Skip to main content

startorch

CI Nightly Tests Nightly Package Tests
Documentation Documentation
Codecov
Code style: black Doc style: google Ruff Doc style: google
PYPI version Python BSD-3-Clause
Downloads Monthly downloads


Overview

Collecting datasets to train Machine Learning models can be time consuming. Another alternative is to use synthetic datasets. startorch is a Python library to generate synthetic time-series. As the name suggest, startorch relies mostly on PyTorch to generate the time series and to control the randomness. startorch is built to be modular, flexible and extensible. Below show some generated sequences by startorch where the values are sampled from different distribution.

uniform log-uniform
sine wave Wiener process

Dependencies

startorch batchtensor coola objectory numpy torch iden* matplotlib* plotly* python
main >=0.0.1,<0.1 >=0.2,<1.0 >=0.1,<1.0 >=1.23,<2.0 >=2.0,<3.0 >=0.0.2,<0.1 >=3.6,<4.0 >=5.0,<6.0 >=3.9,<3.12
0.1.0 >=0.0.1,<0.1 >=0.2,<1.0 >=0.1,<1.0 >=1.22,<2.0 >=2.0,<3.0 >=0.0.2,<0.1 >=3.6,<4.0 >=5.0,<6.0 >=3.9,<3.12

* indicates an optional dependency

older versions
startorch coola objectory redcat torch matplotlib* plotly* python
0.0.8 >=0.0.20,<0.2 >=0.0.7,<0.2 >=0.0.16,<0.1 >=2.0,<3.0 >=3.6,<4.0 >=5.12,<6.0 >=3.9,<3.12
0.0.7 >=0.0.20,<0.0.25 >=0.0.7,<0.0.9 >=0.0.16,<0.0.18 >=2.0,<2.2 >=3.6,<3.9 >=5.12,<5.18 >=3.9,<3.12
0.0.6 >=0.0.20,<0.0.25 >=0.0.7,<0.0.9 >=0.0.16,<0.0.18 >=2.0,<2.2 >=3.6,<3.9 >=3.9,<3.12
0.0.5 >=0.0.20,<0.0.24 >=0.0.7,<0.0.8 >=0.0.16,<0.0.17 >=2.0,<2.1 >=3.6,<3.9 >=3.9,<3.12
0.0.4 >=0.0.20,<0.0.24 >=0.0.7,<0.0.8 >=0.0.16,<0.0.17 >=2.0,<2.1 >=3.6,<3.9 >=3.9,<3.12
0.0.3 >=0.0.20,<0.0.24 >=0.0.7,<0.0.8 >=0.0.9,<0.0.10 >=2.0,<2.1 >=3.6,<3.9 >=3.9,<3.12

Contributing

Please check the instructions in CONTRIBUTING.md.

API stability

:warning: While startorch is in development stage, no API is guaranteed to be stable from one release to the next. In fact, it is very likely that the API will change multiple times before a stable 1.0.0 release. In practice, this means that upgrading startorch to a new version will possibly break any code that was using the old version of startorch.

License

startorch is licensed under BSD 3-Clause "New" or "Revised" license available in LICENSE file.

Metadata

Release files for startorch 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for startorch 0.2.0
File Size Uploaded
startorch-0.2.0.tar.gz 85.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for startorch 0.2.0
File Interpreter ABI Platform
startorch-0.2.0-py3-none-any.whl Python 3 none any Details

Total release size: 254.9 kB

Release files / startorch-0.2.0.tar.gz

Download URL startorch-0.2.0.tar.gz
Size 85.8 kB
Tags Source
SHA-256 checksum
How to use checksums
68f9108be3d5d98905db3d4e821c853841f1159dd8507f56780bd029d653cd48
BLAKE2b-256 checksum
How to use checksums
0f0c4a8029a9a212d20c73ce1446b635c82e66342af6bcb61053b67b703bed5d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.8.3 CPython/3.12.3 Linux/6.5.0-1021-azure

Release files / startorch-0.2.0-py3-none-any.whl

Download URL startorch-0.2.0-py3-none-any.whl
Size 169.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a798a1f1edb23fe6d33713e90c73b23a08ff0fb1b5c55c10a18917034cfa1e50
BLAKE2b-256 checksum
How to use checksums
0d7780b4d36040e836836c9fd2c4afb71c0643050e6d1b98b8629c1f1d82a530
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.8.3 CPython/3.12.3 Linux/6.5.0-1021-azure
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page