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Component definitions for Pip.Services in Python

Project description

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Business Logic Components for Python

This module is a part of the Pip.Services polyglot microservices toolkit.

The Logic module contains standard component definitions to handle complex business transactions.

The module contains the following packages:

  • Cache - distributed cache
  • Lock - distributed lock components
  • State - distributed state management components

Quick links:

Use

Install the Python package as

pip install pip_services4_logic

Example how to use caching and locking. Here we assume that references are passed externally.

from pip_services3_commons.refer import Descriptor, References, IReferences, IReferenceable
from pip_services4_logic.cache import ICache, MemoryCache
from pip_services4_logic.lock.ILock import ILock
from pip_services4_logic.lock.MemoryLock import MemoryLock


class MyComponent(IReferenceable):
    __cache: ICache
    __lock: ILock

    def set_references(self, references: IReferences):
        self.__cache = references.get_one_required(Descriptor("*", "cache", "*", "*", "1.0"))
        self.__lock = references.get_one_required(Descriptor("*", "lock", "*", "*", "1.0"))

    def my_method(self, context, param1):
        # First check cache for result
        result = self.__cache.retrieve(context, 'mykey')

        # Lock..
        self.__lock.acquire_lock(context, "mykey", 1000, 1000, )

        # Do processing
        # ...

        # Store result to cache async
        self.__cache.store(context, 'mykey', result, 3600000)

        # Release lock async
        self.__lock.release_lock(context, 'mykey')

        return result


# Use the component
my_component = MyComponent()
my_component.set_references(References.from_tuples(
    Descriptor("pip-services", "cache", "memory", "default", "1.0"), MemoryCache(),
    Descriptor("pip-services", "lock", "memory", "default", "1.0"), MemoryLock(),
))

result = my_component.my_method(None, param1)

If you need to create components using their locators (descriptors) implement component factories similar to the example below.

from pip_services3_commons.refer import Descriptor
from pip_services4_components.build import Factory


class MyFactory(Factory):
    my_component_descriptor = Descriptor("myservice", "mycomponent", "default", "*", "1.0")

    def __init__(self):
        super(MyFactory, self).__init__()

        self.register_as_type(MyFactory.my_component_descriptor, MyFactory)


# Using the factory
my_factory = MyFactory()
my_component1 = my_factory.create(Descriptor("myservice", "mycomponent", "default", "myComponent1", "1.0"))
my_component2 = my_factory.create(Descriptor("myservice", "mycomponent", "default", "myComponent2", "1.0"))

...

Develop

For development you shall install the following prerequisites:

  • Python 3.7+
  • Visual Studio Code or another IDE of your choice
  • Docker

Install dependencies:

pip install -r requirements.txt

Run automated tests:

python test.py

Generate API documentation:

./docgen.ps1

Before committing changes run dockerized build and test as:

./build.ps1
./test.ps1
./clear.ps1

Contacts

The initial implementation is done by Sergey Seroukhov. Pip.Services team is looking for volunteers to take ownership over Python implementation in the project.

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