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 # 18Test 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%