A Python 3 library that provides a fluent interface for data transformations and aggregations over iterable objects.
from fluentflow import Flows
# Dummy data, pretend this is a warehouse's inventory
def get_inventory():
yield {'Quantity': 123, 'Name': 'Lightbulbs', 'Section': 'Electronics'}
yield {'Quantity': 456, 'Name': 'Nails', 'Section': 'Hardware'}
yield {'Quantity': 789, 'Name': 'Keyboards', 'Section': 'Electronics'}
# Get the total inventory in the warehouse (all items)
print(Flows.calling(get_inventory)
.map(lambda x: x['Quantity'])
.digest(sum)
)
# Get the total distinct item sections
print(Flows.calling(get_inventory)
.map(lambda x: x['Section'])
.distinct()
.count()
)A pyproject.toml file is included in this repository. You should be able to clone this repository, cd into it, and then run the following command:
pip install .There are no additional dependencies, all you need is Python 3.
Static factory methods are available in the Flows class.
# Create an empty flow (contains no elements):
Flows.empty()
# Create a flow from a list of arguments
Flows.of(1, 2, 3)
# Create a flow from an iterable
# Note: Do not pass generators to this function. Consider instead using Flows.calling (see below)
Flows.create([1, 2, 3])
# Create a flow from a function that returns an iterable or a generator.
def generator_func():
yield 1
yield 2
yield 3
Flows.calling(generator_func)Operations may be modifying or terminal. A modifying operation transforms the data in the flow. They may be chained together to form more complicated operations. A terminal operation ends the chain of operations and returns an aggregated result.
- filter
- flatmap
- limit
- map
- reverse
- skip
- slice
- any
- all
- count
- get (get_or)
- digest
- first (first_or)
- last (last_or)
- reduce
- to_list
- to_set
- to_tuple