Saravanan666/pypi-org huggingface dataset:
Package: phir
PHIR:PECOSHigh-level Intermediate Representationphirmodels thePHIR specificationas aPydanticmodel.
Seeour docs.
Included is the toolphir-clithat provides validation and pretty printing on the command line.PrerequisitesPython >=3.10InstallationJust issuepip install phirto obtain the latest stable release.phir CLIThe package includes a CLI for directly validating PHIR JSON files using the command line.❯phir-cli-h
usage:phir-cli[-h][-s][-v][jsonfile]ValidatesandprettyprintsvalidPHIR

positionalarguments:jsonfilejsonfiletovalidateagainstPHIRspec

options:-h,--helpshowthishelpmessageandexit-s,--schemadumpJSONschemaofthePHIRmodelandexit-v,--versionshowprogram'sversionnumberandexitDevelopmentClone the repository and run:python-mvenv.venvsource.venv/bin/activate
pipinstall-Upipsetuptools
pipinstall-rrequirements.txt
pre-commitinstallThen, install the project using:pipinstall-e.SeeMakefilefor other useful commands.TestingIssuepytestfrom the root directory.
Package: phish-ai-api
SummaryOfficial python API for Phish.AI public and private API to detect zero-day phishing websitesHow it Works (TLDR)Essentially we have a very big computer vision database of known websites and their legitimate domains.
The API surf to a given website takes a screenshots of the website and then compare it with our database and if we detect that it is similar to a known website but hosted we classify it as malicious and classify the targeted brand (which website this site tries to mimic).The Engine is in beta and doesn’t protect all brands yet. we make the database bigger every day, if you believe your brand is not in our database and you want us to crawl it, just drop me a line atyp@phish.aiPrivacy PolicyThe full privacy policy is at:https://www.phish.ai/phish-ai-privacy-policy/. By using the Public API you agree to our Privacy Policy and allow us to share your submission with the security community. If you want a Private API Key please contact us atinfo@phish.ai.Useful resourcesUI Version:https://app.phish.aiRaw API Documentation:https://app.phish.ai/(under documentation, “Thanks PyPi for not allowing minimum-cash sign”)Official website:https://www.phish.aiBlog:https://www.phish.ai/blogInstallation$pipinstallphish-ai-apiUsagefrom__future__importprint_functionfromphish_ai_apiimportAPIph=API(api_key='None or private api key you can request at info@phish.ai')res=ph.scan_url('https://google.com')print(res)print(ph.get_report(res['scan_id']))Output{"scan_id":"pQz7bGMwxgzGboNyX8cy"}{"domain":"google.com","ip_address":"74.125.124.113","iso_code":"US","status":"completed","target":"Google","time":"2018-04-15T07:27:37.860Z","title":"google","tld":"com","url":"http://google.com","user_agent":"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/67.0.3391.0 Safari/537.36","user_email":"api","verdict":"clean"}Issues & ContributingFound a Bug/Have a feature request feel free to open an Issue and we will look into it. Cheers.
Package: phishdetect-admin
# PhishDetect AdminThis software is part of the PhishDetect project.This is a simple Flask web application that is meant to run locally in order to remotely connect and manage a PhishDetect Node. You can simply install it with:` pip3 installphishdetect-admin`If you haven’t already done so, add the pip binaries directory to your path by placing the following in your~/.bashrcfile:` exportPATH=$PATH:~/.local/bin`Once installed, you can launch it with:`phishdetect-admin`It will spawn a local webserver and automatically open a tab on your default browser pointing to it. You will then be asked to configure the PhishDetet Node you wish to operate by providing the base URL (e.g.https://phishdetect.example.com) and your admin API key.
Package: phisherman.py
Phisherman.pyAsynchronous Python API Wrapper for phisherman.ggInstallationPython 3.8 or above is required# Stablepipinstallphisherman.py# Developmentpipinstallgit+https://github.com/QristaLabs/phisherman.pyExampleimportasynciofromphishermanimportClientapp=Client(token="Your Token")asyncdefmain():ifawaitapp.check_domain("internetbadguys.com"):print("Detected suspicious.")awaitapp.close()asyncio.run(main())LinksDocumentationPhishermanAPI Support Server
Package: phishfry
PhishFry Remediation Library and Command Line ToolPhishFry is a python library and command line tool for removing and restoring emails in exchange and office365. PhishFry supports shared mailboxes, group mailboxes and distribution lists. PhishFry removes/restores the entire conversation including any replies and forwards of the message.InstallationInstall with pip directly from github.sudopipinstallgit+https://github.com/ace-ecosystem/phishfry.gitAdd credentials for one or more exchange accounts with impersonation rights to the config.ini file.Example config.ini file:[account1]
user=admin@example1.com
pass=123456

[account2]
user=admin@example2.com
pass=123456Command Line Tool# display usage information./phishfry.py-h# Remove message with message_id=<message_id> from the test@example.com mailbox./phishfry.pyremovetest@example.com"<message_id>"# Restores message with message_id="<message_id>" to the test@example.com mailbox./phishfry.pyrestoretest@example.com"<message_id>"Libraryimportphishfry# Instantiate a phishfry account using admin email and passwordaccount=phishfry.Account("admin@example1.com","123456")# remove a messageresults=account.Remove("user@example1.com","<message_id>")# restore a messageresults=account.Restore("user@example1.com","<message_id>")# using the resultsforaddressinresults:# print the email address for these resultsprint(address)# get the remediation result for this addressresult=results[address]# print failure message if remediation action failedifnotresult.success:print(result.message)
Package: phishing-detection
Phishing Detection Using Random ForestDetect phishing websites using machine learningcross checking function -> compare_with_google can be used to cross check the results of the model.usage :detect:from phishing_detection import phishing_detection
print(phishing_detection.detect(‘google.com’))compare_with_google:url=<some url>
api=<your google cloud console api key>print(compare_with_google(url,api))Free software: MIT licenseDocumentation:https://phishing-detection.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1 (2019-07-20)First release on PyPI.0.2bug fixes0.2.1fixed model.sav path bug
added other dependencies in setup.py
Package: phishing-detection-engine
The project is using different techniques to identify phishing URLs.
Machine Learning and use of different APIs is done to get good results.
At first, model checks the URL in databases of phishing URLs.
If URL is found in database, user is given output immediaately.
If URL is not categorized at that point, then it is categorized using
machine learning model whcih is trained on dataset of above 18000 Websites
Package: phishing-detector
PHISHING DETECTORPhishing Detector is a library that can be used to detect phishing websites. You can query any website and find out if it is a phishing site within one line of code.Note:In order to use this library, you must have an API key of Phishing Detector. For more information check ourblog post.Setuppip install phishing_detectorUsageSingle URL Queryfromphishing_detectorimportDetector# while initializing the detector, you should pass your api_key as a parameter# if you don't have an api_key, you can get one from your profile page:# http://phishingdetector.live/profile/detector=Detector(api_key)detector.query('https://google.com')# it returns Legitimate or PhishingMultiple URL Query by Filefromphishing_detectorimportDetector# while initializing the detector, you should pass your api_key as a parameter# if you don't have an api_key, you can get one from your profile page:# http://phishingdetector.live/profile/detector=Detector(api_key)# it creates a new column in the input file and saves the results in this column# it saves into the input file by defaultdetector.query_by_file("input.csv")# also you can set an output filename and save the results in a new filedetector.query_by_file("input.csv",output_file="output.csv")# to query the urls inside a file, multithreading is used to speed up the process# by default, max_workers is set to 10, but you can change itdetector.query_by_file("input.csv",output_file="output.csv",max_workers=20)Multiple URL Query by Listfromphishing_detectorimportDetector# while initializing the detector, you should pass your api_key as a parameter# if you don't have an api_key, you can get one from your profile page:# http://phishingdetector.live/profile/detector=Detector(api_key)url_list=["https://www.google.com","https://www.facebook.com"]# it creates the output file and saves the results in this filedetector.query_by_list(url_list,output_file="output.csv")# to query the urls inside a list, multithreading is used to speed up the process# by default, max_workers is set to 10, but you can change itdetector.query_by_list(url_list,output_file="output.csv",max_workers=20)RequirementsIn order to work this library properly, following libraries must be installed on your computer:requestsvalidatorspandas
Package: phishing-tracker
Phishing TrackerUtility to manage sets of phishing links making it easier to track their removal progress over time.Project started out of frustration in dealing over-and-over again with phishing threat-actors and wanting an easy tool
to handle the tracking of these links over time without needing to roll out a full-fledged CERT stack (eg The Hive)Captures everything per-run in a single JSON file making it easy to compare and track change over time - and integrate
with other tooling if desired.See examples to get a clear idea on usage and possibilities.FeaturesBatch mode with.ymlconfiguration fileSingle shot mode by passing link/hostname/domain in at cliCollects useful reference-information and artifacts per phish link stored in an easy reference json fileCreate rules to define expected (or desired) analyzers output responsesEasy to re-run and hence re-compare the latest status of phish-links over timeDebug mode output to STDERRAnalyzersdigdig-domain - determine domain relative to TLD and collect A, CNAME, NS, MX, TXT recordsdig-hostname - collect hostname A, AAAA, CNAME, NS, MX, TXT recordshttphttp-get - perform http (clear-text) GET request capturing request/response headers and response contenthttpshttps-get - as per http-get using HTTPShttps_certificatehttps-certificate - obtain the https SSL certificate and parse certificate attributessmtpsmtp-headers - connect to hostname/domain MX records and capture the server headersafe_browsingsafe-browsing - query the Google safe-browsing API -https://developers.google.com/safe-browsing/v4whoiswhois - perform a whois and parse associated attributesAnalyzers - TodoVirustotal lookup -https://developers.virustotal.com/reference#url-scanInstallvia PyPipip3installphishing-trackervia Sourcegitclonehttps://github.com/ndejong/phishing-trackercdphishing-tracker
python3-mvenvvenvsourcevenv/bin/activate
pip3install-rrequirements.txt
python3setup.pyclean
python3setup.pytestpython3setup.pyinstallProjectgithub.com/ndejong/phishing-trackerAnalyzer Response Reportsdns_domainname_a_record
dns_domainname_cname_record
dns_domainname_mx_record
dns_domainname_ns_record
dns_domainname_txt_record
dns_domainname_unknown_tld
dns_hostname_aaaa_record
dns_hostname_a_record
dns_hostname_cname_record
dns_hostname_eq_dns_domainname
dns_hostname_mx_record
dns_hostname_ns_record
dns_hostname_txt_record
http_exception
http_hostname_<statuscode>_response
https_certificate_exception
https_certificate_hostname_mismatch
https_exception
https_hostname_<statuscode>_response
safe_browsing_exception
safe_browsing_record
smtp_domainname_active
smtp_exception
smtp_hostname_active
whois_domainname_record
whois_exceptionGoogle Safe Browsing API keyIn order to make use of the Google Safe Browsing API lookup, the environment variableGCP_API_KEYneeds to be
set with an appropriate GCP key that has access to the safe-browsing API -read more here.Examplesexamples01.ymlAuthorsNicholas de JongLicenseBSD-2-Clause - see LICENSE file for full details.
Package: phishme-intelligence
A library created by PhishMe Intelligence to support developing integregations with client security architecture.For more information on gaining access to PhishMe Intelligence data athttps://phishme.com/product-services/phishing-intelligenceIf you are already a customer, detailed documentation on the Intelligence API can be found athttps://www.threathq.com/documentation/display/MADThe download and/or use of this PhishMe application is subject to the terms and conditions set forth athttps://phishme.com/legal/integration-applications/.Copyright 2013-2017 PhishMe, Inc.  All rights reserved.This software is provided by PhishMe, Inc. (“PhishMe”) on an “as is” basis and any express or implied warranties,
including but not limited to the implied warranties of merchantability and fitness for a particular purpose, are
disclaimed in all aspects.  In no event will PhishMe be liable for any direct, indirect, special, incidental or
consequential damages relating to the use of this software, even if advised of the possibility of such damage. Use of
this software is pursuant to, and permitted only in accordance with, the agreement between you and PhishMe.Author: PhishMe Intelligence Solutions Engineering
Support:support@phishme.com
Package: phiskills.grpc
Phi Skills Generic gRPC API Server for PythonHomepagehttps://phiskills.comGitHubhttps://github.com/phiskillsOverviewThis project contains the Python module to create a genericgRPC API Server.Installationpipinstallphiskills.grpcCreating the serverfromphiskills.grpcimportApiapi=Api('My API')xxx.add_XxxServicer_to_server(XxxServicer(),api.server)api.start()For more details, seegRPC Basics - Python: Creating the server.
Package: phisuite.data
Phi Suite Data.pyHomepagehttps://phisuite.comGitHubhttps://github.com/phisuiteOverviewThis project contains the Python module to create theData APIserver & client.For more details, seePhi Suite Data.Installationpipinstallphisuite.dataCreating the serverfromphisuiteimportdataclassEventAPIServicer(data.EventAPIServicer):defPublish(self,request,context):...server=grpc.server(futures.ThreadPoolExecutor(max_workers=10))data.add_EventAPIServicer_to_server(EventAPIServicer(),server)server.add_insecure_port('[::]:50051')server.start()For more details, seegRPC Basics - Python: Creating the server.Creating the clientfromphisuiteimportdatachannel=grpc.insecure_channel('localhost:50051')stub=data.EventAPIStub(channel)event=stub.Publish(event)For more details, seegRPC Basics - Python: Creating the client.
Package: phisuite.schema
Phi Suite Schema.pyHomepagehttps://phisuite.comGitHubhttps://github.com/phisuiteOverviewThis project contains the Python module to create theSchema APIserver & client.For more details, seePhi Suite Schema.Installationpipinstallphisuite.schemaCreating the serverfromphisuiteimportschemaclassEventAPIServicer(schema.EventAPIServicer):defGet(self,request,context):...server=grpc.server(futures.ThreadPoolExecutor(max_workers=10))schema.add_EventAPIServicer_to_server(EventAPIServicer(),server)server.add_insecure_port('[::]:50051')server.start()For more details, seegRPC Basics - Python: Creating the server.Creating the clientfromphisuiteimportschemachannel=grpc.insecure_channel('localhost:50051')stub=schema.EventAPIStub(channel)event=stub.Get(options)For more details, seegRPC Basics - Python: Creating the client.
Package: phix
author: Kit La ToucheOverviewMake writing your Sphinx docs a little easier.This is a command line tool to build and serve your Sphinx docs. Run
this from inside the directory where your Sphinx Makefile is, and it
will build your docs on any*.rstchange, and serve them athttp://localhost:8000.Options:-t,--type: the make subcommand to run, and the_buildsubdirectory to serve. Defaults todirhtml.-p,--port: the port to serve the docs on. Defaults to8000.-r,--root: the root directory of the Sphinx project to build
and serve. Defaults to..--help: Show the help.--version: Show the version.Installation / UsageTo install use pip:$ pip install phixOr clone the repo:$ git clone https://github.com/wlonk/phix.git
$ python setup.py installThen run it:$ phixContributingFork it, make a PR, and I’ll take a look!
Package: phizz
[![Build Status](https://travis-ci.org/moonso/phizz.svg)](https://travis-ci.org/moonso/phizz)# phizz #Tool to query HPO and OMIM## Installation ##```pip install phizz```or```$git clone https://github.com/moonso/phizz.git$cd phizz$python setup.py install```## Usage ##Using command line utility:```Usage: phizz query [OPTIONS]Query the hpo database.Print the result in csv format as default.Options:-c, --config PATH-h, --hpo_term TEXT     Specify a hpo term-m, --mim_term TEXT     Specify a omim id-o, --outfile FILENAME  Specify path to outfile-j, --to_json           If output should be in json format--help                  Show this message and exit.```so trying:```$ phizz query -m OMIM:615373#hpo_id	descriptionHP:0011675	ArrhythmiaHP:0001644	Dilated cardiomyopathyHP:0001653	Mitral regurgitationHP:0000006	Autosomal dominant inheritanceHP:0001711	Abnormality of the left ventricle```to json:```$ phizz query --hpo_term HP:0000002 --to_json[{"hpo_term": "HP:0000002", "description": "Abnormality of body height"}]```Importing in python:```In [1]: import phizzIn [2]: phizz.query_disease(['OMIM:615373'])Out[2]:[{'description': u'Arrhythmia', 'hpo_term': u'HP:0011675'},{'description': u'Dilated cardiomyopathy', 'hpo_term': u'HP:0001644'},{'description': u'Mitral regurgitation', 'hpo_term': u'HP:0001653'},{'description': u'Autosomal dominant inheritance', 'hpo_term': u'HP:0000006'},{'description': u'Abnormality of the left ventricle','hpo_term': u'HP:0001711'}]```
Package: phizz-genes
# phizz-genes #A small django app to represent genes, transcripts, omim phenotypes, aliases etc## Instructions ##- Add phizz-genes to your INSTALLED_APPS settings like:```pythonINSTALLED_APPS = [...'genes',]```- Run `python manage.py migrate` to create the models## Models ##```pythonclass Gene(models.Model):#The ensembl gene id, ex. 'ENSG00000156110'#can be use with link like:#ensembl.org/Homo_sapiens/Gene/Summary?g=ENSG00000156110ensembl_id = models.CharField(max_length=20)chrom = models.CharField(max_length=30)start = models.IntegerField()stop = models.IntegerField()#The hgnc symbol, ex. 'ADKhgnc_symbol = models.CharField(max_length=20, blank=True)description = models.CharField(max_length=200, null=True)#The hgnc id, ex. '257' for using link like:#genenames.org/cgi-bin/gene_symbol_report?hgnc_id=HGNC:257hgnc_id = models.IntegerField(null=True)#entrez id, ex. 132, for using link like:#ncbi.nlm.nih.gov/gene/132entrez_id = models.IntegerField(null=True)#vega id, ex. OTTHUMG00000018506, for using link like:#http://vega.sanger.ac.uk/Homo_sapiens/Gene/Summary?db=core;g=OTTHUMG00000018506vega_id = models.CharField(max_length=20, null=True)#ucsc id, ex. uc001jwi.4, for using link like:#http://genome.cse.ucsc.edu/cgi-bin/hgGene?org=Human&hgg_chrom=none&hgg_type=knownGene&hgg_gene=uc001jwi.4ucsc_id = models.CharField(max_length=20, null=True)#pli_score is the estimated sensibility to lof mutations estimated by ExACpli_score = models.DecimalField(max_digits=6, decimal_places=5, null=True)def __str__(self):return self.hgnc_symbol#One gene can have several transcripts, one transcript are attached to one geneclass Transcript(models.Model):gene = models.ForeignKey(Gene, on_delete=models.CASCADE)refseq_name = models.CharField(max_length=30, null=True)ensembl_transcript_id = models.CharField(max_length=30)def __str__(self):return self.refseq_name#One phenotype can have several transcripts, one transcript are attached to one geneclass Omim(models.Model):gene = models.ForeignKey(Gene, on_delete=models.CASCADE)omim_id = models.IntegerField()class Alias(models.Model):gene = models.ForeignKey(Gene, on_delete=models.CASCADE)alias = models.CharField(max_length=20)class UniProt(models.Model):gene = models.ForeignKey(Gene, on_delete=models.CASCADE)uniprot_id = models.CharField(max_length=20)```
Package: phjob-scraper
job-scraperJob Scraper for jobs from the Philippines from various job posting websites as a python library.Installpython3-mpipinstallphjob-scraperAvailable websitesJorafromjob_scraperimportJorasrc=Jora()results=src.search("quality assurance",location="manila")foriinresults:print(i["title"])@tbdsux | © 2023
Package: phkit
phkitphoneme toolkit: 拼音相关的文本处理工具箱，中文和英文的语音合成前端文本解决方案。安装pip install -U phkit版本v0.2.11pinyinkit文本转拼音的模块，依赖python-pinyin，jieba，phrase-pinyin-data模块。chinese适用于中文、英文和中英混合的音素，其中汉字拼音采用清华大学的音素，英文字符分字母和英文。中文音素简介：声母：
aa b c ch d ee f g h ii j k l m n oo p q r s sh t uu vv x z zh

韵母：
a ai an ang ao e ei en eng er i ia ian iang iao ie in ing iong iu ix iy iz o ong ou u ua uai uan uang ueng ui un uo v van ve vn ng uong

声调：
1 2 3 4 5

字母：
Aa Bb Cc Dd Ee Ff Gg Hh Ii Jj Kk Ll Mm Nn Oo Pp Qq Rr Ss Tt Uu Vv Ww Xx Yy Zz

英文：
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

标点：
! ? . , ; : " # ( )
注：!=!！|?=?？|.=.。|,=,，、|;=;；|:=:：|"="＂“”'＇‘’|#=# 　	|(=(（[［{｛【<《|)=)）]］}｝】>》

预留：
w y 0 6 7 8 9
注：w=%|y=$|0=0|6=6|7=7|8=8|9=9

其他：
_ ~  - *symbol音素标记。
中文音素，简单英文音素，简单中文音素。sequence转为序列的方法，文本转为音素列表，文本转为ID列表。拼音变调，拼音转音素。pinyin转为拼音的方法，汉字转拼音，分离声调。拼音为字母+数字形式，例如pin1。phoneme音素映射表。不带声调拼音转为音素，声调转音素，英文字母转音素，标点转音素。number数字读法。按数值大小读，一个一个数字读。convert文本转换。全角半角转换，简体繁体转换。style拼音格式转换。国标样式的拼音和字母数字的样式的拼音相互转换。englishfromhttps://github.com/keithito/tacotron"
Cleaners are transformations that run over the input text at both training and eval time.Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
hyperparameter. Some cleaners are English-specific. You'll typically want to use:"english_cleaners" for English text"transliteration_cleaners" for non-English text that can be transliterated to ASCII using
the Unidecode library (https://pypi.python.org/pypi/Unidecode)"basic_cleaners" if you do not want to transliterate (in this case, you should also update
the symbols in symbols.py to match your data).历史版本v0.2.10ttskit适配的音素工具。