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README

In this folder you'll find all the book's listings.
Note: Each python file follows the book naming convention (meaning listing_3.4.py refers to the listing 3.4 you can find in the chapter 3).

Creating the Python environment

To leverage the resources provided in this repository it's first recommended to create a python virtual environment.

Why Use Virtual Python Environments?

Using a virtual environment is crucial for managing dependencies in Python projects. It helps to:

  • Avoid Conflicts: Different projects may require different versions of the same package. Virtual environments keep dependencies isolated.
  • Ensure Reproducibility: When sharing your project, others can install the same versions of dependencies you used.
  • Maintain a Clean Global Environment: Prevent clutter in your global Python installation by installing packages only in the virtual environment.

Different Ways to Create Virtual Environments

There are several ways to create and manage virtual environments in Python:

  1. Using venv (Native Python): Lightweight and included in Python 3.3 and later.

  2. Using virtualenv: A widely-used external tool, compatible with Python 2 and older versions of Python 3.

  3. Using conda: An environment manager provided by Anaconda. Suitable for managing Python and non-Python dependencies.

  4. Using pipenv: Combines pip and virtualenv for better dependency management.

Step-by-Step Guide: Using the Native Python Way (venv)

Prerequisites

  • Ensure Python 3.3 or later is installed on your system.

Steps

  1. Navigate to Your Project Directory
    Open a terminal and navigate to the folder where your project is located:

    cd /path/to/your/project

  2. Create a Virtual Environment Run the following command to create a virtual environment named env:

    python3 -m venv env

    This will create a directory called env containing the virtual environment files.

  3. Activate the Virtual Environment On Windows:

    .\env\Scripts\activate

    On macOS/Linux:

    source env/bin/activate

    After activation, your terminal prompt will show (env) indicating the virtual environment is active.

    1. Install Dependencies Use the requirements.txt that is available at the root of the repository and install all the needed libraries like this:
    pip install -r requirements.txt

Installing Alteryx

Fortunately, Alteryx offers a free trial version, available for download here. The trial lasts for 30 days, providing ample time to explore its capabilities and evaluate its potential for data preparation and analysis. As of today, the Alteryx trial version installation process is straightforward and user-friendly, allowing us to get up and running quickly.

  1. Download the Installer: Start by visiting the Alteryx Designer Trial page. Fill out the registration form with basic details to access the download link for the trial version.
  2. Run the Installation: Once the installer file is downloaded, we can launch it and follow the guided setup process. The installer will prompt us to accept the license agreement and choose a destination folder for the installation.
  3. Initial Setup and Activation: After the installation completes, open Alteryx Designer. We will be prompted to activate the 30-day trial by signing in with our Alteryx account (created during the download process).
  4. Access Sample Workflows: Upon activation, Alteryx Designer provides access to sample workflows and built-in tutorials to help you get started quickly. These resources are useful for understanding key functionalities like data input, blending, and transformation.

SYSTEM REQUIREMENTS Alteryx Designer requires a Windows operating system, with recommended specifications including at least 8GB of RAM and adequate disk space for processing large datasets. The entire process is designed to take only a few minutes, ensuring you can begin exploring Alteryx’s features right away without needing any advanced technical setup.

Note: the exports provided in this repository have been created with Alteryx v2024.1.1.93 Patch: 3