Stefan Schenk Menziess

Gitlab PyPi Repo

Create a Gitlab PAT here: link, having the read_api scope.
Modify (or create) ~/.pip/pip.conf on your machine, and replace with your token and <GROUP_ID> with the project's group id:

[global]
index-url = https://pypi.org/simple
extra-index-url = https://__token__:@gitlab.com/api/v4/groups//-/packages/pypi/simple

	"""Stream synchronization.

	$ pip install slipstream-async

	The activity stream depends on the weather stream.
	When weather goes down, activity is paused until weather recovers.
	When it recovers, it moves back to the checkpoint offset
	and reprocesses messages enriched with stale data.
	"""

	"""Stream synchronization.

	$ pip install slipstream-async

	The first stream depends on second, which depends on third.
	And third depends on second.
	1 <- 2 <- 3
	3 <- 2

	When third goes down, second will pause, after which first will pause.

	from tslearn.clustering import TimeSeriesKMeans
	from tslearn.utils import to_time_series_dataset
	import pandas as pd

	data = [
	[0, 1, 2, 3, 4],
	[1, 2, 3, 4, 0],
	[0, 1, 2, 3, 4],
	[0, 1, 2, 3, 4],
	[5, 6, 3, 4, 0],

	class DirectedGraph:
	"""A basic implementation of a directed graph."""

	def __init__(self):
	self.graph = {}

	def add_node(self, node):
	if node not in self.graph:
	self.graph[node] = {}

	from datetime import datetime as dt, timezone
	from re import match

	from toolz.curried import curry


	DATETIME_FORMAT = '%Y-%m-%dT%H:%M:%SZ'
	DATE_FORMAT = '%Y-%m-%d'

	@curry

	from itertools import groupby, islice
	from typing import Iterable, cast

	from toolz.curried import curry, map, pluck


	def batched(iterable, n):
	"""Batch data into tuples of length n.

	>>> list(batched('ABCDEF', 3))

	from typing import Iterable

	def dict_diff(
	old: dict,
	new: dict,
	ignore_keys: Iterable[str] = [],
	include_keys: Iterable[str] = []
	) -> dict:
	"""Capture changes between dictionaries.