<jupyter_start><jupyter_text>Setup your environment  Install anconda Anaconda is a distribution of python for scientific computing that aims to simplify package management and deployment.To install anaconda on windows1. Download anaconda from https://www.anaconda.com/products/individualwindows.2. Double click the downloaded file.3. Proceed with the installation.  Install Git bash Git Bash is an application for Microsoft Windows environments which provides an emulation layer for a Git command lineexperience.To install git bash on windows1. Download anaconda from https://www.anaconda.com/products/individualwindows.2. Double click the downloaded file.3. Proceed with the installation.  git configuration Global config:<jupyter_code>!git config --global user.name "FIRST_<NAME>"
!git config --global user.email "<EMAIL>"<jupyter_output><empty_output><jupyter_text>Local config:<jupyter_code>!git config user.name "FIRST_<NAME>"
!git config user.email "<EMAIL>"<jupyter_output><empty_output><jupyter_text>*Note that you can use git config for futher customization*  Track an existing project To start tracking an existing project use the following commands<jupyter_code>!cd yourproject
!git init .
!git add *
!git commit -m "commit message"<jupyter_output><empty_output><jupyter_text>To make it vailable in github, create a new repository in github then run<jupyter_code>!git remote add origin https://github.com/username/new_repo<jupyter_output><empty_output><jupyter_text>Virtual environments We will use condaconda is a very powerful package manager that excels at managing dependencies and offers an easy way to createand use virtual environments for your projects. It is used primarily in the Data Science world.To create a virtual environment run<jupyter_code>!conda create --name myenv<jupyter_output><empty_output><jupyter_text>To activate your virtual environment run<jupyter_code>!conda activate myenv<jupyter_output><empty_output><jupyter_text>List you virtual environments<jupyter_code>!conda env list<jupyter_output><empty_output><jupyter_text>list packages installed in you virtual environment:<jupyter_code>!conda list -n myenv<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.0703448275862069, 'fraction_numerical': 0.002758620689655172, 'mean_word_length': 7.089219330855019, 'pattern_counts': {'":': 0, '<': 37, '<?xml version=': 0, '>': 37, 'https://': 3, 'lorem ipsum': 0, 'www.': 2, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '8', 'dir': 'jupyter-structured-clean-dedup', 'id': '138366', 'license': 'MIT', 'n_tokens_mistral': 623, 'n_tokens_neox': 607, 'n_words': 217, 'path': 'config.ipynb', 'repo_name': 'AyoubDaoudia/python-bootcamp', 'size': '2215'}