OpenGHG - a cloud platform for greenhouse gas data analysis
Project description
OpenGHG - a cloud platform for greenhouse gas data analysis and collaboration
OpenGHG is a project based on the prototype HUGS platform which aims to be a platform for collaboration and analysis of greenhouse gas (GHG) data.
The platform will be built on open-source technologies and will allow researchers to collaborate on large datasets by harnessing the power and scalability of the cloud.
For more information please see our documentation.
Cloud
You can login to our OpenGHG Cloud JupyterHub and use OpenGHG in the cloud. This will allow you to use the full power of OpenGHG from your local device. Once you're logged in please checkout some of our tutorials to help you get started.
Install locally
To run OpenGHG locally you'll need Python 3.8 or later on Linux or MacOS, we don't currently support Windows.
You can install OpenGHG using pip
or conda
, though conda
allows the complete functionality to be accessed at once.
Using pip
To use pip
, first create a virtual environment
python -m venv openghg_env
Then activate the environment
source openghg_env/bin/activate
It's best to make sure you have the most up to date versions of the packages that pip
will use behind the scenes when installing OpenGHG.
pip install --upgrade pip wheel setuptools
Then we can install OpenGHG itself
pip install openghg
Each time you use OpenGHG please make sure to activate the environment using the source
step above.
NOTE: Some functionality is not completely accessible when OpenGHG is installed with
pip
. This only affects some map regridding functionality. See the Additional Functionality section below for more information.
Using conda
To get OpenGHG installed using conda
we'll first create a new environment
conda create --name openghg_env
Then activate the environment
conda activate openghg_env
Then install OpenGHG and its dependencies from our conda channel and conda-forge.
conda install --channel conda-forge --channel openghg openghg
Note: the xesmf
library is already incorporated into the conda install from vx.x onwards and so does not need to be installed separately.
Additional functionality
Some optional functionality is available within OpenGHG to allow for multi-dimensional regridding of map data (openghg.tranform
sub-module). This makes use of the xesmf
package. This Python library is built upon underlying FORTRAN and C libraries (ESMF) which cannot be installed directly within a Python virtual environment.
To use this functionality these libraries must be installed separately. One suggestion for how to do this is as follows.
If still within the created virtual environment, exit this using
deactivate
We will need to create a conda
environment to contain just the additional C and FORTRAN libraries necessary for the xesmf
module (and dependencies) to run. This can be done by installing the esmf
package using conda
conda create --name openghg_add esmf -c conda-forge
Then activate the Python virtual environment in the same way as above:
source openghg_env/bin/activate
Run the following lines to link the Python virtual environment to the installed dependencies, doing so by installing the esmpy
Python wrapper (a dependency of xesmf
):
ESMFVERSION='v'$(conda list -n openghg_add esmf | tail -n1 | awk '{print $2}')
$ export ESMFMKFILE="$(conda env list | grep openghg_add | awk '{print $2}')/lib/esmf.mk"
$ pip install "git+https://github.com/esmf-org/esmf.git@${ESMFVERSION}#subdirectory=src/addon/ESMPy/"
Note: The pip install command above for esmf
module may produce an AttributeError. At present (19/07/2022) an error of this type is expected and may not mean the xesmf
module cannot be installed. This error will be fixed if PR #49 is merged.
Now the dependencies have all been installed, the xesmf
library can be installed within the virtual environment
pip install xesmf
Setting the object store path
On first import OpenGHG will create a configuration file at ~/.config/openghg/openghg.conf
. This file contains the path to the object store, which by default is set to ~/openghg_store
.
The contents of the file will look like this
[object_store]
local_store = "/home/your_username/openghg_store"
or on macOS
[object_store]
local_store = "/Users/your_username/openghg_store"
Change this path to set the object store path.
Developers
If you'd like to contribute to OpenGHG please see the contributing section of our documentation. If you'd like to take a look at the source and run the tests follow the steps below.
Clone
git clone https://github.com/openghg/openghg.git
Install dependencies
We recommend you create a virtual environment first
python -m venv openghg_env
Then activate the environment
source openghg_env/bin/activate
Then install the dependencies
cd openghg
pip install --upgrade pip wheel setuptools
pip install -r requirements.txt -r requirements-dev.txt
Next you can install OpenGHG in editable mode using the -e
flag. This installs the package from
the local path and means any changes you make to the code will be immediately available when
using the package.
pip install -e .
OpenGHG should now be installed in your virtual environment.
See above for additional steps to install the xesmf
library as required.
Run the tests
To run the tests
pytest -v tests/
NOTE: Some of the tests require the udunits2 library to be installed.
The udunits
package is not pip
installable so we've added a separate flag to specifically run these tests. If you're on Debian / Ubuntu you can do
sudo apt-get install libudunits2-0
You can then run the cfchecks
marked tests using
pytest -v --run-cfchecks tests/
If all the tests pass then you're good to go. If they don't please open an issue and let us know some details about your setup.
Documentation
For further documentation and tutorials please visit our documentation.
Community
If you'd like further help or would like to talk to one of the developers of this project, please join our Gitter at gitter.im/openghg/lobby.
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