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#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright (C) 2017 Google # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) # ---------------------------------------------------------------------------- # # *** AUTO GENERATED CODE *** Type: MMv1 *** # # ---------------------------------------------------------------------------- # # This file is automatically generated by Magic Modules and manual # changes will be clobbered when the file is regenerated. # # Please read more about how to change this file at # https://www.github.com/GoogleCloudPlatform/magic-modules # # ---------------------------------------------------------------------------- from __future__ import absolute_import, division, print_function __metaclass__ = type ################################################################################ # Documentation ################################################################################ ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ["preview"], 'supported_by': 'community'} DOCUMENTATION = ''' --- module: gcp_bigquery_table description: - A Table that belongs to a Dataset . short_description: Creates a GCP Table author: Google Inc. (@googlecloudplatform) requirements: - python >= 2.6 - requests >= 2.18.4 - google-auth >= 1.3.0 options: state: description: - Whether the given object should exist in GCP choices: - present - absent default: present type: str table_reference: description: - Reference describing the ID of this table. required: false type: dict suboptions: dataset_id: description: - The ID of the dataset containing this table. required: false type: str project_id: description: - The ID of the project containing this table. required: false type: str table_id: description: - The ID of the the table. required: false type: str clustering: description: - One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. elements: str required: false type: list description: description: - A user-friendly description of the dataset. required: false type: str friendly_name: description: - A descriptive name for this table. required: false type: str labels: description: - The labels associated with this dataset. You can use these to organize and group your datasets . required: false type: dict name: description: - Name of the table. required: false type: str num_rows: description: - The number of rows of data in this table, excluding any data in the streaming buffer. required: false type: int view: description: - The view definition. required: false type: dict suboptions: use_legacy_sql: description: - Specifies whether to use BigQuery's legacy SQL for this view . required: false type: bool user_defined_function_resources: description: - Describes user-defined function resources used in the query. elements: dict required: false type: list suboptions: inline_code: description: - An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. required: false type: str resource_uri: description: - A code resource to load from a Google Cloud Storage URI (gs://bucket/path). required: false type: str time_partitioning: description: - If specified, configures time-based partitioning for this table. required: false type: dict suboptions: expiration_ms: description: - Number of milliseconds for which to keep the storage for a partition. required: false type: int field: description: - If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. required: false type: str type: description: - The only type supported is DAY, which will generate one partition per day. - 'Some valid choices include: "DAY"' required: false type: str schema: description: - Describes the schema of this table. required: false type: dict suboptions: fields: description: - Describes the fields in a table. elements: dict required: false type: list suboptions: description: description: - The field description. The maximum length is 1,024 characters. required: false type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD. elements: str required: false type: list mode: description: - The field mode. - 'Some valid choices include: "NULLABLE", "REQUIRED", "REPEATED"' required: false type: str name: description: - The field name. required: false type: str type: description: - The field data type. - 'Some valid choices include: "STRING", "BYTES", "INTEGER", "FLOAT", "TIMESTAMP", "DATE", "TIME", "DATETIME", "RECORD"' required: false type: str encryption_configuration: description: - Custom encryption configuration. required: false type: dict suboptions: kms_key_name: description: - Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. required: false type: str expiration_time: description: - The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. required: false type: int external_data_configuration: description: - Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. required: false type: dict suboptions: autodetect: description: - Try to detect schema and format options automatically. Any option specified explicitly will be honored. required: false type: bool compression: description: - The compression type of the data source. - 'Some valid choices include: "GZIP", "NONE"' required: false type: str ignore_unknown_values: description: - Indicates if BigQuery should allow extra values that are not represented in the table schema . required: false type: bool max_bad_records: description: - The maximum number of bad records that BigQuery can ignore when reading data . required: false type: int source_format: description: - The data format. - 'Some valid choices include: "CSV", "GOOGLE_SHEETS", "NEWLINE_DELIMITED_JSON", "AVRO", "DATASTORE_BACKUP", "BIGTABLE", "ORC"' required: false type: str source_uris: description: - The fully-qualified URIs that point to your data in Google Cloud. - 'For Google Cloud Storage URIs: Each URI can contain one ''*'' wildcard character and it must come after the ''bucket'' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the ''*'' wildcard character is not allowed.' elements: str required: false type: list schema: description: - The schema for the data. Schema is required for CSV and JSON formats. required: false type: dict suboptions: fields: description: - Describes the fields in a table. elements: dict required: false type: list suboptions: description: description: - The field description. required: false type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD . elements: str required: false type: list mode: description: - Field mode. - 'Some valid choices include: "NULLABLE", "REQUIRED", "REPEATED"' required: false type: str name: description: - Field name. required: false type: str type: description: - Field data type. - 'Some valid choices include: "STRING", "BYTES", "INTEGER", "FLOAT", "TIMESTAMP", "DATE", "TIME", "DATETIME", "RECORD"' required: false type: str google_sheets_options: description: - Additional options if sourceFormat is set to GOOGLE_SHEETS. required: false type: dict suboptions: skip_leading_rows: description: - The number of rows at the top of a Google Sheet that BigQuery will skip when reading the data. required: false type: int csv_options: description: - Additional properties to set if sourceFormat is set to CSV. required: false type: dict suboptions: allow_jagged_rows: description: - Indicates if BigQuery should accept rows that are missing trailing optional columns . required: false type: bool allow_quoted_newlines: description: - Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file . required: false type: bool encoding: description: - The character encoding of the data. - 'Some valid choices include: "UTF-8", "ISO-8859-1"' required: false type: str field_delimiter: description: - The separator for fields in a CSV file. required: false type: str quote: description: - The value that is used to quote data sections in a CSV file. required: false type: str skip_leading_rows: description: - The number of rows at the top of a CSV file that BigQuery will skip when reading the data. required: false type: int bigtable_options: description: - Additional options if sourceFormat is set to BIGTABLE. required: false type: dict suboptions: ignore_unspecified_column_families: description: - If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema . required: false type: bool read_rowkey_as_string: description: - If field is true, then the rowkey column families will be read and converted to string. required: false type: bool column_families: description: - List of column families to expose in the table schema along with their types. elements: dict required: false type: list suboptions: columns: description: - Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. elements: dict required: false type: list suboptions: encoding: description: - The encoding of the values when the type is not STRING. - 'Some valid choices include: "TEXT", "BINARY"' required: false type: str field_name: description: - If the qualifier is not a valid BigQuery field identifier, a valid identifier must be provided as the column field name and is used as field name in queries. required: false type: str only_read_latest: description: - If this is set, only the latest version of value in this column are exposed . required: false type: bool qualifier_string: description: - Qualifier of the column. required: true type: str type: description: - The type to convert the value in cells of this column. - 'Some valid choices include: "BYTES", "STRING", "INTEGER", "FLOAT", "BOOLEAN"' required: false type: str encoding: description: - The encoding of the values when the type is not STRING. - 'Some valid choices include: "TEXT", "BINARY"' required: false type: str family_id: description: - Identifier of the column family. required: false type: str only_read_latest: description: - If this is set only the latest version of value are exposed for all columns in this column family . required: false type: bool type: description: - The type to convert the value in cells of this column family. - 'Some valid choices include: "BYTES", "STRING", "INTEGER", "FLOAT", "BOOLEAN"' required: false type: str dataset: description: - Name of the dataset. required: false type: str project: description: - The Google Cloud Platform project to use. type: str auth_kind: description: - The type of credential used. type: str required: true choices: - application - machineaccount - serviceaccount service_account_contents: description: - The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it. type: jsonarg service_account_file: description: - The path of a Service Account JSON file if serviceaccount is selected as type. type: path service_account_email: description: - An optional service account email address if machineaccount is selected and the user does not wish to use the default email. type: str scopes: description: - Array of scopes to be used type: list elements: str env_type: description: - Specifies which Ansible environment you're running this module within. - This should not be set unless you know what you're doing. - This only alters the User Agent string for any API requests. type: str ''' EXAMPLES = ''' - name: create a dataset google.cloud.gcp_bigquery_dataset: name: example_dataset dataset_reference: dataset_id: example_dataset project: "{{ gcp_project }}" auth_kind: "{{ gcp_cred_kind }}" service_account_file: "{{ gcp_cred_file }}" state: present register: dataset - name: create a table google.cloud.gcp_bigquery_table: name: example_table dataset: example_dataset table_reference: dataset_id: example_dataset project_id: test_project table_id: example_table project: test_project auth_kind: serviceaccount service_account_file: "/tmp/auth.pem" state: present ''' RETURN = ''' tableReference: description: - Reference describing the ID of this table. returned: success type: complex contains: datasetId: description: - The ID of the dataset containing this table. returned: success type: str projectId: description: - The ID of the project containing this table. returned: success type: str tableId: description: - The ID of the the table. returned: success type: str clustering: description: - One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. returned: success type: list creationTime: description: - The time when this dataset was created, in milliseconds since the epoch. returned: success type: int description: description: - A user-friendly description of the dataset. returned: success type: str friendlyName: description: - A descriptive name for this table. returned: success type: str id: description: - An opaque ID uniquely identifying the table. returned: success type: str labels: description: - The labels associated with this dataset. You can use these to organize and group your datasets . returned: success type: dict lastModifiedTime: description: - The time when this table was last modified, in milliseconds since the epoch. returned: success type: int location: description: - The geographic location where the table resides. This value is inherited from the dataset. returned: success type: str name: description: - Name of the table. returned: success type: str numBytes: description: - The size of this table in bytes, excluding any data in the streaming buffer. returned: success type: int numLongTermBytes: description: - The number of bytes in the table that are considered "long-term storage". returned: success type: int numRows: description: - The number of rows of data in this table, excluding any data in the streaming buffer. returned: success type: int requirePartitionFilter: description: - If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. returned: success type: bool type: description: - Describes the table type. returned: success type: str view: description: - The view definition. returned: success type: complex contains: useLegacySql: description: - Specifies whether to use BigQuery's legacy SQL for this view . returned: success type: bool userDefinedFunctionResources: description: - Describes user-defined function resources used in the query. returned: success type: complex contains: inlineCode: description: - An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. returned: success type: str resourceUri: description: - A code resource to load from a Google Cloud Storage URI (gs://bucket/path). returned: success type: str timePartitioning: description: - If specified, configures time-based partitioning for this table. returned: success type: complex contains: expirationMs: description: - Number of milliseconds for which to keep the storage for a partition. returned: success type: int field: description: - If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. returned: success type: str type: description: - The only type supported is DAY, which will generate one partition per day. returned: success type: str streamingBuffer: description: - Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer. returned: success type: complex contains: estimatedBytes: description: - A lower-bound estimate of the number of bytes currently in the streaming buffer. returned: success type: int estimatedRows: description: - A lower-bound estimate of the number of rows currently in the streaming buffer. returned: success type: int oldestEntryTime: description: - Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available. returned: success type: int schema: description: - Describes the schema of this table. returned: success type: complex contains: fields: description: - Describes the fields in a table. returned: success type: complex contains: description: description: - The field description. The maximum length is 1,024 characters. returned: success type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD. returned: success type: list mode: description: - The field mode. returned: success type: str name: description: - The field name. returned: success type: str type: description: - The field data type. returned: success type: str encryptionConfiguration: description: - Custom encryption configuration. returned: success type: complex contains: kmsKeyName: description: - Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. returned: success type: str expirationTime: description: - The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. returned: success type: int externalDataConfiguration: description: - Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. returned: success type: complex contains: autodetect: description: - Try to detect schema and format options automatically. Any option specified explicitly will be honored. returned: success type: bool compression: description: - The compression type of the data source. returned: success type: str ignoreUnknownValues: description: - Indicates if BigQuery should allow extra values that are not represented in the table schema . returned: success type: bool maxBadRecords: description: - The maximum number of bad records that BigQuery can ignore when reading data . returned: success type: int sourceFormat: description: - The data format. returned: success type: str sourceUris: description: - The fully-qualified URIs that point to your data in Google Cloud. - 'For Google Cloud Storage URIs: Each URI can contain one ''*'' wildcard character and it must come after the ''bucket'' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the ''*'' wildcard character is not allowed.' returned: success type: list schema: description: - The schema for the data. Schema is required for CSV and JSON formats. returned: success type: complex contains: fields: description: - Describes the fields in a table. returned: success type: complex contains: description: description: - The field description. returned: success type: str fields: description: - Describes the nested schema fields if the type property is set to RECORD . returned: success type: list mode: description: - Field mode. returned: success type: str name: description: - Field name. returned: success type: str type: description: - Field data type. returned: success type: str googleSheetsOptions: description: - Additional options if sourceFormat is set to GOOGLE_SHEETS. returned: success type: complex contains: skipLeadingRows: description: - The number of rows at the top of a Google Sheet that BigQuery will skip when reading the data. returned: success type: int csvOptions: description: - Additional properties to set if sourceFormat is set to CSV. returned: success type: complex contains: allowJaggedRows: description: - Indicates if BigQuery should accept rows that are missing trailing optional columns . returned: success type: bool allowQuotedNewlines: description: - Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file . returned: success type: bool encoding: description: - The character encoding of the data. returned: success type: str fieldDelimiter: description: - The separator for fields in a CSV file. returned: success type: str quote: description: - The value that is used to quote data sections in a CSV file. returned: success type: str skipLeadingRows: description: - The number of rows at the top of a CSV file that BigQuery will skip when reading the data. returned: success type: int bigtableOptions: description: - Additional options if sourceFormat is set to BIGTABLE. returned: success type: complex contains: ignoreUnspecifiedColumnFamilies: description: - If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema . returned: success type: bool readRowkeyAsString: description: - If field is true, then the rowkey column families will be read and converted to string. returned: success type: bool columnFamilies: description: - List of column families to expose in the table schema along with their types. returned: success type: complex contains: columns: description: - Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. returned: success type: complex contains: encoding: description: - The encoding of the values when the type is not STRING. returned: success type: str fieldName: description: - If the qualifier is not a valid BigQuery field identifier, a valid identifier must be provided as the column field name and is used as field name in queries. returned: success type: str onlyReadLatest: description: - If this is set, only the latest version of value in this column are exposed . returned: success type: bool qualifierString: description: - Qualifier of the column. returned: success type: str type: description: - The type to convert the value in cells of this column. returned: success type: str encoding: description: - The encoding of the values when the type is not STRING. returned: success type: str familyId: description: - Identifier of the column family. returned: success type: str onlyReadLatest: description: - If this is set only the latest version of value are exposed for all columns in this column family . returned: success type: bool type: description: - The type to convert the value in cells of this column family. returned: success type: str dataset: description: - Name of the dataset. returned: success type: str ''' ################################################################################ # Imports ################################################################################ from ansible_collections.google.cloud.plugins.module_utils.gcp_utils import ( navigate_hash, GcpSession, GcpModule, GcpRequest, remove_nones_from_dict, replace_resource_dict, ) import json ################################################################################ # Main ################################################################################ def main(): """Main function""" module = GcpModule( argument_spec=dict( state=dict(default='present', choices=['present', 'absent'], type='str'), table_reference=dict(type='dict', options=dict(dataset_id=dict(type='str'), project_id=dict(type='str'), table_id=dict(type='str'))), clustering=dict(type='list', elements='str'), description=dict(type='str'), friendly_name=dict(type='str'), labels=dict(type='dict'), name=dict(type='str'), num_rows=dict(type='int'), view=dict( type='dict', options=dict( use_legacy_sql=dict(type='bool'), user_defined_function_resources=dict( type='list', elements='dict', options=dict(inline_code=dict(type='str'), resource_uri=dict(type='str')) ), ), ), time_partitioning=dict(type='dict', options=dict(expiration_ms=dict(type='int'), field=dict(type='str'), type=dict(type='str'))), schema=dict( type='dict', options=dict( fields=dict( type='list', elements='dict', options=dict( description=dict(type='str'), fields=dict(type='list', elements='str'), mode=dict(type='str'), name=dict(type='str'), type=dict(type='str'), ), ) ), ), encryption_configuration=dict(type='dict', options=dict(kms_key_name=dict(type='str'))), expiration_time=dict(type='int'), external_data_configuration=dict( type='dict', options=dict( autodetect=dict(type='bool'), compression=dict(type='str'), ignore_unknown_values=dict(type='bool'), max_bad_records=dict(default=0, type='int'), source_format=dict(type='str'), source_uris=dict(type='list', elements='str'), schema=dict( type='dict', options=dict( fields=dict( type='list', elements='dict', options=dict( description=dict(type='str'), fields=dict(type='list', elements='str'), mode=dict(type='str'), name=dict(type='str'), type=dict(type='str'), ), ) ), ), google_sheets_options=dict(type='dict', options=dict(skip_leading_rows=dict(default=0, type='int'))), csv_options=dict( type='dict', options=dict( allow_jagged_rows=dict(type='bool'), allow_quoted_newlines=dict(type='bool'), encoding=dict(type='str'), field_delimiter=dict(type='str'), quote=dict(type='str'), skip_leading_rows=dict(default=0, type='int'), ), ), bigtable_options=dict( type='dict', options=dict( ignore_unspecified_column_families=dict(type='bool'), read_rowkey_as_string=dict(type='bool'), column_families=dict( type='list', elements='dict', options=dict( columns=dict( type='list', elements='dict', options=dict( encoding=dict(type='str'), field_name=dict(type='str'), only_read_latest=dict(type='bool'), qualifier_string=dict(required=True, type='str'), type=dict(type='str'), ), ), encoding=dict(type='str'), family_id=dict(type='str'), only_read_latest=dict(type='bool'), type=dict(type='str'), ), ), ), ), ), ), dataset=dict(type='str'), ) ) if not module.params['scopes']: module.params['scopes'] = ['https://www.googleapis.com/auth/bigquery'] state = module.params['state'] kind = 'bigquery#table' fetch = fetch_resource(module, self_link(module), kind) changed = False if fetch: if state == 'present': if is_different(module, fetch): update(module, self_link(module), kind) fetch = fetch_resource(module, self_link(module), kind) changed = True else: delete(module, self_link(module), kind) fetch = {} changed = True else: if state == 'present': fetch = create(module, collection(module), kind) changed = True else: fetch = {} fetch.update({'changed': changed}) module.exit_json(**fetch) def create(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.post(link, resource_to_request(module)), kind) def update(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.put(link, resource_to_request(module)), kind) def delete(module, link, kind): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.delete(link), kind) def resource_to_request(module): request = { u'kind': 'bigquery#table', u'tableReference': TableTablereference(module.params.get('table_reference', {}), module).to_request(), u'clustering': module.params.get('clustering'), u'description': module.params.get('description'), u'friendlyName': module.params.get('friendly_name'), u'labels': module.params.get('labels'), u'name': module.params.get('name'), u'numRows': module.params.get('num_rows'), u'view': TableView(module.params.get('view', {}), module).to_request(), u'timePartitioning': TableTimepartitioning(module.params.get('time_partitioning', {}), module).to_request(), u'schema': TableSchema(module.params.get('schema', {}), module).to_request(), u'encryptionConfiguration': TableEncryptionconfiguration(module.params.get('encryption_configuration', {}), module).to_request(), u'expirationTime': module.params.get('expiration_time'), u'externalDataConfiguration': TableExternaldataconfiguration(module.params.get('external_data_configuration', {}), module).to_request(), } return_vals = {} for k, v in request.items(): if v or v is False: return_vals[k] = v return return_vals def fetch_resource(module, link, kind, allow_not_found=True): auth = GcpSession(module, 'bigquery') return return_if_object(module, auth.get(link), kind, allow_not_found) def self_link(module): return "https://bigquery.googleapis.com/bigquery/v2/projects/{project}/datasets/{dataset}/tables/{name}".format(**module.params) def collection(module): return "https://bigquery.googleapis.com/bigquery/v2/projects/{project}/datasets/{dataset}/tables".format(**module.params) def return_if_object(module, response, kind, allow_not_found=False): # If not found, return nothing. if allow_not_found and response.status_code == 404: return None # If no content, return nothing. if response.status_code == 204: return None try: module.raise_for_status(response) result = response.json() except getattr(json.decoder, 'JSONDecodeError', ValueError): module.fail_json(msg="Invalid JSON response with error: %s" % response.text) if navigate_hash(result, ['error', 'errors']): module.fail_json(msg=navigate_hash(result, ['error', 'errors'])) return result def is_different(module, response): request = resource_to_request(module) response = response_to_hash(module, response) # Remove all output-only from response. response_vals = {} for k, v in response.items(): if k in request: response_vals[k] = v request_vals = {} for k, v in request.items(): if k in response: request_vals[k] = v return GcpRequest(request_vals) != GcpRequest(response_vals) # Remove unnecessary properties from the response. # This is for doing comparisons with Ansible's current parameters. def response_to_hash(module, response): return { u'tableReference': TableTablereference(response.get(u'tableReference', {}), module).from_response(), u'clustering': response.get(u'clustering'), u'creationTime': response.get(u'creationTime'), u'description': response.get(u'description'), u'friendlyName': response.get(u'friendlyName'), u'id': response.get(u'id'), u'labels': response.get(u'labels'), u'lastModifiedTime': response.get(u'lastModifiedTime'), u'location': response.get(u'location'), u'name': response.get(u'name'), u'numBytes': response.get(u'numBytes'), u'numLongTermBytes': response.get(u'numLongTermBytes'), u'numRows': response.get(u'numRows'), u'requirePartitionFilter': response.get(u'requirePartitionFilter'), u'type': response.get(u'type'), u'view': TableView(response.get(u'view', {}), module).from_response(), u'timePartitioning': TableTimepartitioning(response.get(u'timePartitioning', {}), module).from_response(), u'streamingBuffer': TableStreamingbuffer(response.get(u'streamingBuffer', {}), module).from_response(), u'schema': TableSchema(response.get(u'schema', {}), module).from_response(), u'encryptionConfiguration': TableEncryptionconfiguration(response.get(u'encryptionConfiguration', {}), module).from_response(), u'expirationTime': response.get(u'expirationTime'), u'externalDataConfiguration': TableExternaldataconfiguration(response.get(u'externalDataConfiguration', {}), module).from_response(), } class TableTablereference(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( {u'datasetId': self.request.get('dataset_id'), u'projectId': self.request.get('project_id'), u'tableId': self.request.get('table_id')} ) def from_response(self): return remove_nones_from_dict( {u'datasetId': self.request.get(u'datasetId'), u'projectId': self.request.get(u'projectId'), u'tableId': self.request.get(u'tableId')} ) class TableView(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'useLegacySql': self.request.get('use_legacy_sql'), u'userDefinedFunctionResources': TableUserdefinedfunctionresourcesArray( self.request.get('user_defined_function_resources', []), self.module ).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'useLegacySql': self.request.get(u'useLegacySql'), u'userDefinedFunctionResources': TableUserdefinedfunctionresourcesArray( self.request.get(u'userDefinedFunctionResources', []), self.module ).from_response(), } ) class TableUserdefinedfunctionresourcesArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict({u'inlineCode': item.get('inline_code'), u'resourceUri': item.get('resource_uri')}) def _response_from_item(self, item): return remove_nones_from_dict({u'inlineCode': item.get(u'inlineCode'), u'resourceUri': item.get(u'resourceUri')}) class TableTimepartitioning(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( {u'expirationMs': self.request.get('expiration_ms'), u'field': self.request.get('field'), u'type': self.request.get('type')} ) def from_response(self): return remove_nones_from_dict( {u'expirationMs': self.request.get(u'expirationMs'), u'field': self.request.get(u'field'), u'type': self.request.get(u'type')} ) class TableStreamingbuffer(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({}) def from_response(self): return remove_nones_from_dict({}) class TableSchema(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get('fields', []), self.module).to_request()}) def from_response(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get(u'fields', []), self.module).from_response()}) class TableFieldsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'description': item.get('description'), u'fields': item.get('fields'), u'mode': item.get('mode'), u'name': item.get('name'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'description': item.get(u'description'), u'fields': item.get(u'fields'), u'mode': item.get(u'mode'), u'name': item.get(u'name'), u'type': item.get(u'type'), } ) class TableEncryptionconfiguration(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'kmsKeyName': self.request.get('kms_key_name')}) def from_response(self): return remove_nones_from_dict({u'kmsKeyName': self.request.get(u'kmsKeyName')}) class TableExternaldataconfiguration(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'autodetect': self.request.get('autodetect'), u'compression': self.request.get('compression'), u'ignoreUnknownValues': self.request.get('ignore_unknown_values'), u'maxBadRecords': self.request.get('max_bad_records'), u'sourceFormat': self.request.get('source_format'), u'sourceUris': self.request.get('source_uris'), u'schema': TableSchema(self.request.get('schema', {}), self.module).to_request(), u'googleSheetsOptions': TableGooglesheetsoptions(self.request.get('google_sheets_options', {}), self.module).to_request(), u'csvOptions': TableCsvoptions(self.request.get('csv_options', {}), self.module).to_request(), u'bigtableOptions': TableBigtableoptions(self.request.get('bigtable_options', {}), self.module).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'autodetect': self.request.get(u'autodetect'), u'compression': self.request.get(u'compression'), u'ignoreUnknownValues': self.request.get(u'ignoreUnknownValues'), u'maxBadRecords': self.request.get(u'maxBadRecords'), u'sourceFormat': self.request.get(u'sourceFormat'), u'sourceUris': self.request.get(u'sourceUris'), u'schema': TableSchema(self.request.get(u'schema', {}), self.module).from_response(), u'googleSheetsOptions': TableGooglesheetsoptions(self.request.get(u'googleSheetsOptions', {}), self.module).from_response(), u'csvOptions': TableCsvoptions(self.request.get(u'csvOptions', {}), self.module).from_response(), u'bigtableOptions': TableBigtableoptions(self.request.get(u'bigtableOptions', {}), self.module).from_response(), } ) class TableSchema(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get('fields', []), self.module).to_request()}) def from_response(self): return remove_nones_from_dict({u'fields': TableFieldsArray(self.request.get(u'fields', []), self.module).from_response()}) class TableFieldsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'description': item.get('description'), u'fields': item.get('fields'), u'mode': item.get('mode'), u'name': item.get('name'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'description': item.get(u'description'), u'fields': item.get(u'fields'), u'mode': item.get(u'mode'), u'name': item.get(u'name'), u'type': item.get(u'type'), } ) class TableGooglesheetsoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict({u'skipLeadingRows': self.request.get('skip_leading_rows')}) def from_response(self): return remove_nones_from_dict({u'skipLeadingRows': self.request.get(u'skipLeadingRows')}) class TableCsvoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'allowJaggedRows': self.request.get('allow_jagged_rows'), u'allowQuotedNewlines': self.request.get('allow_quoted_newlines'), u'encoding': self.request.get('encoding'), u'fieldDelimiter': self.request.get('field_delimiter'), u'quote': self.request.get('quote'), u'skipLeadingRows': self.request.get('skip_leading_rows'), } ) def from_response(self): return remove_nones_from_dict( { u'allowJaggedRows': self.request.get(u'allowJaggedRows'), u'allowQuotedNewlines': self.request.get(u'allowQuotedNewlines'), u'encoding': self.request.get(u'encoding'), u'fieldDelimiter': self.request.get(u'fieldDelimiter'), u'quote': self.request.get(u'quote'), u'skipLeadingRows': self.request.get(u'skipLeadingRows'), } ) class TableBigtableoptions(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = {} def to_request(self): return remove_nones_from_dict( { u'ignoreUnspecifiedColumnFamilies': self.request.get('ignore_unspecified_column_families'), u'readRowkeyAsString': self.request.get('read_rowkey_as_string'), u'columnFamilies': TableColumnfamiliesArray(self.request.get('column_families', []), self.module).to_request(), } ) def from_response(self): return remove_nones_from_dict( { u'ignoreUnspecifiedColumnFamilies': self.request.get(u'ignoreUnspecifiedColumnFamilies'), u'readRowkeyAsString': self.request.get(u'readRowkeyAsString'), u'columnFamilies': TableColumnfamiliesArray(self.request.get(u'columnFamilies', []), self.module).from_response(), } ) class TableColumnfamiliesArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'columns': TableColumnsArray(item.get('columns', []), self.module).to_request(), u'encoding': item.get('encoding'), u'familyId': item.get('family_id'), u'onlyReadLatest': item.get('only_read_latest'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'columns': TableColumnsArray(item.get(u'columns', []), self.module).from_response(), u'encoding': item.get(u'encoding'), u'familyId': item.get(u'familyId'), u'onlyReadLatest': item.get(u'onlyReadLatest'), u'type': item.get(u'type'), } ) class TableColumnsArray(object): def __init__(self, request, module): self.module = module if request: self.request = request else: self.request = [] def to_request(self): items = [] for item in self.request: items.append(self._request_for_item(item)) return items def from_response(self): items = [] for item in self.request: items.append(self._response_from_item(item)) return items def _request_for_item(self, item): return remove_nones_from_dict( { u'encoding': item.get('encoding'), u'fieldName': item.get('field_name'), u'onlyReadLatest': item.get('only_read_latest'), u'qualifierString': item.get('qualifier_string'), u'type': item.get('type'), } ) def _response_from_item(self, item): return remove_nones_from_dict( { u'encoding': item.get(u'encoding'), u'fieldName': item.get(u'fieldName'), u'onlyReadLatest': item.get(u'onlyReadLatest'), u'qualifierString': item.get(u'qualifierString'), u'type': item.get(u'type'), } ) if __name__ == '__main__': main()