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expression-4.2.4


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توضیحات

Practical functional programming for Python 3.9+
ویژگی مقدار
سیستم عامل -
نام فایل expression-4.2.4
نام expression
نسخه کتابخانه 4.2.4
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Dag Brattli
ایمیل نویسنده dag.brattli@cognite.com
آدرس صفحه اصلی https://github.com/cognitedata/Expression
آدرس اینترنتی https://pypi.org/project/expression/
مجوز MIT
# Expression [![PyPI](https://img.shields.io/pypi/v/expression.svg)](https://pypi.python.org/pypi/Expression) ![Python package](https://github.com/cognitedata/expression/workflows/Python%20package/badge.svg) ![Upload Python Package](https://github.com/cognitedata/expression/workflows/Upload%20Python%20Package/badge.svg) [![Documentation Status](https://readthedocs.org/projects/expression/badge/?version=latest)](https://expression.readthedocs.io/en/latest/?badge=latest) [![codecov](https://codecov.io/gh/cognitedata/expression/branch/main/graph/badge.svg)](https://codecov.io/gh/cognitedata/expression) > Pragmatic functional programming Expression aims to be a solid, type-safe, pragmatic, and high performance library for frictionless and practical functional programming in Python 3.9+. By pragmatic, we mean that the goal of the library is to use simple abstractions to enable you to do practical and productive 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). This serves several purposes: - Enable functional programming in a Pythonic way, i.e., make sure we are not over-abstracting things. Expression will not require purely functional programming as would a language like Haskell. - Everything you learn with Expression can also be used with F#. Learn F# by starting in a programming language they already know. Perhaps get inspired to also [try out F#](https://aka.ms/fsharphome) by itself. - Make it easier for F# developers to use Python when needed, and re-use many of the concepts and abstractions they already know and love. Expression will enable you to work with Python 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. > _Expressions evaluate to a value. Statements do something._ 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# is in many ways very similar to Python, but F# can also do a lot of things better than Python: - Strongly typed, if it compiles it usually works making refactoring much safer. You can trust the type-system. With [mypy](http://mypy-lang.org/) or [Pylance](https://github.com/microsoft/pylance-release) you often wonder who is right and who is wrong. - 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 3.9+. ```console > 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. - Support PEP 634 and structural pattern matching. - Code must pass strict static type checking by [pylance](https://devblogs.microsoft.com/python/announcing-pylance-fast-feature-rich-language-support-for-python-in-visual-studio-code/). Pylance is awesome, use it! - [Pydantic](https://pydantic-docs.helpmanual.io/) friendly data types. Use Expression types as part of your Pydantic data model and (de)serialize to/from JSON. ## 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. - **Fluent or Functional** syntax, i.e., dot chain or pipeline operators. - **Pattern Matching** - an alternative flow control to `if-elif-else`. - **Error Handling** - Several error handling types. - **Option** - for optional stuff and better `None` handling. - **Result** - for better error handling and enables railway-oriented programming in Python. - **Try** - a simpler result type that pins the error to an Exception. - **Collections** - immutable collections. - **TypedArray** - a generic array type that abstracts the details of `bytearray`, `array.array` and `list` modules. - **Sequence** - a better [itertools](https://docs.python.org/3/library/itertools.html) and fully compatible with Python iterables. - **Block** - a frozen and immutable list type. - **Map** - a frozen and immutable dictionary type. - **AsyncSeq** - Asynchronous iterables. - **AsyncObservable** - Asynchronous observables. Provided separately by [aioreactive](https://github.com/dbrattli/aioreactive). - **Data Modelling** - sum and product types - **TaggedUnion** - A tagged (discriminated) union type. - **Parser Combinators** - A recursive decent string parser combinator library. - **Effects**: - lightweight computational expressions for Python. This is 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 will let you pipe a value through any number of functions. ```python from expression import pipe v = 1 fn = lambda x: x + 1 gn = lambda x: x * 2 assert pipe(v, fn, gn) == gn(fn(v)) ``` Expression objects (e.g., `Some`, `Seq`, `Result`) also have a `pipe` method, so you can dot chain pipelines directly on the object: ```python from expression import Some v = Some(1) fn = lambda x: x.map(lambda y: y + 1) gn = lambda x: x.map(lambda y: y * 2) assert v.pipe(fn, gn) == gn(fn(v)) ``` So for example with sequences you may create sequence transforming pipelines: ```python from expression.collections import seq, Seq xs = Seq.of(9, 10, 11) ys = xs.pipe( seq.map(lambda x: x * 10), seq.filter(lambda x: x > 100), seq.fold(lambda s, x: s + x, 0) ) assert ys == 110 ``` ### Composition Functions may even be composed directly into custom operators: ```python from expression import compose from expression.collections import seq, Seq xs = Seq.of(9, 10, 11) 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) assert ys == 110 ``` ### Fluent and Functional Expression can be used both with a fluent or functional syntax (or both.) #### Fluent syntax The fluent syntax uses methods and is very compact. But it might get you into trouble for large pipelines since it's not a natural way of adding line breaks. ```python from expression.collections import Seq xs = Seq.of(1, 2, 3) ys = xs.map(lambda x: x * 100).filter(lambda x: x > 100).fold(lambda s, x: s + x, 0) ``` Note that fluent syntax is probably the better choice if you use mypy for type checking since mypy may have problems inferring types through larger pipelines. #### Functional syntax The functional syntax is a bit more verbose but you can easily add new operations on new lines. The functional syntax is great to use together with pylance/pyright. ```python from expression import pipe from expression.collections import seq, Seq xs = Seq.of(1, 2, 3) ys = pipe(xs, seq.map(lambda x: x * 100), seq.filter(lambda x: x > 100), seq.fold(lambda s, x: s + x, 0), ) ``` Both fluent and functional syntax may be mixed and even pipe can be used fluently. ```python from expression.collections import seq, Seq xs = Seq.of(1, 2, 3).pipe(seq.map(...)) ``` ### Option The `Option` type is used when a function or method cannot produce a meaningful output for a given input. An option value may have a value of a given type, i.e., `Some(value)`, or it might not have any meaningful value, i.e., `Nothing`. ```python from expression import Some, Nothing, Option def keep_positive(a: int) -> Option[int]: if a > 0: return Some(a) return Nothing ``` ```python from expression import Option, Ok def exists(x : Option[int]) -> bool: match x: case Some(_): return True return False ``` ### Option as an effect Effects in Expression is implemented as specially decorated coroutines ([enhanced generators](https://www.python.org/dev/peps/pep-0342/)) using `yield`, `yield from` and `return` to consume or generate optional values: ```python from expression import effect, Some @effect.option[int]() 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)`. ```python from expression import effect, Some, Nothing @effect.option[int]() 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://expression.readthedocs.io/en/latest/tutorial/optional_values.html) - [API reference](https://expression.readthedocs.io/en/latest/reference/option.html) ### Result The `Result[T, TError]` type lets you write error-tolerant code that can be composed. A 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`). This type serves the same purpose of an `Either` type where `Left` is used for the error condition and `Right` for a success value. ```python from expression import effect, Ok, Result @effect.result[int, Exception]() def fn(): x = yield from Ok(42) y = yield from Ok(10) return x + y xs = fn() assert isinstance(xs, Result) ``` A simplified type called `Try` is also available. It's a result type that is pinned to `Exception` i.e., `Result[TSource, Exception]`. ### Sequence Sequences is a thin wrapper on top of iterables and contains operations for working with Python iterables. Iterables are immutable by design, and perfectly suited for functional programming. ```python import functools from expression import pipe from expression.collections import seq # 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: zs = 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 ``` ## Tagged Unions Tagged Unions (aka discriminated unions) may look similar to normal Python Unions. But they are [different](https://stackoverflow.com/a/61646841) in that the operands in a type union `(A | B)` are both types, while the cases in a tagged union type `U = A | B` are both constructors for the type U and are not types themselves. One consequence is that tagged unions can be nested in a way union types might not. In Expression you make a tagged union by defining your type as a sub-class of `TaggedUnion` with the appropriate generic types that this union represent for each case. Then you define static or class-method constructors for creating each of the tagged union cases. ```python from dataclasses import dataclass from expression import TaggedUnion, tag @dataclass class Rectangle: width: float length: float @dataclass class Circle: radius: float class Shape(TaggedUnion): RECTANGLE = tag(Rectangle) CIRCLE = tag(Circle) @staticmethod def rectangle(width: float, length: float) -> Shape: return Shape(Shape.RECTANGLE, Rectangle(width, length)) @staticmethod def circle(radius: float) -> Shape: return Shape(Shape.CIRCLE, Circle(radius)) ``` Now you may pattern match the shape to get back the actual value: ```python from expression import match shape = Shape.Rectangle(2.3, 3.3) match shape: case Shape(value=Rectangle(width=2.3)): assert shape.value.width == 2.3 case _: assert False ``` ## Notable differences between Expression and F# In F# 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. ```pycon >>> from expression import Option, option >>> Option <class 'expression.core.option.Option'> >>> option <module 'expression.core.option' from '/Users/dbrattli/Developer/Github/Expression/expression/core/option.py'> ``` ## 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 just a function, so you can easily implement a custom 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 collection of 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 (https://www.python.org/dev/peps/pep-0008/) - 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 (https://www.python.org/dev/peps/pep-0479/) - PEP 634 -- Structural Pattern Matching (https://www.python.org/dev/peps/pep-0634/) - 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 suggestions or PRs :heart_eyes: It is nice if you can try to align the code and naming with F# modules, functions, and documentation if possible. 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 checks are done using - [Black](https://github.com/psf/black) - [flake8](https://github.com/PyCQA/flake8) - [isort](https://github.com/PyCQA/isort) To run code checks on changed files every time you commit, install the pre-commit hooks by running: ```console > pre-commit install ``` ## Code of Conduct This project follows https://www.contributor-covenant.org, see our [Code of Conduct](https://github.com/cognitedata/Expression/blob/main/CODE_OF_CONDUCT.md). ## License MIT, see [LICENSE](https://github.com/cognitedata/Expression/blob/main/LICENSE).


نیازمندی

مقدار نام
>=4.1.1,<5.0.0 typing-extensions


زبان مورد نیاز

مقدار نام
>=3.9,<4 Python


نحوه نصب


نصب پکیج whl expression-4.2.4:

    pip install expression-4.2.4.whl


نصب پکیج tar.gz expression-4.2.4:

    pip install expression-4.2.4.tar.gz