Saravanan666/pypi-org huggingface dataset:
Package: pinference
PinferenciaSimple, but Powerful.English Doc|Seriously, Doc|中文文档|正襟危坐版文档Help wanted. Translation, rap lyrics, all wanted. Feel free to create an issue.Pinferenciatries to be the simplest AI model inference server ever!Serving a model with REST API has never been so easy.If you want tofind a simple but robust way to serve your modelwrite minimal codes while maintain controls over you serviceavoid any heavy-weight solutionseasily to integrate with your CICDmake your model and service portable and runnable across machinesYou're at the right place.FeaturesPinferenciafeatures include:Fast to code, fast to go alive. Minimal codes needed, minimal transformation needed. Just based on what you have.100% Test Coverage: Both statement and branch coverages, no kidding.Easy to use, easy to understand.Automatic API documentation page. All API explained in details with online try-out feature.Serve any model, even a single function can be served.Installpipinstall"pinferencia[uvicorn]"Quick StartServe Any ModelfrompinferenciaimportServerclassMyModel:defpredict(self,data):returnsum(data)model=MyModel()service=Server()service.register(model_name="mymodel",model=model,entrypoint="predict",)Just run:uvicorn app:service --reloadHooray, your service is alive. Go tohttp://127.0.0.1/and have fun.Any Deep Learning Models?Just as easy. Simple train or load your model, and register it with the service. Go alive immediately.PytorchimporttorchfrompinferenciaimportServer# train your modelsmodel="..."# or load your models (1)# from state_dictmodel=TheModelClass(*args,**kwargs)model.load_state_dict(torch.load(PATH))# entire modelmodel=torch.load(PATH)# torchscriptmodel=torch.jit.load('model_scripted.pt')model.eval()service=Server()service.register(model_name="mymodel",model=model,)TensorflowimporttensorflowastffrompinferenciaimportServer# train your modelsmodel="..."# or load your models (1)# saved_modelmodel=tf.keras.models.load_model('saved_model/model')# HDF5model=tf.keras.models.load_model('model.h5')# from weightsmodel=create_model()model.load_weights('./checkpoints/my_checkpoint')loss,acc=model.evaluate(test_images,test_labels,verbose=2)service=Server()service.register(model_name="mymodel",model=model,entrypoint="predict",)Any model of any framework will just work the same way. Now runuvicorn app:service --reloadand enjoy!ContributingIf you'd like to contribute, details arehere
Package: pinferencia
Simple, but Powerful.English Doc|中文文档|中文ReadmeHelp wanted. Translation, rap lyrics, all wanted. Feel free to create an issue.Pinferenciatries to be the simplest machine learning inference server ever!Three extra lines and your model goes online.Serving a model with GUI and REST API has never been so easy.If you want togive your model aGUIandREST APIfind asimple but robustway to serve your modelwriteminimalcodes while maintain controls over you serviceavoidanyheavy-weightsolutionscompatiblewith other tools/platformsYou're at the right place.FeaturesPinferenciafeatures include:Fast to code, fast to go alive. Minimal codes needed, minimal transformation needed. Just based on what you have.100% Test Coverage: Both statement and branch coverages, no kidding. Have you ever known any model serving tool so seriously tested?Easy to use, easy to understand.A pretty and clean GUIout of box.Automatic API documentation page. All API explained in details with online try-out feature.Serve any model, even a single function can be served.Support Kserve API, compatible with Kubeflow, TF Serving, Triton and TorchServe. There is no pain switching to or from them, andPinferenciais much faster for prototyping!InstallRecommendpipinstall"pinferencia[streamlit]"Backend Onlypipinstall"pinferencia"Quick StartServe Any ModelfrompinferenciaimportServerclassMyModel:defpredict(self,data):returnsum(data)model=MyModel()service=Server()service.register(model_name="mymodel",model=model,entrypoint="predict")Just run:pinfer app:serviceHooray, your service is alive. Go tohttp://127.0.0.1:8501/and have fun.Any Deep Learning Models?Just as easy. Simple train or load your model, and register it with the service. Go alive immediately.Hugging FaceDetails:HuggingFace Pipeline - VisionfromtransformersimportpipelinefrompinferenciaimportServervision_classifier=pipeline(task="image-classification")defpredict(data):returnvision_classifier(images=data)service=Server()service.register(model_name="vision",model=predict)PytorchimporttorchfrompinferenciaimportServer# train your modelsmodel="..."# or load your models (1)# from state_dictmodel=TheModelClass(*args,**kwargs)model.load_state_dict(torch.load(PATH))# entire modelmodel=torch.load(PATH)# torchscriptmodel=torch.jit.load('model_scripted.pt')model.eval()service=Server()service.register(model_name="mymodel",model=model)TensorflowimporttensorflowastffrompinferenciaimportServer# train your modelsmodel="..."# or load your models (1)# saved_modelmodel=tf.keras.models.load_model('saved_model/model')# HDF5model=tf.keras.models.load_model('model.h5')# from weightsmodel=create_model()model.load_weights('./checkpoints/my_checkpoint')loss,acc=model.evaluate(test_images,test_labels,verbose=2)service=Server()service.register(model_name="mymodel",model=model,entrypoint="predict")Any model of any framework will just work the same way. Now runuvicorn app:service --reloadand enjoy!ContributingIf you'd like to contribute, details arehere
Package: ping
This library is a fork of George Notaras’ python-ping library, which is
an implementation of the standard ICMP ping in pure Python.As it uses raw ICMP sockets, you need to be root to use the functions
exported by the ping module.This fork by Pierre Bourdon adds a setup.py file in order to permit an
easier distribution of the package. The license of the library remains
unchanged (GPLv2), see COPYING.
Package: pingboard
This tool pings all the servers named on the command line, and shows you a
dashboard display of which hosts are up, which are down, and how long that
has been the case for. It uses raw sockets with protocol icmp, which
normally requires elevated permissions.  Hence you’ll typically invoke it
with something like sudosudo pingboard www1.example.com www2.example.compingboard attempts uses socket.getaddinfo() to resolve your servers to
IPv4 or IPv6 addresses. It only takes the first returned result. Hence you
can specify an IP address (as socket.getaddrinfo() will ‘resolve’ that to
the relevant IP address).  But also, if your name resolves into multiple IP
addresses then it may not be obvious to you which server is actually being
pinged.Instead of listing servers on the command line, you can pass a –server-list
file that lists the servers.  If you do this, the file format is one server
per line.  Any text on a line after a white space is treated as a comment
for that server, and is also displayed by pingboard.Use the –log-file option to have pingboard write a log file of events, so
you can have a historical record of when servers came up and down.For other options, run pingboard with the -h option.Installing:pip install pingboard
Package: pingdat
pingdatA Prometheus exporter for ping statistics.InstallationInstall the published package using pip:pip3installpingdatThis project usespoetryto manage dependencies and a local virtual environment.  To
get started, clone the repository and install the dependencies with the following:poetryinstallGrafana DashboardA Grafana dashboard is available as #(17922)[https://grafana.com/grafana/dashboards/17922].UsageRun the module and tell it which config file to use.python3-mpingdat--configpingdat.yamlIf you are usingpoetryto manage the virtual environment, use the following:poetryrunpingdat--configpingdat.yamlDockerpingdatis available as a published Docker image.  To run, use the latest version:
from Docker Hub:dockercontainerrun--rm--publish9056:9056"jheddings/pingdat:latest"The configuration file is read from/opt/pingdat/pingdat.yamland may be changed
with arguments to the container:dockercontainerrun--rm--tty--publish9056:9056\--volume"/path/to/host/config:/etc/pingdat"\"jheddings/pingdat:latest"--config/etc/pingdat/pingdat.yamlDocker ComposeA sample configuration is also provided for usingdocker compose.  Similar to using
Docker directly, the configuration file can be provided on the host side.  Then,
simply start the cluster normally:dockercomposeupOr detached as a background process:dockercomposeup--detachConfigurationFor now, review the samplepingdat.yamlconfig file for a description of supported
configuration options.
Package: pingdiscover
pingdiscover is simple commandline app for looking up hosts in given networkInstallationUsing Pip```bash$ pip install pingdiscover## Manualbash
$ git clonehttps://github.com/$ cd pingdiscover
$ python3 setup.py installUsing Makefile$ make installUsage$ pingdiscover 192.168.0.0/24 --concurrent 8 --timeout 3
$ pingdiscover 192.168.0.0/24 --concurrent 10
Package: pingdomexport
InstallationTo install simply$pipinstallpingdomexportConfigurationCheck theconfiguration file.Place the configuration file in any place that seems fit to you. Make sure the user you will use to run pingdom export
has read access to the configuration file.Configuration accesspingdom_access:username:dummypassword:dummyaccount_email:dummyapp_key:dummyThe username, password and account email should be easy to fill in (is your credentials to log in in pindgom).To get your app key, log in on pingdom then go to Integrations > The Pingdom API > Register ApplicationConfiguration checks# the checks that you want to export datachecks:# 3 strategies supported# all: all checks# include: will only include the ids specified# exclude: all checks except the ids specifiedstrategy:allids:[]Pindgom export allows to export all checks:checks:strategy:allids:[]Specify the checks to export:checks:strategy:includeids:[12454,32932]Specify the checks to exclude (will export every check except the ones specified):checks:strategy:excludeids:[12454]Configuration exportPingdom export allows to export the checks and results to mysql, postgres or the stdout.load:# type: output|mysql|postgrestype:outputparameters:[]# if mysql#parameters:#  db_url: mysql+pymysql://user:password@host/database# if postgres#parameters:#  db_url: postgres://user:password@host/databaseIf output:load:type:outputparameters:[]If mysql:load:type:mysqlparameters:db_url:mysql+pymysql://user:password@host/databaseIf posgres:load:type:postgresparameters:db_url:mysql+pymysql://user:password@host/databaseDatabase schemaIf you are going to export for database then you need to create the schema upfront:MySQLPostgresDatabase privilegesBoth MySQL and Postgres requires a user with SELECT,INSERT,UPDATE,DELETE permissions to the DB. In case of Postgres the user also requires access to sequences.RunTo list the options available:$pingdom-run-export--helpExport only checks information:$pingdom-run-export--config/full/path/to/config.yml--typechecksExport only checks results:$pingdom-run-export--config/full/path/to/config.yml--typeresultsExport checks information & results:$pingdom-run-export--config/full/path/to/config.yml--typeallRun - partial exportBy default the pingdom export will always export the full results. There is optional arguments to allow to specify a time range, eg:$pingdom-run-export--config/full/path/to/config.yml--typeresults--checks-from1465071758--checks-to1465158158Big dataIn case you have multiple checks with months of history, running everything in a single thread will probably take too much time.You can use multiple configuration files and run one pingdom export per check. Then just have a crontab running daily and
use the checks-from and checks-to.
Package: pingdomv3
Python library for Pingdom V3 APITo generate an Pingdom API V3 Token, go tohttps://my.pingdom.com/3/api-tokensFor Pingdom API V3 documents, go tohttps://docs.pingdom.com/api/import pingdomv3
  client = Client('1234567890-999999999999999999999999999999999999999999999999999999999999')
  # get list of of a checks
  client.get_checks()
  # returns 
  client.get_check(2321)
  # create a new check
  client.create_check({...})
  # make a duplication of a check
  client.duplicate_check('5626090')
  # delete a check
  client.delete_check(5626090)Installation$> pip install pingdomv3Contribution welcomeI simply started this simple project to easily duplicate existing checks so I can quickly manipulate checks in a quickduplicate -> modify -> liveway. If you need other APIs, feel free to contribute.
Package: pingertron
Ping Hosts and URLs and keep stats on successes and failuresRun this as a daemon on your box and check in to see if there are problems.Intended to be a slightly different approach to blackbox_exporter.InstallingpipinstallpingertronRunningpingertronprobes.yamlICMP usually needs root access to send packets:sudopingertronprobes.yamlThere is an exampleprobes.yamlyou can use as a basis for your own.probes.yamlSpecify one or more probes to run using probes.yaml.This file is re-read on each evaluation cycle, so you can update it without restarting the process.Example probes.yaml:interval_seconds:60# seconds between each batch of probes being sentprobes:-protocol:http# one of icmp or httpdescription:my probe# optional description# probe specific properties# HTTP Probe-protocol:http# description: my HTTP probe  # optional descriptionurl:https://example.com/# URL to probe, http or httpsmethod:GET# HTTP method to useexpected_status_code:200# HTTP status code you expect, usually 200# ICMP Probe-protocol:icmp# description: my ICMP probe  # optional descriptionhostname:10.0.0.1# Hostname or IP to ping.The canonical definition of what goes into this file can be found inprobes_config.py.DevelopingdevenvIf you usedevenv:direnvallow.poetryIf you usepoetry:poetryinstall
poetryrunpingertron
Package: pingline
Pingline - a less cool version ofgpingThis is just a package for me to practice working with PyPi. You should probably usegpinginstead. It doesn't require a heavymatplotlibdependency.Why even use this?This is helpful for debugging ping problems with your WiFi:Try starting the interactive plotter and launchingfast.com- see the impact of heavy traffic on your pingCheck if the router ping is as bad as internet ping. If so, the problem is with your router, else it's probably your ISPInstallationpip install pinglineUsageLaunch the recorder - it's pinging our hosts and dumping the ping time-series into a log file, by defaultping_log.csv. This CSV plays nicely with Excel, if you want to explore the data manually.pingline recorder --interval=0 --router-host=192.168.0.1 --internet-host=google.comLaunch the interactive plotter - it watches the log file and shows a live graph of ping data.pingline plotter --interactive --last-n-minutes=5https://user-images.githubusercontent.com/4249837/177884337-d6c235b1-d017-4c9e-97c2-8a38d601e28c.mp4
Package: pingmeen
Pingmeen lets you know, when your computation is done!In ML and some other fields there is a common case, when you deal with computation intensive and time consuming tasks, and your solution is often written in Python. Pingmeen package allows you to ping yourself easily using Telegram when computation is done.How to use PingmeenSend any message to@PingmeenBotin Telegram. It will respond to you with token within 1 minute.Install this package andrequestspackage (https://pypi.org/project/requests/)Write some code using class Pingmeen from package and token you received from PingmeenBot.Code exampleimport pingmeen

# if you have passed invalid token, you'll get exception at next line
ping = pingmeen.Pingmeen(token = '<your token from bot here>') 

# instead of that loop put some code you're waiting to be executed
for i in range(int(1e7)):                                      
    pass

# at next line you'll receive a message from PingmeenBot in Telegram
ping.finish()
Package: ping-module
PingDevice ClassThe PingDevice class is a Python class that allows you to check if a device is online by pinging its IP address.InstallationThe PingDevice class requires Python 3.6 or later. There are no additional dependencies required.UsageFirst, import the PingDevice class:In[7]:fromping_moduleimportPingDeviceCreate object and call ping() method.In[8]:a=PingDevice(host="192.168.178.1")In[9]:a.ping()Out[9]:True

In[10]:a=PingDevice(host="www.ciscoscsdfsdfdsfsfds.com")In[11]:a.ping()Out[11]:False
Package: ping-multi-ext
ping-multi-extThis tool lets you interactively ping:Onehost frommultiplelocations (via SSH)Multiplehosts fromonelocation (local machine, or remote via SSH)Multiplehosts frommultiplelocations (via SSH)ScreenshotsThe main screen:Full history of the “ping” raw output for a selected host:DescriptionThe ping results are summarized in real-time and you can also observe the following statistics:TX_cnt: Count of sent PING requestsRX_cnt: Count of received PING replies which are not timeoutsXX_cnt: Count of timeouts and missing PING repliesLoss%: Packet loss defined as the percentage of timed out and missing repliesAvg: Average round trip time (RTT)Min: Minimum (best) RTTMax: Maximum (worst) RTTStDev: Population standard deviation of all RTT dataThe interactive UI interface lets you visualize theRTT summaryin three modes:Successful vs. unsuccessful PING repliesThe RTT values (ping time) as a numberScaled per 100 ms where “0” means an RTT between 0 and 99 ms,
“1” means an RTT between 100 and 199 ms, and so onYou also have the option to review each host’s “ping” commandraw output.
Thefull historyis kept and you can navigate using the keys PgUp/PgDn/Home/End.No “root” privileges are required because for each host an external process is started which uses the standard “ping” command.You can select the statistics forwards and backwards using the lower “s” and upper “S” keys, similar to the “Vim” behavior.Installationpip3 install ping-multi-extThe executable “ping-multi” is automatically added to your “~/.local/bin” directory which you should add to your “$PATH” environment, so that you can easily execute “ping-multi”.If you install the package globally using “root” privileges, then the binaries are added in “/usr/local/bin” and you should be able to use them right away with no additional setup.ExamplesPing multiple hosts specified directly on the command-line; you can also provide just one host:ping-multi google.com github.comYou can also use SSH to run “ping” on remote machines:ping-multi google.com github.com github.com@root@my-server.comPing multiple hosts specified in a file; you can also add more single hosts directly as additional command-line arguments:ping-multi -f sample.listThe usage help explains the additional command-line options:$ ping-multi -h

usage: ping-multi [-h] [--version] [-W,--wait SECS] [-i,--interval SECS] [-f,--file FILE] [--hosts-max-width HOSTS_MAX_WIDTH] [host [host ...]]

Ping all hosts from FILE and HOSTs.

positional arguments:
  host                  host to ping; you can specify this option many times

optional arguments:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  -W,--wait SECS        timeout in seconds to wait for a ping reply; default=1
  -i,--interval SECS    time in seconds between sending each request; default=1
  -f,--file FILE        read list of hosts from file
  --hosts-max-width HOSTS_MAX_WIDTH
                        maximum width of the hosts column; default=0
Package: ping-overseer
ping-overseerThis is a mass ping monitoring tool with the following features:Easily input a list of IP's from any sourcePing monitors IP's in real timeConstantly displays what IP's are downHighlights for longer downtime IP'sThis is based on some functionality from PingInfoView. However, I needed something that ran on MacOS, thus this project was born!I mainly use this for real-time work during network switch cutovers. It is meant to be a short-term tool (minutes/hours of usage), not something for monitoing over days.InstallationGet the latest version through PIP/PyPi:sudo pip3 install --upgrade ping-overseerNMAP application is also required, download that at:https://nmap.orgThen simply run as:sudo ping-overseer -h
Package: pingphp
#PingPHP[![Build Status](https://travis-ci.org/zxylvlp/PingPHP.svg?branch=master)](https://travis-ci.org/zxylvlp/PingPHP)###A PHP code generator which use Python Like grammar##Introduction- PingPHP essentially is a PHP code generator, similar to CoffeeScript(CS). However there is a big difference between this code and CS.- This library is in order to efficiently write Ping code with Python like grammar, and generate the PHP code which is not different from manual code. So it can improve the production efficiency, and the generated code is easy to maintain.- The purpose of the CS is to maintain the CS code, with a lot of syntax sugar, it improved the efficiency of the code but loss the readability of the code.- For the most of PHPer, such a large number of syntax sugar is very hard to accept.- Moreover, when we work with other developers, maintaining the Ping or CS code directly would impede communication.- Ping is my wife's name. And one of the purposes of writen this library is help PHPer to improve the work efficiency. Help us to spend more time with our family and friends.##InstallationTo install PingPHP, simply:`$ sudo pip install redis`or from source:`$ sudo python setup.py install`##Getting StartedGenerate PingPHP.conf.json file.```$ pinginit```Then edit the config file with Wildcard.```{"ignoreFiles": ["test1/*"],"transFiles": ["test/**/*.ping"],"destDir": "dest"}```Generate files:```$ pingrun```Generate files and observe their changes:```$ pingsee```##CodeSampleInput file: part of typeHinting.ping```''''''#如下面的类class MyClass:'''* 测试函数* 第一个参数必须为 OtherClass 类的一个对象'''public test(otherclass:OtherClass):echo otherclass.var'''* 另一个测试函数* 第一个参数必须为数组'''public test_array(input_array:array):print_r(input_array)'''* 第一个参数必须为递归类型'''public test_interface(iterator:Traversable):echo get_class(iterator)'''* 第一个参数必须为回调类型'''public test_callable(callback:callable, data):call_user_func(callback, data)myclass = new MyClass()```Output file: part of typeHinting.php```<?php/****///如下面的类class MyClass {/*** 测试函数* 第一个参数必须为 OtherClass 类的一个对象**/public function test(OtherClass $otherclass) {echo $otherclass->var;}/*** 另一个测试函数* 第一个参数必须为数组**/public function test_array(array $input_array) {print_r($input_array);}/*** 第一个参数必须为递归类型**/public function test_interface(Traversable $iterator) {echo get_class($iterator);}/*** 第一个参数必须为回调类型**/public function test_callable(callable $callback, $data) {call_user_func($callback, $data);}}$myclass = new MyClass();```## Related* Vim Syntax highlighting plugin: [vim-PingPHP](https://github.com/PingPHP/Vim-PingPHP)* Sublime Text Syntax highlighting plugin: (Temporarily not supported)##Author* [Weibo http://weibo.com/zxylvlp](http://weibo.com/zxylvlp)* [Mail 937141576@qq.com](mailto:937141576@qq.com)##License (MIT)Copyright (c) 2015 zxylvlp[MIT](https://github.com/zxylvlp/PingPHP/blob/master/LICENSE)