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Asked: 2024-09-26T21:03:17+05:30 In:

What are the steps to install Python using conda?

I’ve been trying to get Python set up on my computer using conda, and honestly, I’m a bit lost. I’ve heard that using conda can make life a whole lot easier, especially when managing different environments, but I’m not sure of the exact steps to get everything rolling.

First off, I’m assuming that I need to have Anaconda or Miniconda installed on my system before I can start installing Python, right? I’ve heard about Anaconda being the full package, but Miniconda sounds lightweight, which might be all I need. What’s the right way to go here? Should I just download Miniconda for a quick start?

Once that’s sorted, what’s next? Like, after I download and install it, do I need to open up the Anaconda Navigator, or can I just dive into the command line? I feel more comfortable using the terminal, but I’m not sure if the commands I should use are different between the two options. Any tips on this?

So, say I’m in the terminal and I want to create a new Python environment—what’s the command I need? I think I’ll want Python 3.9 or something, but how do I specify that? Also, once I create the environment, how do I actually activate it? I keep hearing mixed signals about using `activate` or `conda activate`.

After I’m in the right environment, how exactly do I install Python? Is there a specific command to do this, or can I just let conda handle it? I’ve seen some people mention creating a `requirements.txt` file for packages—do I need to worry about that now, or is it more of a later step?

And one more thing—once Python is installed, how can I check that it’s all set up correctly? Do I run some command to see the version or something like that?

I know this sounds like a lot, but I’m really eager to get started and just need a bit of guidance. Would love to hear from anyone who has gone through this process! Thanks!

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    2 Answers

    1. Getting Started with Python and Conda

      Totally get where you’re coming from! Setting up Python with conda can feel overwhelming at first, but once you have it down, it really simplifies things. You’re right that you need either Anaconda or Miniconda installed first.

      Anaconda vs Miniconda

      So, Anaconda comes with a lot of pre-installed packages and tools, which is great if you’re going to be working with data science libraries right away. But if you’re just starting out and want something lightweight, Miniconda is the way to go! You can always install additional packages later. Just grab Miniconda for a quick start.

      Next Steps After Installation

      Once you’ve downloaded and installed Miniconda, you can skip the Anaconda Navigator if you’re comfortable in the terminal—that’s a solid choice. The commands you use in the command line will be the same regardless of whether you use the GUI or not, which is a bonus!

      Creating a New Environment

      Now, to create a new Python environment, you can use the terminal and run:

      conda create --name myenv python=3.9

      Just replace myenv with whatever name you want for your environment. Once that’s done, activate it using:

      conda activate myenv

      And yeah, conda activate is the way to go! The earlier activate commands are from older versions of conda.

      Installing Python and Packages

      If you specified Python when you created the environment, it’s already installed. If you need to install more packages, you can do that with:

      conda install package_name

      About that requirements.txt file: it’s cool for managing dependencies later when you have a project in mind. For now, focus on getting your environment set up!

      Checking Your Setup

      Once you have Python installed, you can check if everything is working by running:

      python --version

      This will display your installed Python version. If you see the version you wanted, you’re all set!

      This might feel like a lot, but just take it step-by-step. You’re on the right track, and you’ll have everything set up in no time!

    2. Indeed, the first step in your Python setup journey using conda is to have either Anaconda or Miniconda installed on your system. Anaconda is the full distribution that includes a vast array of pre-installed packages, which can be incredibly beneficial if you plan on using data science libraries or need a lot of different environments. On the other hand, Miniconda is a more lightweight option, providing just the conda package manager and its dependencies. If disk space or installation time is a concern, Miniconda is a solid choice that allows you to install only the packages you need later on. To get started, simply download and install Miniconda from the official website. Once that’s done, you can begin using the command line for your conda operations, which many developers find to be more efficient than the graphical interface of Anaconda Navigator.

      After you’ve successfully installed Miniconda, you can open your terminal and create a new Python environment with the command conda create --name myenv python=3.9, where “myenv” is the name you choose for your environment. To activate this environment, you’ll use conda activate myenv. Once your environment is activated, Python will be available within it, and you don’t need to install it again explicitly; conda will handle it as part of the environment creation. For managing packages, you can install them using conda install package-name, or you can later create a `requirements.txt` file if you’re handling complex dependencies. To verify your installation, you can check the installed Python version by running python --version, which will confirm that everything is set up correctly. With these steps, you should be well on your way to utilizing Python in your projects!

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