Saravanan666/pypi-org huggingface dataset:
Package: sipvicious
Welcome to SIPVicious OSS security toolsSIPVicious OSS is a set of security tools that can be used to audit SIP based VoIP systems. Specifically, it allows you to find SIP servers, enumerate SIP extensions and finally, crack their password.To get started read the following:Getting started on the WikiCommunication Breakdown blog:Attacking a real VoIP System with SIPVicious OSS.For usage help make use of-hor--helpswitch.A note to vendors and service providersIf you are looking for a professional grade toolset to test your RTC systems, please considerSIPVicious PRO.The toolsThe SIPVicious OSS toolset consists of the following tools:svmapsvwarsvcracksvreportsvcrashsvmapthis is a sip scanner. When launched against
ranges of ip address space, it will identify any SIP servers 
which it finds on the way. Also has the option to scan hosts 
on ranges of ports.

Usage: <https://github.com/EnableSecurity/sipvicious/wiki/SVMap-Usage>svwaridentifies working extension lines on a PBX. A working 
extension is one that can be registered. 
Also tells you if the extension line requires authentication or not. 

Usage: <https://github.com/EnableSecurity/sipvicious/wiki/SVWar-Usage>svcracka password cracker making use of digest authentication. 
It is able to crack passwords on both registrar servers and proxy 
servers. Current cracking modes are either numeric ranges or
words from dictionary files.

Usage: <https://github.com/EnableSecurity/sipvicious/wiki/SVCrack-Usage>svreportable to manage sessions created by the rest of the tools
and export to pdf, xml, csv and plain text.

Usage: <https://github.com/EnableSecurity/sipvicious/wiki/SVReport-Usage>svcrashresponds to svwar and svcrack SIP messages with a message that
causes old versions to crash. 

Usage: <https://github.com/EnableSecurity/sipvicious/wiki/SVCrash-FAQ>InstallationPlease refer to theinstallation documentation.Further informationCheck out thewikifor documentation.
Package: sipxmldevices
Python Module For Fast and easy XML creation for SIP Devices-------------------------------------Now we support only Aastra SIP DevicesWork with- All Aastra SIP Phones of 67xxi serie ( 6730i, 6731i, 6735i, 6737i, 6753i, 6755i, 6757i, 6739i )Support- All XML Root commands ( latest firmware release 3.2.2 )- Support ISO-8859-1 and UTF-8This version requires Python 2 or later;
Package: sipy
SIpySIpy is a fast, lightweight and easily extensible python package for manipulating
physical quantities.For more detailed information read thedocumentation.QuickstartSIpy can be installed viapipenvorpip, and requires Python 3.6.0 or higher.$pipenvinstallsipy$pipinstallsipyOnce SIpy is installed just import the quantities you need and you’re good to go>>>fromsipyimportmiles,hour>>>speed_limit=70*miles/hour>>>print(speed_limit)3.13E+01ms^-1ContributingSIpy is developed onGitLab. If you come across an issue,
or have a feature request please open anissue.  If you want to
contribute a fix or feature-implementation please do by proposing amerge request.TestingSIpy usesPytestfor unit testing and
andpre-commitfor static analysis and auto-formatting.
Code is automatically checked by Gitlab pipelines when pushed but it is
recommended that tests are also run locally.SIpy usedPoetryfor managing all external dependencies.
InstallPoetryusing the instructionshereand then
install dependencies with$poetryinstallpre-commitshould run automatically on every commit. To enable it run$poetryrunpre-commitinstallThe unittests can be run with:$poetryrunpytest--doctest-modulestestssipyREADME.rstHelpThe SIpydocumentationis the best place to start, after that try searching stack overflow,
if you still can’t find an answer pleaseopen an issue.
Package: sipyconfig
SportIdent Config+ ImplementationA python implementation of the functionality of SPORTident Config+.Currently only working and tested under Linux.Note that you might need to add your user to a group that has access to the systems serial interfaces.Installinstall via pip:pip install --upgrade sipyconfigUsageCreate aSiUSBStationobject using:from sipyconfig import SiUSBStation

si = SiUSBStation()
si.trigger_feedback()have fun :)API docsa part of the api is documented inApi.md
Package: sipzamine
Command line SIP dialog matching and searching through offline PCAPs.Installing$sudoapt-getinstallpython-libpcap# or yum install..$sudopipinstallsipzamineExampleA basic example, finding all dialogs that last shorter than 1.5 seconds:$sipzamine-m^BYE-H^BYE--maxdur1.5--pcap'host 22.22.22.22'stored.pcap[ 179978155f707e3622c0886752336210@22.22.22.22 ]
2011-11-23 22:27:20.746782 22.22.22.22:5060 > 123.123.123.123:5060 102 INVITE
2011-11-23 22:27:20.747508 123.123.123.123:5060 > 22.22.22.22:5060 102 INVITE(100)
2011-11-23 22:27:20.783424 123.123.123.123:5060 > 22.22.22.22:5060 102 INVITE(200)
2011-11-23 22:27:20.783956 22.22.22.22:5060 > 123.123.123.123:5060 102 ACK
2011-11-23 22:27:21.665581 22.22.22.22:5060 > 123.123.123.123:5060 103 BYE <--
2011-11-23 22:27:21.665721 123.123.123.123:5060 > 22.22.22.22:5060 103 BYE(200)Command optionsNormally you use-mto match a dialog by regular expression. And-pto filter by IP.To highlight a particular text string in the concise output, use-H.Basic matching options:--pcap filter, -p filter
    pcap filter expression
--pmatch regex, -m regex
    any packet in dialog must match regex (can be used
    multiple times), e.g. ^INVITE to match calls
--amatch regex, -M regex
    all packets in dialog must match regex (can be used
    multiple times), e.g. ^(SIP/2.0|INVITE|BYE) to match
    calls without an ACKOutput options:--contents
    show complete packet contents
--dateskew seconds
    offset added to all dates, can be negative (use when
    pcap clock was off)
--highlight regex, -H regex
    highlight first matchgroup in packets (multiple
    highlights are identified by letters a..z)Special dialog/packet matching options:--mindate date
    packets must be younger than specified date
--maxdate date
    packets must be older than specified date
--mindur seconds
    dialogs/transactions must be shorter than duration
--maxdur seconds
    dialogs/transactions must be longer than duration
--retransmits count
    at least count retransmits must be involvedTODOAdd tests: begin with a smallish pcap.Add the ability to write pcaps from the filter. Combine capability
with sipscrub?Compare this to sipgrep (and other tools?). And homer?Q & AHow do I getpcapfiles?You’re encouraged to always write SIP pcaps on your VoIP machine.tcpdumpallows you easy rotation of pcaps so you won’t run out of disk space.
You can use thetcpdump247init script if you like.
Package: siquant
siquantis a simple pure python 3 library to make dimensional analysis painless.Getting StartedDimensional Analysis>>>fromsiquant.systemsimportsi>>>force=100*si.kilonewtons>>>moment_arm=50*si.meters>>>torque=force*moment_arm>>>torque.quantity5000>>>str(torque.units)'1000*kg**1*m**2*s**-2'>>>torque.get_as(si.newtons*si.meters)5000000.0>>>torque.get_as(si.newtons)Traceback (most recent call last):...siquant.exceptions.UnitMismatchError:...>>>torque=torque.cvt_to(si.newtons*si.meters)>>>torque.quantity5000000.0>>>str(torque.units)'1*kg**1*m**2*s**-2'Validation>>>fromsiquant.dimensionsimportforce,area,stress>>>fromsiquant.systemsimportsi>>>defnormal_stress(force_q,area_q):...assertforce_q.is_of(force)...assertarea_q.is_of(area)...returnforce_q/area_q>>>stress_q=normal_stress(1*si.newtons,1*si.meters**2)>>>stress_q.is_of(stress)True>>>stress_q.is_of(area)FalseSometimes you might want to check for dimensions that aren’t provided by default.>>>fromsiquant.dimensionsimportSIDimensions>>>fromsiquant.systemsimportsi>>>new_dim=SIDimensions(kg=1,m=1,s=1,k=1,a=1,mol=1,cd=1)>>>dist_q=1*si.meters>>>dist_q.is_of(new_dim)FalseNormalization>>>fromsiquantimportScalarQuantity>>>fromsiquant.systemsimportsi>>>meters_cvt=ScalarQuantity.As(si.meters)>>>dist_q=meters_cvt(1000*si.millimeters)>>>dist_q.quantity1>>>dist_q=meters_cvt(1000*si.meters)>>>dist_q.quantity1000>>>dist_q=meters_cvt(1000)>>>dist_q.quantity1000New UnitsSIUnit can be created directly by factory:>>>fromsiquant.unitsimportSIUnit>>>fathom=SIUnit.Unit(1.8288,m=1)SIUnit(1.8288, (0, 1, 0, 0, 0, 0, 0))Alternatively they can be derived:>>>fromsiquant.systemsimportsi>>>rpm=si.unity/si.minutes>>>rpmSIUnit(0.016667, (0, 0, -1, 0, 0, 0, 0))
Package: siqueries
=======SiQueries=======SiQueries utilities for providing read-only user local database access.Version 1.0.8Introduction------------This util permits SiQueries customers to provide database access byopening an SSH reverse tunnel from a SiQueries server to the customerdatabase.Errors, comments, questions may be sent to support[at]siqueries[dot]com.Requirements------------Requires a read-only database role (or authorization to create one)and a local SSH client.Supported Databases-------------------MySQLPostgreSQLInstallation------------To install, type::$ python setup.py installTo uninstall, remove the filessiqueries_installsiqueries_connectTroubleshooting-------------If you encounter an error while running siqueries_install, the file/tmp/siqueries_error_log.htmlmay contain details on what went wrong. In any event, please feel freeto contact support.Documentation-------------Further documentation may be found at http://siqueries.com/Package Contents----------------siqueries_installThe configuration wizardsiqueries_connectA script to keep the SSH tunnel aliveChanges--------Package fixed siqueries_install
Package: sirad
Secure Infrastructure for Research with Administrative Data (SIRAD)siradis an integration framework for data from administrative systems. It
deidentifies administrative data by removing and replacing personally
identifiable information (PII) with a global anonymized identifier, allowing
researchers to securely join data on an individual from multiple tables without
knowing the individual's identity. It is developed byResearch Improving People's Lives (RIPL).For a worked example and further details, please seesirad-example.To learn more about the motivation for creating this package and its potential
uses, please see our article inCommunications of the ACM:J.S. Hastings, M. Howison, T. Lawless, J. Ucles, P. White. (2019).
Unlocking Data to Improve Public Policy.Communications of the ACM62(10): 48-53.
doi:10.1145/3335150InstallationRequires Python 3.7 or later.To install from PyPI usingpip:pip install siradTo install usingAnaconda Python:conda install -c ripl-org siradTo install adevelopment versionfrom the current directory:pip install -e .RunningThere is a single command line script included,sirad.siradsupports the following arguments:process- split raw data files into data and PII filesresearch- create a versioned set of research files with a unique
anonymous identifierConfigurationTo set configuration options, create a file calledsirad_config.pyand place
either in the directory where you are executing thesiradcommand or
somewhere else on your Python path. See_optionsinconfig.pyfor a
complete list of possible options and default values.The following options are available:DATA_SALT: secret salt used for hashing data values. This shouldn't be
shared. A warning will be outputted if it is not set. Defaults to None.PII_SALT: secret salt used for hashing pii values. This shouldn't be
shared. A warning will be issued if it is not set. Defaults to None.LAYOUTS: directory that contains layout files. Defaults tolayouts/.RAW_DIR,DATA_DIR,PII_DIR,LINK_DIR,RESEARCH_DIR: paths to where
the original data, the processed files, and the research files will be saved.VERSION: the current version number of the processed and research files.Layout filessiraduses YAML files to define the layout, or structure, of raw data files.
These YAML files define each column in the incoming data and how it should be
processed. More documentation to come on this YAML format.The following file formats are supported:csv - change delimiter with delimiter optionfixed withxlsx (xls not currently supported)DevelopmentSample test data is randomly generated usingFaker; none of the information identifies
real individuals.tax.txt - sample tax return data. Includes first, last, DOB and SSN.credit_scores.txt - sample credit score information. Includes first, last and
DOB but no SSN.Run unit tests as:python -m unittest discoversiradcan also be used as an API from custom Python code. Documentation to come.AuthorsMark HowisonTed LawlessJohn UclesPreston White
Package: sirataxi
แพ็คเกจนี้ใช้สำหรับโชว์รูปศิลปะ ascii ซึ่งได้ผลงานมาจากสมาชิกเพจ
AIBuilders ช่วยกันเขียนขึ้นมาวิธีติดตั้งเปิด CMD / Terminalpipinstallaibuildersartวิธีใช้งานfromaibuildersartimport*show=UncleEngineer()show.art()print("Author:{}".format(show.name))
Package: sir-bot-a-lot
An asynchronous python bot framework.The uses of bots are nearly endless and come in all shapes and sizes.
They can handle Slack shenanigans, monitor the status of a crypto-currency,
or become your personal assistant. Sir-bot-a-lot can help you get started
writing your own.Sir-bot-a-lot is a project maintained by thepyslackerscommunity.
Want to join?Get an invite!Documentation availablehere.
Package: sirbot.plugins
Collection of various plugins forSir Bot-a-lot.The uses of bots are nearly endless and come in all shapes and sizes.
They can handle Slack shenanigans, monitor the status of a crypto-currency,
or become your personal assistant. Sir Bot-a-lot can help you get started
writing your own.Sir Bot-a-lot and sirbot-plugins are projects maintained by thepyslackerscommunity. Want to join?Get an invite!
Package: sirbot.slack
Sirbot-slack is a slack plugin forSir Bot-a-lot. It aims to provide full
support for the slack API (Web, Events and RTM).The uses of bots are nearly endless and come in all shapes and sizes. They can
handle Slack shenanigans, monitor the status of a crypto-currency, or become
your personal assistant. Sir-bot-a-lot can help you get started writing your
own.Sir-bot-a-lot and sirbot-slack are projects maintained by thepyslackerscommunity. Want to join?Get an invite!Documentation availablehere.
Package: sir-Bychko-serializer
Ne prividi gospod' vi polezete v ety biblioteku. Ono vam ne nadoDesine sperare qui hic intrasLasciate ogne speranza, voi ch’entrateAbandon hope, all ye who enter hereLasst alle Hoffnung fahren, die ihr hier eintretetOh, los que entrais, dejad toda esperanzaОставь надежду, всяк сюда входящий
Package: sire
siresireis a command that generates Python 3.7 project templates, with git, travis, mypy (etc.) support.Version 1.0.4Install sirepipinstallsire#orgitclonehttps://github.com/interrogator/sire&&cdsire&&python.setup.pyinstallUsagesire--mkdocs--virtualenv--git--exclude=mypy<project_name>Alternative usages (not recommended)As Python module:python-msire.siremkdocsvirtualenv<project_name>Or from inside Python (why?):fromsireimportsiresire('project_name',mkdocs=True,virtualenv=True,git=True)What gets generatedPure Python:<project_name>/<project_name>.py<project_name>/__init__.pysetup.pyrequirements.txt(withblack,isort,flake8etc)tests/tests.pyOptional extras:mkdocs (.readthedocs.yaml,./docs,.mkdocs.yml)irtualenv (with dependencies installed)git (.git,.gitignore,.pre-commit-config.yaml)Each of these has an associated flag:sire-v/--virtualenv-m/--mkdocs-g/--gitprojnameOther files.coveragerc.travis.ymlpublish.sh(a script for running tests and authoring a new version)mypy.iniMIT LicenseEmptyCHANGELOG.bumpversion.cfgIf you want to skip any of these files, use the--excludeoption with comma separation:sire--exclude=travis,setup.py,mypyprojnameTriviasireactually generated itself.ContributingI don't really expect many other people to want this, because it's mostly tailored to my specific ideas about how a Pthon project should look. That said, if you do find this projet useful, you are more than welcome to submit pull/feature requests!There are dozens of possible new features that could be added, which I'd personally quite like:a--licenseoption, to choose the correct license fileSetting git remote automatically (get github username from git global config?)Deleting irrelevant strings --- if nocodecoverage, remove the associated badge for exampleProbably more code could be automatically generated and added for the main and test.pyfilesWhile I'd love to have these insire, coding them will take me longer than doing it manually a few times. So, unless this repo somehow becomes popular or finds some new contributors, don't expect any of this stuff to get done in a hurry, unless you add it yourself.
Package: sireader
Sireader is a python module to communicate with a SportIdent main station to
read out SportIdent cards. SportIdent is an electronic punching system mainly
used for orienteering events.Sireader supports two major operation modes. It can be used for complete card
readout or in control station mode to send punches from a control. The first mode
is typically used for card readout after the finish line to read the card data
into an event software. The second mode is used to get live result from an
intermediate control.Website:http://bosco.durcheinandertal.ch/GIT Repository:https://github.com/gaudenz/sireader/UsageThere are 3 classes in the sireader module.SIReaderis the base class
containing common functions. It’s imported to have easy access to it’s
constants.SIReaderReadoutimplements classical card readout.SIReaderControlimplements a station configured as control which
continuously sends punches.First import the relevant classes:from sireader import SIReader, SIReaderReadout, SIReaderControlSIReader only supports the so called “Extended Protocol” mode. If your
base station is not in this mode you have to change the protocol mode
first:# change to extended protocol mode
si.set_extended_protocol()To use a SportIdent base station for card readout:from time import sleep

# connect to base station, the station is automatically detected,
# if this does not work, give the path to the port as an argument
# see the pyserial documentation for further information.
si = SIReaderReadout()

# wait for a card to be inserted into the reader
while not si.poll_sicard():
    sleep(1)

# some properties are now set
card_number = si.sicard
card_type = si.cardtype

# read out card data
card_data = si.read_sicard()

# beep
si.ack_sicard()To use a base station as a control sending punches:# configure station
si.set_operating_mode(SIReader.M_CONTROL)
si.set_station_code(99)
si.set_autosend()

# connect to station
si = SIReaderControl()

# poll for new punches
punches = si.poll_punch()

# reset station configuration
si.set_operating_mode(SIReader.M_READOUT)
si.set_autosend(False)Finally set the station back to basic protocol:# change back to basic protocl
si.set_extended_protocol(False)API DocumentationComplete documentation is contained in the module source code and can
be read online at:http://bosco.durcheinandertal.ch/epydoc-sireader/This documentation is autogenerated from the source code and
represents the version in the GIT repository.
Package: sirene
CO2e Emission Coefficients for the Brazilian EconomyTheSirenepackage is crafted to provide CO2e emissions data for various Brazilian economic activities. This package facilitates the estimation of direct emission coefficients for each sector, representing the volume of emissions in Gg relative to the production volume (expressed in aggregate value in millions of reais).Beyond direct coefficients, it also computes the indirect emission coefficients. The estimation methodology is adopted from Luis Masa's paper, titled"AN ESTIMATION OF THE CARBON FOOTPRINT IN SPANISH CREDIT INSTITUTIONS’ BUSINESS LENDING PORTFOLIO".TheSirenepackage contains a series of variables that detail emissions from various sectors and other related data. The available variables are:atividade_tru68_ibge: Refers to activity (i) of TRU68.production_values_mi_brl: Represents the total production of activity (i) for the year (t) in millions of BRL.ano: Reference year (complete data available only between 2012 and 2020).energia_Gg_CO2e_GWP_SAR: Emissions of CO2e from the energy sector in Gg, calculated using the CO2e_GWP_SAR methodology.residuo_Gg_CO2e_GWP_SAR: Emissions of CO2e from the waste sector in Gg.agropecuaria_Gg_CO2e_GWP_SAR: Emissions of CO2e from the agricultural sector in Gg.ippu_Gg_CO2e_GWP_SAR: Emissions of CO2e from the IPPU sector in Gg.lulucf_Gg_CO2e_GWP_SAR: Emissions of CO2e from the LULUCF sector in Gg.total_Gg_CO2e_GWP_SAR: Total CO2e emissions in Gg.active_loan_portfolio_mi_brl: Value of loans by sector in millions of BRL.q_direct: Coefficient of direct emissions.q_total: Coefficient of total emissions.q_indirect: Coefficient of indirect emissions.Instalation!pipinstallsirenefromsireneimportsrnassrncoef67_t=srn.coef('2019',lulucf=False).resultReading the Raw Emission Data (MCTI/SIRENE)Emission data is available for 3 different gases ('CO2', 'CH4', 'N2O'). If preferred, it is also possible to consult equivalent emissions ('CO2e_GWP_SAR', 'CO2e_GWP_AR5', 'CO2e_GTP_AR5'). The available sectors are: 'agropecuaria', 'energia', 'ippu', 'lulucf', 'residuos' and 'total-brasil-1'.res_m=srn.read('residuos','CO2')Main Function: coef()Thecoef()function is the core of this package and returns all of the above-listed variables. The arguments it accepts are:ano: String representing the desired year, with values between 2012 and 2020.household: Boolean (True or False) determining whether households should be considered when calculating emissions and coefficients.emission: Defines which type of emission will be considered when constructing the emission coefficients. Available options are: 'total', 'total_no_lulucf', 'lulucf', 'ippu', 'residuo', and 'agropecuaria'.Usage Example:result_t=srn.coef('2019',emission='lulucf',household=False).result
Package: siren-torch
Sinusoidal Representation Networks (SIREN)Unofficial PyTorch implementation of Sinusodial Representation networks (SIREN) from the paperImplicit Neural Representations with Periodic Activation Functions. This repository is a PyTorch port ofthisexcellent TF 2.0 implementation of the same.SetupInstall using pip$ pip install siren-torchUsageSine activationYou can use theSineactivation as any other activationfromsirenimportSinex=torch.rand(10)y=Sine(w0=1)(x)InitializationThe authors in the paper propose a principled way of intializing the layers for the SIREN model. The initialization function
can be used as any other initialization present intorch.nn.init.fromsiren.initimportsiren_uniform_w=torch.empty(3,5)siren_uniform_(w,mode='fan_in',c=6)SIREN modelThe SIREN model used in the paper, with sine activation and custom initialization, can directly be created as follows.fromsirenimportSIREN# defining the modellayers=[256,256,256,256,256]in_features=2out_features=3initializer='siren'w0=1.0w0_initial=30.0c=6model=SIREN(layers,in_features,out_features,w0,w0_initial,initializer=initializer,c=c)# defining the inputx=torch.rand(10,2)# forward passy=model(x)Results on Image Inpainting taskA partial implementation of the image inpainting task is available as thetrain_inpainting_siren.pyandeval_inpainting_siren.pyscripts.To run training:$pythonscripts/train_inpainting_siren.pyTo run evaluation:$pythonscripts/eval_inpainting_siren.pyWeight files are made available in the repository under thecheckpointsdirectory. It generates the following output after 5000 epochs of training with batch size 8192 while using only 10% of the available pixels in the image during training phase.TestsTests are written usingunittest. You can run any script under thetestsfolder.ContributingAs mentioned at the beginning, this codebase is a PyTorch port ofthis. So, I might have missed a few details mentioned in the original paper. Assuming that the implemention in the linked repo is correct, one can safely trust this implementation as well. The only major difference from the reference repo is that it hasw0as part of the initialization as well. I did not see that in the paper and hence, didn't include it here. I have not deeply read the paper and this is simply to serve as a starting point for anyone looking for the implementation. Please feel free to make a PR or create an issue if you find a bug or you want to contribute to improve any other aspect of the codebase.