Deploying cross-language in high impact projects

The materials here support a talk at the Spatial Data Science across Languages (SDSL) conference 2024.

See the slides here and in the dropdown menu above.

The quickest way to reproduce the code is probably with GitHub codespaces or Codeanywhere, by opening the following link.

See the source code at github.com/robinlovelace.

See the README for more information.

Based on https://robinlovelace.github.io/reproducible-slides-repo-template/slides

To create your own “reproducible slides repo” follow the instructions in the link above, starting by cloning this repo or creating a template from this one:

gh repo clone robinlovelace/cross_language_projects
code cross_language_projects

Or go to /~https://github.com/Robinlovelace/reproducible-slides-repo-template and click “Use this template”.

Setup

To setup the repo the following commands were used

gh repo create # create the repo on github

# Take snapshot with renv:
renv::snapshot()

Load the renv with this (also in .Rprofile):

source("renv/activate.R")

- The project is out-of-sync -- use `renv::status()` for details.

# make renv pick-up rmarkdown dep:
library(rmarkdown)
library(knitr)

Install Python packages with:

# reticulate::install_python()
reticulate::py_install("geopandas")

Using virtual environment '/home/robin/.virtualenvs/r-reticulate' ...

+ /home/robin/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user geopandas

reticulate::py_install("matplotlib")

Using virtual environment '/home/robin/.virtualenvs/r-reticulate' ...

+ /home/robin/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user matplotlib