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Fix build and coverage badge (#377)
- Specify that coverage must be run for each new release.
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.github/workflows/coverage.yml

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push:
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branches: [ master, develop ]
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pull_request:
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release:
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types: [ published ]
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env:
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CARGO_TERM_COLOR: always

README.md

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<img src="image/logo.svg" height="200" alt="Mamba logo"/>
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<br/><br/>
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<a href="https://github.com/JSAbrahams/mamba/actions/workflows/rust.yml">
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<img src="https://img.shields.io/github/workflow/status/JSAbrahams/mamba/Test?style=for-the-badge" alt="GitHub Workflow Status">
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<img src="https://img.shields.io/github/actions/workflow/status/JSAbrahams/Mamba/test.yml?style=for-the-badge" alt="GitHub Workflow Status">
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</a>
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<a href="https://app.codecov.io/gh/JSAbrahams/mamba/">
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<img src="https://img.shields.io/codecov/c/github/JSAbrahams/mamba?style=for-the-badge" alt="Codecov coverage">
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<h1 align="center">Mamba</h1>
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This is the Mamba programming language.
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This is the Mamba programming language.
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Mamba is like Python, but with a few key features:
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- Strict static typing rules, but with type inference so it doesn't get in the way too much
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- Pure functions, or, functions without side effects
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This is a transpiler, written in [Rust](https://www.rust-lang.org/), which converts Mamba source files to Python source
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files.
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files.
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Mamba code should therefore be interoperable with Python code.
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Functions written in Python can be called in Mamba and vice versa (from the generated Python files).
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This means that the compiler will check for us that factorial is only used with integers as argument.
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_Note_ One could use [dynamic programming](https://en.wikipedia.org/wiki/Dynamic_programming) in the above example so that we consume less memory:
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```mamba
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def factorial(x: Int) -> Int => match x
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0 => 1
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### 🗃 Type refinement (🇻 0.6+)
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As shown above Mamba has a type system.
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As shown above Mamba has a type system.
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Mamba however also has type refinement features to assign additional properties to types.
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Lets expand our server example from above, and rewrite it slightly:
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Mamba has features to ensure that functions are pure, meaning that if `x = y`, for any `f`, `f(x) = f(y)`.
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(Except if the output of the function is say `None` or `NaN`.)
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By default, functions are not pure, and can read any variable they want, such as in Python.
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By default, functions are not pure, and can read any variable they want, such as in Python.
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When we make a function `pure`, it cannot:
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- Read non-final properties of `self`.

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