A containerised platform for Geographic Data Science
BSD-3-CLAUSE License
Published by darribas about 1 year ago
This release incorporates several new backend features that make building faster and more reproducible, in addition to the usual updates of versions and new libraries. In particular:
gds
environment is now built from scratch, rather than added on top of the base environment provided by minimal-notebook
. This makes resolving the versions a lot faster and does not create conflicts with some libraries as in the past.gds
environment is automatically turned on in the container, so the user should see no difference with the past model in accessing geo librariesgds
environment is built from a single .yml
file that includes all downloads (also from pip
), and which can thus be used to recreate the environment in other contexts if necessaryminimal-notebook
is hidden to avoid confusion (though the environment itself is present in the container).Main additions as detailed in #80
@software{gds_env,
author = { { Dani Arribas-Bel } },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {10.0},
date = {2023-10-24},
}
Published by darribas over 1 year ago
Minor point release that only includes as addition files to build explicit conda environments in the three previously supported platforms (linux/macOS intel/windows) and macOS arm (aka Apple silicon) that can run the 1.0 version of the GDS Book. No updates to the platform.
Published by darribas over 1 year ago
Update of the stack:
gds_dev
pygeoda
as it requires a large C++ compiler install) and uploaded manually in 28892d822aac95e7a487ef5bb0166944649b316fpandas
1.XPublished by darribas over 2 years ago
This release provides an update of versions of all core packages, and the following advances:
gds_py_explicit_XXX-latest.txt
, available here) to recreate the exact Python environment in Linux, MacOS, and Windows (all intel-only, for now). These are created following the cloning guidance in conda
, and can be replicated running conda create/install --name myenv --file gds_py_explicit_XXX-latest.txt
gds_py_explicit_XXX-latest.txt
files on each commitPublished by darribas about 3 years ago
Autumn release updating the stack to most recent versions. Most notably:
geopandas
0.10.2 with interactive mapping through gdf.explore()
pysal
2.5XYZservices
to unify basemap providerscontextily
1.2 with XYZservices
backendsfarrow
Full list of version differences is available here (Python) and here (R)
@software{gds_env,
author = { { Dani Arribas-Bel } },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {7.0},
date = {2019-08-06},
}
Published by darribas over 3 years ago
Point release fixing a few regressions introduced in 6.0 and other working issues that cropped up on first use. Upgrade from 6.0
is recommended. Issues and progress was tracked on Milestone 6.1
jupyterbook
is now again part of the base
environment so it can be used in tandem with the rest of the python stackdecktape
is installed from sources and now works as expectedtexbuild
install is updated to point to specific Python version so it works againgeopandas_view
addeddask-geopandas
includedtobler
(ahead of PySAL version)@software{gds_env,
author = { { Dani Arribas-Bel } },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {6.1},
date = {2019-08-06},
}
Published by darribas over 3 years ago
This release updates each stack significantly (see detailed changes), and provides several additional infrastructure innovations:
minimal-notebook
qgrid
and KeplerGL
, at least temporarily while the projects become compatible with JupyterLab 3.0gds_py
and are now included in a separate conda environment (dev
) on gds_dev
. To access them, conda activate dev
inside gds_dev
.gds_py
stackgds_py
is not just over 3.5GB in footprint, down from over 6GB in 5.0
gds_py
are hardcoded so the stack stays stable over timegds_py
pins to versionned environment files@software{gds_env,
author = { { Dani Arribas-Bel } },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {6.0},
date = {2019-08-06},
}
Published by darribas about 4 years ago
This release updates each stack significantly (see detailed changes), and provides several additional infrastructure additions to the project:
gds_py
now includes also libraries installed through pip@software{gds_env,
author = { { Dani Arribas-Bel } },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {5.0},
date = {2019-08-06},
}
Published by darribas over 4 years ago
Point release to include the 1.0 release of contextily
. In addition, the following updates are included too:
cenpy
to gear for 5.0@software{gds_env,
author = {{Dani Arribas-Bel}},
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {4.1},
date = {2019-08-06},
}
Published by darribas over 4 years ago
This version adds a new flavour of the gds_env
containers, gds_dev
, which offloads all dev tools from the other stacks, and adds a few other ones. There are also some changes in the list of libraries included (less non-geo, a few more geo). Important additions/removal followed #25, and a few other issues were also closed (#18, #24).
stack_py.txt
and the detailed changelog is available as a diff
.stack_r.txt
and the detailed changelog is available as a diff
.docker pull darribas/gds_py:4.0
docker pull darribas/gds:4.0
docker pull darribas/gds_dev:4.0
@software{gds_env,
author = {{Dani Arribas-Bel}},
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {4.0},
date = {2020-02-26},
}
Published by darribas about 5 years ago
New features:
gds_py
and gds
images integrated so gds
entirely builds off of gds_py
(#16)rpy2
(#13)Installation:
docker pull darribas/gds:3.0
docker pull darribas/gds_py:3.0
Citation:
@software{hadoop,
author = {{Dani Arribas-Bel}},
title = {\texttt{gds_env}: A containerised platform for Geographic Data Science},
url = {https://github.com/darribas/gds_env},
version = {3.0},
date = {2019-08-06},
}
Published by darribas over 5 years ago
This release brings a few enhancements to the container:
osmnx
, ipyparallel
)start.sh jupyter lab
at the start)gds_py
which contains the same Python stack but no R.You can download it by running:
docker pull darribas/gds:2.0
If you want to access the more lightweight container with only Python:
docker pull darribas/gds_py:2.0