Skip to main content

Representation of continuous timeseries.

Project description

Continuous Timeseries

Representation of continuous timeseries.

Key info : Docs Main branch: supported Python versions Licence

PyPI : PyPI PyPI install

Tests : CI Coverage

Other info : Last Commit Contributors

Status

  • prototype: the project is just starting up and the code is all prototype

Full documentation can be found at: continuous-timeseries.readthedocs.io. We recommend reading the docs there because the internal documentation links don't render correctly on GitHub's viewer.

Installation

As an application

If you want to use Continuous Timeseries as an application, then we recommend using the 'locked' version of the package. This version pins the version of all dependencies too, which reduces the chance of installation issues because of breaking updates to dependencies.

The locked version of Continuous Timeseries can be installed with

=== "pip" sh pip install continuous-timeseries[locked]

As a library

If you want to use Continuous Timeseries as a library, for example you want to use it as a dependency in another package/application that you're building, then we recommend installing the package with the commands below. This method provides the loosest pins possible of all dependencies. This gives you, the package/application developer, as much freedom as possible to set the versions of different packages. However, the tradeoff with this freedom is that you may install incompatible versions of Continuous Timeseries's dependencies (we cannot test all combinations of dependencies, particularly ones which haven't been released yet!). Hence, you may run into installation issues. If you believe these are because of a problem in Continuous Timeseries, please raise an issue.

The (non-locked) version of Continuous Timeseries can be installed with

=== "pip" sh pip install continuous-timeseries

Additional dependencies can be installed using

=== "pip" sh # To add plotting dependencies pip install continuous-timeseries[plots]

For developers

For development, we rely on pdm for all our dependency management. To get started, you will need to make sure that pdm is installed (instructions here, although we found that installing with pipx worked perfectly for us).

For all of our work, we use our Makefile. You can read the instructions out and run the commands by hand if you wish, but we generally discourage this because it can be error prone. In order to create your environment, run make virtual-environment.

If there are any issues, the messages from the Makefile should guide you through. If not, please raise an issue in the issue tracker.

For the rest of our developer docs, please see [development][development].

Original template

This project was generated from this template: copier core python repository. copier is used to manage and distribute this template.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

continuous_timeseries-0.1.0.tar.gz (6.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

continuous_timeseries-0.1.0-py3-none-any.whl (6.1 kB view details)

Uploaded Python 3

File details

Details for the file continuous_timeseries-0.1.0.tar.gz.

File metadata

  • Download URL: continuous_timeseries-0.1.0.tar.gz
  • Upload date:
  • Size: 6.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: pdm/2.22.1 CPython/3.9.20 Linux/6.8.0-1017-azure

File hashes

Hashes for continuous_timeseries-0.1.0.tar.gz
Algorithm Hash digest
SHA256 b514b6eeff55e609f287b80de09b3eb3121078bb55b1dba5be4c44a8723fb0b1
MD5 a5ce61a862c75a49bf0ffae6584d7033
BLAKE2b-256 7f8859c00170e05d468c8a853410baa09dbabe73b623139e09b67af7f3214470

See more details on using hashes here.

File details

Details for the file continuous_timeseries-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for continuous_timeseries-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 24220e779e0cdf4f9b486b0e002fe0c30305ae1cf8726b8dc70008db9769c44f
MD5 3bb29414cd1562d47cdfd02f2aab30cb
BLAKE2b-256 dfea4e8247156a662a10e77223de3d9588bef6eb826e5bc6f6ed0dbe0f224092

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page