semvec/pypi-packages huggingface dataset:
rqpop 0.0.3
A package to enqueue a variable number of jobs with variably distributed TIME x CPU "areas"
Keywords: rq queue distribution scipy tetris-queue tetris test loads populate population job enqueue backfill

A package for creating and enqueueing stressypy jobs
====================================================

``rqpop`` uses the python package ``stressypy`` to create a certain number of cpu-stressing jobs for a variably
distributed amount of time, the distribution type and seed being specified by the user.
It creates ``stressypy``'s ``JobBlock`` objects which contain pertinent information for queueing these test jobs to
test queueing algorithms by enqueueing a certain number of randomly 'sized' jobs, which simulates the real job influx
of a webservice, for example. The jobs are enqueued with RQ (Redis Queue).

JobBlocks:
++++++++++
refer to https://github.com/salbrandi/stressypy#jobblock-attributes for documentation on JobBlock objects


Installation
++++++++++++

``rqpop`` can be installed with ``pip install rqpop`` and will auto-install all dependencies.

Alternatively, it can be cloned manually from the url: https://github.com/salbrandi/rqpop.git
or the tarfile can be downloaded from the url: https://github.com/salbrandi/rqpop/archive/0.1.tar.gz
and setup with ``python setup.py install``

| In order to run rqpop, you must have a REDIS server running and RQ ``rqworkers`` listening on the default queue:
|
| Documentation for quickly setting up a REDIS server can be found here: https://redis.io/topics/quickstart
| Full REDIS documentaiton here: https://redis.io/documentation
|
| Documentation for RQ (Redis Queue) cna be found here: http://python-rq.org/
| but for most users a worker can be started, listening on the default queue with simply the ``rqworker`` command.

Directions
++++++++++

``rqpop`` runs using the command ``rqpop queue`` with the number of jobs desired and the max time allowed being passed as arguments.

The help page:

| Usage: rqpop queue [OPTIONS] NUM_JOBS MAX_TIME
|
| Options:
|  --seed TEXT    The seed to be internalized for the number distribution
|  --dist TEXT    the distirbution to be used for psuedo-random generation
|  --mnc INTEGER  the minimum number of cpus to be used, default 1
|  --mxc INTEGER  maximum number of cores a job should be able to require,
|                 default: maximum configured cores
|  --mnt INTEGER  minimum amount of time the jobs should run for, default 1
|  --q TEXT       the queue that the jobs should be enqueued to, default:
|                 "default"
|  --help         Show this message and exit.



Distributions supported are:

- Log Normal: ``normal`` - default
- Box: ``box``
- Spike/Dirac/Delta: ``spike``
- Exponential/Power: ``power``

Examples
--------
* ``rqpop queue 10 12 --seed 0 --distribution normal``:
    creates and enqueues 10 jobs normally distributed with seed 0 and a max time of 12 seconds


* ``rqpop queue 21456 --seed 1023041 --distribution power --mnc 2 --mxc 10 -q high``:
    creates and enqueues 21, 456 jobs exponentially distributed with seed 1023041, min cores 2, max cores 10 on the queue 'high
patella 0.1.12
A webservice for scraping files and plotting data against presidential party variation
Keywords: plotting data party presidential office term year bokeh

A Webservice for Scraping Files and Plotting Data Against Presidential Party Variation
======================================================================================

``patella`` uses Flask to host an interactive html/css/js frontend through which users can navigate to
data and plot it.




Flask Url Paths
---------------

``patella`` uses the  http ``GET`` and ``POST`` commands to send data between
one page and another. The homepage paths are ``/`` and ``/index`` from which you can
navigate to the rest of the front end.



Install and Run Directions
--------------------------

``patella`` is uploaded to the pip package repository.

To install, simply run ``pip install patella``\ . A ``requirements.txt`` file that comes with the
package specifies its dependencies. Install these with ``pip install -r requirements.txt``\ . It is
recommended you run this in a virtual environment so as not to interfere with previous installations.

To start the Flask server, run ``patella startup <URL>``\ , where URL is the path
to be prepended to the page url. Next, use a browser to browse to ``127.0.0.1:4444``\ .
To access the service from other computers on the same network, use the public ip of the host
computer on port 4444. From these two addresses the webservice can be accessed as long as the server is running.


Files
-----

Log Files
+++++++++
A log file will be generated in the path that you run the webservice from named
``webservice.log``. this file includes server reloads, error reporting, logs get
and post requests and debugger pins. ``POST`` and ``GET`` logs are timestamped, but others are not


Data Files
++++++++++
Data files from the webservice will be downloaded to a ``data/`` directory created at runtime in the directory the
server is started from. In that directory, all files downloaded from the webservice will be browseable.