Metadata-Version: 1.2
Name: sodapy
Version: 1.5.0
Summary: Python library for the Socrata Open Data API
Home-page: https://github.com/xmunoz/sodapy
Author: Cristina Muñoz
Author-email: hi@xmunoz.com
Maintainer: Cristina Muñoz
Maintainer-email: hi@xmunoz.com
License: MIT
Download-URL: https://github.com/xmunoz/sodapy/archive/master.tar.gz
Description: |PyPI version| |Build Status|
        
        sodapy
        ======
        
        Python bindings for the Socrata Open Data API
        
        Installation
        ------------
        
        You can install with ``pip install sodapy``.
        
        If you want to install from source, then clone this repository and run
        ``python setup.py install`` from the project root.
        
        Requirements
        ------------
        
        At its core, this library depends heavily on the
        `Requests <http://docs.python-requests.org/en/latest/>`__ package. All
        other requirements can be found in
        `requirements.txt <https://github.com/xmunoz/sodapy/blob/master/requirements.txt>`__.
        ``sodapy`` is currently compatible with Python 2.7, 3.3, 3.4, 3.5, and
        3.6.
        
        Documentation
        -------------
        
        The `official Socrata API docs <http://dev.socrata.com/>`__ provide
        thorough documentation of the available methods, as well as other client
        libraries. A quick list of eligible domains to use with the API is
        available
        `here <https://opendata.socrata.com/dataset/Socrata-Customer-Spotlights/6wk3-4ija>`__.
        
        Examples
        --------
        
        There are some `jupyter <https://jupyter.org/>`__ notebooks in the
        `examples directory <examples>`__ with usages examples of sodapy in
        action.
        
        Interface
        ---------
        
        Table of Contents
        ~~~~~~~~~~~~~~~~~
        
        -  `client <#client>`__
        -  ```datasets`` <#datasetslimit0-offset0>`__
        -  ```get`` <#getdataset_identifier-content_typejson-kwargs>`__
        -  ```get_metadata`` <#get_metadatadataset_identifier-content_typejson>`__
        -  ```update_metadata`` <#update_metadatadataset_identifier-update_fields-content_typejson>`__
        -  ```download_attachments`` <#download_attachmentsdataset_identifier-content_typejson-download_dirsodapy_downloads>`__
        -  ```create`` <#createname-kwargs>`__
        -  ```publish`` <#publishdataset_identifier-content_typejson>`__
        -  ```set_permission`` <#set_permissiondataset_identifier-permissionprivate-content_typejson>`__
        -  ```upsert`` <#upsertdataset_identifier-payload-content_typejson>`__
        -  ```replace`` <#replacedataset_identifier-payload-content_typejson>`__
        -  ```create_non_data_file`` <#create_non_data_fileparams-file_obj>`__
        -  ```replace_non_data_file`` <#replace_non_data_filedataset_identifier-params-file_obj>`__
        -  ```delete`` <#deletedataset_identifier-row_idnone-content_typejson>`__
        -  ```close`` <#close>`__
        
        client
        ~~~~~~
        
        Import the library and set up a connection to get started.
        
        ::
        
           >>> from sodapy import Socrata
           >>> client = Socrata("sandbox.demo.socrata.com", "FakeAppToken", username="fakeuser@somedomain.com", password="ndKS92mS01msjJKs")
        
        ``username`` and ``password`` are only required for creating or
        modifying data. An application token isn’t strictly required (can be
        ``None``), but queries executed from a client without an application
        token will be subjected to strict throttling limits. To create a
        bare-bones client:
        
        ::
        
           >>> client = Socrata("sandbox.demo.socrata.com", None)
        
        A client can also be created with a context manager to obviate the need
        for teardown:
        
        ::
        
           >>> with Socrata("sandbox.demo.socrata.com", None) as client:
           >>>    # do some stuff
        
        The client, by default, makes requests over HTTPS. To modify this
        behavior, or to make requests through a proxy, take a look
        `here <https://github.com/xmunoz/sodapy/issues/31#issuecomment-302176628>`__.
        
        datasets(limit=0, offset=0)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Retrieve datasets associated with a particular domain. The optional
        ``limit`` and ``offset`` keyword args can be used to retrieve a subset
        of the datasets. By default, all datasets are returned.
        
        ::
        
           >>> client.datasets()
           [{"resource" : {"name" : "Approved Building Permits", "id" : "msk6-43c6", "parent_fxf" : null, "description" : "Data of approved building/construction permits",...}, {resource : {...}}, ...]
        
        get(dataset_identifier, content_type=“json”, \**kwargs)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Retrieve data from the requested resources. Filter and query data by
        field name, id, or using `SoQL
        keywords <https://dev.socrata.com/docs/queries/>`__.
        
        ::
        
           >>> client.get("nimj-3ivp", limit=2)
           [{u'geolocation': {u'latitude': u'41.1085', u'needs_recoding': False, u'longitude': u'-117.6135'}, u'version': u'9', u'source': u'nn', u'region': u'Nevada', u'occurred_at': u'2012-09-14T22:38:01', u'number_of_stations': u'15', u'depth': u'7.60', u'magnitude': u'2.7', u'earthquake_id': u'00388610'}, {...}]
        
           >>> client.get("nimj-3ivp", where="depth > 300", order="magnitude DESC", exclude_system_fields=False)
           [{u'geolocation': {u'latitude': u'-15.563', u'needs_recoding': False, u'longitude': u'-175.6104'}, u'version': u'9', u':updated_at': 1348778988, u'number_of_stations': u'275', u'region': u'Tonga', u':created_meta': u'21484', u'occurred_at': u'2012-09-13T21:16:43', u':id': 132, u'source': u'us', u'depth': u'328.30', u'magnitude': u'4.8', u':meta': u'{\n}', u':updated_meta': u'21484', u'earthquake_id': u'c000cnb5', u':created_at': 1348778988}, {...}]
        
           >>> client.get("nimj-3ivp/193", exclude_system_fields=False)
           {u'geolocation': {u'latitude': u'21.6711', u'needs_recoding': False, u'longitude': u'142.9236'}, u'version': u'C', u':updated_at': 1348778988, u'number_of_stations': u'136', u'region': u'Mariana Islands region', u':created_meta': u'21484', u'occurred_at': u'2012-09-13T11:19:07', u':id': 193, u'source': u'us', u'depth': u'300.70', u'magnitude': u'4.4', u':meta': u'{\n}', u':updated_meta': u'21484', u':position': 193, u'earthquake_id': u'c000cmsq', u':created_at': 1348778988}
        
           >>> client.get("nimj-3ivp", region="Kansas")
           [{u'geolocation': {u'latitude': u'38.10', u'needs_recoding': False, u'longitude': u'-100.6135'}, u'version': u'9', u'source': u'nn', u'region': u'Kansas', u'occurred_at': u'2010-09-19T20:52:09', u'number_of_stations': u'15', u'depth': u'300.0', u'magnitude': u'1.9', u'earthquake_id': u'00189621'}, {...}]
        
        get_metadata(dataset_identifier, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Retrieve the metadata associated with a particular dataset.
        
        ::
        
           >>> client.get_metadata("nimj-3ivp")
           {"newBackend": false, "licenseId": "CC0_10", "publicationDate": 1436655117, "viewLastModified": 1451289003, "owner": {"roleName": "administrator", "rights": [], "displayName": "Brett", "id": "cdqe-xcn5", "screenName": "Brett"}, "query": {}, "id": "songs", "createdAt": 1398014181, "category": "Public Safety", "publicationAppendEnabled": true, "publicationStage": "published", "rowsUpdatedBy": "cdqe-xcn5", "publicationGroup": 1552205, "displayType": "table", "state": "normal", "attributionLink": "http://foo.bar.com", "tableId": 3523378, "columns": [], "metadata": {"rdfSubject": "0", "renderTypeConfig": {"visible": {"table": true}}, "availableDisplayTypes": ["table", "fatrow", "page"], "attachments": ... }}
        
        update_metadata(dataset_identifier, update_fields, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Update the metadata for a particular dataset. ``update_fields`` should
        be a dictionary containing only the metadata keys that you wish to
        overwrite.
        
        Note: Invalid payloads to this method could corrupt the dataset or
        visualization. See `this
        comment <https://github.com/xmunoz/sodapy/issues/22#issuecomment-249971379>`__
        for more information.
        
        ::
        
           >>> client.update_metadata("nimj-3ivp", {"attributionLink": "https://anothertest.com"})
           {"newBackend": false, "licenseId": "CC0_10", "publicationDate": 1436655117, "viewLastModified": 1451289003, "owner": {"roleName": "administrator", "rights": [], "displayName": "Brett", "id": "cdqe-xcn5", "screenName": "Brett"}, "query": {}, "id": "songs", "createdAt": 1398014181, "category": "Public Safety", "publicationAppendEnabled": true, "publicationStage": "published", "rowsUpdatedBy": "cdqe-xcn5", "publicationGroup": 1552205, "displayType": "table", "state": "normal", "attributionLink": "https://anothertest.com", "tableId": 3523378, "columns": [], "metadata": {"rdfSubject": "0", "renderTypeConfig": {"visible": {"table": true}}, "availableDisplayTypes": ["table", "fatrow", "page"], "attachments": ... }}
        
        download_attachments(dataset_identifier, content_type=“json”, download_dir=“~/sodapy_downloads”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Download all attachments associated with a dataset. Return a list of
        paths to the downloaded files.
        
        ::
        
           >>> client.download_attachments("nimj-3ivp", download_dir="~/Desktop")
               ['/Users/xmunoz/Desktop/nimj-3ivp/FireIncident_Codes.PDF', '/Users/xmunoz/Desktop/nimj-3ivp/AccidentReport.jpg']
        
        create(name, \**kwargs)
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        Create a new dataset. Optionally, specify keyword args such as:
        
        -  ``description`` description of the dataset
        -  ``columns`` list of fields
        -  ``category`` dataset category (must exist in /admin/metadata)
        -  ``tags`` list of tag strings
        -  ``row_identifier`` field name of primary key
        -  ``new_backend`` whether to create the dataset in the new backend
        
        Example usage:
        
        ::
        
           >>> columns = [{"fieldName": "delegation", "name": "Delegation", "dataTypeName": "text"}, {"fieldName": "members", "name": "Members", "dataTypeName": "number"}]
           >>> tags = ["politics", "geography"]
           >>> client.create("Delegates", description="List of delegates", columns=columns, row_identifier="delegation", tags=tags, category="Transparency")
           {u'id': u'2frc-hyvj', u'name': u'Foo Bar', u'description': u'test dataset', u'publicationStage': u'unpublished', u'columns': [ { u'name': u'Foo', u'dataTypeName': u'text', u'fieldName': u'foo', ... }, { u'name': u'Bar', u'dataTypeName': u'number', u'fieldName': u'bar', ... } ], u'metadata': { u'rowIdentifier': 230641051 }, ... }
        
        publish(dataset_identifier, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Publish a dataset after creating it, i.e. take it out of ‘working copy’
        mode. The dataset id ``id`` returned from ``create`` will be used to
        publish.
        
        ::
        
           >>> client.publish("2frc-hyvj")
           {u'id': u'2frc-hyvj', u'name': u'Foo Bar', u'description': u'test dataset', u'publicationStage': u'unpublished', u'columns': [ { u'name': u'Foo', u'dataTypeName': u'text', u'fieldName': u'foo', ... }, { u'name': u'Bar', u'dataTypeName': u'number', u'fieldName': u'bar', ... } ], u'metadata': { u'rowIdentifier': 230641051 }, ... }
        
        set_permission(dataset_identifier, permission=“private”, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Set the permissions of a dataset to public or private.
        
        ::
        
           >>> client.set_permission("2frc-hyvj", "public")
           <Response [200]>
        
        upsert(dataset_identifier, payload, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Create a new row in an existing dataset.
        
        ::
        
           >>> data = [{'Delegation': 'AJU', 'Name': 'Alaska', 'Key': 'AL', 'Entity': 'Juneau'}]
           >>> client.upsert("eb9n-hr43", data)
           {u'Errors': 0, u'Rows Deleted': 0, u'Rows Updated': 0, u'By SID': 0, u'Rows Created': 1, u'By RowIdentifier': 0}
        
        Update/Delete rows in a dataset.
        
        ::
        
           >>> data = [{'Delegation': 'sfa', ':id': 8, 'Name': 'bar', 'Key': 'doo', 'Entity': 'dsfsd'}, {':id': 7, ':deleted': True}]
           >>> client.upsert("eb9n-hr43", data)
           {u'Errors': 0, u'Rows Deleted': 1, u'Rows Updated': 1, u'By SID': 2, u'Rows Created': 0, u'By RowIdentifier': 0}
        
        ``upsert``\ ’s can even be performed with a csv file.
        
        ::
        
           >>> data = open("upsert_test.csv")
           >>> client.upsert("eb9n-hr43", data)
           {u'Errors': 0, u'Rows Deleted': 0, u'Rows Updated': 1, u'By SID': 1, u'Rows Created': 0, u'By RowIdentifier': 0}
        
        replace(dataset_identifier, payload, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Similar in usage to ``upsert``, but overwrites existing data.
        
        ::
        
           >>> data = open("replace_test.csv")
           >>> client.replace("eb9n-hr43", data)
           {u'Errors': 0, u'Rows Deleted': 0, u'Rows Updated': 0, u'By SID': 0, u'Rows Created': 12, u'By RowIdentifier': 0}
        
        create_non_data_file(params, file_obj)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Creates a new file-based dataset with the name provided in the files
        tuple. A valid file input would be:
        
        ::
        
           files = (
               {'file': ("gtfs2", open('myfile.zip', 'rb'))}
           )
        
        ::
        
           >>> with open(nondatafile_path, 'rb') as f:
           >>>     files = (
           >>>         {'file': ("nondatafile.zip", f)}
           >>>     )
           >>>     response = client.create_non_data_file(params, files)
        
        replace_non_data_file(dataset_identifier, params, file_obj)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Same as create_non_data_file, but replaces a file that already exists in
        a file-based dataset.
        
        Note: a table-based dataset cannot be replaced by a file-based dataset.
        Use create_non_data_file in order to replace.
        
        ::
        
           >>>  with open(nondatafile_path, 'rb') as f:
           >>>      files = (
           >>>          {'file': ("nondatafile.zip", f)}
           >>>      )
           >>>      response = client.replace_non_data_file(DATASET_IDENTIFIER, {}, files)
        
        delete(dataset_identifier, row_id=None, content_type=“json”)
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Delete an individual row.
        
        ::
        
           >>> client.delete("nimj-3ivp", row_id=2)
           <Response [200]>
        
        Delete the entire dataset.
        
        ::
        
           >>> client.delete("nimj-3ivp")
           <Response [200]>
        
        close()
        ~~~~~~~
        
        Close the session when you’re finished.
        
        ::
        
           >>> client.close()
        
        Run tests
        ---------
        
        ::
        
           $ pytest
        
        Contributing
        ------------
        
        See
        `CONTRIBUTING.md <https://github.com/xmunoz/sodapy/blob/master/CONTRIBUTING.md>`__.
        
        .. |PyPI version| image:: https://badge.fury.io/py/sodapy.svg
           :target: http://badge.fury.io/py/sodapy
        .. |Build Status| image:: https://travis-ci.org/xmunoz/sodapy.svg?branch=master
           :target: https://travis-ci.org/xmunoz/sodapy
        
Keywords: soda socrata opendata api
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
