# Numpy-Tutorial-SciPyConf-2022 **Repository Path**: mirrors_enthought/Numpy-Tutorial-SciPyConf-2022 ## Basic Information - **Project Name**: Numpy-Tutorial-SciPyConf-2022 - **Description**: Public GitHub repo for SciPy 2022 tutorial (Introduction to Numerical Computing With NumPy) - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2022-04-06 - **Last Updated**: 2026-01-03 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # SciPy 2022 Tutorial: Introduction to Numerical Computing With NumPy #### Presented by: Logan Thomas, [Enthought, Inc.](https://www.enthought.com) #### YouTube recording of live tutorial [here](https://youtu.be/bveHFn0G4Zg) This repository contains all the material needed by students registered for the Numpy tutorial of [SciPy 2022](https://www.scipy2022.scipy.org/) on Monday, July 11th 2022. For a smooth experience, you will need to make sure that you install or update your Python distribution and download the tutorial material _before_ the day of the tutorial. ## Running the Exercises the (recommended) Easy Way Run with Binder by clicking this icon: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/enthought/Numpy-Tutorial-SciPyConf-2022/main) ## Running the Exercise Locally ### Install Python If you don't already have a working python distribution, you may download Anaconda Python ([https://www.anaconda.com/products/individual](https://www.anaconda.com/products/individual)). ### Install Packages To be able to run the examples, demos and exercises, you must have the following packages installed: - `ipython` (for running, experimenting, and doing exercises) - `jupyterlab` (for access to the Jupyter Notebook web-based interactive computing platform) - `matplotlib` - `numpy` - `pillow` - `pyqt` If you are using Anaconda, you can use the Anaconda Prompt (Windows) or Terminal.app (macOS) to create an environment with the necessary packages: 1. Open the Anaconda Prompt or Terminal.app using the below instructions: - **Windows**: Click Start and search for "Anaconda Prompt". Click on the application to launch a new Anaconda Prompt window. - **macOS**: Open Spotlight Search (using Cmd+Space) and type "Terminal.app". Click on the application to launch a new Terminal.app window. 1. Create a new Anaconda virtual environment by executing the below command in the application window you opened in step 1 above. You may be prompted to `Proceed([y]/n)?`. If so, type `y` and press `Enter`. ``` $ conda create -n numpy-tutorial ipython jupyterlab matplotlib numpy pillow pyqt ``` 1. Navigate to the directory where you'd like to store materials for this tutorial and download the materials from this GitHub repository by executing the below command. It will create a new folder named `Numpy-Tutorial-SciPyConf-2022/` with all the content you will need. ``` $ git clone git@github.com:enthought/Numpy-Tutorial-SciPyConf-2022.git ``` **NOTE**: If you are not familiar with Git, you can download a zipped archive of the material by clicking on this link: https://github.com/enthought/Numpy-Tutorial-SciPyConf-2022/archive/main.zip. Then, unpack the zipped archive into a directoy named `Numpy-Tutorial-SciPyConf-2022`. You may have to rename the unpacked directory to explicitly be `Numpy-Tutorial-SciPyConf-2022`. 1. To test your installation, please execute the `check_env.py` script in the python virtual environment where you have installed the requirements (from step 2 above). If you created an Anaconda environment using the instructions above, you can use the same application window that you opened in step 1, or launch the platform specific application again -- Anaconda Prompt for Windows or Terminal.app for macOS. Be sure to navigate to where you downloaded this GitHub repository and activate your conda environment *before* executing `python check_env.py`: ``` # Example path to course materials (yours may differ) $ cd ~/Desktop/Numpy-Tutorial-SciPyConf-2022/ $ conda activate numpy-tutorial $ python check_env.py ``` You should see a window pop up with a plot that looks vaguely like a smiley face (as shown below). ![](assets/images/check_env_output.png) ## Tutorial Materials This GitHub repository is all that is needed in terms of tutorial content. If you downloaded these materials in step 3 above, there is no need to do so again. If not, the simplest solution is to download the material using this link: https://github.com/enthought/Numpy-Tutorial-SciPyConf-2022/archive/main.zip If you are familiar with Git, you can also clone this repository with: ``` $ git clone https://github.com/enthought/Numpy-Tutorial-SciPyConf-2022.git ``` The above command will create a new folder named `Numpy-Tutorial-SciPyConf-2022/` with all the content you will need: the slides I will go through (`introduction_to_numerical_computing_with_numpy_manual.pdf`), and a folder of exercises. ## Questions? Problems? You may post messages to the `#tutorial-intro-to-numerical-computing-with-numpy` Slack channel for this tutorial at in the official Slack team: [https://scipy2022.slack.com](https://scipy2022.slack.com) . ## Additional Anaconda Resources - [Managing environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) - To create an Anaconda environment from an existing `environment.yml` file: ``` $ conda env create -f environment.yml -n numpy-tutorial ``` - To remove an existing Anaconda environment: ``` $ conda remove --name numpy-tutorial --all ``` - To completely uninstall Anaconda, see the "Uninstalling Anaconda" documentation [here](https://docs.anaconda.com/anaconda/install/uninstall/). © 2001-2022, Enthought, Inc. All Rights Reserved. Use only permitted under license. Copying, sharing, redistributing or other unauthorized use strictly prohibited. All trademarks and registered trademarks are the property of their respective owners. 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