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
Flexible HDF5 saving/loading and other data science tools from the University of Chicago

deepdish Flexible HDF5 saving/loading and other data science tools from the University of Chicago. This repository also host a Deep Learning blog: htt

UChicago - Department of Computer Science 255 Dec 10, 2022
Snakemake workflow for converting FASTQ files to self-contained CRAM files with maximum lossless compression.

Snakemake workflow: name A Snakemake workflow for description Usage The usage of this workflow is described in the Snakemake Workflow Catalog. If

Algorithms for reproducible bioinformatics (Koesterlab) 1 Dec 16, 2021
A real data analysis and modeling project - restaurant inspections

A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re

Jafar Pourbemany 2 Aug 21, 2022
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Amundsen 3.7k Jan 03, 2023
Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.

Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.

HoloViz 2.9k Jan 06, 2023
Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data.

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing

Lawrence Livermore National Laboratory 14 Aug 19, 2022
Py-price-monitoring - A Python price monitor

A Python price monitor This project was focused on Brazil, so the monitoring is

Samuel 1 Jan 04, 2022
Describing statistical models in Python using symbolic formulas

Patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design mat

Python for Data 866 Dec 16, 2022
CaterApp is a cross platform, remotely data sharing tool created for sharing files in a quick and secured manner.

CaterApp is a cross platform, remotely data sharing tool created for sharing files in a quick and secured manner. It is aimed to integrate this tool with several more features including providing a U

Ravi Prakash 3 Jun 27, 2021
ELFXtract is an automated analysis tool used for enumerating ELF binaries

ELFXtract ELFXtract is an automated analysis tool used for enumerating ELF binaries Powered by Radare2 and r2ghidra This is specially developed for PW

Monish Kumar 49 Nov 28, 2022
Bigdata Simulation Library Of Dream By Sandman Books

BIGDATA SIMULATION LIBRARY OF DREAM BY SANDMAN BOOKS ================= Solution Architecture Description In the realm of Dreaming, its ruler SANDMAN,

Maycon Cypriano 3 Jun 30, 2022
Provide a market analysis (R)

market-study Provide a market analysis (R) - FRENCH Produisez une étude de marché Prérequis Pour effectuer ce projet, vous devrez maîtriser la manipul

1 Feb 13, 2022
DaDRA (day-druh) is a Python library for Data-Driven Reachability Analysis.

DaDRA (day-druh) is a Python library for Data-Driven Reachability Analysis. The main goal of the package is to accelerate the process of computing estimates of forward reachable sets for nonlinear dy

2 Nov 08, 2021
Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

Chris Carbonell 1 Dec 03, 2021
PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to

Derek Snow 527 Jan 02, 2023
statDistros is a Python library for dealing with various statistical distributions

StatisticalDistributions statDistros statDistros is a Python library for dealing with various statistical distributions. Now it provides various stati

1 Oct 03, 2021
Investigating EV charging data

Investigating EV charging data Introduction: Got an opportunity to work with a home monitoring technology company over the last 6 months whose goal wa

Yash 2 Apr 07, 2022
Randomisation-based inference in Python based on data resampling and permutation.

Randomisation-based inference in Python based on data resampling and permutation.

67 Dec 27, 2022
Office365 (Microsoft365) audit log analysis tool

Office365 (Microsoft365) audit log analysis tool The header describes it all WHY?? The first line of code was written long time before other colleague

Anatoly 1 Jul 27, 2022
A library to create multi-page Streamlit applications with ease.

A library to create multi-page Streamlit applications with ease.

Jackson Storm 107 Jan 04, 2023