- Mac visual studio python how to#
- Mac visual studio python install#
- Mac visual studio python software#
- Mac visual studio python code#
Before publishing packages to PyPI, it is typical to “test drive” their publication on TestPyPI, which is a test version of PyPI. In this book we’ll be publishing a package to PyPI.
Mac visual studio python software#
A software repository is a storage location for downloadable software, like Python packages. The Python Package Index (PyPI) is the official online software repository for Python.
Mac visual studio python install#
$ conda install -c conda-forge cookiecutter Once you’ve installed the Miniconda distribution, ensure that Python and conda are up to date by running the following command at the command line: While alternative package and environment managers exist, we choose to use conda in this book because of its popularity, ease-of-use, and ability to handle any software stack (not just Python). You can read more about virtual environments in the conda documentation.
Virtual environments help you compartmentalize and isolate the packages you are using for different projects to avoid this issue.
Mac visual studio python code#
Installing all the packages you need in the same place (i.e., the system default location) can be problematic because different packages often depend on different versions of the same dependencies as you install more packages, you’ll inevitably get conflicts between dependencies, and your code will start to break. An environment manager helps you create “virtual environments” on your machine, where you can safely install different packages and their dependencies in an isolated location.
It is also an environment manager, which is the key function we’ll be using it for in this book. The difference between Anaconda and Miniconda is that Anaconda installs over 250 additional packages (many of which you might never use), while Miniconda is a much smaller distribution that comes bundled with just a few key packages you can then install additional packages as you need them using the command conda install.Ĭonda is a piece of software that supports the process of installing and updating software (like Python packages). If you are unfamiliar with Miniconda and Anaconda, they are distributions of Python that also include the conda package and environment manager, and a number of other useful packages. If you have previously installed the Anaconda or Miniconda distribution feel free to skip to Section 2.2.2. Miniconda is a lightweight version of the popular Anaconda distribution. We recommend installing the latest version of Python via the Miniconda distribution by following the instructions in the Miniconda documentation. The Docker approach is recommended for anyone that runs into issues installing or using any of the software below on their specific operating system, or anyone who would simply prefer to use Docker - if that’s you, skip to Section 2.3 for now, and we’ll describe the Docker setup later in Section 2.6. However, we also support an alternative setup with Docker that has everything you need already installed to get started.
Mac visual studio python how to#
Section 2.2.1 and Section 2.2.2 describe how to install the software you’ll need to develop a Python package and follow along with the text and examples in this book. We’ll assume Mac and Linux users are using the “Terminal” and Windows users are using the “Anaconda Prompt” (which we’ll install in the next section) as a CLI. We’ll be using a CLI for various tasks throughout this book. The command-line interface #Ī command-line interface (CLI) is a text-based interface used to interact with your computer. If you intend to follow along with the code presented in this book, we recommend you follow these setup instructions so that you will run into fewer technical issues.
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