@datafire/opendatasoft
Client library for opendatasoft
Installation and Usage
npm install --save @datafire/opendatasoft
let opendatasoft = require('@datafire/opendatasoft').create({
api_key: "",
username: "",
password: ""
});
.then(data => {
console.log(data);
});
Description
Actions
getRoot
API entry point
Provides links for:
- catalog, your domain's list of datasets
- opendatasoft, all datasets on the Opendatasoft network
opendatasoft.getRoot(null, context)
Input
This action has no parameters
Output
- output
object
- links
array
- items link
- links
getPages
List of all pages from this portal.
opendatasoft.getPages(null, context)
Input
This action has no parameters
Output
getPage
A single page's metadata from this portal
opendatasoft.getPage({
"slug": ""
}, context)
Input
- input
object
- slug required
string
: Page slug.
- slug required
Output
getSource
Source entry points
Provides links for the source's datasets and metadata.
opendatasoft.getSource({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
- source required
Output
- output
object
- links
array
- items link
- links
aggregateDatasets
Compute aggregations from catalog and return a list of each aggregate indexed by their names.
opendatasoft.aggregateDatasets({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - select
string
: A select expression can be used to add, remove or change fields to return. - group_by
string
: A group by expression defines a grouping function for an aggregation. - where
array
: An array of filters. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - order_by
array
: A list of field names or aggregation, followed by an order (asc | desc). - offset
integer
: Index of the first item to return (starting at 0). - limit
integer
: Number of items to return.
- source required
Output
- output
object
- aggregations
array
- items aggregation
- links
array
- items link
- aggregations
getDatasets
List of available datasets, each with their endpoints, paginated.
Links provided:
- previous page
- next page
- last page
- first page
opendatasoft.getDatasets({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
object
getDataset
List of available endpoints for the specified dataset, with metadata and endpoints.
Will provide links for:
- the attachments endpoint
- the files endpoint
- the records endpoint
- the catalog endpoint
opendatasoft.getDataset({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields - select
string
: A select expression can be used to add, remove or change fields to return. - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
aggregateRecords
Compute aggregations from dataset records and return a list of each aggregate indexed by their names.
opendatasoft.aggregateRecords({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - select
string
: A select expression can be used to add, remove or change fields to return. - group_by
string
: A group by expression defines a grouping function for an aggregation. - where
array
: An array of filters. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - order_by
array
: A list of field names or aggregation, followed by an order (asc | desc). - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0).
- source required
Output
- output
object
- aggregations
array
- items aggregation
- links
array
- items link
- aggregations
getDatasetAttachements
Get list of all available attachments
opendatasoft.getDatasetAttachements({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier.
- source required
Output
- output
object
- attachments
array
- items attachment
- links
array
- items link
- attachments
downloadDatasetAttachement
Download attachment
opendatasoft.downloadDatasetAttachement({
"source": "",
"dataset_id": "",
"attachment_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - attachment_id required
string
- source required
Output
Output schema unknown
exportRecordsCSV
Export dataset in CSV format
opendatasoft.exportRecordsCSV({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields - delimiter
string
(values: ,, ;, |): Provide a different delimiter (default ',').
- source required
Output
- output
file
exportRecordsGEOJSON
Export dataset in GEOJSON format
opendatasoft.exportRecordsGEOJSON({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields - pretty
boolean
: Activate pretty print
- source required
Output
- output
file
exportRecordsICAL
Export dataset in ICAL format
opendatasoft.exportRecordsICAL({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
file
exportRecordsJSON
Export dataset in JSON format
opendatasoft.exportRecordsJSON({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
file
exportRecordsOV2
Export dataset in OV2 format
opendatasoft.exportRecordsOV2({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
file
exportRecordsSHP
Export dataset in Esri shapefile (shp) format
opendatasoft.exportRecordsSHP({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
file
exportRecordsXLS
Export dataset in XLS (Excel) format
opendatasoft.exportRecordsXLS({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return in export. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
file
getRecordsFacets
Enumerate facets values for records and return a list of values for each facet. Can be used to implement guided navigation in large result sets.
Read the facets documentation for more details.
opendatasoft.getRecordsFacets({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - where
array
: An array of filters. - search
array
: An array of full text search. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
object
- facets
array
- items facet_enumeration
- facets
sendDatasetFeedback
Create new feedback entry.
opendatasoft.sendDatasetFeedback({
"source": "",
"dataset_id": "",
"feedback": null
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - feedback required
object
- comment
string
- newValues
object
: New record value - recordid
string
: Feedback entry's recordid - schema
object
: Record schema
- comment
- source required
Output
Output schema unknown
getDatasetFile
Download file
opendatasoft.getDatasetFile({
"source": "",
"dataset_id": "",
"file_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - file_id required
string
- thumbnail_size
string
: Set the size of the thumbnail representing the resource (attachment, image or file)
- source required
Output
Output schema unknown
getRecords
Search dataset's records.
opendatasoft.getRecords({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - sort
array
: A list of field names, each possibly prefixed with a minus (-). - select
string
: A select expression can be used to add, remove or change fields to return. - pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
object
getRecord
Retrieve a single record based on its ID.
opendatasoft.getRecord({
"source": "",
"dataset_id": "",
"record_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - record_id required
string
- pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields - select
string
: A select expression can be used to add, remove or change fields to return.
- source required
Output
getDatasetReuses
Get list of reuses
opendatasoft.getDatasetReuses({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - offset
integer
: Index of the first item to return (starting at 0). - limit
integer
: Number of items to return. - timezone
string
: Set timezone for datetime fields
- source required
Output
getDatasetReuse
Retrieve a single reuse based on its ID.
opendatasoft.getDatasetReuse({
"source": "",
"dataset_id": "",
"reuse_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - reuse_id required
string
- timezone
string
: Set timezone for datetime fields
- source required
Output
getDatasetSnapshots
List of all snapshots for this dataset.
opendatasoft.getDatasetSnapshots({
"source": "",
"dataset_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - timezone
string
: Set timezone for datetime fields
- source required
Output
downloadDatasetSnapshot
List of all snapshots for this dataset.
opendatasoft.downloadDatasetSnapshot({
"source": "",
"dataset_id": "",
"snapshot_id": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - dataset_id required
string
: Dataset identifier. - snapshot_id required
string
- timezone
string
: Set timezone for datetime fields
- source required
Output
Output schema unknown
exportDatasetsCSV
Export catalog (source) in CSV format
opendatasoft.exportDatasetsCSV({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets. - delimiter
string
(values: ,, ;, |): Provide a different delimiter (default ',').
- source required
Output
- output
file
exportDatasetsJson
Export catalog (source) in JSON format
opendatasoft.exportDatasetsJson({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - pretty
boolean
: Activate pretty print - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
file
exportDatasetsRDF
Export catalog (source) in RDF/XML format
opendatasoft.exportDatasetsRDF({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
file
exportDatasetsRSS
Export catalog (source) in RSS format
opendatasoft.exportDatasetsRSS({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
file
exportDatasetsTTL
Export catalog (source) in TTL (turtle/rdf) format
opendatasoft.exportDatasetsTTL({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
file
exportDatasetsXLS
Export catalog (source) in XLS (Excel) format
opendatasoft.exportDatasetsXLS({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - where
array
: An array of filters. - search
array
: An array of full text search. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - limit
integer
: Number of items to return. - offset
integer
: Index of the first item to return (starting at 0). - timezone
string
: Set timezone for datetime fields - include_app_metas
boolean
: Explicitely request application metas for each datasets.
- source required
Output
- output
file
getDatasetsFacets
Enumerate facets values for datasets and return a list of values for each facet. Can be used to implement guided navigation in large result sets.
Read the facets documentation for more details.
opendatasoft.getDatasetsFacets({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - facet
array
: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint/facets
). - refine
array
: An array of facet filters. For example city:Paris or modified:2019/12. - exclude
array
: An array of facet filters. For example city:Paris or modified:2019/12. - where
array
: An array of filters. - search
array
: An array of full text search. - timezone
string
: Set timezone for datetime fields
- source required
Output
- output
object
- facets
array
- items facet_enumeration
- facets
getMetadataTemplatesTypes
List of available metadata templates types, each with their endpoints.
opendatasoft.getMetadataTemplatesTypes({
"source": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
- source required
Output
- output
object
- links
array
- items link
- links
getMetadataTemplatesType
List of metadata templates available for this type.
opendatasoft.getMetadataTemplatesType({
"source": "",
"metadata_template_type": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - metadata_template_type required
string
(values: basic, interop, extra)
- source required
Output
- output
object
- links
array
- items link
- metadata_templates
array
- items
object
- links
array
- items link
- metadata_template metadata_template
- links
- items
- links
getMetadataTemplate
A single metadata_template
opendatasoft.getMetadataTemplate({
"source": "",
"metadata_template_type": "",
"metadata_template_name": ""
}, context)
Input
- input
object
- source required
string
(values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query. - metadata_template_type required
string
(values: basic, interop, extra) - metadata_template_name required
string
- source required
Output
- output
object
- links
array
- items link
- metadata_template metadata_template
- links
Definitions
aggregation
- aggregation
object
: Result of an aggregation request.
attachment
- attachment
object
- href
string
- metas
object
- href
dataset
- dataset
object
- attachments
array
- items
object
- items
- data_visible
boolean
- dataset_id
string
- features
array
: A map of available features for a dataset, with the fields they apply to.- items
string
- items
- fields
array
- items
object
- annotations
object
- description
string
- label
string
- name
string
- type
string
- annotations
- items
- has_records
boolean
- metas
object
- attachments
datasets
- datasets
array
- items dataset
facet_enumeration
- facet_enumeration
object
- facets
array
- items facet_value_enumeration
- name
string
- facets
facet_value_enumeration
- facet_value_enumeration
object
- count
integer
- facets
array
- items facet_value_enumeration
- name
string
- value
string
- count
link
- link
object
- href
string
- rel
string
- href
links
- links
array
- items link
metadata_template
- metadata_template
object
- name
string
- schema
array
- items
object
- items
- type
string
- name
page
- page
object
- description
string
- slug
string
- title
object
: A localized string (that is an object where the keys are language codes and the values translations of a same- en
string
- fr
string
- en
- description
query_string
- query_string
string
: Query string using the query language.
record
- record
object
- fields
object
- id
string
- size
integer
- timestamp
string
- fields
records
- records
array
- items record
reuse
- reuse
object
- created_at
string
: Date when the reuse was submitted. - id
string
: reuse id - thumbnail
string
: URL illustrating the work. - title
string
: Short description of the user's work. - url
string
: URL where the work can be accessed publicly. - user
object
- first_name
string
- last_name
string
- username
string
- first_name
- created_at
snapshot
- snapshot
object
- created_at
string
- description
string
- href
string
- snapshot_id
string
- created_at
timezone
- timezone
string
: A timezone