Project description

Tests

Data Generator

The Data Generator has its own in-depth documentation. For the purpose of capacity testing it simulates the generation of timeseries data, without the need to set up an ingestion chain (which could be Azure IoTHub, RabbitMQ, etc.)

Maximizing Performance

To maximize performance multiple instances of the Data Generator must be run in parallel. One way to achieve this is using kubernetes how to do this is documented here.

Setup sandbox

python3 -m venv .venv
source .venv/bin/activate
pip install --editable=.[testing]
pytest -vvv tests

Project details

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

1.1.0

Jun 1, 2021

Download files

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

Source Distribution

tsperf-1.1.0.tar.gz (46.1 kB view hashes)

Uploaded Jun 1, 2021 Source

Built Distribution

tsperf-1.1.0-py3.9.egg (140.2 kB view hashes)

Uploaded Jun 1, 2021 Source

Hashes for tsperf-1.1.0.tar.gz

Hashes for tsperf-1.1.0.tar.gz
Algorithm	Hash digest
SHA256	`fbeb782d733244182e0e99c1cb009da17736862b14e9380ffeeb1d52aae502dd`
MD5	`9479b8524aafda8a61169bc2b664ae74`
BLAKE2b-256	`9834f586026d9248e7d3972dcef1c7a16dd0111078bc043b0a699946c21930ea`

Hashes for tsperf-1.1.0-py3.9.egg

Hashes for tsperf-1.1.0-py3.9.egg
Algorithm	Hash digest
SHA256	`bb9490da6386ce1517769f290f26770e3dc7706e88354e4a6b62446d31afc832`
MD5	`16d9004b2b7db63a1fb8fab439c287c9`
BLAKE2b-256	`48914cf1ad60adbdeb32ed6ba0656ea2da1958c234c154af8f74ee1ff81b4bba`