Saravanan666/pypi-org huggingface dataset:
Package: prtg-sensor
Prtg-sensorSimple data generator for advanced PRTG sensors.It will help you to generate output in JSON format for the Python Script Advanced, EXE/Script Advanced, SSH Script Advanced and HTTP Data Advanced sensors.You can refer to theofficial PRTG manualto figuring out all the features of custom sensors.InstallingInstall withpippipinstallprtg-sensorExampleExecutable sensors likePython Script Advanced sensormust send the result to the stdout.HTTP Data Advanced sensormust send the result in the http response body.fromprtg_sensorimportSensorsensor=Sensor()sensor.add_channel('Duration',32,unit='timeseconds')sensor.add_channel('Loading',12.55,unit='percent',float=1,decimal_mode='all')sensor.add_channel('Status',0,value_lookup='prtg.standardlookups.aws.status')sensor.text='Everything is ok'print(sensor.get_result())PRTG interprets this result to sensor by itself
Package: prtg-utils
Prtg Utils=======================Ths ulilities use the PRTG API to access prtg.
They allow one to download historic data.UsageQuery prtg historic data

prtg_history_csv [-h] --ids IDS --starttime STARTTIME --endtime ENDTIME [--average AVERAGE] [--host HOST] [--user USER] [--password PASSWORD] --output OUTPUT [--locale LOCALE] [--ilocale LOCALE] [--raw]


optional arguments:
  -h, --help              show this help message and exit
  --ids IDS               List of PRTG ids
  --starttime STARTTIME   Start time
  --endtime ENDTIME       End Time
  --average AVERAGE       Average
  --host HOST             PRTG host
  --user USER             PRTG user
  --password PASSWORD     PRTG password
  --output OUTPUT         Output file
  --locale LOCALE         [us|euro]
  --ilocale LOCALE        [us|euro]
  --raw                   Only output raw data
Package: prtogerrit
This is a script Mike is working on to transfer pull requests from
github and bitbucket into gerrit.RequirementsYou need a running instance of Gerrit available, and also you must have
thegit-reviewtool installed locally.Installationpip install prtogerritConfigurationCreate a new file ${HOME}/.prtogerrit.config.  In it, place instructions
as to where your git repositories are, and into what part of your gerrit
server you’d like them to go:# place this file in $HOME/.prtogerrit.config

[myproject_github]
gerrit=https://gerrit.myproject.com/
service=github
repo=myusername/myproject
username=myusername
password=foobar

[myproject_bitbucket]
gerrit=https://gerrit.myproject.com/
service=bitbucket
repo=myusername/myproject
username=myusername
password=foobarRunning itTo use the script, suppose you receive pull request number 14 on “myproject”
at Github.  Go to your git working directory, select the desired branch
(usually master), and type:prtogerrit myproject_github 14If the pull request merges cleanly, that’s it!  The script will contact
the Github API, get the branch information for pull request 14, squash-merge
it into a new local branch called “myproject_github_14”, and will then
push it up with “git review”.  It will also close the pull request and
add comments for the contributor how to find the review.ConflictsIf the squash-merge has conflicts, prtogerrit will stop and let you correct
the changes, by using “git add <filename>” just like any other merge
resolution.  Then run the command again with--continue:prtogerrit myproject_github 14 --continue
Package: prt-phasecurve
prt_phasecurveBulding phasecurves of exoplanetary atmospheres using petitradtransDocumentation:https://prt-phasecurve.readthedocs.ioInstall:pip install prt_phasecurveCurrently usable functions:Integrate the global spectra to calculate the phase curve:phase_curve()Calculate the spectra of the (lowres) GCM output:calc_spectra()
Package: prtpy
prtpyPython code for multiway number partitioning and bin packing algorithms.Supports several exact and approximate algorithms, with several input formats, optimization objectives and output formats.InstallationBasic installation:pip install prtpyTo run simulation experiments:pip install prtpy[simulations]To speed up the ILP code, you can install the GUROBI solver.
See thedocumentation of Python-MIPfor more information.UsageThe functionprtpy.partitioncan be used to activate all number-partitioning algorithms. For example, to partition the values [1,2,3,4,5] into two bins using the greedy approximation algorithm, do:import prtpy
prtpy.partition(algorithm=prtpy.partitioning.greedy, numbins=2, items=[1,2,3,4,5])To use the exact algorithm based on ILP, and maximize the smallest sum:prtpy.partition(algorithm=prtpy.partitioning.ilp, numbins=2, items=[1,2,3,4,5], objective=prtpy.obj.MaximizeSmallestSum)Similarly, the functionprtpy.packingcan be used to activate all bin-packing algorithms.For more features and examples, see:Number-partitioning algorithms;Bin-packing algorithms;Bin-covering algorithms;Input formats;Optimization objectives;Output formats.Adding new algorithmsTo add a new algorithm for number partitioning, write a function that accepts the following parameters:binner- an item of classBinnerstructure (see below).numbins- an integer - how many bins to put the items into.items- a list of item-names (the item values are given by the functionbinner.valueof).Any other parameters that are required by your algorithm.For an example, see the implementation of existing algorithms, e.g.greedy.To add a new algorithm for bin packing or bin covering, write a function that accepts the following parameters:binner- an item of classBinnerstructure (see below).binsize- the capacity of a bin (maximum sum in bin-packing; minimum sum in bin-covering).items- a list of item-names (the item values are given by the functionbinner.valueof).Any other parameters that are required by your algorithm.For an example, see the implementation of existing algorithms, e.g.first_fit.TheBinnerclass contains methods for handling bins in a generic way --- handling both item-names and item-values with a single interface. The main supported methods are:bins = binner.new_bins(numbins)--- constructs a new array of empty bins.binner.add_item_to_bin(bins, item, index)--- updates the givenbinsarray by adding the given item to the bin with the given index.binner.sums(bins)--- extracts, from the bins array, only the array of sums.bins = binner.add_empty_bins(bins, numbins)--- creates a newbinsarray with some additional empty bins at the end.bins = binner.remove_bins(bins, numbins)--- creates a newbinsarray with some bins removed at the end.binner.valueof(item)--- returns the value (size) of the given item.Related librariesnumberpartitioningby SÃ¸ren Fuglede JÃ¸rgensen - the code forcomplete_greedyandcomplete_karmarkar_karpwas originally adapted from there.binpackingby Ben Maier.LimitationsThe package is tested on Python versions 3.8, 3.9 and 3.10. Other versions are not supported.
Package: prtx-faq
This is a plugin forpretixandpretalx, helping you create and manage a
helpful FAQ page for your attendees.
You can see an examplehere.Features: FAQ categories for helpful grouping, tags for searching, and a search
function helping attendees find the answer they’re looking for quickly.LicenseCopyright 2018 Tobias KunzeReleased under the terms of the Apache License 2.0
Package: prude
Prudeprudeis a generic code annalyser to checklanguageerror. Thelanguagecheck is the english.![Badge](https://badge.fury.io/py/prude.pngInstructionsThis is a tool to annalyse C, C++ file and determine if it have some english word that does not exist.Prude is under a FREE license that can be found in the COPYING file.
Any contribution is more than welcome ;)git repositoryhttp://github.com/HeeroYui/prude/InstallationRequirements:Python >= 2.7andpipJust run:pip install prudeInstall pip on debian/ubuntu:sudo apt-get install pipInstall pip on ARCH-linux:sudo pacman -S pipInstall pip on MacOs:sudo easy_install pipdeveloppement for prude:git clone http://github.com/HeeroYui/prude/
cd prude
./setup.py develop --userDocumentationUsageGo to your coding directory and execute:prude yourFileToParce.cpp
  # OR (multiple files)
  prude yourFileToParce.cpp other_file.py and.txt
  # simply the path
  prude .You can use some options:--color/-C to have beautifull color check
  --recursive/-r Parse all under directoriesCreate exceptions:prude parse all upper folder to find all file ".prude_*" and add it in the list of exceptions error.The search end when find the file ".prude".you can have:root_path
    --> .prude
    --> .prude_lua
    --> .prude_tinyxml
    --> module
          --> submodule
                --> .prude_local
                --> .prude_local2
                --> my_file_cpp.cpp
          --> sub_second
                --> file_c.cThe check of the filemy_file_cpp.cppuse all the .prude* file and the filefile_c.conly use the file on the root_pathA prude file is contituated like:#Comment the line+Use the end of the line to check the exact match of the string (ex: +MY_VariableStupidName)direct element is use to comare each word in lower case to exclude error on it (ex: destructor)!Command to apply at the configuration.!NO_CAPITAL_LETTER==> disable the check of the word in capital letter!CAPITAL_LETTER==> enable the check of the word in capital letter (default)Some tricky things (removed because it is errored at the declaration and no more need in library using it):The namespace call are disable (ex namespace::prout)The parameter access are disable (ex: variable.hello() or variable->hello())The "#include ..." and the "# include ..."Now you can play.Note: in thehttp://github.com/HeeroYui/prude/common/you have some common C library that declare stupid thing in global...License (APACHE v2.0)Copyright prude Edouard DUPINLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: prudence
prudenceis a lightweight tool for building command-line applications.ObjectivesInstallingInstall and update usingpip:pipinstall-UprudenceA Simple Examplefromprudenceimportmainmain()LinksWebsite:Documentation:License:https://www.gnu.org/licenses/agpl.htmlReleases:https://pypi.org/project/prudence/Code: _To be released soon…_Issue tracker:Test status:Test coverage:
Package: pruebadd
Welcome to the project’s homepage.The purpose of this package is …SCOPE
…DESCRIPTION
…QUICKSTART USAGE EXAMPLES
…USAGE GUIDE
…INTERESTED ON COLLABORATING AS A DEVELOPER IN OUR PROJECT?
…THANKS FOR YOUR SUPPORT!
We are happy to develop applications that can contribute to as many people as possible. If you like our applications and are interested in supporting our work, you can make a donation or buy me a coffee: buymeacoffee.com/…
Package: prueba-primo
Prueba_primo“Este es un codigo que comprueba numeros primos”Free software: MIT licenseDocumentation:https://prueba-primo.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-03-10)First release on PyPI.
Package: prueba-temporal
# Prueba Temporal[![Coverage Status](https://coveralls.io/repos/github/datosgobar/prueba-temporal/badge.svg?branch=master)](https://coveralls.io/github/datosgobar/prueba-temporal?branch=master)
[![Build Status](https://travis-ci.org/datosgobar/prueba-temporal.svg?branch=master)](https://travis-ci.org/datosgobar/prueba-temporal)
[![PyPI](https://badge.fury.io/py/prueba-temporal.svg)](http://badge.fury.io/py/prueba-temporal)
[![Stories in Ready](https://badge.waffle.io/datosgobar/prueba-temporal.png?label=ready&title=Ready)](https://waffle.io/datosgobar/prueba-temporal)
[![Documentation Status](http://readthedocs.org/projects/prueba-temporal/badge/?version=latest)](http://prueba-temporal.readthedocs.org/en/latest/?badge=latest)Descripción corta del proyecto.Licencia: MIT licenseDocumentación:https://prueba-temporal.readthedocs.io## InstalaciónAYUDA: ¿Qué dependencias del sistema son necesarias? ¿Tests/pruebas post instalación? Usar screenshots/gifs (si cabe).cd path/to/prueba-temporalypip install -e .para instalar el repo clonado localmente enmodo developer(cualquier cambio en el código está disponible en el entorno virtual donde fue instalado).## UsoAYUDA: Ejemplo rápido. Usar screenshots/gifs (si cabe).## TestsAYUDA: ¿Cómo correr los tests? ¿Cómo me instalo dependencias para los tests?## CréditosAYUDA: ¿Usás código de otra persona/organización? ¿Alguien o algo fue una fuente de inspiración/asesoramiento/ayuda para este repositorio? ¿Es esto un fork?## ContactoTe invitamos a [crearnos un issue](https://github.com/datosgobar/prueba-temporal/issues/new?title=Encontreun bug en prueba-temporal) en caso de que encuentres algún bug o tengas feedback de alguna parte deprueba-temporal.Para todo lo demás, podés mandarnos tu comentario o consulta a [datos@modernizacion.gob.ar](mailto:datos@modernizacion.gob.ar).History
===0.1.0 (2017-01-04)First release on PyPI.
Package: prun
prun readmeprunis a convenience app for working with virtual environments.
Useprunwithin a folder structure that has a virtual environment folder
to automatically work with the python of the virtual environment.First, create a local virtual environment in the.venvfolder.
This can be done using the virtualenv package.python -m virtualenv .venvThe path to the python executable of the local virtual environment can be printed using the following command:prun -showpruncan be used to install python packages in the local virtual environment.prun pip install numpyRunning a python file, using the python executable from the local virtual environment is easy withprun.prun script.py arg0 arg1When executingprunwithout any extra command line arguments,
the python of the virtual environment will be executed.prunpruncan run any command line command.prun command arg0 arg1 ...
Package: pruna-engine
Pruna EnginePruna Engine is a Python package providing the capability of running deep learning models optimized through Pruna AI.InstallationYou can install Pruna Engine via pip from PyPI:CPUpipinstallpruna-engineGPUpipinstallpruna-engine[gpu]--extra-index-urlhttps://pypi.nvidia.com--extra-index-urlhttps://pypi.ngc.nvidia.comRequirementsYou need CUDA 12 to be installed on your machine for the GPU versionYou need to have CUDA toolkit installed on your machine. If you are using a conda environment you can do this by running:condainstallnvidia/label/cuda-12.1.0::cudaWe support python 3.8, 3.9, or 3.10UsageHere is a simple example of how to use Pruna Engine with a ResNet50 optimized model:frompruna_engine.PrunaModelimportPrunaModel# And 'your_api_key' is your actual API keyyour_api_key='test'smashed_model=PrunaModel.load_model('resnet50_model',your_api_key)# Run predictiony=smashed_model(x)LicenseAll Rights ReservedCopyright 2023 Pruna AI
Package: prune
pruneTrim Entries from a Python Dictionaryinstallpipenv install pruneorpip3 install pruneusagefrompruneimportprunetree={"ford":{"country":"USA","year":"2005"},"ferrari":{"country":"Italy","year":"1995"}}branches=["ford.year","ferrari.year"]prune(tree,branches)# tree is now { "ford": { "country": "USA" }, "ferrari": { "country": "Italy" }}supportPost an issue athttps://github.com/DanielJDufour/prune/issuesor email the package author atdaniel.j.dufour@gmail.com
Package: prune-ebs-snapshots
Prune EBS Snapshots based on a simple backup retention policyConfigurationThis script uses the boto3 library to communicate with AWS. You must configure your AWS credentials using one
of the methods supported by boto3. For full details see:https://boto3.readthedocs.io/en/latest/guide/configuration.html#guide-configurationThe AWS user must have appropriate permissions. Here is an example AWS policy:{
        "Version": "2012-10-17",
        "Statement": [
                {
                        "Sid": "Stmt1422916495000",
                        "Effect": "Allow",
                        "Action": [
                                "ec2:DeleteSnapshot",
                                "ec2:DescribeSnapshots"
                        ],
                        "Resource": [
                                "*"
                        ]
                }
        ]
}UsageAlways use the--helpoption to see the most up-to-date options available.Basic usage is:prune-ebs-snapshots[options] volume_id tag_name tag_valuevolume_idspecifies which EBS volume to prune snapshots fortag_nameandtag_valuespecify a tag and corresponding value that must be present on all snapshots considered for pruning.
Typically you would configure a backup script to include this particular tag value on all snapshots created for backup purposes.
Snapshots created for other purposes would not have this tag, and therefore would not be deleted by this pruning script, or considered
as part of the backup set for determining which snapshots to delete.Options are used to specify how many daily, weekly, monthly and yearly snapshots to retain. Use--helpfor more details.
Package: prune-envs
Prune (conda) EnvironmentsIf you're a heavy user of conda environments there inevitably comes a time that you want to clean things up. Of course, you can use:$ conda env remove -n my_old_envfor each and every environment you have lying around. You can also find out where your environments live and manually remove their folders.Now, there is another way, using a TUI!Installation and usageYou can install the application usingpipx:$ pipx install prune-envsOf course, you can also use plain oldpip. Start the application by typing:$ prune-envsSimply select an environment using the mouse or arrow keys and press 'D' to delete!
Package: pruning-tools
## 概述
EasyPruner是一个轻量且实用的PyTorch神经网络剪枝工具包，提供了一系列即插即用的网络结构裁剪接口。任何不具备模型压缩知识背景的工程师都可通过在PyTorch工程代码中添加几行代码实现网络模型的精准瘦身，并导出用于多种平台部署的onnx模型。可使模型保持现有精度水平的情况下，成倍提升执行效率和存储效率。<br />​<br />
<a name=”EHucI”></a>
## 特点透明性：不需懂模型压缩知识即可流畅使用。<br />**灵活性**：无需更换训练框架，也不用为剪枝接口重构训练或评测代码，仅在原训练框架中进行几行代码增        加，即插即用。<br />**通用性**：支持所有工程场景中常用的网络结构，例如ResNet、VGGNet、Inception、MobileNet等；支持多种训练框架代码，open-mmlab系列开源框架、u版YOLO系列等。<br />**精确性**：吸取神经网络剪枝的最新研究成果，提供在公开评测集上处于SOTA水平的剪枝方法，可对网络冗余连接进行精确识别，在一些常规任务上可以实现无损压缩。<br />**实用性**：剪枝后的模型可直接导出onnx，实现在NPU、ARM、GPU、CPU等多种平台的通用部署<br /><a name=”BXs1U”></a>
## 创新
与其他开源模型剪枝工具项目相比，本项目做了如下创新，以使剪枝工具更加强大：1. 提出基于ONNX的图分析的网络拓扑排序方法，可以实现前后依赖算子的自动化识别，以兼容多样化的训练框架。
1. 提出基于自研GradDecay稀疏方法的进阶剪枝模式，该方法可以在不增加训练成本的情况下，最大限度保留网络原始表达能力，在一般情况下实现无损剪枝，在大剪枝率情况下依旧保持低精度损失。
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## 功能介绍
本工具包提供两种剪枝模式，分别具有不同的代码修改方式，以及剪枝效果，用户可自行选择：<br />**快捷模式**：遵循 “模型加载–>裁剪–>常规微调”三段式，易用性更强，代码修改便捷<br />**进阶模式**：遵循 “模型加载–>稀疏微调–>裁剪”三段式，适合大剪枝率剪枝，需找到训练代码中的权重更新部分，进行修改。
<a name=”C2W7S”></a>详细使用文档请参加语雀：https://www.yuque.com/books/share/d1639c26-4a93-4274-b028-3134ebcada17?# 《EasyPruner剪枝工具》
Package: prunner
Pipeline RunnerWhen running, the configuration folder should have the following structure  example_configuration_folder
├──   pipelines.yaml
├──   variables.yaml
├──   functions.py
├──   templates
│  ├──   script.jinja2
│  ├──   singularity.jinja2
│  ├──   etc.jinja2pipelines.yamlThe root element should be a dictionary in which thekeys= pipeline names,
thevalues= an array of tasks to run.You can use the variables within the values by prefixing with a dollar sign
($), similar to shell expansions. You can escape$by doubling it to$$For a full example look atexample/pipelines.yaml. The possible tasks are:set_from_env: dictTypically used in the beginning, used to define variables based on values
from environment variables.
Example:-set_variables:USER:steveHOME:/scratch/$USER/home/set_variables: dictDirectly define or override specific variables.
Example:-set_variables:NEW_VARIABLE:SupermanVAR2:Trueload_variables: strThis will load the flat dictionary of key str. Example:-load_variables:pipeline_onedump_variables: filenameThis will dump all of the current variables into a file, specified by filename. Example:-dump_variables:$SUBJECT/${SESSION}.sh# Assumming SUBJECT + SESSION have been defined in a prior stepgenerate_file: dictCreate a file from a Jinja2 template. This step accepts a yaml dictionary
with the following key-value pairs:templateThe Jinja2 template file to use relative to theconfiguration_dir/templates/filepathThe full path onto which the new file should be saved to.variableThe dynamic value of filepath is converted to a static absolute path and
  saved to the specifed variable. The default value = "OUTPUT_FILE".Example:-generate_file:template:script.jinja2filepath:$WORKING_DIR/$SUBJECT/$SESSION_PROCESSING.shvariable:PROCESSING_SCRIPT# now $PROCESSING_SCRIPT can be used in a future step# for example, a function that adds the script on the PBS queuefunction: strThe function to call. Note: The functions must be defined inconfiguration_dir/functions.pyExample:-function:load_scripts_onto_pbs
Package: prusa2mqtt
prusa2mqttCommand line tool that parses the USB serial output of a Prusa 3D printer and publishes the sensor values and progress to an MQTT server.The difference between this script and the MQTT plugin for Octoprint is, that this script only connects once to the /dev/ttyACM0 port and the connection doesn't abort if you power down the printer.Install:pipinstallprusa2mqttprusa2mqtt--helpusage: prusa2mqtt [-h] [--topic TOPIC] [--client_id CLIENT_ID]
                     [--check_interval CHECK_INTERVAL]
                     [--serial_port SERIAL_PORT] [--mqtt_address MQTT_ADDRESS]
                     [--mqtt_port MQTT_PORT] [--mqtt_username MQTT_USERNAME]
                     [--mqtt_password MQTT_PASSWORD]
                     [--discrete_topics DISCRETE_TOPICS]

Log temperature data and progress from the USB port of a Prusa printer to an MQTT server.

optional arguments:
  -h, --help            show this help message and exit
  --serial_port SERIAL_PORT
                        Path to the serial port device. (default: /dev/ttyACM0)
  --topic TOPIC         Topic for the MQTT message. (default: prusa)
  --client_id CLIENT_ID
                        Distinct client ID for the MQTT connection. (default: prusa2mqtt)
  --check_interval CHECK_INTERVAL
                        Interval in seconds for checking the temperatures. (default: 5)
  --serial_port SERIAL_PORT
                        Path to the serial port device.
  --mqtt_address MQTT_ADDRESS
                        Address for the MQTT connection. (default: localhost)
  --mqtt_port MQTT_PORT
                        Port for the MQTT connection. (default: 1883)
  --mqtt_username MQTT_USERNAME
                        User name for the MQTT connection. (default: None)
  --mqtt_password MQTT_PASSWORD
                        Password name for the MQTT connection. (default: None)
  --discrete_topics DISCRETE_TOPICS
                        Post sensor data to discrete topics instead of one JSON payload. (default: False)Send GCODE over MQTT:You can also send GCODE to your printer if you publish something to $TOPIC/gcode