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Merge pull request #1 from stefmolin/env-check-workflow
Add env check workflow with GitHub Actions
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‎.github/workflows/env-checks.yml

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# This workflow builds the workshop environment on Mac, Linux, and Windows for
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# multiple versions of Python to confirm it can be properly installed.
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#
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# Author: Stefanie Molin
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name: Env Build
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# Controls when the workflow will run
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on:
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# Triggers the workflow on push events
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push:
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branches: [ "main" ]
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# Trigger on pull request always (note the trailing colon)
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pull_request:
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# Allows you to run this workflow manually from the Actions tab
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workflow_dispatch:
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# Run this every month
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schedule:
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- cron: "44 22 11 * *"
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# A workflow run is made up of one or more jobs that can run sequentially or in parallel
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jobs:
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# This workflow contains a single job called "build"
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build:
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name: Python ${{ matrix.python-version }}, ${{ matrix.os }}
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# The type of runner that the job will run on
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runs-on: ${{ matrix.os }}
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defaults:
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run:
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shell: bash -el {0}
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strategy:
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fail-fast: false
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matrix:
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os: [macos-latest, ubuntu-latest, windows-latest]
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python-version: ["3.8", "3.9", "3.10"]
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# Steps represent a sequence of tasks that will be executed as part of the job
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steps:
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# checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
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- uses: actions/checkout@v3
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# remove the Python version from the file for testing
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- name: strip hardcoded Python version from environment for testing
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run: |
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if [[ ${{ matrix.os }} == "macos"* ]]; then
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sed -i '' -e '/- python/d' environment.yml;
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else
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sed -i -e '/- python/d' environment.yml;
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fi;
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# create the conda env
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- uses: conda-incubator/setup-miniconda@v2
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with:
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python-version: ${{ matrix.python-version }}
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auto-update-conda: true
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miniforge-variant: Mambaforge
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use-mamba: true
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channel-priority: true
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activate-environment: pandas_workshop
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environment-file: environment.yml
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- name: conda diagnostics
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run: |
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conda info
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conda list
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conda config --show-sources
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conda config --show
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printenv | sort
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- name: verify install
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run: cd notebooks && python check_env.py
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‎README.md

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# Pandas Workshop
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/stefmolin/pandas-workshop/main?urlpath=lab) [![Nbviewer](https://img.shields.io/badge/render-nbviewer-lightgrey?logo=jupyter)](https://nbviewer.jupyter.org/github/stefmolin/pandas-workshop/tree/main/) ![GitHub repo size](https://img.shields.io/github/repo-size/stefmolin/pandas-workshop) [![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=github)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/stefmolin/pandas-workshop/main?urlpath=lab) [![Nbviewer](https://img.shields.io/badge/render-nbviewer-lightgrey?logo=jupyter)](https://nbviewer.jupyter.org/github/stefmolin/pandas-workshop/tree/main/) [![Env Build Workflow Status](https://img.shields.io/github/actions/workflow/status/stefmolin/pandas-workshop/env-checks.yml?label=env%20build&logo=github&logoColor=white)](https://github.com/stefmolin/pandas-workshop/actions/workflows/env-checks.yml) ![GitHub repo size](https://img.shields.io/github/repo-size/stefmolin/pandas-workshop?logo=git&logoColor=white) [![View slides in browser](https://img.shields.io/badge/view-slides-orange?logo=reveal.js&logoColor=white)](https://stefmolin.github.io/pandas-workshop/slides/html/workshop.slides.html#/)
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Working with data can be challenging: it often doesn’t come in the best format for analysis, and understanding it well enough to extract insights requires both time and the skills to filter, aggregate, reshape, and visualize it. This session will equip you with the knowledge you need to effectively use pandas – a powerful library for data analysis in Python – to make this process easier.
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@@ -31,7 +31,7 @@ You should have basic knowledge of Python and be comfortable working in Jupyter
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## Setup Instructions
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0. Install Python >= version 3.8.0 and <= version 3.10.2 OR install [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html). Note that Anaconda/Miniconda is recommended if you are working on a Windows machine and are not very comfortable with the command line. Alternatively, you can use [this](https://mybinder.org/v2/gh/stefmolin/pandas-workshop/main?urlpath=lab) Binder environment if you don't want to install anything on your machine.
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0. Install Python >= version 3.8.0 and < version 3.11 OR install [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html). Note that Anaconda/Miniconda is recommended if you are working on a Windows machine and are not very comfortable with the command line. Alternatively, you can use [this](https://mybinder.org/v2/gh/stefmolin/pandas-workshop/main?urlpath=lab) Binder environment if you don't want to install anything on your machine.
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1. Fork this repository:
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![location of fork button in GitHub](./images/fork_button.png)

‎environment.yml

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@@ -2,8 +2,8 @@ name: pandas_workshop
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channels:
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- conda-forge
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dependencies:
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- python=3.10.2
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- jupyterlab=3.3.0
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- python>=3.8.0,<=3.10.15
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- jupyterlab=3.5.2
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- matplotlib=3.5.1
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- numpy=1.22.3
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- pandas=1.4.1

‎images/env_check.png

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‎images/open_env_check_notebook.png

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‎notebooks/0-check_your_env.ipynb

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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Using Python in /Users/stefanie/miniconda3/envs/pandas_workshop:\n",
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"\u001b[42m[ OK ]\u001b[0m Python is version 3.10.2 | packaged by conda-forge | (main, Mar 8 2022, 15:57:32) [Clang 11.1.0 ]\n",
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"\n",
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"\u001b[42m[ OK ]\u001b[0m Python\n",
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"\u001b[42m[ OK ]\u001b[0m jupyterlab\n",
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"\u001b[42m[ OK ]\u001b[0m matplotlib\n",
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"\u001b[42m[ OK ]\u001b[0m numpy\n",
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}
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],
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"source": [
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"from utils import run_env_check\n",
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"from check_env import run_env_check\n",
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"run_env_check()"
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]
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.2"
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"version": "3.10.8"
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}
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},
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"nbformat": 4,

‎notebooks/check_env.py

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"""Check the setup for the workshop."""
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from functools import partial
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from packaging.version import Version
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import importlib
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import json
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import os
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import sys
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import yaml
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def _print_version_ok(item):
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"""
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Print an OK message for version check.
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Parameters
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----------
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item : str
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The item being inspected (package, tool, etc.).
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"""
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print('\x1b[42m[ OK ]\x1b[0m', '%s' % item)
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def _print_version_failure(item, req_version, version, failures):
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"""
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Print a failure message for version check.
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Parameters
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----------
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item : str
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The item being inspected (package, tool, etc.).
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req_version : str
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The required version.
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version : str
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The version currently installed.
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failures : list
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The list of items currently failing the environment check.
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"""
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failures.append(item)
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if version:
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msg = '%s version %s is required, but %s installed.'
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values = (item, req_version, version)
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else:
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msg = '%s is not installed.'
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values = item
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print('\x1b[41m[FAIL]\x1b[0m', msg % values)
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def run_env_check(raise_exc=False):
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"""
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Check that the packages we need are installed and, if necessary,
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whether the Python version is correct.
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Parameters
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----------
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raise_exc : bool, default ``False``
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Whether to raise an `Exception` if any of the packages doesn't
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match the requirements (used for GitHub Action).
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"""
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failures = []
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_print_failure = partial(_print_version_failure, failures=failures)
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# read in the environment file and process versions
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with open('../environment.yml', 'r') as file:
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env = yaml.safe_load(file)
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requirements = {}
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for line in env['dependencies']:
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try:
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if '>=' in line:
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pkg, versions = line.split('>=')
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if ',<=' in versions:
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version = versions.split(',<=')
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else:
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version = [versions, None]
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else:
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pkg, version = line.split('=')
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except ValueError:
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pkg, version = line, None
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if '-' in pkg:
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continue
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requirements[pkg.split('::')[-1]] = version
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# check the python version, if provided
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try:
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required_version = requirements.pop('python')
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python_version = sys.version_info
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base_python_version = Version(
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f'{python_version.major}.{python_version.minor}.{python_version.micro}'
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)
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if isinstance(required_version, list):
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min_version, max_version = (
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Version(version_str) for version_str in required_version
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)
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if (
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min_version > base_python_version
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or (
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max_version and base_python_version > max_version
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)
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):
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print(f'Using Python at {sys.prefix}:\n-> {sys.version}')
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_print_failure(
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'Python',
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f'>= {min_version}{f" and <= {max_version}" if max_version else ""}',
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base_python_version
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)
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else:
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_print_version_ok('Python')
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else:
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for component, value in zip(
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['major', 'minor', 'micro'], required_version.split('.')
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):
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if getattr(python_version, component) != int(value):
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print(f'Using Python at {sys.prefix}:\n-> {sys.version}')
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_print_failure(
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'Python',
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required_version,
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f'{python_version.major}.{python_version.minor}'
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)
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break
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else:
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_print_version_ok('Python')
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except KeyError:
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pass
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for pkg, req_version in requirements.items():
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try:
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mod = importlib.import_module(pkg)
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if req_version:
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version = mod.__version__
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installed_version = Version(version).base_version
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if isinstance(req_version, list):
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min_version, max_version = req_version
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if (
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installed_version < Version(min_version).base_version
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or (
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max_version and
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installed_version > Version(max_version).base_version
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)
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):
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_print_failure(
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pkg,
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f'>= {min_version}{f" and <= {max_version}" if max_version else ""}',
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version
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)
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continue
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elif Version(version).base_version != Version(req_version).base_version:
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_print_failure(pkg, req_version, version)
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continue
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_print_version_ok(pkg)
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except ImportError:
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_print_failure(pkg, req_version, None)
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if failures and raise_exc:
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raise Exception(
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'Environment failed inspection due to incorrect versions '
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f'of {len(failures)} item(s): {", ".join(failures)}.'
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)
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if __name__ == '__main__':
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print(f'Using Python at {sys.prefix}:\n-> {sys.version}')
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run_env_check(raise_exc=True)

‎notebooks/utils.py

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This file was deleted.

‎requirements.txt

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jupyterlab==3.3.0
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jupyterlab==3.5.2
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matplotlib==3.5.1
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numpy==1.22.3
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pandas==1.4.1

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