Installation

The package is available at PyPI and it can be installed via pip by executing following command:

pip install groupdocs-classification-cloud

Requirements

• Python 2.7 or 3.4+
• pip package manager
• GroupDocs Cloud credentials — Client ID and Client Secret from the Dashboard

Dependencies

The SDK automatically installs the following packages:

Document Classification Python Cloud REST API

GroupDocs.Classification Cloud SDK for Python is a powerful REST API designed for developers needing advanced text and document classification capabilities. Supporting multiple document formats and a wide range of taxonomies, this API allows you to classify raw text, documents, and batches of texts across various categories, including IAB-2, Documents, and Sentiment taxonomies. The API is secured with JWT authentication, and the Python SDK simplifies integration into your web apps, scripts, and automation workflows.

Document Classification Features

File Format Support - Classify text and documents in many formats like PDF, DOCX, TXT.
Multi-language Support - Classify documents in multiple languages including English, Chinese, Spanish, and German.
Custom Classification - Create custom classification categories to fit your needs.
Batch Classification - Classify up to 10 texts in one request.
Content-Based Classification - Classify documents based on their body content.

Taxonomy Classification Features

IAB-2 Taxonomy - Classify using the IAB-2 standard taxonomy for digital content and advertising.
Document Taxonomy - Classify documents into categories like ADVE, Email, Form, Letter, Memo, Invoice, Report, Resume.
Sentiment Taxonomy - Classify text into Positive or Negative sentiment.
Sentiment3 Taxonomy - Classify text into Positive, Neutral, or Negative sentiment.

API Integration Features

RESTful API - Access classification via a REST API for easy integration.
Real-time Classification - Perform real-time classification of text and documents.
JSON and XML Responses - Receive results in JSON or XML for easy system integration.

Security and Authentication Features

JWT Authentication - Secure API access with JWT authentication.
Client ID and Secret - Use Client ID and Secret for secure API calls.
Data Encryption - Encrypt communication between client apps and Classification Cloud API.

Performance Features

Scalable Infrastructure - Handles large document volumes efficiently.
High Accuracy - Delivers highly accurate results using advanced ML algorithms.
Fast Processing - Optimized for fast classification for high‑performance apps.

Licensing and Authentication

Evaluation Mode - Try the API with a free trial account.
Secure Authentication - Use Client ID and Client Secret for secure API access.
MIT License - The Python SDK is licensed under the MIT License.

Supported Document Formats

GroupDocs.Classification Cloud supports classification for the following file formats:

For the complete format list, see the documentation.

Supported Taxonomies

IAB-2 Taxonomy - Categories like Automotive, Books & Literature, Business & Finance, Technology & Computing, Travel, and more.
Documents Taxonomy - Classifications like ADVE, Email, Form, Letter, Memo, News, Invoice, Report, Resume, Scientific, Other.
Sentiment Taxonomy - Binary sentiment classification: Negative and Positive.
Sentiment3 Taxonomy - Three‑class sentiment: Negative, Neutral, Positive.

For taxonomy details, see the documentation.

Quick Start

Get your API credentials

To use GroupDocs.Classification Cloud, sign up at GroupDocs.Cloud Dashboard and get your Client ID and Client Secret.

Initialize the API

Use the following code to start using the GroupDocs.Classification Cloud SDK for Python:

import groupdocsclassificationcloud
from groupdocsclassificationcloud import ClassificationApi, Configuration

# Get your ClientId and ClientSecret at https://dashboard.groupdocs.cloud
client_id = "YourClientId"
client_secret = "YourClientSecret"

# Create API configuration
configuration = Configuration(client_id, client_secret, "https://api.groupdocs.cloud")

# Create instance of the Classification API
classification_api = ClassificationApi(configuration=configuration)

Classify raw text

Once initialized, use this basic example to classify raw text:

import groupdocsclassificationcloud
from groupdocsclassificationcloud import ClassificationApi, Configuration, BaseRequest, ClassifyRequest

client_id = "YourClientId"
client_secret = "YourClientSecret"

configuration = Configuration(client_id, client_secret, "https://api.groupdocs.cloud")
classification_api = ClassificationApi(configuration=configuration)

request = ClassifyRequest(BaseRequest("Try text classification"), 3)
result = classification_api.classify(request)

print("Best class name = " + result.best_class_name)
print("Best class probability = " + str(result.best_class_probability))

With this quick start guide, you’re all set to begin classifying text and documents using GroupDocs.Classification Cloud in your Python applications. For more details, visit the documentation.

Get Supported File Formats

Retrieve the full list of supported file formats available through the Classification API.

import groupdocsclassificationcloud
from groupdocsclassificationcloud import ClassificationApi, Configuration, GetSupportedFileFormatsRequest

client_id = "YourClientId"
client_secret = "YourClientSecret"

configuration = Configuration(client_id, client_secret, "https://api.groupdocs.cloud")
classification_api = ClassificationApi(configuration=configuration)

request = GetSupportedFileFormatsRequest()
response = classification_api.get_supported_file_formats(request)

print("Supported file-formats:")
for fmt in response.formats:
    print("{0} ({1})".format(fmt.file_format, fmt.extension))

Classify Document from Cloud Storage

Classify a document stored in GroupDocs Cloud storage using the Documents taxonomy.

import groupdocsclassificationcloud
from groupdocsclassificationcloud import ClassificationApi, Configuration, BaseRequest, ClassifyRequest, FileInfo

client_id = "YourClientId"
client_secret = "YourClientSecret"

configuration = Configuration(client_id, client_secret, "https://api.groupdocs.cloud")
classification_api = ClassificationApi(configuration=configuration)

request = ClassifyRequest(
    BaseRequest(document=FileInfo(name="test_multi_pages.docx", folder="Temp/SdkTests/python"))
)
result = classification_api.classify(request)

print("Best class name = " + result.best_class_name)
print("Best class probability = " + str(result.best_class_probability))

Classify Text with Sentiment Taxonomy

Perform binary or three-class sentiment analysis on raw text.

import groupdocsclassificationcloud
from groupdocsclassificationcloud import ClassificationApi, Configuration, BaseRequest, ClassifyRequest

client_id = "YourClientId"
client_secret = "YourClientSecret"

configuration = Configuration(client_id, client_secret, "https://api.groupdocs.cloud")
classification_api = ClassificationApi(configuration=configuration)

request = ClassifyRequest(
    BaseRequest("This product exceeded my expectations!"),
    best_classes_count=1,
    taxonomy="Sentiment3"
)
result = classification_api.classify(request)

print("Sentiment = " + result.best_class_name)

Sample Projects on GitHub

The GroupDocs.Classification Cloud Python SDK repository includes ready-to-run unit tests and examples covering:

How to run the examples

1. Clone or download the SDK repository
2. Edit Settings/servercreds.json and set your AppSid and AppKey
3. Install dependencies: pip install groupdocs-classification-cloud -U
4. Run tests from the repository root: python -m unittest discover -s test

For more details, visit Getting Started.

Tags

Document Classification API | Python Cloud API | GroupDocs.Classification Cloud | REST API | Text Classification | Document Taxonomy | IAB-2 Taxonomy | Sentiment Taxonomy | Sentiment3 Taxonomy | JWT Authentication | Multi-language Support | Batch Classification | Content-Based Classification | Real-time Classification | Sentiment Analysis | Machine Learning Classification | High Accuracy Classification | Secure API Access | Cloud Storage Integration | Customer Feedback Analysis | Social Media Monitoring | Cross-platform API