Once you have installed pygeoapi, it’s time to setup a configuration. pygeoapi’s runtime configuration is defined in the YAML format which is then referenced via the PYGEOAPI_CONFIG environment variable. You can name the file whatever you wish; typical filenames end with .yml.


A sample configuration can always be found in the pygeoapi GitHub repository.

pygeoapi configuration contains the following core sections:

  • server: server-wide settings

  • logging: logging configuration

  • metadata: server-wide metadata (contact, licensing, etc.)

  • resources: dataset collections, processes and stac-collections offered by the server


Standard YAML mechanisms can be used (anchors, references, etc.) for reuse and compactness.

Configuration directives and reference are described below via annotated examples.



The server section provides directives on binding and high level tuning.

      host:  # listening address for incoming connections
      port: 5000  # listening port for incoming connections
  url: http://localhost:5000/  # url of server
  mimetype: application/json; charset=UTF-8  # default MIME type
  encoding: utf-8  # default server encoding
  language: en-US  # default server language
  gzip: false # default server config to gzip/compress responses to requests with gzip in the Accept-Encoding header
  cors: true  # boolean on whether server should support CORS
  pretty_print: true  # whether JSON responses should be pretty-printed
  limit: 10  # server limit on number of items to return

  templates: # optional configuration to specify a different set of templates for HTML pages. Recommend using absolute paths. Omit this to use the default provided templates
    path: /path/to/jinja2/templates/folder # path to templates folder containing the jinja2 template HTML files
    static: /path/to/static/folder # path to static folder containing css, js, images and other static files referenced by the template

  map:  # leaflet map setup for HTML pages
      attribution: '<a href="">Wikimedia maps</a> | Map data &copy; <a href="">OpenStreetMap contributors</a>'
  ogc_schemas_location: /opt/  # local copy of

  manager:  # optional OGC API - Processes asynchronous job management
      name: TinyDB  # plugin name (see pygeoapi.plugin for supported process_manager's)
      connection: /tmp/pygeoapi-process-manager.db  # connection info to store jobs (e.g. filepath)
      output_dir: /tmp/  # temporary file area for storing job results (files)


The logging section provides directives for logging messages which are useful for debugging.

    level: ERROR  # the logging level (see
    logfile: /path/to/pygeoapi.log  # the full file path to the logfile


If level is defined and logfile is undefined, logging messages are output to the server’s stdout.


The metadata section provides settings for overall service metadata and description.

        title: pygeoapi default instance  # the title of the service
        description: pygeoapi provides an API to geospatial data  # some descriptive text about the service
        keywords:  # list of keywords about the service
            - geospatial
            - data
            - api
        keywords_type: theme  # keyword type as per the ISO 19115 MD_KeywordTypeCode codelist. Accepted values are discipline, temporal, place, theme, stratum
        terms_of_service:  # terms of service
        url:  # informative URL about the service
    license:  # licensing details
        name: CC-BY 4.0 license
    provider:  # service provider details
        name: Organization Name
    contact:  # service contact details
        name: Lastname, Firstname
        position: Position Title
        address: Mailing Address
        city: City
        stateorprovince: Administrative Area
        postalcode: Zip or Postal Code
        country: Country
        phone: +xx-xxx-xxx-xxxx
        fax: +xx-xxx-xxx-xxxx
        url: Contact URL
        hours: Mo-Fr 08:00-17:00
        instructions: During hours of service. Off on weekends.
        role: pointOfContact


The resources section lists 1 or more dataset collections to be published by the server.

The resource.type property is required. Allowed types are:

  • collection

  • process

  • stac-collection

The providers block is a list of 1..n providers with which to operate the data on. Each provider requires a type property. Allowed types are:

  • feature

  • coverage

  • tile

A collection’s default provider can be qualified with default: true in the provider configuration. If default is not included, the first provider is assumed to be the default.

        type: collection  # REQUIRED (collection, process, or stac-collection)
        title: Observations  # title of dataset
        description: My cool observations  # abstract of dataset
        keywords:  # list of related keywords
            - observations
            - monitoring
        context:  # linked data configuration (see Linked Data section)
            - datetime:
            - vocab:
              stn_id: "vocab:stn_id"
              value: "vocab:value"
        links:  # list of 1..n related links
            - type: text/csv  # MIME type
              rel: canonical  # link relations per
              title: data  # title
              href:  # URL
              hreflang: en-US  # language
        extents:  # spatial and temporal extents
            spatial:  # required
                bbox: [-180,-90,180,90]  # list of minx, miny, maxx, maxy
                crs:  # CRS
            temporal:  # optional
                begin: 2000-10-30T18:24:39Z  # start datetime in RFC3339
                end: 2007-10-30T08:57:29Z  # end datetime in RFC3339
        providers:  # list of 1..n required connections information
            # provider name
            # see pygeoapi.plugin for supported providers
            # for custom built plugins, use the import path (e.g. mypackage.provider.MyProvider)
            # see Plugins section for more information
            - type: feature # underlying data geospatial type: (allowed values are: feature, coverage, record, tile, edr)
              default: true  # optional: if not specified, the first provider definition is considered the default
              name: CSV
              data: tests/data/obs.csv  # required: the data filesystem path or URL, depending on plugin setup
              id_field: id  # required for vector data, the field corresponding to the ID
              uri_field: uri # optional field corresponding to the Uniform Resource Identifier (see Linked Data section)
              time_field: datetimestamp  # optional field corresponding to the temporal property of the dataset
              title_field: foo # optional field of which property to display as title/label on HTML pages
              format:  # optional default format
                  name: GeoJSON  # required: format name
                  mimetype: application/json  # required: format mimetype
              options:  # optional options to pass to provider (i.e. GDAL creation)
                  option_name: option_value
              properties:  # optional: only return the following properties, in order
                  - stn_id
                  - value

    hello-world:  # name of process
        type: collection  # REQUIRED (collection, process, or stac-collection)
            name: HelloWorld  # Python path of process defition

See also

Linked Data for optionally configuring linked data datasets

See also

Customizing pygeoapi: plugins for more information on plugins

Validating the configuration

To ensure your configuration is valid, pygeoapi provides a validation utility that can be run as follows:

pygeoapi config validate /path/to/my-pygeoapi-config.yml

Using environment variables

pygeoapi configuration supports using system environment variables, which can be helpful for deploying into 12 factor environments for example.

Below is an example of how to integrate system environment variables in pygeoapi.

        host: ${MY_HOST}
        port: ${MY_PORT}

Linked Data

JSON-LD support

pygeoapi supports structured metadata about a deployed instance, and is also capable of presenting data as structured data. JSON-LD equivalents are available for each HTML page, and are embedded as data blocks within the corresponding page for search engine optimisation (SEO). Tools such as the Google Structured Data Testing Tool can be used to check the structured representations.

The metadata for an instance is determined by the content of the metadata section of the configuration. This metadata is included automatically, and is sufficient for inclusion in major indices of datasets, including the Google Dataset Search.

For collections, at the level of item, the default JSON-LD representation adds:

  • An @id for the item, which is the URL for that item. If uri_field is specified, it is used, otherwise the URL is to its HTML representation in pygeoapi.

  • Separate GeoSPARQL/WKT and versions of the geometry. only supports point, line, and polygon geometries. Multipart lines are merged into a single line. The rest of the multipart geometries are transformed reduced and into a polygon via unary union or convex hull transform.

  • @context for the GeoSPARQL and schema geometries.

  • The unpacked properties block into the main body of the item.

For collections, at the level of items, the default JSON-LD representation adds:

  • A itemList of the @id and @type of each feature in the collection.

The optional configuration options for collections, at the level of an item of items, are:

  • If uri_field is specified, JSON-LD will be updated such that the @id has the value of uri_field for each item in a collection


While this is enough to provide valid RDF (as GeoJSON-LD), it does not allow the properties of your items to be unambiguously interpretable.

pygeoapi currently allows for the extension of the @context to allow properties to be aliased to terms from vocabularies. This is done by adding a context section to the configuration of a dataset.

The default pygeoapi configuration includes an example for the obs sample dataset:

    - datetime:
    - vocab:
      stn_id: "vocab:stn_id"
      value: "vocab:value"

This is a non-existent vocabulary included only to illustrate the expected data structure within the configuration. In particular, the links for the stn_id and value properties do not resolve. We can extend this example to one with terms defined by

    - schema:
      stn_id: schema:identifer
          "@id": schema:observationDate
          "@type": schema:DateTime
          "@id": schema:value
          "@type": schema:Number

Now this has been elaborated, the benefit of a structured data representation becomes clearer. What was once an unexplained property called datetime in the source CSV, it can now be expanded to, thereby eliminating ambiguity and enhancing interoperability. Its type is also expressed as

This example demonstrates how to use this feature with a CSV data provider, using included sample data. The implementation of JSON-LD structured data is available for any data provider but is currently limited to defining a @context. Relationships between items can be expressed but is dependent on such relationships being expressed by the dataset provider, not pygeoapi.

An example of a data provider that includes relationships between items is the SensorThings API provider. SensorThings API, by default, has relationships between entities within its data model. Setting the intralink field of the SensorThings provider to true sets pygeoapi to represent the relationship between configured entities as intra-pygeoapi links or URIs. This relationship can further be maintained in the JSON-LD structured data using the appropiate @context with the sosa/ssn ontology. For example:

      - sosa: ""
        ssn: ""
        Datastreams: sosa:ObservationCollection

      - sosa: ""
        ssn: ""
        Observations: sosa:hasMember
        Thing: sosa:hasFeatureOfInterest

      - sosa: ""
        ssn: ""
        Datastream: sosa:isMemberOf


At this point, you have the configuration ready to administer the server.