{
  "source_file": "0930",
  "source_platform": "Medium",
  "author": "Dario Radečić",
  "title_listed": "Python Pipreqs - How to Create requirements.txt File Like a Sane Person",
  "keywords": "pipreqs,依赖",
  "domain": "数据处理",
  "content_type": "深度技术解析",
  "is_paid_flag": "部分免费/会员墙",
  "url": "https://towardsdatascience.com/python-pipreqs-how-to-create-requirements-txt-file-like-a-sane-person-c82da5d5cd13/",
  "publish_date": "2022-12",
  "corpus_stage": "预训练/SFT",
  "notes": "",
  "id": "c0fe9753214e",
  "collected_at": "2026-10-01T21:34:37",
  "title": "Python Pipreqs - How to Create requirements.txt File Like a Sane Person | Towards Data Science",
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It also helps in adverstising on the website.\n\n\n  * Cookie\nedgebucket\n  * Duration\nsession\n  * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n  * Cookie\ndid\n  * Duration\n1 year\n  * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Data Science](https://towardsdatascience.com/category/data-science/)\n# Python Pipreqs - How to Create requirements.txt File Like a Sane Person\nWant to include only the libraries you use in requirements.txt? Try pipreqs, a Python module for creating leaner requirements files.\n[Dario Radečić](https://towardsdatascience.com/author/radecicdario/)\nDecember 5, 20224 min read\n![Article thumbnail \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1_rlos6uVk6XMkhSKwTrL3Q.jpeg)\nArticle thumbnail (image by author)\nEvery Python project should have a `requirements.txt` file. It stores the information of all libraries needed for a project to run, and is essential when deploying Python projects. This is traditionally done via the `pip freeze` command, which outputs all libraries installed in a virtual environment.\nBut what if you want only the ones used in the project? That's where pipreqs comes into play. It does the same thing as `pip freeze`, but better.\nPicture this - you create a new virtual environment and install a bunch of dependencies. During the project, you decide not to use some libraries, but you forget to delete them from the environment. A `requirements.txt` file generated with `pip freeze` will include both used and unused libraries, which is just a waste of resources.\nThere's a better way, and today you'll learn all about it.\nDon't feel like reading? Well, you don't have to:\n* * *\nLearn this step by step with the interactive [AI and Data Scientist](https://roadmap.sh/ai-data-scientist) and [Computer Science](https://roadmap.sh/computer-science) roadmaps.\n## How to Use Python Pipreqs to Create requirements.txt File\nLet's get to it. I've created a new virtual environment with Anaconda called `pipreqs_test` based on Python 3.10. You're free to use Anaconda or any other environment manager:\nbash\n\n```\nconda create --name pipreqs_test python=3.10 -y\nconda activate pipreqs_test\n```\n\nFrom here, let's install a bunch of Python libraries with pip:\nbash\n\n```\npip install numpy pandas matplotlib seaborn statsmodels plotly scikit-learn\n```\n\nHere's the shell output:\n![Image 1 - Installing Python libraries with pip \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/18erJc-hGWC7lTOOEhplMkg.png)\nImage 1 - Installing Python libraries with pip (image by author)\nAnd now, create a Python script that only uses Numpy and Pandas:\npython\n\n```\nimport numpy as np\nimport pandas as pd\n\narr = np.array([1, 2, 3])\ndf = pd.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})\n```\n\nI've named mine `script.py`:\n![Image 2 - Contents of a Python file \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/10cIqljrnhQrsLuUJSgljYg.png)\nImage 2 - Contents of a Python file (image by author)\nLet's first see what issuing a `pip freeze` command will save into the requirements file:\nbash\n\n```\npip freeze > requirements.txt\n```\n\nAs it turns out, a whole lot of libraries - both used and unused with their dependencies:\n![Image 3 - Requirements file generated with pip freeze \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1B0f2Zo7lIQcsk7YEAnvs8g.png)\nImage 3 - Requirements file generated with pip freeze (image by author)\nIf you were to run this script on a new machine and install Python dependencies from a `requirements.txt` file, many unused libraries would get installed. It would be better if you could somehow install only the libraries that were used in the project.\nThat's where pipreqs shines. But first, we have to install it:\ntypescript\n\n```\npip install pipreqs\n```\n\nPipreqs works by scanning all `.py` files in a given directory and looking for the imports in Python files. This way, it should write only the libraries you actually use to `requirements.txt`.\nHere's the general command for saving requirements:\nbash\n\n```\npipreqs <path-to-python-project-folder>\n```\n\nIf you're in a Python project folder, simply run this command:\nbash\n\n```\npipreqs .\n```\n\nYou'll see the following output:\n![Image 4 - Using pipreqs to create requirements.txt file \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1CzAXhoA_GNrXw_Ud8ib6jw.png)\nImage 4 - Using pipreqs to create requirements.txt file (image by author)\nThe dependencies are now saved to `requirements.txt`, so let's see what's inside:\n![Image 5 - Requirements file generated with pipreqs \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1Dc7WgK6BiFJflFWD_yEwoA.png)\nImage 5 - Requirements file generated with pipreqs (image by author)\nAmazing - only Numpy and Pandas were included! These are all the dependencies you need to run the project on a new machine or a new environment.\nBut is that all you can do with Pipreqs? Let's go over a couple of \"advanced\" use cases next.\n## What Else Can You Do With Pipreqs?\nYou can just check which libraries are used in the project by printing them to the console:\nbash\n\n```\npipreqs <path-to-folder> --print\n```\n\nHere are the results:\n![Image 6 - Print dependencies \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/156JzqIjifwfSz0U12cKEPw.png)\nImage 6 - Print dependencies (image by author)\nThis won't write the dependencies to a file, so keep that in mind.\nYou can also force overwrite the `requirements.txt` file. This command is needed if you already have the requirements file present, as running `pipreqs .` alone won't overwrite it:\nbash\n\n```\npipreqs <path-to-folder> --force\n```\n\nThe updated `requirements.txt` file is now saved:\n![Image 7 - Force overwrite requirements.txt file \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1Uonh6TMUdRFygejyfij3Zw.png)\nImage 7 - Force overwrite requirements.txt file (image by author)\nYou can also save the `requirements.txt` file to a different destination. Just make sure to include the full file path including the file name:\nbash\n\n```\npipreqs <path-to-folder> --savepath <path-to-file>\n```\n\nHere's how I saved the file to the Desktop:\n![Image 8 - Saving requirements.txt to a different location \\(image by author\\)](https://assets.insightmediagroup.io/media/wp-content/uploads/2022/12/1dDYxCrD3utDLisZRAp0BLA.png)\nImage 8 - Saving requirements.txt to a different location (image by author)\nAnd that's pretty much all you can do with Pipreqs. There are some additional options and parameters, but these are the ones you'll use 99% of the time.\nLet's make a short recap next.\n* * *\n## Summing up Python Pipreqs\nThere's nothing wrong with generating requirements files the old way via `pip freeze`. It just includes a bunch of unnecessary libraries and their dependencies, as everything installed in an environment (or God forbid, globally) gets picked.\nPipreqs solves this inconvenience by scanning Python files in a given project folder and looking for libraries that were actually imported. It's not something groundbreaking, but it will make your projects tidier, which is always welcome.\n_What do you use to kee track of project dependencies? Do you see Pipreqs as a better alternative?_ Let me know in the comment section below.\n* * *\n_Loved the article? Become a_[ _Medium member_](https://towardsdatascience.com/@radecicdario/membership) _to continue learning without limits. I'll receive a portion of your membership fee if you use the following link, with no extra cost to you._\n> [**Join Medium with my referral link - Dario Radečić**](https://medium.com/@radecicdario/membership)\n* * *\n### Stay connected\n  * Hire me as a [technical writer](https://betterdatascience.com/contact/)\n  * Subscribe on [YouTube](https://www.youtube.com/c/BetterDataScience)\n  * Connect on [LinkedIn](https://www.linkedin.com/in/darioradecic/)\n\n\n* * *\n_Originally published at_[ _https://betterdatascience.com_](https://betterdatascience.com/python-pipreqs/) _on December 5, 2022._\n## Register Now to Continue Reading\n### Unlock Towards Data Science with a Free Account\nAll articles on Towards Data Science are available to registered users. 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