I have two environments within Anaconda, and I would like to remove one, but preserve the various modules installed in each.
One is base (root), and the other is Miniconda3, in which I've installed the plotly module. This was not intentional. I am not planning to need multiple environments in the foreseeable future.
Some Jupyter notebooks only run after switching to the Miniconda3 environment (otherwise the error of not finding the plotly module in the base (root) environment)
Another acceptable solution might be to set the Miniconda3 environment to default.
Another acceptable solution - install modules into the base environment.
You could try using conda-merge. According to the developer, it preserves dependencies between environments.
Install it from this command: conda install -c conda-forge conda-merge
Then use the following command to merge the environments:
conda-merge FILE1 FILE2 ... FILE-N > OUTPUT-FILE
Related
I downloaded Anaconda and started using it on my Mac but now I am switching laptops. I will be using a Windows laptop now and I need to transfer my environments to my new laptop. How best can I do this?
I am using Python version 3.8 and was using Jupyter notebooks to run my code. But if I simply try to run the notebook on my Windows laptop I am getting one error after another (because I don't have the packages installed). Installing them one by one will take time and I don't even remember most of what I installed.
If you are working across platforms (osx-64 -> win-64) you'll need to be minimal about what packages you export from the existing environment. While Conda does have a recommended intra-platform procedure for exactly recreating environments, it does not directly translate to the cross-platform situation. Instead, try using:
conda env export --from-history > environment.yml
and then, on the new computer,
conda env create -f environment.yml
This will only export the packages that you have explicitly specified to be in the environment at some point (e.g., using conda install foo). Dependencies will be resolved automatically on the new system. This does not guarantee there still won't be packages that aren't available on Windows, but they should be less frequent and easier to resolve manually (typically by removing them from the YAML or adjusting versions).
I downloaded Anaconda and started using it on my Mac but now I am switching laptops. I will be using a Windows laptop now and I need to transfer my environments to my new laptop. How best can I do this?
I am using Python version 3.8 and was using Jupyter notebooks to run my code. But if I simply try to run the notebook on my Windows laptop I am getting one error after another (because I don't have the packages installed). Installing them one by one will take time and I don't even remember most of what I installed.
If you are working across platforms (osx-64 -> win-64) you'll need to be minimal about what packages you export from the existing environment. While Conda does have a recommended intra-platform procedure for exactly recreating environments, it does not directly translate to the cross-platform situation. Instead, try using:
conda env export --from-history > environment.yml
and then, on the new computer,
conda env create -f environment.yml
This will only export the packages that you have explicitly specified to be in the environment at some point (e.g., using conda install foo). Dependencies will be resolved automatically on the new system. This does not guarantee there still won't be packages that aren't available on Windows, but they should be less frequent and easier to resolve manually (typically by removing them from the YAML or adjusting versions).
I mainly use Jupyter Notebooks/Lab through Anaconda and typically install needed packages using pip. However, I've recently started using PyCharm and have been unable to access these packages despite using a Conda environment as my project interpreter and instead have to individually reinstall each of the packages through PyCharm.
These are my settings when creating a new project in PyCharm:
New environment using Conda
Location: C:\Users\Name\anaconda3\envs\untitled
Python Version: 3.8
Conda executable: C:\Users\Name\anaconda3\Scripts\conda.exe
I've also added the following three paths to my environment variables:
...\anaconda3\Scripts
...\anaconda3
...\anaconda3\Library\bin
Is there a way for me to access the Anaconda packages without reinstalling them for PyCharm? Thank you.
If you haven't checked it out already, Anaconda has some good documentation on how to use PyCharm with an Anaconda environment that you can check out here.
You will probably want to use an Existing Environment rather than create a new one and will have to make sure you point your Conda path to the existing executable (C:\Users\Name\anaconda3\Scripts\conda.exe). You should then be able to select the existing environments you have setup in the Interpreter drop down.
I want to start using Anaconda the correct way, by making a new environment for each project instead of always using base. I completely reinstalled Anaconda. As far as making my first environment, do I need to specify every module that I want or are the basic ones that come with python (like OS and MATH) included?
The standard library should be included with all python installs (which also applies to conda environments when you specify python or a python version). Here you can find what is included in the standard library.
Creating a new environment in conda the following way:
conda create --name <name> python=3.x.y
or
conda create --name <name> python
will install python in your environment.
You can reference this nice cheatsheet for more conda commands.
I am going through the painful process of learning how to manage packages/ different (virtual) environments in Python/Anaconda. I was told that Anaconda is basically a python installation with all the packages I need (e.g. numpy, scipy, sci-kit learn etc).
However, when I create a new environment, none of these packages is readily available. I cannot import them when using PyCharm with the newly created environment. When I check the Pycharm project interpreter, or the anaconda navigator environments tab, It seems that indeed none of these packages are installed in my new environments. Why is this? It doesn't make sense to me to provide all these packages, but then not make them ready for use when creating new environments. Do I have to install all these packages manually in new env's or am I missing something?
Kindest regards, and thanks in advance.
The reason the default python environment doesn't come with numpy is because maybe you don't want numpy in the environment. Imagine writing an API (or general software package) where your users may or may not have access to numpy. You might want to run tests to make sure your software fails gracefully or has a pure python fallback if numpy is not installed on your user's machine. Conda environments provide this (insanely useful) benefit. Of course, the package in question doesn't have to be numpy. There are some more esoteric packages where this type of testing is useful.
Furthermore, you can create a conda environment with numpy pre-installed, or any other package you want pre-installed (just add them to the end of the conda create command):
conda create --name my-env-name numpy
Anaconda comes with available packages such as numpy, scipy, and sci-kit learn, but if you want to use them within your environment, you must:
1) Create the environment:
conda create --name new_env
2) Activate the environment:
source activate new_env
3) Install the desired package using conda install
conda install numpy
If you'd like to create a new environment that includes installations of all available Anaconda packages, see create anaconda python environment with all packages. You can include anaconda in the list of packages to install in the environment, which is a 'meta-package' meaning 'all the packages that come with the Anaconda installation'.
I don't know about "conda" environments but in general virtual environments are used to provide you a "unique" environment. This might include different packages, different environment variables etc.
The whole point of making a new virtual environment is to have a separate place where you can install all the binaries ( and other resources ) required for your project. If you have some pre-installed binaries in the environment, doesn't it defeat the purpose of creating one in the first place?
The fact that you can create multiple environments helps you to separate binaries that might be needed by one and not by the other.
For instance, if you are creating a project which requires numpy:1.1 but you have numpy:2.1 installed , then you have to change it. So basically, by not installing any other packages, they are not making assumptions about your project's requirements.
You can check the packages you have in your environment with the command:
conda list
If packages are not listed you just have to add it, with the command:
conda install numpy