Install & Compatibility
Where this runs
tested against v2.21.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.95 runs
installs and imports cleanly · install 0.0s · import 1.576s · 70.2MB
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 6.1s · import 1.134s · 69MB
69MB installed
● package 69MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
LanguageServiceClient
✓ from google.cloud import language_v1
✗ from google.cloud import language_v1
This quickstart demonstrates how to perform sentiment analysis using the `google-cloud-language` library. It initializes the client and sends a text document for sentiment detection. Ensure your Google Cloud project has the Natural Language API enabled and that you've set up authentication, preferably using Application Default Credentials, for local development or deployed applications.
import os
from google.cloud import language_v1
# Set up Application Default Credentials if running locally
# This line is usually not needed when running on Google Cloud services (e.g., Compute Engine, Cloud Run)
# For local development, ensure GOOGLE_APPLICATION_CREDENTIALS points to a service account key file
# or run `gcloud auth application-default login`
# os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = os.environ.get('GOOGLE_APPLICATION_CREDENTIALS', '')
def analyze_sentiment(text_content):
"""Analyzes the sentiment of the provided text."""
client = language_v1.LanguageServiceClient()
# Available document types: PLAIN_TEXT, HTML
document = language_v1.types.Document(
content=text_content, type_=language_v1.Document.Type.PLAIN_TEXT
)
# Detects the sentiment of the document
sentiment = client.analyze_sentiment(request={'document': document}).document_sentiment
print(f"Text: {text_content}")
print(f"Sentiment Score: {sentiment.score}")
print(f"Sentiment Magnitude: {sentiment.magnitude}")
# Example usage
if __name__ == '__main__':
analyze_sentiment("Hello, world! This is a great day.")
analyze_sentiment("I am very unhappy with the service.")
Debug
Known issues
breakingThe Natural Language API v2 introduces breaking changes, including renaming the `language` field to `language_code` in responses and removing fields like `salience` and `wikipedia_url` for entity analysis. Ensure you use the correct client (`language_v1` or `language_v2`) and adapt your code accordingly.fixFor new projects or if you need v2 features, explicitly import `language_v2` (e.g., `from google.cloud import language_v2`). Review the v2 API documentation for specific field changes.
affects: API v2 (client library versions supporting v2, e.g., from `google.cloud import language_v2`)
gotchaDirect API Key authentication is generally not supported for Google Cloud client libraries. Attempting to use an API key might result in authentication errors.fixUse Application Default Credentials (ADC). For local development, run `gcloud auth application-default login` in your terminal. For deployed applications on Google Cloud, a service account attached to the resource is the preferred method.
affects: All versions
deprecatedThe direct import `from google.cloud.language import enums` is deprecated. Enums are now nested under the versioned types module (e.g., `language_v1.types.Document.Type`).fixUpdate imports to access enums directly via the versioned module, for example, `language_v1.Document.Type.PLAIN_TEXT`.
affects: Older versions allowed this; newer versions (2.0.0+) strongly encourage direct access via versioned `types`.
gotchaNaming your Python script `google.py`, `language.py`, or similar names can lead to import conflicts (shadowing) with the installed `google.cloud.language` library, causing `ImportError`.fixAlways use distinct names for your local Python files that do not conflict with installed package names.
affects: All versions (Python-specific issue)
Upgrade
Version history
2.21.0latest on PyPI · released Jun 22, 2026
Audit
Dependencies
google-api-corerequiredCore library for Google API clients, handling common functionality like retries and API versioning.
google-authrequiredManages authentication with Google Cloud, typically via Application Default Credentials (ADC).
protobufrequiredUsed for serializing and deserializing API request and response data.