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🤗 Welcome

👍🎉 First off, We are really glad you're reading this, because we need volunteer developers to help improve the Field Mapping Tasking Manager (FMTM)! 🎉👍

We welcome and encourage contributors of all skill levels, and we are committed to making sure your participation is inclusive, enjoyable, and rewarding. If you have never contributed to an open source project before, we are a good place to start, and we will make sure you are supported every step of the way. If you have any questions, please ask!

You can see an overview of the project and the process we have gone through in developing FMTM so far in these [slides](https://docs.google.com/presentation/d/ 1UrBG1X4MXwVd8Ps498FDlAYvesIailjjPPJfR_B4SUs/edit#slide=id.g15c1f409958_0_0)

Furthermore, there are many ways to contribute to the Field Mapping Tasking Manager (FMTM), which includes:

Testing

Right now, we are in the process of building the prototype. We warmly welcome your input in testing and sharing your feedback. If you are also interested in coordinating a field testing session, please reach out!

Code contributions

Create pull requests (PRs) for changes that you think are needed. We would really appreciate your help!

Skills with the following would be beneficial:

  • Python
  • FastAPI
  • Javascript
  • React
  • Docker
  • CI/CD workflows

Our latest task board can be found here.

Report bugs and suggest improvements

The issue queue is the best way to get started. There are issue templates for BUGs and FEATURES that you can use, you could also create your own. Once you have submitted an issue, it will be assigned one label from the following [label categories](<https://github.com/hotosm/fmtm/labels). If you are wondering where to start, you can filter by the good first issue label.

🤝 Thank you

Thank you very much in advance for your contributions!! Please ensure you refer to our Code of Conduct. If you've read the guidelines, but are still not sure how to contribute on Github, please reach out to us via our Slack #geospatial-tech-and-innovation.

Code Contribution guidelines

Workflow

We operate the "Fork & Pull" model explained at About Pull Requests

You should fork the project into your own repo, create a topic branch there and then make one or more pull requests back to the repository. Your pull requests will then be reviewed and discussed by other developers. Don't submit a Pull Request while still developing the code, wait till the feature is complete and ready for review. A preliminary review by other developers can be requested via the comments for the issue on github, or via slack or email.

It is prefered that all patches contain any documentation updates made, and for any new features, a test case is preferred when possible. Keep patches focused on a single feature to avoid merging complications with other developers. The old free software joke is "patches are better than bug reports" is how we contribute to the community of people involved with this project.

If you are reporting a problem

  • Describe exactly what you were trying to achieve, what you did, what you expected to happen and what did happen instead. Include relevant information about the platform, OS version etc. you are using. Include shell commands you typed in, log files, errors messages etc.

  • Please open a separate issue for each problem, question, or comment you have. Do not re-use existing issues for other topics, even if they are similar. This keeps issues small and manageable and makes it much easier to follow through and make sure each problem is taken care of.

Documentation

Project documentation should be in Markdown format, and in a docs subdirectory. While it is possible to use HTML in Markdown documents for tables and images, it is prefered to use the Markdown style as it's much easier to read.

Coding Style

Python enforces a certain amount of style due to indent levels. Unlike C/C++, we don't have to worry about curly braces. It is prefered that all code follows object oriented techniques, with a minimal amount of code other than basic control in the main function. This allows code to be easily reused and run either standalone, or part of a REST API backend. Code that is not designed to be run standalone can have a main function to do simple testing during development. That test code should be moved to a standalone test case when possible. Pytest is used as the test framework for standalone test cases.

Code follows a CamelCase style. Classes use an Upper Case for the first word, method use a lower case for the first word. Variable names are all lower case with an underbar as a word separator. Properly naming everything makes it much easier to read the code and get an idea of what it is doing. This enables people new to this project to contribute easier.

All methods should have a comment that can be used by pydoc. The usage of base classes is encouraged so functionality can be shared. Comments in the code are encouraged when necessary to explain code that may not be obvious, but avoid over commenting as well. Code should be able to be read like a book, with descriptive names used, no fancy tricks unless required. Always be concious of performance and security.