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Cate: ESA CCI Toolbox

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cate

ESA CCI Toolbox (Cate) Python package, API and CLI.

Installation

Cate can be installed into a new or existing Python 3.7 Miniconda or Anaconda environment as follows:

$ conda install -c ccitools cate-cli

Installation from Sources

Cate's sources (this repository) are organised as follows:

  • setup.py - main build script to be run with Python 3.6+
  • cate/ - main package and production code
  • test/ - test package and test code
  • doc/ - documentation in Sphinx/RST format

We recommend installing Cate into an isolated Python 3 environment, because this approach avoids clashes with existing versions of Cate's 3rd-party Python package requirements. Using Miniconda or Anaconda will usually avoid platform-specific issues caused by module native binaries.

The first step is to clone latest Cate code and step into the check out directory:

$ git clone https://github.com/CCI-Tools/cate.git
$ cd cate

Using Conda

Conda is the package manager used by the Miniconda or Anaconda Python distributions.

Creating a new Python environment for Cate will require around 2.2 GB disk space on Linux/Darwin and and 1.2 GB on Windows. To create a new Conda environment cate-env in your Anaconda/Miniconda installation directory, type:

$ conda env create

If you want the environment to be installed in another location, e.g. due to disk space limitations, type:

$ conda env create --prefix some/other/location/for/cate

Next step is to activate the new environment.

$ conda activate cate-env

You can now safely install Cate sources into the new cate-env environment.

(cate-env) $ python setup.py install

Using Docker

You can also use pre-build Docker images that contain a Python environment with the cate package already installed. The images are quay.io/bcdev/cate:<version>. E.g.

$ docker run -d -v ${my_local_dir}:/home/cate quay.io/bcdev/cate:2.1.1 bash
(cate-env) $ cate -h  

where ${my_local_dir} refers to any directory on your computer that you may want to access from within the running Docker container.

Getting started

To test the installation, first run the Cate command-line interface. Type

$ cate -h

IPython notebooks for various Cate use cases are on the way, they will appear in the project's notebooks folder.

To use them interactively, you'll need to install Jupyter and run its Notebook app:

$ conda install jupyter
$ jupyter notebook

Open the notebooks folder and select a use case.

Running Cate App in Stand-Alone mode

To run the the graphical user interface Cate App in stand-alone mode you'll need to start a Cate Web API service. To do so, first install the cate Python package as described above. Then Cate Web API service is started from the command-line. To run the service on port 9090 on your local computer, type:

$ cate-webapi-start --port 9090 

Then open Cate App in a browser and enter the URL http://localhost:9090. Press the "Cate Stand-Alone Mode" button above. This will launch the Cate App in stand-alone mode. If you wish to run a service with limited file system access (sandboxed), you can specify the root option that defines a new file system root:

$ cate-webapi-start --port 9090 --root /home/fritz

Use CTRL+C or the command

$ cate-webapi-stop --port 9090

to stop the service.

To run the service from the docker image, type:

$ docker run -it -v ${my_local_dir}:/home/cate -p 9090:4000 quay.io/bcdev/cate:2.1.1 bash
(cate-env) $ cate-webapi-start --port 4000 --root ${my_local_dir}    

Conda Deployment

There is a dedicated repository cate-conda which provides scripts and configuration files to build Cate's Conda packages and a stand-alone installer.

Development

Contributors

Contributors are asked to read and adhere to our Developer Guide.

Unit-testing

For unit testing we use pytest and its coverage plugin pytest-cov.

To run the unit-tests with coverage, type

$ export NUMBA_DISABLE_JIT=1
$ py.test --cov=cate test

We need to set environment variable NUMBA_DISABLE_JIT to disable JIT compilation by numba, so that coverage reaches the actual Python code. We use Numba's JIT compilation to speed up numeric Python number crunching code.

Other recognized environment variables to customize the unit-level tests are

CATE_DISABLE_WEB_TESTS=1
CATE_DISABLE_PLOT_TESTS=1
CATE_DISABLE_GEOPANDAS_TESTS=1
CATE_DISABLE_CLI_UPDATE_TESTS=1

Generating the Documentation

We use the wonderful Sphinx tool to generate Cate's documentation on ReadTheDocs. If there is a need to build the docs locally, first create a Conda environment:

$ cd cate
$ conda env create -f environment-rtd.yml

To regenerate the HTML docs, type

$ cd doc
$ make html

License

The CCI Toolbox is distributed under terms and conditions of the MIT license.