Metadata-Version: 2.1
Name: Expression
Version: 0.25.0
Summary: Practical functional programming for Python 3.8+
Home-page: https://github.com/dbrattli/expression
Author: Dag Brattli
Author-email: dag@brattli.net
License: MIT License
Download-URL: https://github.com/dbrattli/expression
Description: # Expression
        
        [![PyPI](https://img.shields.io/pypi/v/expression.svg)](https://pypi.python.org/pypi/Expression)
        ![Python package](https://github.com/dbrattli/expression/workflows/Python%20package/badge.svg)
        ![Upload Python Package](https://github.com/dbrattli/expression/workflows/Upload%20Python%20Package/badge.svg)
        [![codecov](https://codecov.io/gh/dbrattli/expression/branch/master/graph/badge.svg)](https://codecov.io/gh/dbrattli/expression)
        
        > *Expressions evaluates to a value. Statements do something.*
        
        Expression aims to be a solid, type safe and high performance library
        for practical functional programming in Python 3.8+. By practical we
        mean that the goal of the library is to use simple abstractions to
        enable you to do productive and meaningful functional programming in
        Python (instead of being a [Monad
        tutorial](https://github.com/dbrattli/OSlash)).
        
        Python is a multi-paradigm programming language that also supports
        functional programming constructs such as functions, higher-order
        functions, lambdas, and in many ways favors composition over inheritance.
        
        > Better Python with F#
        
        Expression tries to make a better Python by providing several functional
        features inspired by [F#](https://fsharp.org) into Python. This serves
        two purposes:
        
        - Make it easier for Python programmers to learn F# by starting out in a
          programming language they already know. Then get inspired to [try out
          F#](https://aka.ms/fsharphome) by itself. Everything you learn with
          Expression can also be used with F#.
        - Make it easier for F# developers to use Python when needed, and re-use
          many of the concepts and abstractions that they already know and love.
        
        Expression will enable you to work with Python along with F# using many
        of the same programming concepts and abstractions. This enables concepts
        such as [Railway oriented
        programming](https://fsharpforfunandprofit.com/rop/) (ROP) for better
        and predictable error handling. Pipelining for workflows, computational
        expressions, etc.
        
        F# is a functional programming language for .NET that is succinct
        (concise, readable and type-safe) and kind of
        [Pythonic](https://docs.python.org/3/glossary.html). F# looks a lot more
        like Python than C# and F# can also do a lot of things better than
        Python:
        
        - Strongly typed, if it compiles it usually works making refactoring
          much safer.
        - Type inference, the compiler deduces types during compilation
        - Expression based language
        
        ## Getting Started
        
        You can install the latest `expression` from PyPI by running `pip` (or
        `pip3`). Note that `expression` only works for Python 3.8+.
        
        ```sh
        $ pip3 install expression
        ```
        
        ## Goals
        
        - Industrial strength library for functional programming in Python.
        - The resulting code should look and feel like Python
          ([PEP-8](https://www.python.org/dev/peps/pep-0008/)). We want to make
          a better Python, not some obscure DSL or academic Monad tutorial.
        - Provide pipelining and pipe friendly methods. Compose all the things!
        - Dot-chaining on objects as an alternative syntax to pipes.
        - Lower the cognitive load on the programmer by:
          - Avoid currying, not supported in Python by default and not a well
            known concept by Python programmers.
          - Avoid operator (`|`, `>>`, etc) overloading, this usually confuses
            more than it helps.
          - Avoid recursion. Recursion is not normally used in Python and any
            use of it should be hidden within the SDK.
        - Provide [type-hints](https://docs.python.org/3/library/typing.html) for all
          functions and methods.
        - Code must pass strict static type checking by
          [mypy](http://mypy-lang.org/) and
          [pylance](https://devblogs.microsoft.com/python/announcing-pylance-fast-feature-rich-language-support-for-python-in-visual-studio-code/).
          Pylance is awesome, use it!
        
        ## Supported features
        
        Expression will never provide you with all the features of F# and .NET. We are
        providing a few of the features we think are useful, and will add more
        on-demand as we go along.
        
        - **Pipelining** - for creating workflows.
        - **Composition** - for composing and creating new operators
        - **Pattern Matching** - a better of testing than if-elif-else.
        
        - **Option** - for optional stuff and better `None` handling.
        - **Result** - for better error handling and enables railway-oriented
          programming in Python.
        - **Collections** - immutable collections.
          - **Sequence** - a better
            [itertools](https://docs.python.org/3/library/itertools.html) and
            fully compatible with Python iterables.
          - **FrozenList** - a frozen and immutable list type.
          - **Map** - a frozen and immutable dictionary type.
          - **AsyncSeq** - Asynchronous iterables.
        - **Effects**: - lightweight computational expressions for Python. This
          is actually amazing stuff.
          - **option** - an optional world for working with optional values.
          - **result** - an error handling world for working with result values.
        - **Mailbox Processor**: for lock free programming using the [Actor
          model](https://en.wikipedia.org/wiki/Actor_model).
        - **Cancellation Token**: for cancellation of asynchronous (and
          synchronous) workflows.
        - **Disposable**: For resource management.
        
        ### Pipelining
        
        Expression provides a `pipe` function similar to `|>` in F#. We don't
        want to overload any Python operators e.g `|` so `pipe` is a plain old
        function taking N-arguments and thus lets you pipe a value though any
        number of functions.
        
        ```py
        from expression.core import pipe
        
        gn = lambda g: g * y
        fn = lambda x: x + z
        value = pipe(
            x,
            fn,
            gn
        )
        
        assert value == gn(fn(x))
        ```
        
        Expression objects also have a pipe method so you can dot chain
        pipelines directly on the object:
        
        ```py
        from expression.core import pipe
        
        gn = lambda g: g * y
        fn = lambda x: x + z
        value = x.pipe(
            fn,
            gn
        )
        
        assert value == gn(fn(x))
        ```
        
        So for example with sequences you may create sequence transforming
        pipelines:
        
        ```py
        ys = xs.pipe(
            seq.map(lambda x: x * 10),
            seq.filter(lambda x: x > 100),
            seq.fold(lambda s, x: s + x, 0)
        )
        ```
        
        ### Composition
        
        Functions may even be composed directly into custom operators:
        
        ```py
        from expression.core import compose
        
        custom = compose(
            seq.map(lambda x: x * 10),
            seq.filter(lambda x: x > 100),
            seq.fold(lambda s, x: s + x, 0)
        )
        
        ys = custom(xs)
        
        ```
        
        ### Options
        
        The option type is used when an actual value might not exist for a named
        value or variable. An option has an underlying type and can hold a value
        of that type `Some(value)`, or it might not have the value `Nothing`.
        
        ```py
        from expression.core import Some, Nothing, Option
        
        def keep_positive(a: int) -> Option[int]:
            if a > 0:
                return Some(a)
            else:
                return Nothing
        ```
        
        ```py
        def exists(x : Option[int]) -> bool:
            for value in x.match(Ok):
                return True
            else:
                return False
        ```
        
        Options as decorators for computational expressions. Computational
        expressions in Expression are implemented as coroutines ([enhanced
        generators](https://www.python.org/dev/peps/pep-0342/)) using `yield`,
        `yield from` and `return` to consume or generate optional values:
        
        ```py
        from expression import effect
        from expression.core import Some
        
        @effect.option
        def fn():
            x = yield 42
            y = yield from Some(43)
        
            return x + y
        
        xs = fn()
        ```
        
        This enables ["railway oriented
        programming"](https://fsharpforfunandprofit.com/rop/) e.g if one part of
        the function yields from `Nothing` then the function is side-tracked
        (short-circuit) and the following statements will never be executed. The
        end result of the expression will be `Nothing`. Thus results from such
        an option decorated function can either be `Ok(value)` or
        `Error(error_value)`.
        
        ```py
        from expression import effect
        from expression.core import Some, Nothing
        
        @effect.option
        def fn():
            x = yield from Nothing # or a function returning Nothing
        
            # -- The rest of the function will never be executed --
            y = yield from Some(43)
        
            return x + y
        
        xs = fn()
        assert xs is Nothing
        ```
        
        For more information about options:
        
        - [Tutorial](https://github.com/dbrattli/Expression/blob/master/notebooks/Options.ipynb)
        - [API reference](https://dbrattli.github.io/Expression/expression/core/option.html)
        
        ### Results
        
        The `Result[T, TError]` type lets you write error-tolerant code that can
        be composed. Result works similar to `Option` but lets you define the
        value used for errors, e.g an exception type or similar. This is great
        when you want to know why some operation failed (not just `Nothing`).
        
        ```py
        from expression import effect
        from expression.core import Result, Ok, Error, pipe
        
        @effect.result
        def fn():
            x = yield from Ok(42)
            y = yield from OK(10)
            return x + y
        
        xs = fn()
        assert isinstance(xs, Some)
        ```
        
        ### Sequences
        
        Contains operations for working with iterables. Thus all the functions
        in this module will work on normal Python iterables. Iterables are
        already immutable by design, so they are already perfectly suited for
        using with functional programming.
        
        ```py
        # Normal python way. Nested functions are hard to read since you need to
        # start reading from the end of the expression.
        xs = range(100)
        ys = functools.reduce(lambda s, x: s + x, filter(lambda x: x > 100, map(lambda x: x * 10, xs)), 0)
        
        # With Expression you pipe the result so it flows from one operator to the next:
        ys = pipe(
            xs,
            seq.map(lambda x: x * 10),
            seq.filter(lambda x: x > 100),
            seq.fold(lambda s, x: s + x, 0),
        )
        assert ys == zs
        ```
        
        ### Pattern Matching
        
        Pattern matching is a bit tricky for a language like Python. We are
        waiting for [PEP 634](https://www.python.org/dev/peps/pep-0634/) and
        structural pattern matching for Python. But we need something that can
        by handled by static type checkers and will also unwrap inner e.g
        optional values and results.
        
        Goals for pattern matching:
        
        - Type safety
        - Case handling must be inline, i.e we want to avoid lambdas which would
          make things difficult for async code.
        - Unpacking of wrapped values, e.g options and results.
        - Pythonic. Is it possible?
        - Check multiple cases with default handling.
        
        The solution we propose is based on for-loops and singleton iterables.
        This lets us write code inline, unwrap inner values and also effectively
        skip cases that doesn't match.
        
        ```py
        from expression.core import match
        
        m = match("expression")
        
        for _ in m.case("rxpy"):
            assert False
        
        for value in m.case(str):
            assert value == "expression"
        
        for value in m.case(float):
            assert False
        
        for _ in m.default():
              assert False
        ```
        Classes may also support `match` with pattern directly, i.e:
        `xs.match(pattern)` is effectively the same as
        `match(xs).case(pattern)`. For multiple cases you will need to use
        `match` to get a match object (since the match object will keep state to
        know if it has found a match or not).
        
        ```py
          xs = Some(42)
          ys = xs.map(lambda x: x + 1)
        
          for value in ys.match(Some):
              assert value == 43
              break
          else:
              assert False
        ```
        
        Pattern matching can also be used with destructuring of e.g iterables:
        
        ```py
        xs: FrozenList[int] = empty.cons(42)
        for (head, *_) in xs.match(FrozenList):
            assert head == 42
        ```
        
        Classes may decide to support more advance pattern matching by
        subclassing or implementing the matching protocol:
        
        ```py
        class Matchable(Protocol[TSource]):
            """Pattern matching protocol."""
        
            @abstractmethod
            def __match__(self, pattern: Any) -> Iterable[TSource]:
                """Return a singleton iterable item (e.g `[ value ]`) if pattern
                matches, else an empty iterable (e.g. `[]`)."""
                raise NotImplementedError
        ```
        
        ## Notable Differences
        
        In F# you modules are capitalized, in Python they are lowercase
        ([PEP-8](https://www.python.org/dev/peps/pep-0008/#package-and-module-names)).
        E.g in F# `Option` is both a module (`OptionModule` internally) and a type. In Python the module is
        `option` and the type is capitalized i.e `Option`.
        
        Thus in Expression you use `option` as the module to access module
        functions such as `option.map` and the name `Option` for the type
        itself.
        
        ```py
        >>> from expression.core import Option, option
        >>> Option
        <class 'expression.core.option.Option'>
        >>> option
        <module 'expression.core.option' from '/Users/dbrattli/Developer/Github/Expression/expression/core/option.py'>
        ```
        
        ## Why
        
        - I love F#, and know F# quite well. I'm the creator of projects such as
          [Oryx](https://github.com/cognitedata/oryx),
          [Fable.Reaction](https://github.com/dbrattli/Fable.Reaction) and
          [Feliz.ViewEngine](https://github.com/dbrattli/Feliz.ViewEngine)
        - I love Python, and know Python really well. I'm the creator of both
          [RxPY](https://github.com/ReactiveX/RxPY) and
          [OSlash](https://github.com/dbrattli/OSlash), two functional style
          libraries for Python.
        
        For a long time I'm been wanting to make a "bridge" between these two
        languages and got inspired to write this library after watching "[F# as
        a Better Python](https://www.youtube.com/watch?v=_QnbV6CAWXc)" - Phillip
        Carter - NDC Oslo 2020. Doing a transpiler like
        [Fable](https://fable.io) for Python is one option, but a Python library
        may give a lower barrier and a better introduction to existing Python
        programmers.
        
        Expression is an F# inspired version of my previously written
        [OSlash](https://github.com/dbrattli/OSlash) monad tutorial where I
        ported a number of Haskell abstractions to Python. I never felt that
        OSlash was really practically usable in Python, but F# is much closer to
        Python than Haskell, so it makes more sense to try and make a functional
        library inspired by F# instead.
        
        ## Common Gotchas and Pitfalls
        
        A list of common problems and how you may solve it:
        
        ### Expression is missing the function / operator I need
        
        Remember that everything is a function, so you can easily implement the
        function yourself and use it with Expression. If you think the function
        is also usable for others, then please open a PR to include it with
        Expression.
        
        ## Resources and References
        
        A collections and resources that were used as reference and inspiration
        for creating this library.
        
        - F# (http://fsharp.org)
        - Get Started with F# (https://aka.ms/fsharphome)
        - F# as a Better Python - Phillip Carter - NDC Oslo 2020
          (https://www.youtube.com/watch?v=_QnbV6CAWXc)
        - OSlash (https://github.com/dbrattli/OSlash)
        - RxPY (https://github.com/ReactiveX/RxPY)
        - PEP 8 -- Style Guide for Python Code (Style Guide for Python Code)
        - PEP 342 -- Coroutines via Enhanced Generators
          (https://www.python.org/dev/peps/pep-0342/)
        - PEP 380 -- Syntax for Delegating to a Subgenerator
          (https://www.python.org/dev/peps/pep-0380)
        - PEP 479 -- Change StopIteration handling inside generators
        - Thunks, Trampolines and Continuation Passing
          (https://jtauber.com/blog/2008/03/30/thunks,_trampolines_and_continuation_passing/)
        - Tail Recursion Elimination
          (http://neopythonic.blogspot.com/2009/04/tail-recursion-elimination.html)
        - Final Words on Tail Calls
          (http://neopythonic.blogspot.com/2009/04/final-words-on-tail-calls.html)
        - Python is the Haskell You Never Knew You Had: Tail Call Optimization
          (https://sagnibak.github.io/blog/python-is-haskell-tail-recursion/)
        
        ## How-to Contribute
        
        You are very welcome to contribute with PRs :heart_eyes: It is nice if
        you can try to align the code with F# modules, functions and
        documentation. But submit a PR even if you should feel unsure.
        
        Code, doc-strings and comments should also follow the [Google Python
        Style Guide](https://google.github.io/styleguide/pyguide.html). Code is
        formatted using [Black](https://github.com/psf/black).
        
        ## License
        
        MIT, see [LICENSE](https://github.com/dbrattli/Expression/blob/master/LICENSE).
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Description-Content-Type: text/markdown
