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            "Programming Language :: Python :: 3.6",
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        "description": "# Functional Python - Scala-like monadic data types\n\n**Functional Python** is a framework which implements Scala-like monadic data types,\nsuch as [Option](https://scala-lang.org/api/2.13.x/scala/Option.html) or [Map](https://docs.scala-lang.org/overviews/collections/maps.html).\n\n## Why?\n##### Method chaining\n```python\n# ToDo: Example\n```\n\n##### Type Safety\n```python\n# ToDo: Example\n```\n\n## Api Description\n### Options\nRepresents optional values.\nInstances of Option are either an instance of Some or the object None.\nOptions are generics of single type parameter.\n\n##### Creating an Option\n```python\nfrom functional.option import *\n\n# Scala-like constructor\nx = Some(4)      # Some(4)\ny = Option.empty # None\nz = none         # None\n\n# Python-like constructor\nx = Option(4)    # Some(4)\ny = Option(None) # None\n```\n\nNote that `None` which is printed **is not** Python `None`\nbut is special object which does not contain any value and equals to `Option(None)`.\n\n##### Getting value of an Option\nOptions implement `.get` property and `.getOrElse(default)` method.\nFirst one checks Option is not empty and either returns value or throws an exception.\nSecond one returns *default* instead of throwing an exception.\n\n```python\nfrom functional.option import *\nx = Some(4)      # Some(4)\ny = none         # None\n\nx.get            # 4\ny.get            # raises EmptyOption\n\nx.get_or_else(5) # 4\ny.get_or_else(5) # 5\n\n# .is_defined returns True if Option is not None\nx.is_defined     # True\ny.is_defined     # False\n\n# .is_empty is the opposite\nx.is_empty       # False\ny.is_empty       # True\n\n# .non_empty is the same as .is_defined\nx.non_empty      # True\ny.non_empty      # False\n```\n\nNote that unlike in Scala, this Option's `.get_or_else` is not lazy-evaluated,\nso this code will fail:\n```python\nSome(4).get_or_else(1/0)\n```\n\nTo prevent, it is recommended use python-like accessors (see below).\n\n##### Mapping an Option\nOptions are both functors and monads, meaning they possess `.map()` and `.flat_map()` methods\nwith the following signatures (where object is a type `Option[A]`):\n - `.map(f: A => B): Option[B]` - map value inside an Option.\n - `.flat_map(f: A => Option[B]): Option[B]` - map value inside an Option to an Option.\n\nBoth these methods work only on non-empty options, returning `Option.empty` for otherwise.\n\n```python\nfrom functional.option import *\nx = Some(4)            # Some(4)\ny = none               # None\nz = Some(6)            # Some(6)\n\nx.map(lambda v: v + 2) # Some(6)\ny.map(lambda v: v + 2) # None\nz.map(lambda v: v + 2) # Some(8)\n\nx.flat_map(lambda v: Some(v) if v < 5 else none) # Some(4)\ny.flat_map(lambda v: Some(v) if v < 5 else none) # None\nz.flat_map(lambda v: Some(v) if v < 5 else none) # None\n```\n\n##### Flattening an Option\nSometimes you get an Option which contains Option.\nThere is special property `.flatten` which converts `Option[Option[T]]` into `Option[T]`\n\n```python\n# ToDo: Example\n```\n\n##### Python-style accessors\nOptions support python-like accessors / converters `__bool__`, `__iter__`, `__len__`, and `__enter__/__exit`.\n\n```python\n# ToDo: Example\n```\n\n### Map\n**TODO**\n\n## Plans\n - Test coverage\n - Support Maps (both mutable and immutable)\n - Support Lists (both mutable and immutable)\n\n\n",
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