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Linqit!

Extends python's list builtin with fun, robust functionality - .NET's Language Integrated Queries (Linq) and more.
Write clean code with powerful syntax.

pip install linqit


Stop using loops, complex conditions, list comprehension and filters.
Doesn't it looks better?

from linqit import List # Go ahead and fill the list with whatever you want... like a list of <Programmer> objects. programmers = List() Avi = type("Avi", (), {}) Entrepreneur = type("Entrepreneur", ('talented'), {}) elon_musk = Entrepreneur(talented=True) # Then play: last_hot_pizza_slice = ( programmers.where(lambda e: e.experience > 15) .except_for(elon_musk) .of_type(Avi) .take(3) # [<Avi>, <Avi>, <Avi>] .select(lambda avi: avi.lunch) # [<Pizza>, <Pizza>, <Pizza>] .where(lambda p: p.is_hot() and p.origin != "Pizza Hut") .last() # <Pizza> .slices.last() # <PizzaSlice> ) # What do you think?

We all use multiple aggregations in our code, while multiple filters/comprehensions are not pythonic at all.
The whole idea is is to use it for nested, multiple filters/modifications :).
Some of the methods might look ridiculous for a single calls, comparing to the regular python syntax.
Here are some use cases:

Methods:

all any concat contains distinct except_for first get_by_attr intersect last select skip take where of_type 

Properties:

sum min max avg sorted 

Deeper - Let's play with a list of people, a custom type.

import List class Person(): def __init__(self, name, age): self.name = name self.age = age def __repr__(self): return f'Person(name="{self.name}", age={self.age})') # Creating a list of people avi, bill, bob, harry = Person('Avi', 23), Person('Bill', 41), Person('Bob', 77), Person('Harry', 55) people = List(avi, bill, bob, harry)

Use LINQ selections, write cleaner code

people = people.where(lambda p: p.age > 23) # [<Person name="Bill" age="41">, <Person name="Bob" age="77">, <Person name="Harry" age="55">] people.first() # <Person name="Bill" age="41"> people.last() # <Person name="Harry" age="55"> people.any(lambda p: p.name.lower().startswith('b')) # True people.where(age=55) # [<Person name="Harry" age="55">] people.skip(3).any() # False people.skip(2).first() # <Person name="Harry" age="55"> # Isn't it better than "for", "if", "else", "filter", "map" and list comprehensions in the middle of your code?

More selections

new_kids_in_town = [Person('Chris', 18), Person('Danny', 16), Person('John', 17)] people += new_kids_in_town # Also works: people = people.concat(new_kids_in_town) teenagers = people.where(lambda p: 20 >= p.age >= 13) danny = teenagers.first(lambda t: t.name == 'Danny') # <Person name="Danny" age="16"> oldest_teen = teenagers.order_by(lambda t: t.age).last() # <Person name="John" age="17">

Let's make python more dynamic

names = people.name # ['Avi', 'Bill', 'Bob', 'Harry', 'Chris', 'John'] ages = people.age # [23, 41, 77, 55, 18, 17] teenagers_names = teenagers.name # ['Chris', 'Danny', 'John'] teenagers_names.take(2).except_for(lambda n: n == 'Danny') # ['Chris'] teenagers.age.min # 16 teenagers.age.avg # 17 teenagers.age.max # 18

Test Coverage

linqit git:(master) ✗ coverage report Name Stmts Miss Cover ----------------------------------------- linqit/__init__.py 2 0 100% linqit/linq_list.py 101 11 89% tests/__init__.py 0 0 100% tests/test_list.py 203 0 100% ----------------------------------------- TOTAL 306 11 96%