pytoolz 0.1.7

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pytoolz 0.1.7

[](https://travis-ci.com/andrea-lascola/Pytoolz)[](https://badge.fury.io/py/pytoolz)[](https://bestpractices.coreinfrastructure.org/projects/2441)# Pytoolz 🚀Module containing some python utilities/abstractionspython >= 3.7 compatible## Prerequisites python >= 3.7## Installing pip install pytoolz## Sections* [Functional](#functional) λ* [Data Structures](#data-structures) 📂* [Cache](#cache) 🚀* [Design](#design) 🏛* [Logs](#logs) 📖* [Multiprocess](#multiprocess) 👯* [Serialization](#serialization) 🤖#### FunctionalA set of utilities oriented to functional programming.##### compose(f1: Callable, f2: Callable) -> CallableCompose two functions: return the fn composition of the two```pythonfrom pytoolz.functional import composeif __name__ == "__main__": f = compose(lambda x: x * 2, lambda x: x * 3) f(10) # 60```##### pipe(functions: List[Callable], obj)Recursively apply a list of morphism to an input value```pythonfrom pytoolz.functional import pipeif __name__ == "__main__": pipe([lambda x: x * 3, lambda x: x * 2, lambda x: x / 3], 10) # 20.0```##### flat_map(fn: Callable, collection: Iterable)Apply the input function to every element in iterable and flatten the result lists```pythonfrom pytoolz.functional import flat_mapif __name__ == "__main__": flat_map(lambda x: [x, x], [1, 2, 3]) # [1, 1, 2, 2, 3, 3] flat_map(lambda x: (x, x), [1, 2, 3]) # [1, 1, 2, 2, 3, 3]```##### iflat_map(fn: Callable, collection: Iterable)Apply the input function to every element in iterable and flatten the result list **lazily**```pythonfrom pytoolz.functional import iflat_mapif __name__ == "__main__": iflat_map(lambda x: [x, x], [1, 2, 3]) # [1, 1, 2, 2, 3, 3] iflat_map(lambda x: (x, x), [1, 2, 3]) # [1, 1, 2, 2, 3, 3]```##### for_each(fn: Callable, collection: Iterable)Create side effect applying the input function for every element in iterable```pythonfrom pytoolz.functional import iflat_mapif __name__ == "__main__": iflat_map(lambda x: [x, x], [1, 2, 3]) # [1, 1, 2, 2, 3, 3] iflat_map(lambda x: (x, x), [1, 2, 3]) # [1, 1, 2, 2, 3, 3]```##### Stream(iterable: Iterable) -> Stream[Experiment] Emulate the Java Stream API to create pipelines of transformations unsing function composition```pythonfrom pytoolz.functional import Streamif __name__ == "__main__": Stream([1, 2, 3]).map(lambda x: x * 3).to_list() # [3, 6, 9] Stream([1, 2, 3]).sum().to_int() # 6 Stream([1, 2, 3]).map(lambda x: x * 3).filter(lambda x: x >= 6).to_tuple() # (6, 9) Stream(["a", "b", "c"]).map(lambda x: x + "a").to_set() == {'aa', 'ba', 'ca'} # True Stream([1, 4, 3]) \ .map(lambda x: x + 3) \ .map(lambda x: x * x) \ .filter(lambda x: x > 3) \ .sum() \ .to_float() # 101.0 #Alternative constructor Stream.of([1, 2, 3], [ (Stream.map, lambda x: x * 3), (Stream.map, lambda x: x * 3) ]).to_list() # [9, 18, 27]```#### SerializationSerialization and deSerialization of objects:different engine are built-in: Json/Pickle/Dict```pythonfrom pytoolz.serialization import Dict, Json, Pickleif __name__ == "__main__": original = '{"users": ["bob", "foo", "bar"], "companies": {}}' data = Json(original).deserialize() print(type(data)) # '<class 'dict'>' string_data = Json(data).serialize() print(type(string_data)) # '<class 'str'>'```#### Data structuresUtilities related to data structures (missing data structures or customization of existing ones) ##### LinkedList ```pythonfrom pytooolz.ds import LinkedList, Nodeif __name__ == "__main__": ll = LinkedList() ll.add(Node(3)) ll.add(Node(4)) ll.add(Node(5)) ll.add(Node(6)) print(ll) #$ LinkedList(head=Node(value=6, next=Node(value=5, next=Node(value=4, next=Node(value=3, next=None)))))```##### DoublyLinkedListTODO complete#### CacheUtilities related to **caching**. Different backend will be implemented:ex:* Redis* Memcache* LRU in-memory* Filesystem```pythonfrom pytooolz.cache import memoize # memoize decoratorfrom pytooolz.cache import FileEngine # Disk cache enginefrom pytooolz.cache import InMemoryEngine # LRU in memory enginefrom pytooolz.cache import MemcachedEngine # Memcache enginefrom pytooolz.cache import RedisEngine # Redis engineif __name__ == "__main__": @memoize(InMemoryEngine(limit=10, expiration=10)) def fn(*args): return args fn(1, 2, 3, 4, 5) # fn evaluated fn(1, 2, 3, 4, 5) # got from cache fn(1, 2, 3, 4, 5) # got from cache fn(1, 2, 3, 4, 5) # got from cache```#### DesignUtilities related to application design**Singleton decorator** - Examples:```pythonfrom pytooolz.design import singletonif __name__ == "__main__": @singleton.singleton class MyClass: pass assert id(MyClass()) == id(MyClass())```**Traits** Attach a specific trait to an instance.This should enable polimorphism using composition instead of classic inheritanceTo use this feature:* decorate your class with ```@extendable``` decorator* implement your custom class that implements ```Trait``` interface* choose one (or more) traits during the class init using ```.with_trait(...)```Example: ```python from pytooolz.design import Trait from pytooolz.design import extendable if __name__ == "__main__": class UserRenderHtml(Trait): def render(self): print(""" <h1>{0!s}</h1> <p>{1!s}</p> """.format(self.name, self.surname)) class UserRenderText(Trait): def render(self): print(self.name, self.surname) @extendable class User: def __init__(self, name, surname): self.name = name self.surname = surname usr = User("Andrea", "La Scola").with_trait(UserRenderHtml) print(usr.render()) ```#### Logs**log decorators** - multiple backends## Authors* **Andrea La Scola** - *Initial work* - [PurpleBooth](https://github.com/andrea-lascola)