qcri | Import test results to HP Quality Center | Functional Testing library

by douville Python Version: 0.2.0 License: BSD-2-Clause

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | qcri Summary

qcri is a Python library typically used in Testing, Functional Testing, Pytorch, Selenium applications. qcri has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install qcri' or download it from GitHub, PyPI.

QCRI imports test results from multiple testing tools to HP Quality Center by GUI, API, or Batch Command.

Support

Quality

Security

License

Reuse

Support

qcri has a low active ecosystem.

It has 9 star(s) with 3 fork(s). There are no watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 1 have been closed. On average issues are closed in 8 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of qcri is 0.2.0

Quality

qcri has 0 bugs and 0 code smells.

Security

qcri has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

qcri code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

qcri is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

qcri releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 3104 lines of code, 87 functions and 15 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed qcri and discovered the below as its top functions. This is intended to give you an instant insight into qcri implemented functionality, and help decide if they suit your requirements.

Parse an excel sheet file
Parse a step
Get the value of col_name
Parse a test
Handle the command line arguments
Get the parser for a file
Set the value of an argument
Import a test result
Link a bug
Populate the test cache
Get a list of parsers from a file
Update history
Refreshes the bug cluster
Load the history
Called when the connection is changed
Called when the connection is closed
Login to QC
Create the widget
Create the main pane
Parse the results
Called when parser changes
Called when a branch is opened
Create a zip file from a qc directory
Autoconnect slot activated when upload button clicked
Import results from qCC
Called when the BugWindow is clicked

Get all kandi verified functions for this library.

qcri Key Features

No Key Features are available at this moment for qcri.

qcri Examples and Code Snippets

Configuration

Python

Lines of Code : 14

License : Permissive (BSD-2-Clause)

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[main]
history=true

[parsers]
robotframework=true
uftrunreport=true
seleniumtestresults=true

[uftrunreport]
test_column=test
description_column=description
subject_column=subject
suite_column=suite
replace_warning_with_passed=true

Usage,API

Python

Lines of Code : 6

License : Permissive (BSD-2-Clause)

Copy

>>> import qcri
>>> loc = 'c:/TestResults/output.xml'
>>> parsers = qcri.get_parsers(loc)
>>> results = qcri.parse_results(parsers[0], loc)
>>> conn = qcri.connect('http://localhost:8080/qcbin', 'QA', 'WEB

Usage,GUI

Python

Lines of Code : 1

License : Permissive (BSD-2-Clause)

Copy

qcri

Community Discussions

Trending Discussions on qcri

why I could not rehydrate more than 18 tweets out of 24000 tweet ids using TWARC/ hydrator app? Does any one know a better way?

Validation loss having a sinusoidal wave form

QUESTION

why I could not rehydrate more than 18 tweets out of 24000 tweet ids using TWARC/ hydrator app? Does any one know a better way?

Asked 2020-Aug-06 at 12:21

I have a question regarding rehydrate of the tweet's text. Any help would be appreciated.

This is the source of my data; which is about corona tweets:

source of data set

I have downloaded a data set from it which is in the photo (named 01-feb-2020)

Then, I filter this data to show me the only tweets from 'GB' which is almost 24000 tweets

I have used twarc to hydrate my tweets' text as below :

first, install twarc using pip

then, type this in the command line: twarc configure

then, inter consumer key and secret key

then, write a command:

...

ANSWER

Answered 2020-Aug-05 at 18:24

The Tweet ID collection method (which was copy-pasting ) was not correct. After writing a proper code to save tweet ID into text file, the problem has been solved.

Also, Andy Piper mentioned the same thing in the comment part which I copy past here.

How are you getting from JSON format downloaded, into a CSV format? I'm wondering whether the Tweet ID values are valid. – Andy Piper 5 hours ago

I've managed to reproduce this now, and I believe that in the process of converting your JSON input to CSV / Excel to a list of Tweet IDs to hydrate, you are probably using JavaScript (?) and the Tweet IDs are losing their accuracy. The clue was when I noticed all of the Tweet IDs ending in 0000 in my Excel column. You'll need to use a more precise method of getting the Tweet IDs into twarc

Source https://stackoverflow.com/questions/63254995

QUESTION

Validation loss having a sinusoidal wave form

Asked 2020-Jun-01 at 18:33

I am training an LSTM model on the SemEval 2017 task 4A dataset (classification problem with 3 classes). I observe that first validation loss decreases but then suddenly increases by a significant amount and again decreases. It is showing a sinusoidal nature which can be observed from the below training epochs.

Here is the code of my model

...

ANSWER

Answered 2020-May-31 at 19:52

When you have more than two classes you cannot use binary crossentropy. Change your loss function to categorical crossentropy and set your output layer to have three neurons (one for each class)

Source https://stackoverflow.com/questions/62115029

Community Discussions, Code Snippets contain sources that include Stack Exchange Network