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If Funcy and Pipe had a baby. Decorates all Funcy methods with Pipe superpowers.

Project description

Funcy with pipeline-based operators

If Funcy and Pipe had a baby. Deal with data transformation in python in a sane way.

I love Ruby, but believe Python is the way of the future. As I worked more with Python, it was driving me nuts that the data transformation options were not chainable like Ruby + Elixir. This project fixes this pet peeve.

Examples

import funcy_pipe as fp

entities_from_sql_alchemy
  | fp.lmap(lambda r: r.to_dict())
  | fp.lmap(lambda r: r | fp.omit(["id", "created_at", "updated_at"]))
  | fp.to_list

Or, you can be more fancy and use whatever and pmap:

import funcy_pipe as f
import whatever as _

entities_from_sql_alchemy
  | fp.lmap(_.to_dict)
  | fp.pmap(fp.omit(["id", "created_at", "updated_at"]))
  | fp.to_list

Grab the ID of a specific user:

filter_user_id = (
  collaborator_map().values()
  | fp.where(email=target_user)
  | fp.pluck("id")
  | fp.first()
)

What if the objects are not dicts?

filter_user_id = (
  collaborator_map().values()
  | fp.where_attr(email=target_user)
  | fp.pluck_attr("id")
  | fp.first()
)

A more complicated example (lifted from this project):

comments = (
    # tasks are pulled from the todoist api
    tasks
    # get all comments for each relevant task
    | fp.lmap(lambda task: api.get_comments(task_id=task.id))
    # each task's comments are returned as an array, let's flatten this
    | fp.flatten()
    # dates are returned as strings, let's convert them to datetime objects
    | fp.lmap(enrich_date)
    # no date filter is applied by default, we don't want all comments
    | fp.lfilter(lambda comment: comment["posted_at_date"] > last_synced_date)
    # comments do not come with who created the comment by default, we need to hit a separate API to add this to the comment
    | fp.lmap(enrich_comment)
    # only select the comments posted by our target user
    | fp.lfilter(lambda comment: comment["posted_by_user_id"] == filter_user_id)
    | fp.sort(key="posted_at_date")
    # create a dictionary of task_id => [comments]
    | fp.group_by(lambda comment: comment["task_id"])
)

Extras

  • to_list
  • log
  • bp. run breakpoint() on the input value
  • sort
  • exactly_one. Throw an error if the input is not exactly one element
  • reduce
  • pmap. Pass each element of a sequence into a pipe'd function

Coming From Ruby?

  • uniq => distinct
  • detect => where(some="Condition") | first or where_attr(some="Condition") | first

Module Alias

Create a module alias for funcy-pipe to make things clean (import * always irks me):

# fp.py
from funcy_pipe import *

# code py
import fp

Inspiration

TODO

  • tests
  • docs for additional utils
  • relax python version
  • fix typing threading

Project details


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