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Parse and manipulate structured data and metadata in a tabular format.

Project description

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Metapack, Metatab Data Packaging

Parse and manipulate structured data and metadata in a tabular format.

Metatab is a data format that allows structured metadata – the sort you’d normally store in JSON, YAML or XML – to be stored and edited in tabular forms like CSV or Excel. Metatab files look exactly like you’d expect, so they are very easy for non-technical users to read and edit, using tools they already have. Metatab is an excellent format for creating, storing and transmitting metadata. For more information about metatab, visit http://metatab.org.

Metapack is a packaging system that uses Metatab to create Zip, Excel and filesystem data packages.

This repository has a Python module and executable. For a Javascript version, see the metatab-js repository.

See the documentation for full details

Install

Metapack requires geographic libraries, most importantly gda, pyproj, shapely and geopandas. These libraries can be difficult to install, often requiring compilation. By far, the easiest way to install them properly is with Anaconda. And, because, metapack has a lot of dependencies, you’ll want to install it in a virtual environment. Metapack only works with Python 3.5 or later:

$ conda create --name metapack python=3.7
$ conda activate metapack
$ conda install numpy pandas gdal geos pyproj=1.9.5.1 fiona shapely geopandas
$ pip install metapack

Verify that the install worked by running `` mp config``

Getting Started

See Getting Started for an initial tutorial, or the other guides in the docs directory on Github

Development Notes

Clearing the Cache

Some tests can pass despite errors if the file the test is looking for is cached. The cache can be set with an evironmental variable and cleared before the tests to solve this problem

$ cache_dir=/tmp/some/dir
$ rm -rf $cache_dir
$ mkdir -p  $cache_dir
$ APPURL_CACHE=$cache_dir python setup.py test

Development Testing with Docker

Testing during development for other versions of Python is a bit of a pain, since you have to install the alternate version, and Tox will run all of the tests, not just the one you want.

One way to deal with this is to install Docker locally, then run the docker test container on the source directory. This is done automatically from the Makefile in appurl/tests

$ cd metapack/metapack/test
$ make build # to create the container image
$ make shell # to run bash the container

You now have a docker container where the /code directory is the appurl source dir. Since the Docker container is running code from your host machine, you can edit it normally.

Now, run tox to build the tox virtual environments, then enter the specific version you want to run tests for and activate the virtual environment.

To run one environment. for example, Python 3.4

# tox -e py34

To run one test in one environment environment. for example, Python 3.4

# tox -e py34 -- -s

Project details


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