near-pytest 0.7.0

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near-pytest

A pytest-native framework for testing NEAR smart contracts in Python.

✨ Features  •  📥 Installation  •  🚀 Getting Started  •  📊 Examples  •  📘 API Reference

Overview

near-pytest enables intuitive testing of NEAR smart contracts directly from Python. It provides a pytest-native approach that automatically handles compilation, sandbox initialization, account creation, contract deployment, and state management - allowing you to focus on writing tests that truly validate your contract's behavior.

Features

🚀 Zero-config setup - Everything works out-of-the-box: automatic sandbox management, contract compilation, and account creation

⚡ Lightning-fast tests - State snapshots between tests eliminate repeated setup operations, making test suites run orders of magnitude faster than traditional approaches

🧩 Intuitive API - Simple, Pythonic interfaces for interacting with contracts and accounts

🤝 Two testing styles - Choose between class-based tests or modular fixtures-based tests according to your preference

🔄 State snapshots - Create a full blockchain state once, then reset to this state between tests in milliseconds instead of seconds

🛠️ Complete toolchain integration - Seamless integration with NEAR compiler, Python SDK, and sandbox

🧪 Pytest native - Leverages the full power of pytest for smart contract testing

🔍 Rich logging - Detailed logs for troubleshooting and debugging

🧠 Smart caching - Automatically caches compiled contracts for faster subsequent runs

✨ Requests-like Response API - Familiar interface for handling contract responses with .json() method and .text property

Installation

uv add near-pytest

Prerequisites

• Python 3.11 or higher
• For contract compilation: nearc package
• The framework automatically handles downloading and installing the NEAR sandbox binary

Getting Started

You can choose between two testing approaches:

1. Modular Fixtures Approach - More pytest-native, with composable fixtures
2. Class-based Approach - Traditional approach with test classes inheriting from NearTestCase

Modular Fixtures Approach

import pytest
from near_pytest.compiler import compile_contract

@pytest.fixture(scope="session")
def counter_wasm():
    """Compile the counter contract."""
    return compile_contract("path/to/contract.py", single_file=True)

@pytest.fixture
def counter_contract(sandbox, counter_wasm):
    """Deploy a fresh counter contract for each test."""
    account = sandbox.create_random_account("counter")
    return sandbox.deploy(
        wasm_path=counter_wasm,
        account=account,
        init_args={"starting_count": 0}
    )

def test_increment(counter_contract, localnet_alice_account):
    """Test incrementing the counter."""
    # Call contract method using method chaining
    result = counter_contract.call("increment").as_transaction(localnet_alice_account)
    assert int(result) == 1
    
    # View state
    count = counter_contract.call("get_count").as_view()
    assert int(count) == 1

Class-based Approach

from near_pytest.testing import NearTestCase

class TestCounter(NearTestCase):
    @classmethod
    def setup_class(cls):
        # Call parent setup method first
        super().setup_class()
        
        # Compile the contract
        wasm_path = cls.compile_contract("path/to/contract.py", single_file=True)
        
        # Create account for contract
        cls.counter = cls.create_account("counter")
        
        # Deploy contract
        cls.counter_contract = cls.deploy_contract(
            cls.counter, 
            wasm_path, 
            init_args={"starting_count": 0}
        )
        
        # Create test accounts
        cls.alice = cls.create_account("alice")
        cls.bob = cls.create_account("bob")
        
        # Save initial state for future resets
        cls.save_state()

    def setup_method(self):
        # Reset to initial state before each test method
        self.reset_state()

    def test_increment(self):
        # Call contract method
        result = self.counter_contract.call("increment", {})
        assert int(result.text) == 1

Examples

Counter Contract Example (Fixtures Approach)

from near_pytest.modular import sandbox, compile_contract, sandbox_alice

@pytest.fixture(scope="session")
def counter_wasm():
    """Compile the counter contract."""
    return compile_contract("counter_contract/__init__.py", single_file=True)

@pytest.fixture
def fresh_counter(sandbox, counter_wasm, temp_account):
    """Deploy a fresh counter contract for each test."""
    return sandbox.deploy(
        wasm_path=counter_wasm,
        account=temp_account,
        init_args={"starting_count": 0}
    )

def test_increment_fresh(fresh_counter, sandbox_alice):
    """Test incrementing a fresh counter."""
    # This always starts with count=0
    result = fresh_counter.call("increment").as_transaction(sandbox_alice)
    assert int(result) == 1
    
    # Increment again
    result = fresh_counter.call("increment").as_transaction(sandbox_alice)
    assert int(result) == 2

JSON Response Example

def test_json_response(self):
    # Call a method that returns JSON data
    response = self.contract.call("get_user_data", {"user_id": "alice"})
    
    # Parse the JSON response
    data = response.json()
    
    # Assert on the parsed data
    assert data["name"] == "Alice"
    assert data["score"] == 100
    assert "created_at" in data

Key Concepts

1. Testing Styles

near-pytest supports two testing styles:

Modular Fixtures (Recommended)

• More pytest-native approach with composable fixtures
• Better test isolation with fixtures per test
• Method chaining for contract calls with clear semantics
• Easier to use with parallel testing (pytest-xdist)

Class-based (NearTestCase)

• Traditional approach with a base class
• All test methods share setup
• State management with save_state and reset_state

2. Smart Contract Compilation

near-pytest automatically handles compilation of your Python smart contracts to WASM using the NEAR SDK for Python.

# Fixtures approach
wasm_path = compile_contract("path/to/contract.py", single_file=True)

# Class-based approach
wasm_path = cls.compile_contract("path/to/contract.py", single_file=True)

The compilation process includes:

• Automatic caching of compiled contracts (based on content hash)
• Support for single-file contracts or multi-file projects
• Seamless integration with the nearc compiler

3. Sandbox Management

The framework automatically:

• Downloads the appropriate NEAR sandbox binary for your platform
• Manages sandbox lifecycle (start/stop)
• Provides methods for state manipulation

4. Account Management

Create test accounts easily:

# Fixtures approach
account = sandbox.create_account("alice")
random_account = sandbox.create_random_account()

# Class-based approach
cls.alice = cls.create_account("alice")

5. Contract Deployment

Deploy contracts to accounts and initialize them:

# Fixtures approach
contract = sandbox.deploy(
    wasm_path=wasm_path,
    account=account,
    init_args={"param": "value"}
)

# Class-based approach
cls.contract = cls.deploy_contract(cls.account, wasm_path, init_args={"param": "value"})

6. Contract Calls

Call contract methods:

# Fixtures approach (with method chaining)
result = contract.call("increment").as_transaction(account)
view_result = contract.call("get_count").as_view()

# Class-based approach
result = contract.call("increment", {})
view_result = contract.view("get_count", {})

7. State Management

Save and restore state for fast test execution:

# Fixtures approach
state = sandbox.save_state()
sandbox.reset_state(state)

# Class-based approach
cls.save_state()
self.reset_state()

7. ContractResponse

Contract call responses are wrapped in a ContractResponse object that provides a familiar interface similar to Python's requests library:

# Get the raw text response
text_content = response.text

# Parse JSON response
json_data = response.json()

# String representation
str_value = str(response)  # Same as response.text

API Reference

Modular Fixtures

Provided Fixtures

• sandbox: Main entry point for interacting with the NEAR sandbox
• sandbox_alice, sandbox_bob: Pre-created accounts for tests
• temp_account: Creates a fresh random account for each test
• create_account: Factory fixture to create accounts on demand
• near_client: Direct access to the NEAR client for RPC operations

SandboxProxy Methods

• create_account(name): Create a new account with the given name
• create_random_account(prefix="test"): Create a new account with a random name
• deploy(wasm_path, account, init_args=None, init_method="new"): Deploy a contract
• save_state(): Save current blockchain state
• reset_state(state): Reset to a previously saved state

EnhancedContract Methods

• call(method_name, **kwargs): Create a contract call with method chaining
• account_id: Property to get the contract account ID

ContractCall Methods

• as_transaction(account, amount=0, gas=None): Execute as a transaction
• as_view(): Execute as a view call

Helper Functions

• compile_contract(contract_path, single_file=False): Helper function to compile a contract to WASM

Using nearc Directly

If you prefer to use the NEAR compiler (nearc) directly for more control over the compilation process:

import nearc

# Compile your contract with custom options
wasm_path = nearc.builder.compile_contract(
    contract_path="path/to/contract.py", 
    output_path="path/to/output.wasm",
    single_file=True
)

Network Distinction

Our fixtures use a naming convention to distinguish between different networks:

• sandbox - The main fixture that provides access to the NEAR sandbox node
• localnet_alice, localnet_bob, localnet_temp_account - Account fixtures that operate on the local network

This distinction allows for future expansion to other networks like testnet or mainnet while maintaining a clear separation of concerns.

NearTestCase Methods

• setup_class(cls): Set up shared resources for the test class
• compile_contract(contract_path, single_file=False): Compile a contract to WASM
• create_account(name, initial_balance=None): Create a new test account
• deploy_contract(account, wasm_path, init_args=None): Deploy a contract
• save_state(): Save the current state for later reset
• reset_state(): Reset to the previously saved state

Account Methods

• call_contract(contract_id, method_name, args=None, amount=0, gas=None): Call a contract method
• view_contract(contract_id, method_name, args=None): Call a view method
• deploy_contract(wasm_file): Deploy a contract to this account

Contract Methods

• call(method_name, args=None, amount=0, gas=None): Call as the contract account
• call_as(account, method_name, args=None, amount=0, gas=None): Call as another account
• view(method_name, args=None): Call a view method

ContractResponse

A wrapper for contract call responses that provides a familiar interface for handling response data.

Properties

• text: Get the raw text response as a string
• transaction_result: Access the underlying transaction result (if available)

Methods

• json(): Parse the response as JSON and return the resulting Python object

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Environment Variables

You can customize the behavior of near-pytest using these environment variables:

• NEAR_PYTEST_LOG_LEVEL: Set logging level (DEBUG, INFO, WARNING, ERROR)
• NEAR_SANDBOX_HOME: Specify a custom home directory for the sandbox

Architecture

near-pytest consists of several core components:

• SandboxManager: Handles the NEAR sandbox process lifecycle
• NearClient: Manages communication with the NEAR RPC interface
• Account/Contract: Simplified models for interacting with the blockchain
• ContractResponse: Wraps contract call responses with a user-friendly API
• NearTestCase: Base class that ties everything together for testing

Troubleshooting

Common Issues

1. Sandbox doesn't start

   • Check if port 3030 is available
   • Ensure you have proper permissions to execute downloaded binaries

2. Contract compilation fails

   • Verify that the nearc package is installed
   • Check Python version compatibility (3.11+ required)

3. Slow test execution

   • Ensure you're using save_state() and reset_state() pattern
   • Verify if cache directory (~/.near-pytest/cache) exists and is writeable

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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