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A modern Python SDK for the Zoho Creator API

Project description

Zoho Creator Python SDK

PyPI version Build Status Coverage Status Python versions License: MIT

A modern Python SDK for interacting with the Zoho Creator API. This library provides a simple, intuitive, and fluent interface for managing your Zoho Creator applications, forms, records, and more. It is designed with a "zero-config" approach, making it easy to get started quickly and securely.

Requires Python 3.8.1+.

Key Features

  • Fluent Interface: Chain method calls for clean, readable, and intuitive API interactions.
  • Zero-Config Initialization: Automatically loads configuration from environment variables—no need to hardcode credentials.
  • OAuth 2.0 Handling: Robust OAuth2 authentication with automatic token refresh.
  • Pydantic Models: Strongly typed data models for all Zoho Creator entities, ensuring data validation and type safety.
  • Automatic Pagination: Generator-based pagination for effortlessly fetching all records without manual page handling.
  • Robust HTTP Client: Built on httpx with automatic retries, exponential backoff, and rate limiting.
  • Comprehensive Error Handling: A full suite of custom exception classes for predictable error handling.
  • Full Type Hinting: Modern, fully type-hinted codebase for excellent editor support and static analysis.

Installation

Install the SDK using pip:

pip install zoho-creator-sdk

Quick Start

The SDK is designed for a simple, fluent workflow. With zero-config initialization, you can get started in just a few lines of code.

First, set your environment variables. The client will automatically pick them up.

# OAuth2 Credentials
export ZOHO_CLIENT_ID="your_client_id"
export ZOHO_CLIENT_SECRET="your_client_secret"
export ZOHO_REFRESH_TOKEN="your_refresh_token"

# Datacenter (e.g., US, EU, IN, AU, CN, JP)
export ZOHO_CREATOR_DATACENTER="US"

Now, you can use the client in your Python code:

from zoho_creator_sdk import ZohoCreatorClient

# 1. Initialize the client with zero-config
# Credentials are automatically loaded from environment variables.
client = ZohoCreatorClient()

# 2. Discover your applications to find the correct owner and app link names
# The owner_name is typically your Zoho username.
applications = client.get_applications("your-owner-name")
print(f"Found {len(applications)} applications:")
for app in applications:
    print(f"  - {app.name} (Link Name: {app.link_name})")

# 3. Use the fluent interface to access a specific application and its components
# Replace with your actual app link name, owner name, and report link name.
app_context = client.app(app_link_name="my-app", owner_name="your-owner-name")
report_context = app_context.report("all-records")

# 4. Fetch records with automatic pagination
# The get_records() method returns a generator that handles pagination for you.
print("Fetching all records...")
for record in report_context.get_records():
    print(f"  - Record ID: {record.id}, Data: {record.data}")

# 5. Add a new record
form_context = app_context.form("my-form")
new_record_data = {"field1": "value1", "field2": "value2"}
response = form_context.add_record(data=new_record_data)
print(f"\nSuccessfully added new record with ID: {response['data']['id']}")

# 6. Update an existing record
update_data = {"field1": "new_value"}
# The record ID can be obtained from a previous get_records() call.
updated_response = report_context.update_record("RECORD_ID_HERE", data=update_data)
print(f"Successfully updated record: {updated_response['data']['id']}")

## Advanced Get Records options (field_config, fields, record_cursor)

The v2.1 "Get Records" API supports selecting which fields are returned and,
for some integration reports, paging large datasets using a `record_cursor`
header. The SDK exposes these features via typed helpers on `ReportContext`.

```python
from zoho_creator_sdk import ZohoCreatorClient
from zoho_creator_sdk.models import FieldConfig

client = ZohoCreatorClient()
report = client.report(
    app_link_name="my-app",
    owner_name="your-owner-name",
    report_link_name="All_Orders",
)

# Fetch only specific fields from the detail view layout
for record in report.get_records(
    field_config=FieldConfig.DETAIL_VIEW,
    fields=["Email", "Phone"],
    criteria='Status == "Open"',
):
    print(record.get_form_data())

# For integration form reports that return a record_cursor header, use the
# dedicated iterator to automatically follow the cursor across pages:
for record in report.iter_records_with_cursor(
    field_config=FieldConfig.ALL,
    fields=["Order_ID", "Total"],
):
    process(record)

Examples

The examples/ directory contains more complete scripts demonstrating:

  • Basic usage (examples/basic_usage.py)
  • Configuration and zero-config loading (examples/configuration.py)
  • Datacenter configuration (examples/datacenter_usage.py)
  • Error handling patterns (examples/error_handling.py)
  • OAuth2 authentication details (examples/oauth2_auth.py)
  • Record CRUD operations (examples/record_management.py)

Configuration

The SDK is designed for "zero-config" initialization by loading all required settings from environment variables.

Required Environment Variables

Variable Description
ZOHO_CLIENT_ID Your OAuth2 Client ID.
ZOHO_CLIENT_SECRET Your OAuth2 Client Secret.
ZOHO_REFRESH_TOKEN Your OAuth2 Refresh Token.
ZOHO_CREATOR_DATACENTER The Zoho datacenter for your account (e.g., US, EU, IN).

Optional Environment Variables

These variables enable environment-specific behavior and demo users, as described in the Zoho Creator v2.1 API docs:

Variable Description
ZOHO_CREATOR_ENVIRONMENT Optional environment header value, e.g. development or stage.
ZOHO_CREATOR_DEMO_USER_NAME Optional demo user name used together with environment.

The SDK exclusively uses OAuth 2.0 authentication for enhanced security. API key authentication is not supported.

Development

This project uses uv for dependency management and task running.

Development Setup

  1. Clone the repository:

    git clone https://github.com/carlospaiva/zoho-creator-sdk.git
    cd zoho-creator-sdk
    
  2. Install dependencies:

    uv sync
    

Running Tests

The project has a comprehensive test suite with 95%+ coverage across all modules. Our testing infrastructure includes unit tests, integration tests, and comprehensive coverage enforcement.

  • Run all tests with coverage:

    uv run pytest --cov=zoho_creator_sdk --cov-report=term-missing --cov-report=html
    
  • Run tests with coverage verification (enforces 95% minimum):

    python scripts/verify_coverage.py
    
  • Run specific test categories:

    # Unit tests only
    uv run pytest tests/unit/
    
    # Integration tests only
    uv run pytest tests/integration/
    
    # Model tests
    uv run pytest tests/models/unit/
    
    # Client tests
    uv run pytest tests/client/unit/
    
  • Run tests in parallel for faster execution:

    uv run pytest -n auto
    

Coverage Requirements

  • Minimum Coverage: 95% enforced in CI/CD
  • Current Coverage: ~76% and actively improving
  • Coverage Reports: Generated in XML, HTML, and terminal formats
  • Coverage Tracking: Integrated with Codecov for visualization

Pre-commit Hooks

The project includes comprehensive pre-commit hooks that enforce code quality and test coverage:

# Install pre-commit hooks
pre-commit install

# Hooks will automatically run on each commit:
# - Code formatting (black, isort)
# - Linting (flake8, mypy)
# - Test collection validation
# - Coverage verification (95% minimum)

Test Structure

Tests are organized by feature and type:

tests/
├── auth/                 # Authentication handlers and OAuth2 tests
├── client/               # HTTP client and fluent client tests
├── config/               # Configuration loading and environment handling
├── integration/          # API integration and workflow tests
├── models/               # Model validation and behavior tests
├── utils/                # Utility and helper tests
└── workflows/            # Workflow models and execution tests

Each test file focuses on specific functionality with comprehensive edge case coverage, proper mocking, and deterministic test execution.

Code Quality and Linting

The project uses comprehensive tooling to enforce code quality, type safety, and consistent style.

  • Format code:

    uv run black .
    uv run isort .
    
  • Run linters and type checking:

    # Run all quality checks
    uv run python scripts/run_lint.py
    
    # Individual tools
    uv run flake8 .
    uv run pylint src
    uv run mypy src
    
  • Check code coverage:

    # Verify 95% coverage requirement
    python scripts/verify_coverage.py
    

Quality Standards

  • Code Formatting: Black (88-character line length) + isort
  • Linting: flake8 with comprehensive rule set
  • Type Checking: mypy with strict optional checking
  • Test Coverage: 95% minimum enforced in CI/CD
  • Pre-commit Hooks: Automated quality checks on every commit

Building the Package

To build the distributable package:

make build
# or, equivalently:
uv run python -m build

Contributing

Contributions are welcome! Please follow the guidelines in our Contributing Guide.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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