# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.service_client import ServiceClient
from msrest import Configuration, Serializer, Deserializer
from .version import VERSION
from msrest.pipeline import ClientRawResponse
from . import models
class TextAnalyticsAPIConfiguration(Configuration):
"""Configuration for TextAnalyticsAPI
Note that all parameters used to create this instance are saved as instance
attributes.
:param azure_region: Supported Azure regions for Cognitive Services
endpoints. Possible values include: 'westus', 'westeurope',
'southeastasia', 'eastus2', 'westcentralus', 'westus2', 'eastus',
'southcentralus', 'northeurope', 'eastasia', 'australiaeast',
'brazilsouth'
:type azure_region: str or
~azure.cognitiveservices.language.textanalytics.models.AzureRegions
:param credentials: Subscription credentials which uniquely identify
client subscription.
:type credentials: None
"""
def __init__(
self, azure_region, credentials):
if azure_region is None:
raise ValueError("Parameter 'azure_region' must not be None.")
if credentials is None:
raise ValueError("Parameter 'credentials' must not be None.")
base_url = 'https://{AzureRegion}.api.cognitive.microsoft.com/text/analytics'
super(TextAnalyticsAPIConfiguration, self).__init__(base_url)
self.add_user_agent('azure-cognitiveservices-language-textanalytics/{}'.format(VERSION))
self.azure_region = azure_region
self.credentials = credentials
[docs]class TextAnalyticsAPI(object):
"""The Text Analytics API is a suite of text analytics web services built with best-in-class Microsoft machine learning algorithms. The API can be used to analyze unstructured text for tasks such as sentiment analysis, key phrase extraction and language detection. No training data is needed to use this API; just bring your text data. This API uses advanced natural language processing techniques to deliver best in class predictions. Further documentation can be found in https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview
:ivar config: Configuration for client.
:vartype config: TextAnalyticsAPIConfiguration
:param azure_region: Supported Azure regions for Cognitive Services
endpoints. Possible values include: 'westus', 'westeurope',
'southeastasia', 'eastus2', 'westcentralus', 'westus2', 'eastus',
'southcentralus', 'northeurope', 'eastasia', 'australiaeast',
'brazilsouth'
:type azure_region: str or
~azure.cognitiveservices.language.textanalytics.models.AzureRegions
:param credentials: Subscription credentials which uniquely identify
client subscription.
:type credentials: None
"""
def __init__(
self, azure_region, credentials):
self.config = TextAnalyticsAPIConfiguration(azure_region, credentials)
self._client = ServiceClient(self.config.credentials, self.config)
client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)}
self.api_version = 'v2.0'
self._serialize = Serializer(client_models)
self._deserialize = Deserializer(client_models)
[docs] def key_phrases(
self, documents=None, custom_headers=None, raw=False, **operation_config):
"""The API returns a list of strings denoting the key talking points in
the input text.
We employ techniques from Microsoft Office's sophisticated Natural
Language Processing toolkit. See the <a
href="https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages">Text
Analytics Documentation</a> for details about the languages that are
supported by key phrase extraction.
:param documents:
:type documents:
list[~azure.cognitiveservices.language.textanalytics.models.MultiLanguageInput]
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: KeyPhraseBatchResult or ClientRawResponse if raw=true
:rtype:
~azure.cognitiveservices.language.textanalytics.models.KeyPhraseBatchResult
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.cognitiveservices.language.textanalytics.models.ErrorResponseException>`
"""
input = models.MultiLanguageBatchInput(documents=documents)
# Construct URL
url = '/v2.0/keyPhrases'
path_format_arguments = {
'AzureRegion': self._serialize.url("self.config.azure_region", self.config.azure_region, 'AzureRegions', skip_quote=True)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(input, 'MultiLanguageBatchInput')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('KeyPhraseBatchResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
[docs] def detect_language(
self, documents=None, custom_headers=None, raw=False, **operation_config):
"""The API returns the detected language and a numeric score between 0 and
1.
Scores close to 1 indicate 100% certainty that the identified language
is true. A total of 120 languages are supported.
:param documents:
:type documents:
list[~azure.cognitiveservices.language.textanalytics.models.Input]
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: LanguageBatchResult or ClientRawResponse if raw=true
:rtype:
~azure.cognitiveservices.language.textanalytics.models.LanguageBatchResult
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.cognitiveservices.language.textanalytics.models.ErrorResponseException>`
"""
input = models.BatchInput(documents=documents)
# Construct URL
url = '/v2.0/languages'
path_format_arguments = {
'AzureRegion': self._serialize.url("self.config.azure_region", self.config.azure_region, 'AzureRegions', skip_quote=True)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(input, 'BatchInput')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LanguageBatchResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
[docs] def sentiment(
self, documents=None, custom_headers=None, raw=False, **operation_config):
"""The API returns a numeric score between 0 and 1.
Scores close to 1 indicate positive sentiment, while scores close to 0
indicate negative sentiment. Sentiment score is generated using
classification techniques. The input features to the classifier include
n-grams, features generated from part-of-speech tags, and word
embeddings. See the <a
href="https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages">Text
Analytics Documentation</a> for details about the languages that are
supported by sentiment analysis.
:param documents:
:type documents:
list[~azure.cognitiveservices.language.textanalytics.models.MultiLanguageInput]
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: SentimentBatchResult or ClientRawResponse if raw=true
:rtype:
~azure.cognitiveservices.language.textanalytics.models.SentimentBatchResult
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.cognitiveservices.language.textanalytics.models.ErrorResponseException>`
"""
input = models.MultiLanguageBatchInput(documents=documents)
# Construct URL
url = '/v2.0/sentiment'
path_format_arguments = {
'AzureRegion': self._serialize.url("self.config.azure_region", self.config.azure_region, 'AzureRegions', skip_quote=True)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(input, 'MultiLanguageBatchInput')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SentimentBatchResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized