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Project description
DaprGen: Streamlining Microservice Development
Welcome to DaprGen, a powerful command-line interface (CLI) designed to revolutionize microservice development by leveraging Dapr modules. Inspired by the efficiency and modularity of frameworks like Ruby on Rails, DaprGen simplifies the process of creating, developing, and deploying microservices.
Table of Contents
- Introduction
- Features
- Getting Started
- Usage
- Module Creation
- Best Practices
- Structuring Code: A New Class of Digital Assets (by Dr Holger Vogel)
- Contributing
- License
Introduction
DaprGen, influenced by the pioneering work of Sean Chatman and James I. Chatman, embodies a structured approach to microservice development. This tool is designed to streamline your workflow, enhance productivity, and ensure you stay ahead in the rapidly evolving tech landscape.
Features
- Quick Initialization: Set up your DaprGen project in seconds, echoing the ease of starting new projects with Ruby on Rails.
- Modular Approach: Inspired by Ruby on Rails' modular design, DaprGen allows for the easy generation and enhancement of Dapr modules.
- Intuitive Command Structure: Manage your microservice development workflow with straightforward commands.
Quick Start
Initialize a new DaprGen project:
daprgen init my_project
cd my_project
Generate a new module:
daprgen module new -cn OrderProcessor -i "order" -o "confirmation"
Run the module:
daprgen module order_processor call '{"orderId": "12345"}'
Serve the REST API:
docker-compose up app
Module Creation
The daprgen module new
command is the cornerstone of DaprGen, enabling users to create new modules efficiently. This section highlights the usage and provides common use cases for microservices.
Usage
daprgen module new [OPTIONS]
Options
--class-name, -cn TEXT
: The name of the module class (required).--inputs, -i TEXT
: A comma-separated list of input names.--output, -o TEXT
: Output name for the module.--help
: Show this message and exit.
Common Use Cases
-
Order Processing:
daprgen module new -cn OrderProcessor -i "order" -o "confirmation"
-
Inventory Management:
daprgen module new -cn InventoryManager -i "productId,quantity" -o "status"
-
Payment Processing:
daprgen module new -cn PaymentProcessor -i "paymentDetails" -o "receipt"
-
User Authentication:
daprgen module new -cn Authenticator -i "username,password" -o "token"
-
Notification Service:
daprgen module new -cn Notifier -i "message,recipient" -o "status"
Getting Started
Using Dapr Components:
from daprgen.utils.dapr_tools import init_dapr
from daprgen.modules.order_processor_module import order_processor_call
init_dapr(component="pubsub", config="config.yaml")
order_processor_call({"orderId": "12345"})
Using Redis State Store:
Ensure your .env
file is configured for Redis. Modify your config.yaml
as necessary.
from daprgen.utils.dapr_tools import init_dapr
from daprgen.state.redis import RedisState
from daprgen.modules.order_processor_module import order_processor_call
init_dapr(state_store=RedisState, config="config.yaml")
order_processor_call({"orderId": "12345"})
Privacy and Data Protection: For privacy and data loss protection, we recommend initializing DaprGen with secure state stores.
Install Redis: Follow the official Redis installation guide to set up the necessary tools.
from daprgen.utils.dapr_tools import init_dapr
from daprgen.state.redis import RedisState
from daprgen.modules.order_processor_module import order_processor_call
init_dapr(state_store=RedisState, config="config.yaml")
order_processor_call({"orderId": "12345"})
By following these steps, you can integrate the concept of structured commodities into your microservice development workflow, ensuring compliance and fair compensation for creators.
By understanding and utilizing the daprgen module new
command, you can harness the full potential of DaprGen to create powerful and flexible microservice development workflows.
Production Module
The following example demonstrates a production module that generates a mock Pytest module for a given Python source code. This module is designed to create comprehensive and robust mock tests that simulate possible unit tests based on the functions and methods defined within the source code.
import dapr
class GenerateMockPytest(dapr.Signature):
"""
Generates a mocked pytest module for the provided Python source code.
This class aims to create comprehensive and robust mock tests that simulate
possible unit tests based on the functions and methods defined within the source code.
Write the test like a FAANG Python architect at Meta.
Only reply within ```python``` block. All other text needs to be in docstrings or comments.
"""
source_code = dapr.InputField(desc="Python source code for which to generate a mock test.")
mocked_pytest = dapr.OutputField(desc="Generated mock pytest code. Within triple backticks",
prefix="```python\n")
class PytestModule(dapr.Module):
"""PytestModule"""
def __init__(self, **forward_args):
super().__init__()
self.forward_args = forward_args
self.output = None
def forward(self, source_code):
pred = dapr.Predict(GenerateMockPytest)
self.output = pred(source_code=source_code).mocked_pytest
return self.output
def pytest_call(source_code):
pytest = PytestModule()
return pytest.forward(source_code=source_code)
example_code = """def fetch_user_name(user_id):
import requests
response = requests.get(f'https://api.example.com/users/{user_id}')
return response.json()['name']
"""
def main():
from daprgen.utils.dapr_tools import init_dapr
dapr_instance = init_dapr()
source_code = example_code
result = pytest_call(source_code=source_code)
from daprgen.utils.file_tools import extract_code
print(extract_code(result))
print(dapr_instance.inspect_history(n=1))
if __name__ == "__main__":
main()
Example: Generated Pytest Module (Continued)
import pytest
from your_module import fetch_user_name
@pytest.fixture
def mocker():
return pytest.mockito()
def test_fetch_user_name(mocker):
mocked_requests_get = mocker.patch('requests.get')
response_json = {'name': 'John Doe'}
mocked_requests_get.return_value.json.return_value = response_json
result = fetch_user_name(123)
assert result == 'John Doe'
# Verify that the requests.get call was not made
assert not mocked_requests_get.called
Example: Running the Test
Initial state: ANALYZING_REQUIREMENTS
Test Failed: ============================= test session starts ==============================
platform darwin -- Python 3.12.3, pytest-8.2.0, pluggy-1.5.0 -- /Users/sac/Library/Caches/pypoetry/virtualenvs/soc-FgW3JNy9-py3.12/bin/python
cachedir: .pytest_cache
rootdir: /var/folders/s6/jqyw48zs39z38b_3f6f_x2sc0000gn/T
plugins: anyio-4.3.0, clarity-1.0.1, Faker-23.3.0, asyncio-0.23.6, mock-3.14.0, xdist-3.6.1
asyncio: mode=Mode.STRICT
collecting ... collected 1 item
../../../../../../../var/folders/s6/jqyw48zs39z38b_3f6f_x2sc0000gn/T/tmp880863oe_test.py::test_fetch_user_name ERROR [100%]
==================================== ERRORS ====================================
____________________ ERROR at setup of test_fetch_user_name ____________________
@pytest.fixture
def mocker():
> return pytest.mockito()
E AttributeError: module 'pytest' has no attribute 'mockito'
/var/folders/s6/jqyw48zs39z38b_3f6f_x2sc0000gn/T/tmp880863oe_test.py:6: AttributeError
=========================== short test summary info ============================
ERROR ../../../../../../../var/folders/s6/jqyw48zs39z38b_3f6f_x2sc0000gn/T/tmp880863oe_test.py::test_fetch_user_name
=============================== 1 error in 0.04s ===============================
Best Practices
Daily Productivity Process
- Set Clear Goals: Use the Ivy Lee Method to prioritize your daily tasks.
Use Pomodoro Technique: Work in focused intervals to maintain productivity. 3. Regular Reviews: Reflect on progress and plan for the next day.
Embrace Continuous Learning
Stay updated with the latest advancements in microservice technology and share your insights with the community to enhance collective productivity.
Structuring Code: A New Class of Digital Assets
Dematerialized Commodity Concept
Inspired by financial engineering and the structuring of financial products, we aim to bring the same level of compliance and innovation to code generation systems. In today's technology-driven world, it is crucial to ensure that creators of valuable, new code receive appropriate compensation whenever their code is analyzed, cloned, or used, especially at the enterprise level.
NFTs as Structured Commodities
The foundation for all valuable, useful code should be a new form of NFT – a structured commodity of code. This concept is akin to a dematerialized asset, similar to the Meta-Bricks repository we previously created. This would involve a massive store of runnable and easily pluggable/composable elements of code, paired with terms and conditions familiar from classical structured products (e.g., Ricardian Contracts).
Legal Compliance and Revenue Sharing
To minimize legal risks and ensure proper compensation, retrievers should use these structured commodities for code generation workflows. They should always send payments or share revenues from new creations derived from these meta-bricks to the original creators. While many current code generation tools do not reference the source of the code, this is an area that can and should be improved.
Contributing
We welcome contributions to improve DaprGen. Please follow the guidelines in the CONTRIBUTING.md
file.
License
This project is licensed under the MIT License. See the LICENSE
file for more details.
By leveraging the structured approach and productivity principles from the Sean Chatman and James I. Chatman Methods, DaprGen aims to enhance your microservice development experience. Get started today and streamline your workflow with ease!
For more information, visit our GitHub repository.
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