| name | azure-ai-textanalytics-py |
| description | Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | cloud-infrastructure |
| category | azure |
| risk | unknown |
| source | community |
| tags | ["skill","cloud-infrastructure","azure","textanalytics"] |
Azure AI Text Analytics SDK for Python
Client library for Azure AI Language service NLP capabilities including sentiment, entities, key phrases, and more.
Installation
pip install azure-ai-textanalytics
Environment Variables
AZURE_LANGUAGE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
AZURE_LANGUAGE_KEY=<your-api-key>
Authentication
API Key
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.textanalytics import TextAnalyticsClient
endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
key = os.environ["AZURE_LANGUAGE_KEY"]
client = TextAnalyticsClient(endpoint, AzureKeyCredential(key))
Entra ID (Recommended)
from azure.ai.textanalytics import TextAnalyticsClient
from azure.identity import DefaultAzureCredential
client = TextAnalyticsClient(
endpoint=os.environ["AZURE_LANGUAGE_ENDPOINT"],
credential=DefaultAzureCredential()
)
Sentiment Analysis
documents = [
"I had a wonderful trip to Seattle last week!",
"The food was terrible and the service was slow."
]
result = client.analyze_sentiment(documents, show_opinion_mining=True)
for doc in result:
if not doc.is_error:
print(f"Sentiment: {doc.sentiment}")
print(f"Scores: pos={doc.confidence_scores.positive:.2f}, "
f"neg={doc.confidence_scores.negative:.2f}, "
)
sentence doc.sentences:
opinion sentence.mined_opinions:
target = opinion.target
()
assessment opinion.assessments:
()
