Metadata-Version: 2.1
Name: super-mario
Version: 0.0.3
Summary: Library for separating data input, output and processing in your business application.
Home-page: https://github.com/best-doctor/Mario/
Author: Ilya Lebedev
Author-email: melevir@gmail.com
License: MIT
Description: # Mario
        
        [![Build Status](https://travis-ci.org/best-doctor/Mario.svg?branch=master)](https://travis-ci.org/best-doctor/Mario)
        [![Maintainability](https://api.codeclimate.com/v1/badges/86b3c0549c660bda7f4f/maintainability)](https://codeclimate.com/github/best-doctor/Mario/maintainability)
        [![Test Coverage](https://api.codeclimate.com/v1/badges/86b3c0549c660bda7f4f/test_coverage)](https://codeclimate.com/github/best-doctor/Mario/test_coverage)
        [![PyPI version](https://badge.fury.io/py/super-mario.svg)](https://badge.fury.io/py/super-mario)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/super-mario)
        
        Library for separating data input, output and processing in your business application.
        
        ![Mario](https://raw.githubusercontent.com/best-doctor/Mario/master/docs_imgs/mario.png)
        
        **Disclaimer**: the library is sooo pre-alpha.
        
        ## Motivation & main idea
        
        You have tons of business logic.
        You like clean architecture, but you're sane. 
        You like dynamic structure of Python, but you're tied of runtime errors.
        You want to break things a little less and keep moving fast.
        You're is the right place.
        
        Mario is a framework for business logic.
        Like Django or Flask for web-services.
        
        It makes you put logic to pipelines: sets of pipes,
        each pipe does only one thing and only non-complex types
        can be transferred from pipe to pipe.
        
        Each pipe is one of 3 types: input, output, processing.
        Input and output should be non-complex (like really non-complex,
        cyclomatic complexity ~3), processing pipes should be pure.
        
        ## Installation
        
        `pip install super-mario`
        
        ## Docs
        [Here they are](https://github.com/best-doctor/Mario/blob/master/docs/index.md).
        
        ## Usage example
        
        Here is simple pipeline, that send notifications on new comments in Jira
        tickets to Slack. 
        
        ```python
        class JiraCommentsNotificationPipeline(BasePipeline):
            pipeline = [
                'fetch_new_comments',
                'fetch_users_mapping',
                'generate_slack_message',
                'send_slack_message',
            ]
        
            @input_pipe
            def fetch_new_comments(jira_ticket_id: str) -> ImmutableContext:
                return {'new_comments':
                    fetch_jira_comments(
                        ticket_id=jira_ticket_id,
                        date_from=datetime.datetime.now().replace(hours=0, minutes=0, seconds=0, milliseconds=0),
                    ),
                }
        
            @input_pipe
            def fetch_users_mapping(new_comments: List[IssueComment]) -> ImmutableContext:
                return {
                    'jira_to_slack_id_mapping': dict(User.objects.filter(
                        jira_id__in=[c['user_id'] for c in new_comments],
                    ).values_list('jira_id', 'slack_id'))
                }
        
            @process_pipe
            def generate_slack_message(
                jira_ticket_id: str,
                new_comments: List[IssueComment],
                jira_to_slack_id_mapping: Mapping[str, str],
            ) -> ImmutableContext:
                message = '\n'.join([
                    f'@{jira_to_slack_id_mapping[c["user_id"]]} wrote comment for {jira_ticket_id}: "{c["text"]}"'
                    for c in new_comments
                ])
                return {'message': message}
        
            @output_pipe
            def send_slack_message(message: str) -> None:
                send_message(
                    destination='slack',
                    channel=COMMENTS_SLACK_CHANNEL_ID,
                    text=message,
                )
        
        # run pipeline for specific ticket
        JiraCommentsNotificationPipeline().run(jira_ticket_id='TST-12')
        ``` 
        
Keywords: project structure
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: Freely Distributable
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
