A Python library for creating human and machine-readable metadata for geospatial data.

Supported datatypes include:

• everything supported by GDAL
• tabular formats supported by frictionless
• compressed formats supported by frictionless

See requirements.txt for dependencies.

This library comes with a command-line interface (CLI) called geometamaker. Many of the examples below show how to use the Python interface, and then how to do the same thing, if possible, using the CLI.

Creating & adding metadata to file:

Python

import geometamaker

data_path = 'data/watershed_gura.shp'
resource = geometamaker.describe(data_path)

resource.set_title('My Dataset')
resource.set_description('all about my dataset')
resource.set_keywords(['hydrology', 'watersheds'])

# For a vector:
resource.set_field_description(
    'field_name',  # the name of an actual field in the vector's table
    description='something about the field',
    units='mm')

# or for a raster:
data_path = 'data/dem.tif'
resource = geometamaker.describe(data_path)
resource.set_band_description(
    1,  # a raster band index, starting at 1
    description='something about the band',
    units='mm')


resource.write()

CLI

geometamaker describe data/watershed_gura.shp

The CLI does not provide options for setting metadata properties such as keywords, field or band descriptions, or other properties that require user-input. If you create a metadata document with the CLI, you may wish to add these values manually by editing the watershed_gura.shp.yml file in a text editor.

Creating metadata for a batch of files:

Python

import os

import geometamaker

data_dir = 'C:/Users/dmf/projects/invest/data/invest-sample-data'
geometamaker.describe_dir(data_dir, recursive=True)

CLI

geometamaker describe -r data/invest-sample-data

Validating a metadata document:

If you have manually edited a .yml metadata document, it is a good idea to validate it for correct syntax, properties, and types.

Python

import geometamaker

document_path = 'data/watershed_gura.shp.yml'
error = geometamaker.validate(document_path)
print(error)

CLI

geometamaker validate data/watershed_gura.shp.yml

Validating all metadata documents in a directory

Python

import geometamaker

directory_path = 'data/'
yaml_files, messages = geometamaker.validate_dir(data)
for filepath, msg in zip(yaml_files, messages):
    print(f'{filepath}: {msg}')

CLI

geometamaker validate data

Configuring default values for metadata properties:

Users can create a "profile" that will apply some common properties to all datasets they describe. Profiles can include contact information and/or license information.

A profile can be saved to a configuration file so that it will be re-used everytime you use geometamaker. In addition, users can set a profile during runtime, which takes precedence over a profile in the config file.

Create & apply a Profile at runtime

import os

import geometamaker
from geometamaker import models

contact = {
    'individual_name': 'bob'
}
license = {
    'title': 'CC-BY-4'
}

# Two different ways for setting profile attributes:
profile = models.Profile(contact=contact)  # keyword arguments
profile.set_license(**license)             # `set_*` methods

data_path = 'data/watershed_gura.shp'
# Pass the profile to the `describe` function
resource = geometamaker.describe(data_path, profile=profile)

Store a Profile in user-configuration

Python

import os

import geometamaker
from geometamaker import models

contact = {
    'individual_name': 'bob'
}

profile = models.Profile(contact=contact)
config = geometamaker.Config()
config.save(profile)

data_path = 'data/watershed_gura.shp'
# A profile saved in the user's configuration file does not
# need to be passed to `describe`. It is always applied.
resource = geometamaker.describe(data_path)

CLI

geometamaker config

This will prompt the user to enter their profile information.
Also see geometamaker config --help.

For a complete list of methods:

https://geometamaker.readthedocs.io/en/latest/api/geometamaker.html