python-ode 0.0.3

A framework to drive a clean code

Ode

Overview

The Ode initiative, originally founded by Caio Sanchez Christino in 2012 and reinvented by Bárbara Zaccarias in 2022, is a systematic and innovative effort aimed at addressing both the technical complexities and the emotional challenges inherent in digital product development. Positioned against industry challenges such as burnout and turnover, exacerbated by high costs due to software failures, Ode emerges as a strategic solution to improve efficiency, quality, and well-being in the software development environment.

Motivation

Software developers spend approximately 75% of their time on debugging activities. This not only increases operational costs but also risks the reputation of the companies involved. In this context, Ode is more than just another technical framework; it is designed to facilitate developers' work by promoting more efficient practices and reducing the incidence of costly error corrections.

Objectives

1. Enhance Developer Efficiency: By providing tools and practices that streamline the development process.
2. Improve Software Quality: Reducing bugs and errors, thereby decreasing time spent on debugging.
3. Promote Developer Well-being: Addressing the emotional and mental challenges in the development environment.
4. Attract and Retain Talent: By creating a more supportive and efficient work environment, Ode helps to bridge the gap between the supply and demand for tech talent.

Principles and Metrics

Ode is based on the principles of Clean Code, SOLID, and KISS. It leverages both direct and indirect metrics such as:

• Cyclomatic Complexity
• Circular Dependency
• Number of Dependencies
• Afferent and Efferent Couplings
• Main Sequence

In this scenario, Ode stands out as a disruptive innovation. Launched in 2022, this open-source library was developed not just as a coding tool, but as a means to radically transform the narrative of software development.

Key Features

• Error Reduction: Tools and practices to minimize bugs and errors.
• Efficiency Boost: Streamlined workflows and processes.
• Developer Support: Resources and strategies to combat burnout and turnover.
• Talent Attraction: Creating a favorable work environment to attract new professionals.

Approach

Ode positions itself as a multithread helper library for digital product development, emphasizing the product rather than the software. It assists developers in maintaining their digital product commitments without compromising software quality. Ode avoids the use of anti-patterns and addresses issues from both developer and business perspectives:

Developer Perspective:

• Maintenance Difficulty
• Low Code Reusability
• Lack of Scalability
• Integration Challenges
• Insufficient Documentation
• Error-Prone Code

Business Perspective:

• Higher Costs
• Development Delays
• Low Product Quality
• Integration Difficulty
• Security Risks
• Reduced Competitiveness

Development Process

The initial development phase discusses the core functionalities of Ode using Use Cases (UML), supporting individual, pair, and batch processing. The library distinguishes itself with its coding style guidelines and integrated testing, ensuring consistency and comprehension among development teams and semantic dispatch channels. Key features include:

• Reduced Code Verbosity: Optimizes writing to be clearer and more concise.
• Focus on Central Problem: Directs developers to the essence of challenges, improving efficiency.
• Logical Narrative: Transforms code into a logical, structured narrative, facilitating maintenance and collaboration.

Legacy System Compatibility

Ode is crucially compatible with legacy systems, allowing smooth and uninterrupted transitions to modernization. It incorporates use cases directly into the code, providing dynamic and always up-to-date documentation that reflects real-time changes, aligning development with actual user needs.

Accessibility

Ode is democratic and easily accessible to clients, integrating into their projects through simple imports from major online library stores (e.g., npm, CocoaPods, NuGet). Its initial installation is straightforward, requiring no additional scripts, complex commands, or specific adjustments in the target product.

Practical Application

Ode is applied directly to the classes of digital products. It relies on inheritance and polymorphism principles, using Use Cases and auxiliary classes and functions. These are available for implementation and testing in the client's native language, avoiding the need for binary conversion or learning a new programming language. Additionally, Ode's documentation is detailed and comprehensive, complemented by a range of online learning resources to help developers quickly familiarize themselves with the library and its functionalities.

Main Features

• Dispatch UseCase: Dispatch a UseCase<P, R>.
• Dispatch Chain UseCase: Dispatch a UseCase<P, R> that depends on other use cases.
• Dispatch Sequence UseCase: Dispatch a list of UseCase<P, R> that are independent of each other.
• Guard of UseCase: Safely blocks the execution of a UseCase<P, R> and prevents cyclomatic complexity in the presenter.

Getting Started

Installation

pip install ode-style

Usage

class GETAPIUseCase(UseCase[int, HousesToReturn]):
    def __init__(self, repo: RepositoryAPI):
        self.repo = repo

    def execute(self, param: int) -> Output[HousesToReturn]:
        print("GETAPIUseCase.execute")
        site = self.repo.do_fetch(page=param)
        houses = self.repo.read_tags_from_site(site)
        
        return ValueOutput(HousesToReturn(houses))

Contributing

We welcome contributions from the community. Please read our contributing guide to learn how you can get involved.

License

Ode is licensed under the MIT License.

Contact

For more information, please contact us at [e-mail].

Acknowledgements

We thank all contributors and supporters who have been part of the Ode journey since its inception.