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Share environments

Python (using Conda)​

You may share environments by referencing them in your scripts. Conda environment will be re-used by many users, which is more space- and time-efficient.

To achieve it, do the following steps:

  1. Create one package to contain global environments (say, GlobalEnvs).
  2. Create an environment to share inside of this package (let it be GlobalEnvDataAnalysis).
  3. Publish GlobalEnvs package with --release option to the platform.
  4. Share it with the specific group of users you want to have access to these environments.
  5. Environment will be available as GlobalEnvs:GlobalEnvDataAnalysis

Conda and Pip custom repositories​

By default, Conda uses Conda-forge and PyPI repositories to install packages. You may specify your own package repositories in the environment specification.

For example, to use http://my-repo/custom/ as Conda repository and https://mirrors.sustech.edu.cn/pypi/simple as PIP repository use the following code:

#environment: channels: [http://my-repo/custom/], dependencies: [python=3.8, glom, {pip: [--index-url https://mirrors.sustech.edu.cn/pypi/simple, requests]}]

Common issues with Conda environments​

There is a known issue of Conda that sometimes it takes a long time to resolve dependencies. Datagrok will interrupt Conda environment creation if it takes more than 5 minutes.

If you encounter a timing problem, try to find an equivalent set of packages from PIP repositories.

R (using Renv)​

Datagrok supports Renv environments. Each R script has a temporary folder with a unique name. This folder becomes an Renv project folder for the current run of the script.

Start using Renv by initializing it and installing packages (see a full example):

#language: r

renv::init()
renv::install("hunspell@3.0.1")

Renv session only impacts the R environment for this one single run. No other R scripts are aware of this local script environment.

Renv uses a global package cache. It caches a package requested once with renv::install and re-uses it whenever it is requested.

In case the latest package version is requested, such as in renv::install("hunspell"), Renv connects to remote R package repositories assuring if the cached package needs to be updated to the newer version. This may introduce a significant delay in the script run, several seconds in practice. To avoid this, we recommend installing a specific version of the package, such as in renv::install("hunspell@3.0.1").

Automatic deactivation

At the R script's start and finish, Datagrok calls renv::deactivate() to assure the script's body isolation. You don't have to call renv::deactivate() manually.