Package: pip-services4-container
IoC container for PythonThis module is a part of thePip.Servicespolyglot microservices toolkit. It provides an inversion-of-control (IoC) container to facilitate the development of services and applications composed of loosely coupled components.The module containes a basic in-memory container that can be embedded inside a service or application, or can be run by itself.
The second container type can run as a system level process and can be configured via command line arguments.
Also it can be used to create docker containers.The containers can read configuration from JSON or YAML files use it as a recipe for instantiating and configuring components.
Component factories are used to create components based on their locators (descriptor) defined in the container configuration.
The factories shall be registered in containers or dynamically in the container configuration file.The module contains the following packages:Containers- Basic in-memory and process containersBuild- Default container factoryConfig- Container configuration componentsRefer- Inter-container reference management (implementation of the Referenceable pattern inside an IoC container)Test- minimal set of test components to make testing easierQuick links:API ReferenceChange LogGet HelpContributeUseInstall the Python package aspipinstallpip_services4_containerCreate a factory to create components based on their locators (descriptors).frompip_services4_commons.referimportDescriptorfrompip_services4_components.buildimportFactoryclassMyFactory(Factory):MyComponentDescriptor=Descriptor("myservice","mycomponent","default","*","1.0")def__init__(self):super(MyFactory,self).__init__()self.register_as_type(MyFactory.MyComponentDescriptor,MyComponent)Then create a process container and register the factory there. You can also register factories defined in other
modules if you plan to include external components into your container.frompip_services4_containerimportProcessContainerfrompip_services3_rpc.buildimportDefaultRpcFactoryclassMyProcess(ProcessContainer):def__init__(self):super(MyProcess,self).__init__('myservice','My service running as a process')self._factories.add(DefaultRpcFactory())self._factories.add(MyFactory())Define YAML configuration file with components and their descriptors.
The configuration file is pre-processed usingHandlebars templating enginethat allows to inject configuration parameters or dynamically include/exclude components using conditional blocks.
The values for the templating engine are defined via process command line arguments or via environment variables.
Support for environment variables works well in docker or other containers like AWS Lambda functions.---# Context information-descriptor:"pip-services:context-info:default:default:1.0"name:myservicedescription:My service running in a process container# Console logger-descriptor:"pip-services:logger:console:default:1.0"level:{{LOG_LEVEL}}{{^LOG_LEVEL}}info{{/LOG_LEVEL}}# Performance counters that posts values to log-descriptor:"pip-services:counters:log:default:1.0"# My component-descriptor:"myservice:mycomponent:default:default:1.0"param1:XYZparam2:987{{#if HTTP_ENABLED}}# HTTP endpoint version 1.0- descriptor:"pip-services:endpoint:http:default:1.0"connection:protocol:"http"host:"0.0.0.0"port:{{HTTP_PORT}}{{^HTTP_PORT}}8080{{/HTTP_PORT}}# Default Status- descriptor:"pip-services:status-service:http:default:1.0"# Default Heartbeat- descriptor:"pip-services:heartbeat-service:http:default:1.0"{{/if}}To instantiate and run the container we need a simple process launcher.importsysfromMyFactoryimportMyFactorytry:proc=MyProcess()proc._config_path='./config/config.yml'proc.run()exceptExceptionasex:sys.stderr.write(ex)And, finally, you can run your service launcher aspythonservice.pyDevelopFor development you shall install the following prerequisites:Python 3.7+Visual Studio Code or another IDE of your choiceDockerInstall dependencies:pipinstall-rrequirements.txtRun automated tests:pythontest.pyGenerate API documentation:./docgen.ps1Before committing changes run dockerized build and test as:./build.ps1
./test.ps1
./clear.ps1ContactsThe Python version of Pip.Services is created and maintained bySergey Seroukhov