Conda Environment Cheat Sheet

Posted : admin On 1/29/2022

See the conda cheat sheet PDF (1 MB) for a single-page summary of the most important information about using conda. ANACONDA CHEAT SHEET. Get your conda cheat sheet. Environment combines code execution, rich text, mathematics, plots and rich media 10. Python Virtual environment Cheat sheet. Leave a Comment / PainPoint / By Anindya Naskar. What is virtual environment? Virtual environment is a space or tool which helps to keep libraries or packages for different projects separate by creating virtual environments. $ conda create -n ENVNAME python=3.6.3 anaconda.

Deploying conda environments inside a container looks like a straight-forward conda install. But with a bit more love for details, you can optimise the process so that the build is faster and the resulting container much smaller.

This post intends to be an addition to a Jim Crist-Harif’s “Smaller Docker images with Conda” and a condensed version of the long-read I’ve published at the same time as this post. If you want to understand the reasoning of the tips here, you should head over to the long-read. Otherwise, I hope that this post serves as a cheatsheet to lookup every time you want to put a conda environment inside a (Docker) container.

The dependencies of your to-be-containerised environment should be specified as you typically specify a conda environment using an environment.yml file. An example looks like:

While this is a nice human-readable file, it doesn’t provide you with reproducibility across runs. Thus we pin the requirements down to the actual build of each package using conda-lock. This has the advantage that with the given lockfile, you can recreate the exact environment every time. Also, the lockfiles switch conda into a special mode where it only installs packages but doesn’t do a new solving step. This dramatically improves installation time.

Conda Environment Cheat Sheet

To generate a lock file from an environment.yml you can use the following command:

And install it using:

As the base of your images, you should pick one the following three containers that come with a basic / minimal conda installation. In the case of using one of the conda-forge provided images, we always pick the ones that come with mamba included as this speeds up the installation dramatically.

  • continuumio/miniconda3: Debian Buster with a minimal conda installation configured for the Anaconda defaults channel (continuumio/miniconda3:4.9.2 is 437MB in uncompressed size)
  • conda-forge/mambaforge3: Ubuntu 20.04 with a minimal conda and mamba installation configured with conda-forge as the default package source (conda-forge/mambaforge:4.9.2-5 is 411MB in uncompressed size)
  • conda-forge/mambaforge-pypy3: Ubuntu 20.04 with a minimal conda and mamba installation configured with conda-forge as the default package source and using PyPy instead of CPython (conda-forge/mambaforge-pypy3:4.9.2-5 is 449MB in uncompressed size)

If you do not plan to use your container interactively but only want to package a service inside of it, you should use multi-stage builds. In the first stage, you should take one of the above containers and build the conda environment in it. As the second stage, you should pick the most minimal container that is required to run the conda environment namely gcr.io/distroless/base-debian10. This container only contains the bare essential like a libc but no shell or package manager at all.

A Dockerfile for this multi-stage approach looks like the following:

This picks up the ideas of Jim’s post. While conda environments come with all batteries included, batteries weigh quite a bit and you don’t need all of them at runtime. Thus you should get rid of those that you know that you will not need.

  • Delete the conda metadata in conda-meta
  • Delete C/C++ includes in include (only required at compile-time)
  • Delete libpython*.so.*; this only works in the case where your entrypoint is calling the python executable which is statically linked, i.e. contains the same symbols as libpython.so. This wouldn’t work if we had an application that would embed the Python interpreter itself.
  • Delete __pycache__ with find -name '__pycache__' -type d -exec rm -rf '{}' '+'
  • Delete pip with rm -rf /env/lib/python3.9/site-packages/pip as we don’t plan to install any packages
  • Delete lib/python3.9/i{dlelib, ensurepip} from the standard library
  • Delete lib{a,t,l,u}san.so as the various sanitizers are not used during production
  • Delete the binaries like x86_64-conda-linux-gnu-ld, sqlite3, openssl from bin. In most cases, these binaries are not used for running a service
  • Delete share/terminfo as we don’t expect to run a terminal

The above tips boil down to the following statement. Be aware though that not every file listed here can be safely removed in all cases.

Title picture: Photo by Jonas Smith on Unsplash

Conda create environment python 3

Building a Python 3 Conda Environment, Command line package and environment manager. Learn to use Create a new environment named py35, install Python 3.5 'numpy=1.11.1 1.11.3'. 1.11.1 conda create -n mypython3 python=3. To activate the environment: source activate mypython3. To get all the goodies (e.g. Jupyter Notebook, NumPy, matplotlib ) you can install Anaconda, which will auto-magically use Python 3. conda install anaconda. and then our additional install, netcdf4-python.

Managing environments, 3 MINUTES. Managing environments. Create environments and move easily between them. 5 MINUTES. Managing Python. Create an environment that has a​ Check conda is installed and in your PATH. Open a terminal client. Enter conda -V into the terminal command line and press enter. If conda is installed you should see somehting like the following.

[PDF] CONDA CHEAT SHEET, 1. Check conda is installed and in your PATH · 2. Check conda is up to date · 3. Create a virtual environment for your project · 4. Activate your To quickly create an environment using conda, you can type in the command: conda create --name your_env_name python=3.7 -y In this command, the ‘ python=3.7 ’ portion specifies which version of python I want to set up the environment in; you can change the version to whatever suits your needs.

Conda base environment

Create a conda environment to isolate any changes pip makes. Environments take up little space thanks to hard links. Care should be taken to avoid running pip in the root environment. Recreate the environment if changes are needed. Once pip has been used, conda will be unaware of the changes.

To use R in an environment, all you need to do is install the r-base package. (conda-env) % conda install r-base. Of course, you can always do this when first creating an environment. % conda create -n r-env r-base ⚠️ Note: Replace “r-env” with the name of your environment.

On installation, conda creates a base environment. However, you can also create your own base environment with packages you frequently use. The - -clone option will create a clone (or snapshot) of the environment, <span>conda create --name snapshot --clone myenv</span>

Conda rename environment

How can I rename a conda environment?, You can't. One workaround is to create clone environment, and then remove original one: (remember about deactivating current environment But I can suggest another solution: rename enviroment folder ( old_name to new_name) open shell and activate env with custom folder: conda.bat activate 'C:UsersUSER_NAMEMiniconda3envs ew_name' now you can use this enviroment, but it's not on the enviroment list. Updateinstallremove any

How to rename a conda environment (workaround) · GitHub, How to rename a conda environment (workaround). GitHub Gist: instantly share code, notes, and snippets. The environment list is: In this tutorial, we will rename py3 to py 3.5. Rename py3 to py3.5. Anaconda does not provide conda rename command, we can copy and delete old one to implement it. Copy py3 to py3.5. conda create --name py3.5 --clone py3

request: conda 'rename' (or conda 'move') for changing name of an , All is in the title :) Today I wanted to rename my historic 'dev' environment to '​devel'. This did the trick: conda create --name devel --clone dev Change Python conda environment old to new by cloning the environment and deleting the original environment, as follows. conda create --name new --clone old conda remove --name old --all Conda environment maintenance

Conda cheat sheet

CONDA CHEAT SHEET Command line package and environment manager Learn to use conda in 30 minutes at bit.ly/trycondaTIP:Anaconda Navigator is a graphical interface to use conda. Double-click the Navigator icon on your desktop or in a Terminal or at the Anaconda prompt, type anaconda-navigator CONTINUED ON BACK →

Cheat sheet¶. See the conda cheat sheet PDF (1 MB) for a single-page summary of the most important information about using conda.

EXAMPLE: conda create --help CONDA 4.6 CHEAT SHEET. conda search PKGNAME --info conda clean --all conda uninstall PKGNAME --name ENVNAME conda update --all --name ENVNAME

Cheat

Conda activate

conda activate: The logic and mechanisms underlying environment activation have been reworked. With conda 4.4, conda activate and conda deactivate are now the preferred commands for activating and deactivating environments. You’ll find they are much more snappy than the source activate and source deactivate commands from previous conda versions.

Conda is a powerful package manager and environment manager that you use with command line commands at the Anaconda Prompt for Windows, or in a terminal window for macOS or Linux. This 20-minute guide to getting started with conda lets you try out the major features of conda.

Activating an environment ¶ Conda init ¶. Earlier versions of conda introduced scripts to make activation behavior uniform across operating systems. Nested activation ¶. By default, conda activate will deactivate the current environment before activating the new Environment variable for DLL

List python environments

Python on Microsoft® Azure, Build Better Web Apps Faster in the Azure Cloud w/ a Managed Platform Optimized for Python pip list will display all of the packages installed in the virtual environment: ( tutorial-env ) $ pip list novas ( 3 .1.1.3 ) numpy ( 1 .9.2 ) pip ( 7 .0.3 ) requests ( 2 .7.0 ) setuptools ( 16 .0 )

Managing environments, Using environments. Create a new environment named py35, install Python 3.5. Activate the new environment to use it. Get a list of all my environments, active. The Python: Select Interpreter command displays a list of available global environments, conda environments, and virtual environments. (See the Where the extension looks for environments section for details, including the distinctions between these types of environments.)

[PDF] CONDA CHEAT SHEET, This tutorial walks you through installing and using Python packages. lsvirtualenv: List all of the environments. cdvirtualenv: Navigate into the directory of the Environments¶ Below is the list of Deep Learning environments supported by FloydHub. Any of these can be specified in the floyd run command using the --env option. If no --env is provided, it uses the tensorflow-1.9 image by default, which comes with Python 3.6, Keras 2.2.0 and TensorFlow 1.9.0 pre-installed.

Clone python environment

How To: Clone a Python environment with the Python Command , First of all this is a Python/Anaconda question and should probably be asked in a different stack exchange subsite. As for the question itself - you can export your Procedure Run the Python Command Prompt as an administrator. Click the Start icon. Navigate to the ArcGIS folder. Right-click Click the Start icon. Navigate to the ArcGIS folder. Right-click Python Command Prompt > More > Open file location. Right-click Python Command Prompt and click Run as

Conda Environment Cheat Sheet

Managing environments, it can also change /usr/bin/env python shebangs to be absolute too, though this functionality is not exposed at present. checks sys.path of the cloned virtualenv Cloning an environment: From an existing environment: $ conda create --name ORIG_ENV_NAME --clone CLONE_ENV_NAME. From an exported environment file on the same machine: $ conda create --name ENV_NAME —-file FILE_NAME.yml. From an exported environment file on a different machine: $ conda env export > ENV_NAME.yml $ conda env create -f ENV_NAME.yml```

How to clone Python working environment on another machine , Create an environment. To create a clone of the default arcgispro-py3 environment, on the Manage Environments dialog box, click the Clone Default I have an existing Python django Project running in Web Server. Now the client needs to make some changes in the existing code. So I need to set it up in my Local Machine. All the packages needed for this project is installed in a Virtual environment. How can I copy or clone this virtual environment to my Local machine to run this Project.

Conda environment variables

Managing environments, Conda-build sets the CONDA_BUILD_STATE environment variable during each of these phases. The possible values are: RENDER---Set during evaluation of the There are times when you may want to process a single file in different ways at more than 1 step in the render-build-test flow of conda-build. Conda-build sets the CONDA_BUILD_STATE environment variable during each of these phases. The possible values are: RENDER---Set during evaluation of the meta.yaml file.

Environment variables, Use the files $CONDA_PREFIX/etc/conda/activate.d and $CONDA_PREFIX/etc/​conda/deactivate.d , where $CONDA_PREFIX is the path to the What is the environment variable? Environment variables basically define the behavior of the environment. They can affect the processes ongoing or the programs that are executed in the environment. The region from which this variable can be accessed or over which it is defined is termed as the scope of the variable. Steps for setting up the environment variable:

Conda Create Environment Cheat Sheet

How to set specific environment variables when activating conda , PATH includes the binary directory from the current conda environment. These variables always exist and can always be used in your Python code. Using To set environment variables, run conda env config vars set my_var=value. Once you have set an environment variable, you have to reactivate your environment: conda activate test-env. To check if the environment variable has been set, run echo my_var or conda env config vars list.

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