pydelhivery 0.1.2

Thin Python Wrapper for India's Biggest 3rd Party Logistics Service Provider

pydelhivery

A Python wrapper for Delhivery's B2C API, providing a clean and type-safe interface for integrating with India's largest third-party logistics service provider.

This library is based on the Delhivery Developer Portal Documentation.

Note: This is an independent, open-source project. The author is not affiliated with Delhivery in any way. This project is provided as-is in the hope that others find it helpful for integrating with Delhivery's APIs.

Features

• ✅ Pincode Serviceability Check - Verify if a location is serviceable for delivery
• ✅ Warehouse Management - Create and update warehouse configurations
• ✅ Shipping Cost Calculation - Calculate shipping charges before creating orders
• ✅ Order Management - Create, update, and cancel shipments
• ✅ Pickup Scheduling - Schedule pickups for your shipments
• ✅ Tracking - Track shipments using waybill numbers
• ✅ Label Generation - Generate packing slips and shipping labels
• ✅ Type-Safe - Built with Pydantic for robust data validation
• ✅ Comprehensive Logging - Built-in logging for debugging and monitoring

Installation

pip install pydelhivery

Or using uv:

uv add pydelhivery

Configuration

Set up your Delhivery API credentials using environment variables:

# Required
DELHIVERY_AUTH_TOKEN=your_auth_token_here

# Optional (defaults to https://track.delhivery.com)
DELHIVERY_API_BASE_URL=https://track.delhivery.com

You can use a .env file in your project root:

DELHIVERY_AUTH_TOKEN=your_auth_token_here
DELHIVERY_API_BASE_URL=https://track.delhivery.com

Quick Start

from pydelhivery import DelhiveryIntegration
from pydelhivery.models.DelhiveryModels import (
    DelhiveryShippingCostRequest,
    DelhiveryOrderTrackingRequest,
)

# Initialize the client
client = DelhiveryIntegration()

# Check pincode serviceability
pincode_response = client.check_pincode_serviceability("560001")
print(f"Serviceable: {pincode_response.is_serviceable}")
print(f"COD Supported: {pincode_response.supports_cod}")

# Calculate shipping cost
cost_request = DelhiveryShippingCostRequest(
    md="E",  # Express
    cgm=500,  # 500 grams
    o_pin=560001,  # Origin pincode
    d_pin=110053,  # Destination pincode
    ss="Delivered",
    pt="Pre-paid"
)
shipping_cost = client.calculate_shipping_cost(cost_request)
print(f"Shipping cost: {shipping_cost.total_amount}")

# Track an order
tracking_request = DelhiveryOrderTrackingRequest(waybills=["WB1234567890"])
tracking_response = client.track_orders(tracking_request)
print(f"Status: {tracking_response.latest_status}")

API Reference

DelhiveryIntegration

The main client class for interacting with Delhivery APIs.

Methods

check_pincode_serviceability(pincode: str, filter_codes: Optional[str] = None) -> DelhiveryPincodeResponse

Check if a pincode is serviceable for delivery.

Parameters:

• pincode (str): The pincode to check (6-digit)
• filter_codes (str, optional): Optional filter parameter

Returns: DelhiveryPincodeResponse with serviceability information

Example:

response = client.check_pincode_serviceability("560001")
if response.is_serviceable:
    print(f"COD: {response.supports_cod}, Prepaid: {response.supports_prepaid}")

create_warehouse(warehouse: DelhiveryWarehouseCreateRequest) -> bool

Create a new warehouse in Delhivery system.

Parameters:

• warehouse: Warehouse configuration (Pydantic model)

Returns: bool - True if successful

Example:

from pydelhivery.models.WareHouseModels import DelhiveryWarehouseCreateRequest

warehouse = DelhiveryWarehouseCreateRequest(
    name="My Warehouse",
    registered_name="My Company Pvt Ltd",
    address="123 Main Street",
    city="Bangalore",
    pin="560001",
    phone="9876543210",
    email="[e-mail]",
    return_address="123 Main Street",
    return_city="Bangalore",
    return_state="Karnataka",
    return_pin="560001"
)
client.create_warehouse(warehouse)

update_warehouse(warehouse_update: DelhiveryWarehouseUpdateRequest) -> bool

Update an existing warehouse configuration.

Parameters:

• warehouse_update: Warehouse update payload

Returns: bool - True if successful

calculate_shipping_cost(request_data: DelhiveryShippingCostRequest) -> DelhiveryInvoiceChargeItem

Calculate shipping cost for a shipment.

Parameters:

• request_data: Shipping cost request with origin, destination, weight, etc.

Returns: DelhiveryInvoiceChargeItem with cost breakdown

Example:

from pydelhivery.models.DelhiveryModels import DelhiveryShippingCostRequest

request = DelhiveryShippingCostRequest(
    md="E",  # Express or Surface
    cgm=1000,  # Weight in grams
    o_pin=560001,
    d_pin=110053,
    ss="Delivered",  # Status
    pt="Pre-paid"  # Payment type
)
cost = client.calculate_shipping_cost(request)
print(f"Total: {cost.total_amount}")

create_order(shipment_config: ShipmentConfig, order_id: UUID) -> DelhiveryCMUCreateResponse

Create a new shipment order.

Parameters:

• shipment_config: Shipment configuration
• order_id: Unique order identifier (UUID)

Returns: DelhiveryCMUCreateResponse with waybill numbers

update_order(order_update: DelhiveryOrderUpdateRequest) -> Dict[str, Any]

Update an existing order.

Parameters:

• order_update: Order update payload

Returns: API response dictionary

schedule_pickup(pickup_request: DelhiveryPickupRequest) -> DelhiveryPickupSuccessResponse

Schedule a pickup for shipments.

Parameters:

• pickup_request: Pickup request with date, time, and location

Returns: DelhiveryPickupSuccessResponse with pickup details

Example:

from pydelhivery.models.DelhiveryModels import DelhiveryPickupRequest

pickup = DelhiveryPickupRequest(
    pickup_date="2025-12-31",
    pickup_time="11:00:00",
    pickup_location="My Warehouse",
    expected_package_count=5
)
response = client.schedule_pickup(pickup)

generate_shipping_label(label_request: DelhiveryPackingSlipRequest) -> DelhiveryPackingSlipResponse

Generate packing slip/shipping label for waybills.

Parameters:

• label_request: Label request with waybill number and format options

Returns: DelhiveryPackingSlipResponse with PDF links

Example:

from pydelhivery.models.DelhiveryModels import DelhiveryPackingSlipRequest

label_request = DelhiveryPackingSlipRequest(
    waybill="WB1234567890",
    pdf=True,
    pdf_size="A4"
)
response = client.generate_shipping_label(label_request)
print(f"PDF URL: {response.pdf_links[0]}")

track_orders(tracking_request: DelhiveryOrderTrackingRequest) -> DelhiveryTrackingResponse

Track one or more shipments.

Parameters:

• tracking_request: Tracking request with waybill numbers

Returns: DelhiveryTrackingResponse with tracking details

Example:

from pydelhivery.models.DelhiveryModels import DelhiveryOrderTrackingRequest

request = DelhiveryOrderTrackingRequest(waybills=["WB1234567890", "WB0987654321"])
response = client.track_orders(request)
print(f"Latest Status: {response.latest_status}")
print(f"Location: {response.latest_status_location}")

cancelShipment(waybill: str) -> None

Cancel a shipment.

Parameters:

• waybill: Waybill number to cancel

Example:

client.cancelShipment("WB1234567890")

Error Handling

The library uses standard Python exceptions:

• ValueError: Raised for invalid input or missing configuration
• requests.exceptions.HTTPError: Raised for HTTP errors from the API
• requests.exceptions.RequestException: Raised for network/request errors

All errors are logged using the built-in logger.

Example:

try:
    response = client.check_pincode_serviceability("560001")
except ValueError as e:
    print(f"Invalid input: {e}")
except requests.exceptions.HTTPError as e:
    print(f"API error: {e.response.status_code} - {e.response.text}")

Logging

The library uses Python's logging module. Logs are automatically configured when you import the package.

from pydelhivery import logger

logger.info("Custom log message")
logger.debug("Debug information")
logger.error("Error occurred")

Development

Prerequisites

• Python >= 3.12
• uv (recommended) or pip

Setup

1. Clone the repository:

git clone <repository-url>
cd pydelhivery

2. Install dependencies:

uv sync

Or with pip:

pip install -e ".[dev]"

3. Set up environment variables:

cp .env.example .env
# Edit .env with your credentials

Project Structure

pydelhivery/
├── src/
│   └── pydelhivery/
│       ├── __init__.py
│       ├── DelhiveryApis.py      # Main API client
│       ├── models/               # Pydantic models
│       │   ├── DelhiveryModels.py
│       │   ├── ShippingCostModel.py
│       │   ├── ShippingCreateRequest.py
│       │   ├── Tracking.py
│       │   └── WareHouseModels.py
│       └── utils/                # Utilities
│           ├── constants.py
│           └── logger.py
├── tests/                        # Test suite
├── pyproject.toml               # Project configuration
└── README.md

Developer Guidelines

Code Style

• Follow PEP 8 style guidelines
• Use type hints for all function parameters and return types
• Use Pydantic models for all API request/response data
• Maximum line length: 100 characters (where reasonable)

Adding New API Methods

1. Create Pydantic Models (if needed):

   • Add request models in the appropriate file under models/
   • Add response models if the API returns structured data
   • Use field validators for input validation

2. Add API Method:

   • Add the method to DelhiveryIntegration class in DelhiveryApis.py
   • Follow the existing pattern:

     def new_method(self, request: RequestModel) -> ResponseModel:
         """
         Brief description of what the method does.
         
         Args:
             request: Description of request parameter
         
         Returns:
             Description of return value
         
         Raises:
             ValueError: When auth token is missing
             requests.exceptions.HTTPError: For API errors
         """
         if not self.auth_token:
             raise ValueError("DELHIVERY_AUTH_TOKEN is not configured")
         
         url = f"{self.base_url}/api/endpoint"
         headers = self._get_headers()
         payload = request.model_dump()
         
         try:
             logger.info("Description of action")
             response = requests.post(url, headers=headers, json=payload, timeout=20)
             response.raise_for_status()
             
             logger.info("Action successful")
             parsed = self._parse_response(response, ResponseModel)
             return parsed
             
         except requests.exceptions.HTTPError as e:
             logger.error(f"Action failed | Status: {e.response.status_code}")
             raise
         except requests.exceptions.RequestException as e:
             logger.error(f"Request error: {e}")
             raise
     

3. Use Existing Helpers:

   • Use _get_headers() for authentication headers
   • Use _parse_response() for parsing API responses into Pydantic models
   • Always use the logger for important events

4. Error Handling:

   • Always check for auth_token at the start of public methods
   • Use response.raise_for_status() to handle HTTP errors
   • Log errors with context (status code, response text)
   • Re-raise exceptions to allow caller to handle them

5. Logging:

   • Use logger.info() for successful operations
   • Use logger.debug() for detailed information (response bodies, etc.)
   • Use logger.error() for errors
   • Include relevant context in log messages (pincodes, waybills, etc.)

Testing

1. Write tests for new functionality in the tests/ directory
2. Use the scratch/main.py file for manual testing and experimentation
3. Ensure all tests pass before submitting changes

Documentation

1. Update this README when adding new features
2. Include docstrings for all public methods
3. Add usage examples for new APIs
4. Document any breaking changes

Pull Request Process

1. Create a feature branch from main
2. Make your changes following the guidelines above
3. Ensure all tests pass
4. Update documentation
5. Submit a pull request with a clear description

Model Design Guidelines

• Use Pydantic BaseModel for all data structures
• Use Field for field descriptions and validation
• Use field_validator for custom validation logic
• Use appropriate types (str, int, float, bool, Optional, List, etc.)
• Use Literal types for enum-like string values
• Include descriptions for all fields using Field(..., description="...")
• Use exclude_none=True in model_dump() when updating existing resources

API Response Handling

• Always use _parse_response() for structured responses
• Handle XML responses separately (e.g., DelhiveryInvoiceChargeItem.from_xml())
• Validate responses using Pydantic models
• Raise meaningful errors when validation fails

Environment Configuration

• Use dotenv for loading environment variables
• Provide sensible defaults where appropriate
• Document all required and optional environment variables
• Use os.getenv() with defaults for optional configuration

Resources

• Delhivery Developer Portal Documentation - Official API documentation and reference
• Delhivery Official Website

License

See LICENSE file for details.

Contributing

Contributions are welcome! Please read the developer guidelines above and submit a pull request.

Support

For issues and questions:

• Check existing issues in the repository
• Create a new issue with details about your problem
• Include relevant error messages and code snippets
• Refer to the Delhivery Developer Portal Documentation for API details