VRT is a library for integrating Visual Regression Tracker with Robot Framework.
Project description
VRT
VRT is a library for integrating Visual Regression Tracker with Robot Framework. For information about Visual Regression Tracker please visit the project page.
Prerequisites
- Visual Regression Tracker
##Installation
The package is stored in PyPI . To install package execute command:
pip install VRT
##Importing
To import library use below command:
Library VRT
##Configure connection
Connection with Visual Regression Tracker should be configured using environment variables:
Example:
VRT_APIURL= http://localhost:4200 #URL where backend is running VRT_PROJECT= Default project #Project name or ID VRT_APIKEY= YourAPIKey #User apiKey VRT_CIBUILDID= $CI_COMMIT_SHA #Current git commit SHA VRT_BRANCHNAME= $CI_COMMIT_REF_NAME #Current git branch VRT_ENABLESOFTASSERT= "false" #Log errors instead of exceptions
For local use and test debugging vrt.json file can be used. The file should be placed in the project root.
*vrt.json* { "apiUrl":"http://localhost:4200", "project":"Default project", "apiKey":"YourAPIKey", "ciBuildId":"commit_sha", "branchName":"develop", "enableSoftAssert":false }
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file vrt-0.1.3.tar.gz
.
File metadata
- Download URL: vrt-0.1.3.tar.gz
- Upload date:
- Size: 6.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.7.1 CPython/3.12.0 Linux/6.2.0-1018-azure
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1c1f51c26e3353bab44d5f94fe1c27e8becb73bb63f6375b5859cd7b48eb8ff4 |
|
MD5 | d509e7d2b1af52956676f5a152eaa157 |
|
BLAKE2b-256 | a9fe2998390129bcfc5adef62e695d85d172247c64fa223c82ac6b38294a7327 |
File details
Details for the file vrt-0.1.3-py3-none-any.whl
.
File metadata
- Download URL: vrt-0.1.3-py3-none-any.whl
- Upload date:
- Size: 7.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.7.1 CPython/3.12.0 Linux/6.2.0-1018-azure
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9a54b7c597408f292b6f2fbad23d1ca9e434ab0d08c53fc40b3604fcf0e73ed4 |
|
MD5 | 8f3f7f94bf1e227fdca647fb8e87a66e |
|
BLAKE2b-256 | db4fc1b4a623171bfb8e0a71b52910febf2f1cee04f6c3db8240a4147b5944b3 |