Saravanan666/pypi-org huggingface dataset:
Package: phpipam-exporter
phpipam-exporterThe generator DHCP, DNS or hosts records fromphpipam.UsageAll parameters can be defined as environment variables.Program parametersParameterENV variableRequiredDescription--subnet/-sPHPIPAM_SUBNETSYesFilter output for specific PHPIPAM subnet. Can be used more times (inPHPIPAM_SUBNETS, subnets are separated by coma).--hostPHPIPAM_HOSTYesphpipam API entrypoint formathttps://<fqdn>/api/<api_id>/(e.g.https://phpipam.example.com/api/exporter/)--tokenPHPIPAM_TOKENYesphpipam API token.--format/-fPHPIPAM_FORMATNo (default:json)Output format. (dhcpd,dnsmasq,hosts)--output/-oPHPIPAM_OUTPUTNo (default:stdout)Output file.--on-change-actionPHPIPAM_ON_CHANGE_ACTIONNoBash command. This command is fired only when the output file is changed. This parameter has to be defined only together with--output. (e.g.systemctl reload named)--custom-templatePHPIPAM_CUSTOM_TEMPLATENoPath to customJinjatemplate file.Generate API tokenEnable API plugin:Administration > phpIPAM settings > API = OnCreate token:Administration > API > Create API keyToken parametersApp IDexporterApp permissionsReadApp securitySSL with App code tokenCopyApp codeand use it asPHPIPAM_TOKEN.App IDhas to be used as part ofPHPIPAM_HOST.Hosts fileexportPHPIPAM_TOKEN='12345678945678912345678a1235'exportPHPIPAM_HOST='https://phpipam.example.com/api/exporter/'cat/etc/hosts.static127.0.0.1localhostlocalhost.localdomain::1localhostlocalhost.localdomainphpipam_export-s192.168.1.0/24-fdhcpd-o/etc/hosts.dynamic--on-change-action"cat /etc/hosts.static /etc/hosts.dynamic >> /etc/hosts"DHCPdexportPHPIPAM_TOKEN='12345678945678912345678a1235'exportPHPIPAM_HOST='https://phpipam.example.com/api/exporter/'phpipam_export-s192.168.1.0/24-fdhcpd-o/etc/dhcp/subnet.conf--on-change-action"systemctl reload dhcpd"/etc/dhcp/dhcpd.confauthoritative;
ddns-update-style none;
default-lease-time 86400;
max-lease-time 172800;
shared-network "lan" {
    subnet 192.168.1.0 netmask 255.255.255.0 {
        option subnet-mask 255.255.255.0;
        option domain-name-servers 192.168.1.1, 192.168.1.2;
        option broadcast-address 192.168.1.255;
        option routers 192.168.1.1;
        pool {
            range 192.168.1.254 192.168.1.254;
            deny unknown-clients;
            include "/etc/dhcp/subnet.conf";
        }
    }dnsmasqexportPHPIPAM_TOKEN='12345678945678912345678a1235'exportPHPIPAM_HOST='https://phpipam.example.com/api/exporter/'phpipam_export-s192.168.1.0/24-fdnsmasq-o/etc/dnsmasq.d/subnet.conf--on-change-action"systemctl reload dnsmasq"json formatexportPHPIPAM_TOKEN='12345678945678912345678a1235'exportPHPIPAM_HOST='https://phpipam.example.com/api/exporter/'phpipam_export-s192.168.1.0/24-fjsonCustom templateWe can create a customJinjatemplate file and use it for formating output data. The addresses are stored in theaddressestemplate variable. Attributes of each device are described here3.4 Addresses controlleror we can usejsonformat to get all attributes.exportPHPIPAM_TOKEN='12345678945678912345678a1235'exportPHPIPAM_HOST='https://phpipam.example.com/api/exporter/'phpipam_export-s192.168.1.0/24--custom-templateansible_inventory.j2-o/ansible-project/inventory.yml
Package: phpIPAM-Scraper
What is this?This is a tool written in python to retrieve information on devices in phpIPAM based on a keyword supplied.This package provides a python module to retrieve info, and a command-line tool for interactive information retrievalThe tool will grab and display a switch’s IP address, hostname, and descriptionModuleTo Install:pip installphpIPAM-ScraperTo Use:import phpipam_scraperorfrom phpipam_scraper import IPAMThe IPAM class accepts optional parameters for username, password, and URL. If these values are not supplied when
instantiating the class, this module will attempt to prompt for them from stdin.
see theAPI Docfor additional information.Command Line Toolthe command line tool is calledphpipamand can be used in one of two ways:When called with an argument, it processes that specific request, and then exits. When called without a command, it
drops you into a shell from which you can run multiple subcommands.The benefit of running the shell is that phpIPAM authentication details will only be asked for once, and will be stored
in memory until you exit the shell.Warning:Please take caution when using the shell. Since phpIPAM username and password details are stored in memory
for as long as the shell is active, any*disreputable*program running on your computer while the shell is runningmaybe able to access those details while the shell is running. Most operating systems prevent this sort of
behaviour, but not all do, so take care.There are two main groups of commands which can be run from this command line tool: config and get.configcommands allow you to get or set the URL of the phpIPAM installation to connect togetcommands allow you to retrieve device information from phpIPAM’s search page, device page, or both.
you can typephpipam [group]--helpto get more information, or typehelpor?from within the shell to get
more information.Want to contribute?See the see the project page / wiki on github for details
Package: phplist-client
This is a python 3 library for interacting with the PHPList REST API.To Usepip install-rrequirementsWrite your code:```python from phplist import PHPListClientclient = PHPListClient(”https://myphplistresturl”, secret=”mysecret”)
client.login(login=”myusername”, password=”mypassword”) output =
client.lists_get() ```Run Testspip install nosenosetests tests.pyTODOadd setup.pypush up to pypi
Package: php-var-dump
![Python package](https://github.com/jvanasco/php_var_dump/workflows/Python%20package/badge.svg)A port of thevar_dumpfunction of PHP to Python.This module allows you to “dump” trivial Python objects into PHP code.Why? So you can use Python to write fast PHP websites when you need to run PHP websites.Sometimes you need to run a PHP website.Why on earth would you want this?!?!?Imagine that you have to deploy something in PHP.  You don’t have a choice.
You HAVE to.php_var_dumplets you do all your data processing and management in Python.
You can then convert your native Python data structures into PHP code,
which can then be saved as include fles for PHP.Other Python modules that can accomplish the general idea:phpserialize
implements the PHP serialize/unserialize functions in Python
allows you to serialize a Python data structure to PHP
allows you to unserialize a php data structure to Pythonsimplejson
there are json parsers in PHP, which can read code you saveThe main benefit of using the var_dump method, is that there is no overhead
in loading/unloading/parsing/etc.This method allows you to build a PHP include file that simply runs fast,
and that can use multiple includes within the filesystem as a “database”
like system. This way you don’t have to set up any databases, libraries,
or whatever - you can just deploy PHP code without coding much in PHP.Usagefromphp_var_dumpimportphp_var_dumpdata="Hello World"as_php=php_var_dump('var',data)print(as_php)That will generate valid PHP code:$var = 'Hello World';You’d probable then want to save it…data_string="<?php\n\n%s\n\n?>"%as_phpopen('data.php','w').write(data_string.encode("utf-8"))Then just include thedata.phpfile in your PHP programs.There’s also aphp_as_blockfunction, which does the trivial encapsulation as above.copyright:2012 by Jonathan Vanascolicense:BSDChangelogv0.3.2
* packaging fixesv0.3.1
* packaging fixesv0.3
* upgraded black; 20.8b1
* integrated with pre-commit
* tox, github actions
* python3 supportv0.2
* flake8v0.1
* initial
Package: php-whisperer
php_whisperer"I heard you help people with PHP problems?" "Truth is, I help PHP with people problems."Read PHPConvert PHP arrays to Python objects using read_phpPHP File:<?php
# /tmp/a_php_file.php
$data = [
    "My Php Array" => [
        "You",
        "get",
        "the",
        "point"
    ]
];Python Code:from php_whisperer import read_php
read_php('/tmp/a_php_file.php', variable='data')Result:{'My Php Array': ['You', 'get', 'the', 'point']}Execute Arbitrary PHPfrom php_whisperer import read_raw

php_code = """<?php

$v = explode(" ", "You get the point");
"""
data = read_raw(php_code, "v")
print(data)Write PHPConvert Python lists and dictionaries to PHP using generate_phpfrom php_whisperer import generate_php
generate_php([1, 2, 3, 4])Result:array(1, 2, 3, 4);Modern syntax also available:from php_whisperer import generate_php
generate_php([1, 2, 3, 4], modern=True)Result:[1, 2, 3, 4];
Package: phrase
PhraseA library that builds on nltk and gensim to automatically generate phrases.InstallationAdd the package to your python path using pip:`bash pip install phrase `UsageTo create a phrase dictionary and print out the top 25 phrases:`bash create_phrase_dictionary <corpus_folder> <phrase_dictionary_output_filename> `This is not a light process, it can take a lot of memory and time, so be warned.TestsTo run all the tests, you need to run py.test to pick up the unit tests.  Lettuce is currently being used for BDD tests
and needs to be run from the tests folder or with tests/ added to the PYTHONPATH (the tests utilize the units.helpers modules)`bash py.test PYTHONPATH=tests lettuce tests/features cd tests lettuce features/ `
Package: phrasebook
Store phrases (SQL, messages, what-have-you) alongside your modules.Project Featuresphrasebooka starterClickcommand-line
applicationautomated unit tests you can run withpytestaSphinxdocumentation
projectGetting StartedThe project’s documentation contains a section to help youget
startedas a developer or user of the library.Development PrerequisitesIf you’re going to be working in the code (rather than just using the
library), you’ll want a few utilities.GNU MakePandocResourcesBelow are some handy resource links.Project DocumentationClickis a Python package for
creating beautiful command line interfaces in a composable way with
as little code as necessary.Sphinxis a tool that
makes it easy to create intelligent and beautiful documentation,
written by Geog Brandl and licnsed under the BSD license.pytesthelps you write
better programs.[GNU Make] is a tool which controls the generation of executables and
other non-source files of a program from the program’s source files.AuthorsPat Daburu-Initial work-githubSee also the list ofcontributorswho participated in this project.LicenseMIT LicenseCopyright (c) patdaburuPermission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
“Software”), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Package: phrase-counter
Common Phrase DetectionThis is an API python library which is developed for detecting stop phrases.Table of ContentsBackgroundInstallAPIMaintainersBackgroundNLP (Natural Language Processing) techniques is very helpful in various applications such as sentiment analysis, chatbots and other areas. For developing NLP models a need for a large & clean corpus for learning words relations is indisputable. One of the challanges in achieving a clean corpus is stop phrases. Stop phrases usually does not contain much information about the text and so must be identified and removed from the text.This is the aim of this repo to provide a structure for processing HTML pages (which are a valuable source of text for all languages) and finding a certain number of possible combinations of words and using human input for identifying stop phrases.InstallMake sure you havedocker,docker-composeandpython 3.8and above installed.create a.envfile with desired values based on.env.examplefile.After cloning the project, go to the project directory and run below command.docker-compose-fdocker-compose-dev.ymlbuildAfter the images are built successfully, run below command for starting the project.docker-compose-fdocker-compose-dev.ymlup-dWe need to create a database and collection in mongo in order to use the API. First run mongo bash.docker exec -it db bashAuthenticate in mongo container.mongo -u ${MONGO_INITDB_ROOT_USERNAME} -p ${MONGO_INITDB_ROOT_PASSWORD} -- authenticationDatabase adminCreate the database and collection based onMONGO_PHRASE_DBandMONGO_PHRASE_COLnames you provided in step2.use phrasedb;  # Database creation
db.createCollection("common_phrase");  # Collection creationNow you're ready yo use the API section.APIThis API has three endpoints.Document ProcessHere you can pass a HTML text in request body to process it.The process stages are:Fetching all H1-H6 and p tagsCleaning textFinding bags (from 1 to 5 bags of word)Counting the number of occurences in textIntegrating results in database
(Updating count field of the phrase if already exists, otherwise inserting a
new record)Status UpdaterUpdates statuses.Changing the status of a phrase to eitherstoporhighlight.Data FetcherFetching data from database based on the statuses.
Here you can fetch phrases based on 4 different situation for statuses:Stop phrasesHighlight phrasesPhrases that have status (either stop or highlight)Phrases which statuses are not yet determinedAPI detailsAPI Base URL127.0.0.1:8000API Swagger UI127.0.0.1:8000/docsFor futher details and how to make request to each endpoint refer to the swagger of the API.MaintainersMaani BeygiReza Shabrang
Package: phrase-detective
Installation from pip3pip3install--verbosephrase_detectivepython-mspacydownloaden_core_web_trf
python-mspacydownloades_dep_news_trf
python-mspacydownloadde_dep_news_trfUsagePlease refer toapi docsDetect noun phrasesimport spacy
from spacy import Language
from phrase_detective import NounPhraseRecognizer, PKG_INDICES

@Language.factory("nprecog")
def create_np_parser(nlp: Language, name: str):
  return NounPhraseRecognizer(nlp) 

def noun_phrase(lang, sentence):
  nlp = spacy.load(PKG_INDICES[lang])
  nlp.add_pipe("nprecog")
  doc = nlp(sentence)
  for np in doc._.noun_phrases:
    print(np.text)Detect verb phrasesimport spacy
from spacy import Language
from phrase_detective import VerbKnowledgeRecognizer, PKG_INDICES

@Language.factory("vkbrecog")
def create_vkb_parser(nlp: Language, name: str):
  return VerbKnowledgeRecognizer(nlp) 

def verb_knowledge(lang, sentence):
  nlp = spacy.load(PKG_INDICES[lang])
  nlp.add_pipe("vkbrecog")
  doc = nlp(sentence)
  for v in doc._.verbs:
    print("TEXT: {}, TAG: {}, FORM: {}, ORIGNAL: {}".format(v.text, v.tag_, spacy.explain(v.tag_), v.lemma_))
  for pp in doc._.passive_phrases:
    print(pp.text)
  for vp in doc._.verb_phrases:
    print(vp)DevelopmentClone projectgit clone https://github.com/qishe-nlp/phrase-detective.gitInstallpoetryInstall dependenciespoetry updateTest and Issuepoetry run pytest -rPwhich run tests undertests/*Create sphinx docspoetry shell
cd apidocs
sphinx-apidoc -f -o source ../phrase_detective
make html
python -m http.server -d build/htmlHose docs on github pagescp -rf apidocs/build/html/* docs/BuildChangeversioninpyproject.tomlandphrase_detective/__init__.pyBuild python package bypoetry buildGit commit and pushPublish from local dev envSet pypi test environment variables in poetry, refer topoetry docPublish to pypi test bypoetry publish -r testPublish through CIGithub action build and publish package totest pypi repogit tag [x.x.x]
git push origin masterManually publish topypi repothroughgithub action
Package: phraseextractor
phrase extractorA shallow phrase extractor based on nltkInstallationpip3 install phraseextractorExamplefromextractorimportphrases_extractortext=('GOP Sen. Rand Paul was assaulted in his home in Bowling Green, Kentucky, on Friday, ''according to Kentucky State Police. State troopers responded to a call to the senator\'s ''residence at 3:21 p.m. Friday. Police arrested a man named Rene Albert Boucher, who they ''allege "intentionally assaulted" Paul, causing him "minor injury". Boucher, 59, of Bowling ''Green was charged with one count of fourth-degree assault. As of Saturday afternoon, he ''was being held in the Warren County Regional Jail on a $5,000 bond.')grammar=r"""NP:   {<NNP>?<NNP>?}"""label='NP'terms=phrases_extractor.get_phrases(text,grammar,label)
Package: phrase-hunter
Phrase HunterThis is a simple game for guessing the letters of a phrase, similar to hangman.Install it with$ pip install phrase-hunterRun it with$ phrase-hunterSource codeMajority of the code can be found in the classes in the includedphrasehunterpackage. This is my Unit 3 submission for my Treehouse Python Development TechDegree
so any and all feedback is welcome!
Package: phrase-pickers
#Use
Example usage for np_picker:from phrase_pickers.np_picker import \*

nlp = spacy.load("en_core_web_sm")

print(get_np_indices(nlp('We produce oil and natural gas.')))
print(get_np_indices(nlp('I like green and red cars.')))
print(get_np_indices(nlp('I like Starbucks coffee.')))```

Example usage for vp_picker:
```import spacy
from phrase_pickers.vp_picker import \*

nlp = spacy.load("en_core_web_sm")

print(get_vp_indices(nlp("We will be offering general clothes after we get approval.")))
print(get_vp_indices(nlp("We make transportation and fracturing pipelines.")))
print(get_vp_indices(nlp("We provide repair services.")))
print(get_vp_indices(nlp("We are a car manufacturer.")))
print(get_vp_indices(nlp("We have not experienced any significant shortages of raw materials, components or finished parts and normally do not carry inventories of raw materials or finished parts in excess of those reasonably required to meet our production and shipping schedules.")))```#Packaging
Packaging for this module is tricky, because it requires a spacymodel(e.g.en_core_web_sm) to work properly.
To create a new release & push package to PyPI:Change the version number insetup()insetup.pyDelete any old .whl or .tar.gz files indistfolderIn your dev environment, runpython setup.py clean --all sdist bdist_wheelTest upload to TestPyPI:python -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*In a clean, new environment, verify that package downloaded from TestPyPI is working:pip install --extra-index-url https://testpypi.python.org/pypi pn-phrase-pickersUpload to PyPI with twine.
Package: phrases-case
phrases caseConvert phrases between different cases.Not usingremodule.>>>importphrases_case>>>phrases_case.snake('camelCase')'camel_case'>>>phrases_case.snake('camelCase',separator='-')'camel-case'>>>phrases_case.hyphen('camelCase')'camel-case'>>>phrases_case.space('camelCase')'camel case'>>>phrases_case.camel('snake_case')'snakeCase'>>>phrases_case.pascal('snake_case')'SnakeCase'
Package: phrasetms-client
Welcome to Phrase&#39;s TMS API documentation.    Please visit our [help center](https://support.phrase.com/hc/en-us/sections/5709662083612) for more information about the APIs.    If you have any questions, please contact [Support](https://support.phrase.com/hc/requests/new).    Please, include the &#x60;User-Agent&#x60; header with the name of your application or project. It might be a good idea to include some sort of contact information as well, so that we can get in touch if necessary. Examples of excellent &#x60;User-Agent&#x60; headers:  &gt; User-Agent: Example mobile app (example@phrase.com) &lt;br/&gt; User-Agent: ACME Inc Java 1.8 Client (http://acmeinc.com/contact)  # noqa: E501
Package: phrase-tokenizer
Phrase TokenizerTokenize an English sentence to phrases via benepar.Installationpipinstallphrase-tokenizer# pip install phrase-tokenizer -U to update# or to install the latest from github:# pip git+https://github.com/ffreemt/phrase-tokenizer.gitOr clone the repohttps://github.com/ffreemt/phrase-tokenizer.git:gitclonehttps://github.com/ffreemt/phrase-tokenizer.gitcdphrase-tokenizer
pipinstalllogzerobenepartensorflowOr usepoetry, e.g.gitclonehttps://github.com/ffreemt/phrase-tokenizer.gitcdphrase-tokenizer
poetryinstallUsagefromphrase_tokenizerimportphrase_tokres=phrase_tok("Short cuts make long delays.")print(res)# ['Short cuts', 'make long delays']# verbose=True turns on verbose to see the tokenizing processres=phrase_tok("Short cuts make long delays",verbose=True)# ',..Short.cuts,.make..long.delays..'Consult the source code for details.For Developersgitclonehttps://github.com/ffreemt/phrase-tokenizer.gitcdphrase-tokenizer
pipinstall-rrequirements-dev.txtInipython,plot_treeis able to draw a nice tree to aid the development, e.g.,fromphrase_tokenizer.phrase_tokimportplot_treeplot_tree("Short cuts make long delays.")
Package: phrazor
Phrazor API Postman WorkspacePhrazor Insights CollectionFor Postman Docs visitPhrazor Postman DocsPhrazor Python LibraryPhrazor is a Python library that converts your data into textual insights.You can find usage examples for the Phrazor Python library in ourPhrazor DocsQuick StartClick here to go toQuick start of Phrazor SDKInstallationYou don't need this source code unless you want to modify the package. If you just
want to use the package, just run:pipinstall--upgradephrazorInstall from source with:pythonsetup.pyinstallUsageThe library needs to be configured with your account's secret key which is available on
thewebsite.Or setphrazor.API_KEYto its value:importphrazorphrazor.API_KEY="YOUR API KEY"phrzr=phrazor.Phrazor()# set dataphrzr.set_data({"Column Name 1":[listofvalues],"Column Name 2":[listofvalues]})# set column metaphrzr.set_column_meta(date_column="Date Column Name",metric_column=["Metric Column Name 2"],dimension_column="Dimension Column Name")# supported analysis - ("descriptor", "change", "compare_measure", "compare_dimension", "target_vs_achievement", "budget" or "trend")# print the generated insightsprint(phrzr.get_insights("descriptor"))
Package: phreeqcrm
PhreeqcRM: A reaction module for transport simulators based on the geochemical model PHREEQCReaction module for reactive-transport simulators. Based on IPhreeqc, allows access to all PHREEQC reaction capabilities. Contains methods for initial and boundary conditions, running reactions on all model cells, transfer of data to and from the module, and parallelization by MPI or OpenMP.This is the development repository for PhreeqcRM. The official USGS distribution is available atUSGS Release Page.DisclaimerThis software is preliminary or provisional and is subject to revision. It is
being provided to meet the need for timely best science. The software has not
received final approval by the U.S. Geological Survey (USGS). No warranty,
expressed or implied, is made by the USGS or the U.S. Government as to the
functionality of the software and related material nor shall the fact of release
constitute any such warranty. The software is provided on the condition that
neither the USGS nor the U.S. Government shall be held liable for any damages
resulting from the authorized or unauthorized use of the software.
Package: phreeqpy
PhreeqPy provides Python tools to work withPHREEQC.Currently it provides access to the newIPhreeqcinterface without the need to
run a COM server and therefore also works on non-Windows systems.
IPhreeqc is described in more detail in thispublication. Thispublication at the conference MODFLOW and More 2011demonstrates with an
example how PhreeqPy works.