{"id":112095,"date":"2021-11-19T11:30:02","date_gmt":"2021-11-19T16:30:02","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=112095"},"modified":"2022-11-21T09:49:28","modified_gmt":"2022-11-21T14:49:28","slug":"pickle-python-how-to-use-need-and-example-part-ii","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/pickle-python-how-to-use-need-and-example-part-ii\/","title":{"rendered":"Pickle Python \u2013 How to use, Need and Example &#8211; Part II"},"content":{"rendered":"\n<p><em>See <a href=\"\/campus\/ibkr-quant-news\/pickle-python-how-to-use-need-and-example\/\">Part I<\/a> to get started with Pickle Python.<\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"pickle-python-scenario-2\">Pickle Python Scenario 2<\/h3>\n\n\n\n<p>In the following scenario, we can see a Pickle object between the testing process and the forecasting process.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"637\" height=\"309\" data-src=\"\/campus\/wp-content\/uploads\/sites\/2\/2021\/11\/pickle-python-example-pickle-object-quantinsti.png\" alt=\"Pickle Python\" class=\"wp-image-112105 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2021\/11\/pickle-python-example-pickle-object-quantinsti.png 637w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2021\/11\/pickle-python-example-pickle-object-quantinsti-300x146.png 300w\" data-sizes=\"(max-width: 637px) 100vw, 637px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 637px; aspect-ratio: 637\/309;\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><em>Pickle Python example &#8211; Pickle object between the testing process and the forecasting process<\/em><\/p>\n\n\n\n<p>In short, Pickle allows us to dump the Python objects in memory to a binary file to retrieve them later and continue working. Let&#8217;s see how to dump the memory to the file and load the memory from the file later.<\/p>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"how-to-use-pickle-python-to-save-work\">How to use Pickle Python to save work<\/h2>\n\n\n\n<p>The process of dumping objects from RAM to binary file with Pickle Python is quite simple:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code><code>import pickle<\/code><\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code>pickle.dump(object, model_x.pkl, other_params)<\/code><\/pre>\n\n\n\n<p>This simple line of code certainly saves us a great deal of work. On the other hand, the function accepts many other parameters for which it is recommended to consult the&nbsp;<a href=\"https:\/\/docs.python.org\/3\/library\/pickle.html#\" target=\"_blank\" rel=\"noreferrer noopener\">official documentation<\/a>.<\/p>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"how-to-use-pickle-python-to-retrieve-work\">How to use Pickle Python to retrieve work<\/h2>\n\n\n\n<p>The loading process from binary Pickle file to RAM is just as simple:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>import pickle<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code>model = pickle.load(model_x.pkl)<\/code><\/pre>\n\n\n\n<p>With this simple line of code we get our model back in memory as if we had just finished the model testing process.<\/p>\n\n\n\n<p>It is important to note that&nbsp;<strong>loading unknown Pickle files into RAM can seriously compromise the security of the machine<\/strong>, so it is not recommended to use pickle files of unknown origin.<\/p>\n\n\n\n<p><em>Visit QuantInsti to read the full article:&nbsp;<a href=\"https:\/\/blog.quantinsti.com\/pickle-python\/\">https:\/\/blog.quantinsti.com\/pickle-python\/<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the following scenario, we can see a Pickle object between the testing process and the forecasting process.<\/p>\n","protected":false},"author":387,"featured_media":25709,"comment_status":"closed","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,343,349,338,350,341,344],"tags":[5121,806,852,10562],"contributors-categories":[13654],"class_list":{"0":"post-112095","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-programing-languages","9":"category-python-development","10":"category-ibkr-quant-news","11":"category-quant-asia-pacific","12":"category-quant-development","13":"category-quant-regions","14":"tag-big-data","15":"tag-data-science","16":"tag-machine-learning","17":"tag-pickle-python","18":"contributors-categories-quantinsti"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin 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