time_trial | Time Trial - A tool for performing feasibility analyses | Monitoring library

by dmayer Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | time_trial Summary

time_trial is a Python library typically used in Performance Management, Monitoring applications. time_trial has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However time_trial build file is not available. You can download it from GitHub.

Time Trial - A tool for performing feasibility analyses of timing attacks

Support

Quality

Security

License

Reuse

Support

time_trial has a low active ecosystem.

It has 77 star(s) with 15 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of time_trial is current.

Quality

time_trial has 0 bugs and 0 code smells.

Security

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

time_trial code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

time_trial is licensed under the MIT License. This license is Permissive.

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

Reuse

time_trial releases are not available. You will need to build from source code and install.

time_trial has no build file. You will be need to create the build yourself to build the component from source.

time_trial saves you 664 person hours of effort in developing the same functionality from scratch.

It has 1540 lines of code, 129 functions and 33 files.

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

Top functions reviewed by kandi - BETA

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

Start a trial
Update the trial details
Refreshes the query
Reset the plot
Updates the plot
Clear axes
Add a plot to the plot
Add a histogram to the plot
Execute a trial
Parse a HTTP request
Store a new experiment
Refreshes the list of experiments
Update the current experiment
Called when an event is selected
Delete the current roster
Delete the currently selected trial
Called when a file is selected
Close the session
Duplicate the current trial
Updates the roster dialog
Create a roster
Updates the trial details
Cancel the current trial
Performs the analysis
Return the data at the given index
Apply plot settings

Get all kandi verified functions for this library.

time_trial Key Features

No Key Features are available at this moment for time_trial.

time_trial Examples and Code Snippets

No Code Snippets are available at this moment for time_trial.

Community Discussions

Trending Discussions on time_trial

How to check if unique column does not already contain data being inserted, preventing error

QUESTION

How to check if unique column does not already contain data being inserted, preventing error

Asked 2021-Jan-28 at 06:35

I'm working with this database... basically I have to create a "promote_cyclist" trigger, to memorize the eligible athletes (who are ranked first on a stage of the Giro d'Italia) in the mesh table.

The tables are:

...

ANSWER

Answered 2021-Jan-28 at 00:09

Your query in that function may look like this:

Source https://stackoverflow.com/questions/65929046

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

Vulnerabilities

No vulnerabilities reported

Install time_trial

You can download it from GitHub.
You can use time_trial like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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