Time ranges with python

Related tags

Data Analysistimeranges
Overview

Discord

Badges
Build Python package semantic-release PyPI Read the Docs
Tests coverage pre-commit
Standards SemVer 2.0.0 Conventional Commits
Code Code style: black Imports: isort Checked with mypy
Repo GitHub issues GitHub stars GitHub license All Contributors Contributor Covenant

timeranges

Time ranges.

Read the Docs

Installation

pip

timeranges is available on pip:

pip install timeranges

GitHub

You can also install the latest version of the code directly from GitHub:

pip install git+git://github.com/MicaelJarniac/timeranges

Usage

For more examples, see the full documentation.

10:00" time_range = TimeRange(time(0), time(10)) # Check if these times are contained in `time_range` assert time(0) in time_range assert time(5) in time_range assert time(10) in time_range # Check if these times aren't contained in `time_range` assert time(10, 0, 1) not in time_range assert time(11) not in time_range assert time(20) not in time_range time_range_2 = TimeRange(time(15), time(20)) time_ranges = TimeRanges([time_range, time_range_2]) assert time(0) in time_ranges assert time(5) in time_ranges assert time(10) in time_ranges assert time(12) not in time_ranges assert time(15) in time_ranges assert time(17) in time_ranges assert time(20) in time_ranges assert time(22) not in time_ranges "> 
from datetime import time

from timeranges import TimeRange, TimeRanges, WeekRange, Weekday


# Create a `TimeRange` instance with the interval "0:00 -> 10:00"
time_range = TimeRange(time(0), time(10))

# Check if these times are contained in `time_range`
assert time(0) in time_range
assert time(5) in time_range
assert time(10) in time_range

# Check if these times aren't contained in `time_range`
assert time(10, 0, 1) not in time_range
assert time(11) not in time_range
assert time(20) not in time_range


time_range_2 = TimeRange(time(15), time(20))
time_ranges = TimeRanges([time_range, time_range_2])

assert time(0) in time_ranges
assert time(5) in time_ranges
assert time(10) in time_ranges
assert time(12) not in time_ranges
assert time(15) in time_ranges
assert time(17) in time_ranges
assert time(20) in time_ranges
assert time(22) not in time_ranges

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

More details can be found in CONTRIBUTING.

Contributors ✨

License

MIT

Created from cookiecutter-python-project.

Comments
  • fix: proper handling with empty structures

    fix: proper handling with empty structures

    As presented in https://github.com/tractian/tractian-python-sdk/issues/30#issuecomment-993901186,

    • empty dictionary in day_ranges means all days, with this, any datetime should return True in __contains__
    • empty list in time_ranges means all hours, with this, any datetime at the same weekday should return True in __contains__ The actual PR is a suggestion to this behavior works, which is not working properly.

    Examples of misleading behavior:

    • Datetime in a weekday with empty list as time_ranges image
    • Datetime not in a empty dict as day_ranges image
    opened by lucascust2 1
  • docs: add MicaelJarniac as a contributor for bug, code, doc, example, ideas, maintenance, projectManagement, review, tool, test

    docs: add MicaelJarniac as a contributor for bug, code, doc, example, ideas, maintenance, projectManagement, review, tool, test

    Add @MicaelJarniac as a contributor for bug, code, doc, example, ideas, maintenance, projectManagement, review, tool, test.

    This was requested by MicaelJarniac in this comment

    opened by allcontributors[bot] 0
  • Fix public API

    Fix public API

    On VS Code, if I type

    from timeranges import

    it doesn't auto-complete.

    Something about the way I'm "exporting" the public items on __init__.py isn't quite right.

    bug 
    opened by MicaelJarniac 0
  • Create a method for getting a fully-filled object

    Create a method for getting a fully-filled object

    Something like TimeRanges.full() that'd return TimeRanges([TimeRange()]), and WeekRange.full() that'd return WeekRange({Weekday.MONDAY: TimeRanges.full(), ...}) (with all days of the week).

    enhancement 
    opened by MicaelJarniac 0
  • Make `TimeRanges` and `WeekRange` behave more like native collections

    Make `TimeRanges` and `WeekRange` behave more like native collections

    TimeRanges could behave like a list, and WeekRange like a dict.

    https://docs.python.org/3/reference/datamodel.html#emulating-container-types

    • [ ] __bool__
    enhancement 
    opened by MicaelJarniac 1
  • Compare multiple times at once

    Compare multiple times at once 

    assert (time(...), time(...)) in TimeRange(...)
assert (time(...), time(...)) in TimeRanges(...)
assert (datetime(...), datetime(...)) in WeekRange(...)
    enhancement 
    opened by MicaelJarniac 0
Releases(v1.0.2)
Owner
Micael Jarniac
Micael Jarniac
GitHub Repository
A computer algebra system written in pure Python

SymPy See the AUTHORS file for the list of authors. And many more people helped on the SymPy mailing list, reported bugs, helped organize SymPy's part

SymPy 9.9k Dec 31, 2022
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti

Roger Labbe 2.5k Dec 30, 2022
Python library for creating data pipelines with chain functional programming

PyFunctional Features PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do

Pedro Rodriguez 2.1k Jan 05, 2023
This is a tool for speculation of ancestral allel, calculation of sfs and drawing its bar plot.

superSFS This is a tool for speculation of ancestral allel, calculation of sfs and drawing its bar plot. It is easy-to-use and runing fast. What you s

3 Dec 16, 2022
MapReader: A computer vision pipeline for the semantic exploration of maps at scale

MapReader A computer vision pipeline for the semantic exploration of maps at scale MapReader is an end-to-end computer vision (CV) pipeline designed b

Living with Machines 25 Dec 26, 2022
follow-analyzer helps GitHub users analyze their following and followers relationship

follow-analyzer follow-analyzer helps GitHub users analyze their following and followers relationship by providing a report in html format which conta

Yin-Chiuan Chen 2 May 02, 2022
Scraping and analysis of leetcode-compensations page.

Leetcode compensations report Scraping and analysis of leetcode-compensations page.

utsav 96 Jan 01, 2023
A 2-dimensional physics engine written in Cairo

A 2-dimensional physics engine written in Cairo

Topology 38 Nov 16, 2022
This module is used to create Convolutional AutoEncoders for Variational Data Assimilation

VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat

Julian Mack 23 Dec 16, 2022
Synthetic Data Generation for tabular, relational and time series data.

An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github

The Synthetic Data Vault Project 1.2k Jan 07, 2023
MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

MetPy MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data. MetPy follows semantic versioni

Unidata 971 Dec 25, 2022
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown.

Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown

915 Dec 26, 2022
[CVPR2022] This repository contains code for the paper "Nested Collaborative Learning for Long-Tailed Visual Recognition", published at CVPR 2022

Nested Collaborative Learning for Long-Tailed Visual Recognition This repository is the official PyTorch implementation of the paper in CVPR 2022: Nes

Jun Li 65 Dec 09, 2022
An Aspiring Drop-In Replacement for NumPy at Scale

Legate NumPy is a Legate library that aims to provide a distributed and accelerated drop-in replacement for the NumPy API on top of the Legion runtime. Using Legate NumPy you do things like run the f

Legate 502 Jan 03, 2023
INF42 - Topological Data Analysis

TDA INF421(Conception et analyse d'algorithmes) Projet : Topological Data Analysis SphereMin Etant donné un nuage des points, ce programme contient de

2 Jan 07, 2022
Template for a Dataflow Flex Template in Python

Dataflow Flex Template in Python This repository contains a template for a Dataflow Flex Template written in Python that can easily be used to build D

STOIX 5 Apr 28, 2022
A lightweight, hub-and-spoke dashboard for multi-account Data Science projects

A lightweight, hub-and-spoke dashboard for cross-account Data Science Projects Introduction Modern Data Science environments often involve many indepe

AWS Samples 3 Oct 30, 2021
Vaex library for Big Data Analytics of an Airline dataset

Vaex-Big-Data-Analytics-for-Airline-data A Python notebook (ipynb) created in Jupyter Notebook, which utilizes the Vaex library for Big Data Analytics

Nikolas Petrou 1 Feb 13, 2022
Statistical Rethinking course winter 2022

Statistical Rethinking (2022 Edition) Instructor: Richard McElreath Lectures: Uploaded Playlist and pre-recorded, two per week Discussion: Online, F

Richard McElreath 3.9k Dec 31, 2022
Yet Another Workflow Parser for SecurityHub

YAWPS Yet Another Workflow Parser for SecurityHub "Screaming pepper" by Rum Bucolic Ape is licensed with CC BY-ND 2.0. To view a copy of this license,

myoung34 8 Dec 22, 2022