>t2<\/strong>os<strong>threading&#8217;<\/strong><\/p>\n\n\n\n<p>Python<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import threading\nimport os\n\ndef task1():\n    print(\"Task 1 assigned to thread: {}\".format(threading.current_thread().name))\n    print(\"ID of process running task 1: {}\".format(os.getpid()))\n\ndef task2():\n    print(\"Task 2 assigned to thread: {}\".format(threading.current_thread().name))\n    print(\"ID of process running task 2: {}\".format(os.getpid()))\n\nif __name__ == \"__main__\":\n\n    print(\"ID of process running main program: {}\".format(os.getpid()))\n\n    print(\"Main thread name: {}\".format(threading.current_thread().name))\n\n    t1 = threading.Thread(target=task1, name='t1')\n    t2 = threading.Thread(target=task2, name='t2')\n\n    t1.start()\n    t2.start()\n\n    t1.join()\n    t2.join()\n<\/code><\/pre>\n\n\n\n<p><strong>Output<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>ID of process running main program: 19\nMain thread name: MainThread\nTask 1 assigned to thread: t1\nID of process running task 1: 19\nTask 2 assigned to thread: t2\nID of process running task 2: 19<\/code><\/pre>\n\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>ID of process running main program: 1141\nMain thread name: MainThread\nTask 1 assigned to thread: t1\nID of process running task 1: 1141\nTask 2 assigned to thread: t2\nID of process running task 2: 1141<\/code><\/pre>\n\n\n\n<p>The diagram below clarifies the above concepts.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"402\" height=\"402\" src=\"http:\/\/thelivesmart.com\/w\/wp-content\/uploads\/2024\/10\/img_4.png\" alt=\"\" class=\"wp-image-24041\" srcset=\"https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_4.png 402w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_4-300x300.png 300w, https:\/\/atmokpo.com\/w\/wp-content\/uploads\/2024\/10\/img_4-150x150.png 150w\" sizes=\"auto, (max-width: 402px) 85vw, 402px\" \/><\/figure>\n\n\n\n<p>Multithreading<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>In conclusion, we briefly introduced multithreading in Python. The next article in this series will cover<strong> synchronization between multiple threads<\/strong>. &nbsp;<a href=\"https:\/\/www.geeksforgeeks.org\/multithreading-in-python-set-2-synchronization\/\">Multithreading in Python | Set 2 (Synchronization)<\/a>&nbsp;<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\">Python Thread Pool<\/h2>\n\n\n\n<p>A thread pool is a collection of threads that can be reused to execute multiple tasks, which are created in advance. The Concurrent.futures module in Python provides the ThreadPoolExecutor class, which allows easy creation and management of thread pools.&nbsp;<\/p>\n\n\n\n<p>This example defines a function worker that will be executed in the threads. It creates a ThreadPoolExecutor with a maximum of 2 worker threads. The two tasks are then submitted to the pool using the submit method. The pool manages the execution of tasks by the worker threads. To wait for all tasks to complete before the main thread continues, the shutdown method is used.<\/p>\n\n\n\n<p>Multithreading helps improve a program&#8217;s efficiency and responsiveness. However, it is crucial to be cautious when working with threads to avoid issues like race conditions and deadlocks.<\/p>\n\n\n\n<p>This code runs two worker tasks simultaneously using a thread pool created by&nbsp;concurrent.futures. It allows efficient parallel processing of tasks in a multithreaded environment.<strong>&nbsp;<\/strong><strong>concurrent.futures.ThreadPoolExecutor<\/strong><strong>pool.shutdown(wait=True)<\/strong><\/p>\n\n\n\n<p>Python<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import concurrent.futures\n\ndef worker():\n    print(\"Worker thread running\")\n\npool = concurrent.futures.ThreadPoolExecutor(max_workers=2)\n\npool.submit(worker)\npool.submit(worker)\n\npool.shutdown(wait=True)\n\nprint(\"Main thread continuing to run\")\n<\/code><\/pre>\n\n\n\n<p><strong>Output<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Worker thread running\nWorker thread running\nMain thread continuing to run<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Multithreading in Python \u2013 FAQ<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">What is Multithreading in Python?<\/h3>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Multithreading in Python involves executing multiple threads simultaneously within a single process to achieve parallelism and utilize&nbsp;<strong>multiple CPU cores<\/strong>.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">Is Python suitable for Multithreading?<\/h3>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Due to the GIL (Global Interpreter Lock), which limits Python to execute only one thread at a time for CPU-bound tasks, Python is suitable for using multithreading for&nbsp;<strong>I\/O-bound<\/strong>&nbsp;tasks. For CPU-bound tasks, multiprocessing is often more effective.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">Which module is used for Multithreading in Python?<\/h3>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>The<strong>&#8216;threading&#8217;<\/strong>&nbsp;module is used for multithreading in Python.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">What are the various types of threads in Python?<\/h3>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>The two main types of threads in Python are:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Main Thread<\/strong>: The initial thread that runs when the program starts.<\/li>\n\n\n\n<li><strong>Daemon Threads<\/strong>: Background threads that automatically terminate when the main thread exits.<\/li>\n\n\n\n<li><strong>Non-Daemon Threads<\/strong>: Threads that continue to run until their tasks are complete, even if the main thread exits.<\/li>\n<\/ul>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">How many threads can Python have for Multithreading?<\/h3>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>There is no fixed limit on the number of threads in Python, but the actual limit is determined by system resources and the GIL, so having too many threads may degrade performance. Generally, Python applications use dozens to hundreds of threads, but for intensive tasks, it&#8217;s recommended to use multiprocessing.<\/p>\n<\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Multithreading in Python This document covers the basics of multithreading in the Python programming language.&nbsp;Multiprocessing&nbsp;as well as&nbsp;multithreading is a method to achieve multitasking. In multithreading, the concept of a&nbsp;thread&nbsp;is used. First, let\u2019s understand the concept of a&nbsp;thread&nbsp;in computer architecture. What is a Process in Python? In computing, a&nbsp;process&nbsp;is an instance of a running computer program. &hellip; <a href=\"https:\/\/atmokpo.com\/w\/31629\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;Python Multithreading&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[98],"tags":[95],"class_list":["post-31629","post","type-post","status-publish","format-standard","hentry","category--en","tag--en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python Multithreading - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/31629\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python Multithreading - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"Multithreading in Python This document covers the basics of multithreading in the Python programming language.&nbsp;Multiprocessing&nbsp;as well as&nbsp;multithreading is a method to achieve multitasking. 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In multithreading, the concept of a&nbsp;thread&nbsp;is used. First, let\u2019s understand the concept of a&nbsp;thread&nbsp;in computer architecture. What is a Process in Python? 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