Saravanan666/pypi-org huggingface dataset:
Package: scylla-http
ScyllaScyla downloads files in parallel.It is aimed at speeding up concurrent downloads, not at being as fast as possible per download.There are probably a bunch of tools out there that are faster, as that is not scylas goal.The reason scylla exists is because I had to repeatedly download a bunch of files and it took a while withwget.It can be used from the command line or as importable module.From the commandline it is quite easy to use:kazaamjt@workstation:~$scylla-furl_list-oartifacts/Alternativly you can import the module from in a script.CLI OptionsAs mentioned, the CLI is quite simple, it does not have many options:kazaamjt@workstation:~$scylla--help
Usage:scylla[OPTIONS]Options:-f,--fileTEXTPathtoafilecontainingurls.-o,--output-dirTEXTDirectorytostoretheretrievedfiles.-s,--max-concurrentINTEGERMaximumnumberofsimultaniousfilestodownload.Settingthisto0willmakescyllatrytodownloadallthefilesatonce.--helpShowthismessageandexit.Using as a moduleUsing as a module is also not very difficult.Do note that the module usesasync, so it does have some gotchas.Also note that the module is fully typed, hopefully making its usage easier.To use it simply import the module and instantiate theDownloaderclass:importasynciofrompathlibimportPathimportscyllaurls=["https://www.kernel.org/pub/linux/kernel/v5.x/linux-5.10.17.tar.xz","https://example.com/",]asyncdefmain()->None:downloader=Downloader(urls,Path("."))awaitdownloader.start()if__name__=="__main__":asyncio.run(main())The most important gotcha here is making sure thedownloaderclass is instantiated in
the same event-loop asDownloader.startis called from.We do this here by wrapping them in a singleasyncfunction.And that's it really.The class has a couple more init parameters that are more for advanced usage:- max_concurrent: int = 5  
  Same as the CLI, this changes the maximum number of downloads that run simultaniously.  
- chunk_report_cb: Optional[ChunkReportCallback] = None  
  The function passed to this parameter will be called everytime a chunk was succesfully downloaded and saved.  
  Usefull for tracking download progress.  
- report_done_cb: Optional[Callable[[str], None]] = None  
  The function passed to this parameter will be called everytime a download is completed.  
  The parameter being passed back is the name of the file.
Package: scyrpt-studio-ip-scanner
ip-scannerPip package to scan IP address on local ip range.It scans all ip addresses on specified range and port/s and returns the list of live IP addresses.InstallationYou can install the IP Scanner from PyPI:python -m pip install scyrpt-studio-ip-scannerIP Scanner is supported on Python 3.8 and above.How to useThere are 2 ways to use this library -Start IP scanning from command line. To do that, simply run -ip_scanner <<First 3 parts of IP>> <<Ports (Can be multiple, separated by comma)>> <<Start IP Address>> <<End IP Address>>

Ex. - ip_scanner "192.168.1." "80" "5" "15" 
Will scan IP's from 192.168.1.5 to 192.168.1.15 on Port 80Import in your code and scan/trigger it via your code -from ip_scanner.ip_scanner import IPScanner

ipScanner = IPScanner(base_ip="192.168.1.", ports=(80, ), start_ip=5, end_ip=15)
ipScanner.start_scanning()It returns a list of live IP addresses found in the specified range
Package: scytale-cipher
ScytaleJust a very simple python script to calculate the scytale-cipher through an cli-wizard.The projects main purpose is to showcase interesting tooling to build, publish and develop python apps.Code StatusCode documentation:https://scytale.readthedocs.ioDescriptionThe scytale was used more than 2500 years ago by the Spartans, and is one example of ancient cryptography.
A message gets written on a ribbon which is then wrapped around a stick with a certain diameter (the scytale).Below is a sample encryption of the plain text "prove me wrong!" with a scytale of diameter 3.
We write the message around the scytale, and then|p|r|o|
 - - -
|v|e| |
 - - -
|m|e| |
 - - -
|w|r|o|
 - - -
|n|g|!|The cipher text is obtained by reading from top to bottom, left to right.
In this example, the cipher text ispvmwnreergo  o!SetupUsing NixTo follow this path at least Nix has to be installed (and flakes have to be enabled).nix developwill drop you into a shell containing everything to further hack on the project.
Inside the devShell invokingscytaleshould bring up a prompt.nix runwill run the default app of the flake file.nix buildwill build the default package with the help ofpoetry2nixdefault.nixis included to build the package the non-flake way withnix-build.shell.nixcontains instructions to provide a non-flake shell vianix-shell.Without NixAt least Poetry needs to be installed.poetry run scytalewill activate the poetry environment and execute the script held inpyproject.toml.
If errors are occurringpoetry install(installs the virtual environment and all given requirements)poetry shell(activates and enters the virtual environment)poetry run python -m unittest discover(runs all tests). Alternativelypoetry run python -m pytest teststo use pytest for test execution.
Package: scythe
Scythe, Selection of Conserved Transcript by Homology Evaluation, tries to find the best matching set of transcripts for each one-to-one orthologous gene from two or more species.Usage (GUI):scythe-gui.pyUsage (command line):######################################
   # scythe.py v0.1a1                   #
   ######################################
 usage:
    scythe.py -i DIR -g .grpFILE -d DELIMITER --cleanup

 usage with configuration file:
    scythe.py --config configuration.scy

 general options:
   -C, --config                     use configuration file instead of
                                    command line parameters
   -c, --cleanup                    remove temporary files when done
   -h, --help                       prints this
   -i, --in_dir=DIR                 folder w/ subfolders "fa" and "loc"

   -o, --out_dir=DIR                output directory [default:./]
   -N, --num_cores=NUM              number of processors to use [default 1]

algorithm options:
   -R, --sl_ref                     find best matches to reference
   -G, --sl_glob                    best scoring pair as seed
   -M, --mx_sum                     optimize sum of pairwise scores


 alignment options:
    -O, --gap_open=FLOAT           needleall gap opening cost [default 10]
    -E, --gap_extend=FLOAT         needleall gap extension cost

 fasta options:
   -d, --delim=STRING               split fasta headers at STRING
   -a, --asID=INT                   use INTth part of fasta header as transcript-ID
                                    (default:0)

 further help:
   Please see documentation.InstallationScythe needs Python 3. You might want to set up a virtual environment with Python 3 for easier package management.
Please see the documentation for more details.
(In your virtual environment) install Scythe viapip install scytheRequirementsPython modulesconfigparsermysql-connector-pythonpip install configparser
pip install --allow-external mysql-connector-python mysql-connector-pythonExternal programsneedleall (version 6.3.1; EMBOSS package,http://emboss.sourceforge.net/)
Package: scythe-cli
ScytheScythe is a TUI and set of CLI utilties for interacting with the Harvest Time tracking ApplicationInstallationInstallable via pip/pipx (pipx is recommended)pipx install scythe-cliSetupFirst, you need to authenticate Scythe to your harvest account.To do this, run the following command:scythe initThis will open a new browser tab to perform an OAuth flow with Harvest. Once you have authenticated, you will be redirected to a page with a code. Copy this code and paste it into the terminal.UsageTUIStart the TUI withscytheThe interface has the following features:View all timers for a given dayStart a new timerStop a running timerEdit a TimerDelete a TimerCLIThe CLI also has a few other utilties:scythe timer- The Scythe Timer namespace has some utilties for interacting with timers.scythe timer --helpfor more infoscythe projects- List all the projects and tasks that you have access toQuickstartingQuickstarting is a feature of Scythe that allows you to start a timer with a single command. This is useful for setting up a timer for a task that you do frequently.To create a new quickstart entry run:scythe quickstart add <name>This will create a new quickstart entry with the name<name>. It will prompt you with a list of projects and tasks to choose from (And optionally, a note & a command to execute after the timer start). Once you have completed the prompt, you can start the timer with:scythe quickstart <name>This will start a timer with the details you entered when creating the quickstart entry and will execute the command you entered (if any).`
Package: scythe-extractors
ScytheScythe is a library of tools that generate summaries of the data contained in scientific data files.
The goal of Scythe is to provide a shared resources of these tools ("extractors") to avoid duplication of effort between the many emerging materials databases.
Each extractor is designed to generate the sum of all data needed by each of these databases with a uniform API so that specific projects can write simple adaptors for their needs.InstallationInstall using an up-to-date version ofpipon version 3.8 or higher of Python:pipinstallscythe-extractorsEach specific extractor module has its own set of required libraries.
Given that some modules have extensive dependencies, we do not install all of them automatically.
You can install them either module-by-module using the pip "extras" installation (e.g.,pip install scythe-extractors[image]"),
or install all extractors withpip install scythe-extractors[all]".Development/ContributionIf you wish to develop new features using Scythe, please consult theContributor Guidethat will
walk you through installingPoetryand the Scythe dependencies.DocumentationComplete documentation for Scythe is onRead the Docs.List of Available ExtractorsSupportThis work was performed in partnership withCitrine Informatics.
This was also performed under financial assistance award 70NANB14H012 from U.S. Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Material Design (CHiMaD).
This work was also supported by the National Science Foundation as part of the Midwest Big Data Hub under NSF Award Number: 1636950 "BD Spokes: SPOKE: MIDWEST: Collaborative: Integrative Materials Design (IMaD): Leverage, Innovate, and Disseminate".
Package: scythe-game
# Scythe[![Build Status](https://img.shields.io/travis/chucksmash/scythe.game.svg)](https://travis-ci.org/chucksmash/scythe-game)
[![Coverage](https://img.shields.io/coveralls/chucksmash/scythe-game.svg)](https://coveralls.io/r/chucksmash/scythe-game)
[![PyPi Version](https://img.shields.io/pypi/v/scythe-game.svg)](https://pypi.python.org/pypi/scythe-game)
[![Python Versions](https://img.shields.io/pypi/pyversions/scythe-game.svg)](https://pypi.python.org/pypi/scythe-game/)
[![Daily Downloads](https://img.shields.io/pypi/dd/scythe-game.svg)](https://pypi.python.org/pypi/scythe-game/)Modeling the board gameScytheand creating agents to play it.
Package: sczpy
Azure Percept Secured AI Model Management Python SDKThe Python SDK is designed to be used in Jupyter Notebooks, AI module containers as well as stand-alone Python programs.
When working on a compatible device, it verifies hardware root of rust through Trusted Platform Module (TPM) attached to the device and uses Azure Attestation service to ensure the hardware and software on the device is not tempered. Then, it authenticates with the Azure Percept backend server with verified device identity and retrieves encrypted AI models or version-specific encryption keys from the server.InstallationBefore the sczpy Python package is official published, you can run the following commaned to install from a local .whl file (see building instructions below):pipinstall<pathtosczpy.whlfile>Once the package is published, you should be able to install the package by:pipinstallsczpyUsageWhen used outside a device context (such as in Jupyter Notebook or a regular Python program), the SDK usesAzure Service Principalto authenticate with the Azure Percept server.To setup authentication with Azure Service Principal, define the following environment variables:AZURE_CLIENT_ID
AZURE_CLIENT_SECRET
AZURE_TENANT_IDThen, use the SDK as the following:importsczpymodel_name='my-sklearn-model'model_version='v1'server_address="https://scz-mm.westus2.cloudapp.azure.com:443"# Replace with your own server address# Create a new clientc=sczpy.SCZClient(server_address)# Register a modelc.register_model(model_name,model_version)# Encrypt a modelc.encrypt(model_name,model_version,"your-model.pkl","your-model.pkl.enc")# Decrypt a modelc.decrypt(model_name,model_version,"your-model.pkl.enc","your-model.pkl")Building sczpyTo build sczpy package, use the following command from thescz-pythonfolder:pythonsetup.pybdist_wheel#build wheel packagepythonsetup.pysdist#or, build final package (tar)Developing sczpyTo install sczpy, along with the tools you need to develop and run tests, run the following in your virtualenv:pipinstall-e.[dev]
Package: sd212review
sd212reviewSimple Python module to tell you which unit to write review questions for SD212Usagefrom sd212review import whichunit

# you can call it with a number
whichunit(257863) # returns 2

# or you can call it with a string
whichunit('m264351') # returns 3Build instructionsFollowthis tutorial on packagingandthis quickstart for setuptools.Pip/conda/mamba packages needed:build twineTo test:python3 test.pyTo build:python3 -m buildTo publish on pypi (requires account setup andapi token):python3 -m twine upload --repository testpypi dist/*
Package: sdaab
sdaabSimple Data Abstraction provides an abstraction layer to access different types of storage (e.g. local disk, S3).
Basic file management methods are implemented for each type of storage.InstallationTo install the package:pip install sdaabExample of usage:fromsdaab.disk.storage_diskimportStorageDisk# Initialize the storage objects=StorageDisk(root_path="/tmp/")# You can mkdir, rename, ls, cp, mv, etc.s.mkdir("folder1")s.rename("folder1","folder2")# You can also upload or download files.v1="Hello world!"s.upload_from_memory(v1,"v1")v2=s.download_to_memory(v2,"/folder3/v2")# When you want to switch to another storage,# just re-initialize the storage object and# the methods will work exactly as before.s=StorageS3boto(host="s3.eu-west-3.amazonaws.com",port=1234,access_key="xxxyyyzzz",secret_key="aaabbbccc",bucket="bucket-x",calling_format="boto.s3.connection.SubdomainCallingFormat",secure=True,root_path="/")
Package: sdag2
The Python Simple Directed Graph whith Cicle Detector and TopoloGical sorter utilities.Project Home PageThis project was be hosted onGithub.AuthorsMoises P. SenaInstallInstall it using thePython PIP Project.pipinstallsdag2Scriptstsort.pySources from Standard Input:echo-e'C A\nA B\nB D\nC D'|tsort.pySources from another file:echo-e'C A\nA B\nB D\nC D'>verticies.txttsort.pyverticies.txtMore Options:tsort.py--helpUsage:tsort.py[options][FILE[OUT_FILE]]Options:-h,--helpshowthishelpmessageandexit-fFILE,--file=FILEWithnoFILE,orwhenFILEis-,readstandardinput.-oOUT_FILE,--out-file=OUT_FILEWriteresulttoOUT_FILE,defaultisstandardoutput.-sSEP,--separator=SEPItemsseparator,defaultis\sregex.-qQUIT_SEQ,--quit-sequence=QUIT_SEQStopreadFILEwherelineequalsQUIT_SEQ,defaultis:quit.Testsimportunittestfromsdag2importDAG,CycleDetectedExceptionclassDAGTest(unittest.TestCase):deftest_simple(self):'''
        Tests the verticles order in:

        C --> A --> B --> D
        '''dag=DAG()a=dag.add("A")b=dag.add("B")c=dag.add("C")d=dag.add("D")dag.add_edge(c,a)dag.add_edge(a,b)dag.add_edge(b,d)dag.add_edge(c,d)rs=dag.topologicaly()self.assertTrue(rs.index("C")<rs.index("A"))self.assertTrue(rs.index("A")<rs.index("B"))self.assertTrue(rs.index("B")<rs.index("D"))self.assertTrue(rs.index("C")<rs.index("D"))deftest_cicle_detect(self):'''
        Tests the verticles order in:

        C --> A --> B --> D -> C
        '''dag=DAG()a=dag.add("A")b=dag.add("B")c=dag.add("C")d=dag.add("D")dag.add_edge(c,a)dag.add_edge(a,b)dag.add_edge(b,d)dag.add_edge(c,d)try:# add cicle at A --> C --> Adag.add_edge(a,c)raiseException("Cycle not detected")exceptCycleDetectedException:passdefmain():unittest.main()if__name__=="__main__":main()
Package: sd-aiosmtplib
aiosmtplib is an asynchronous SMTP client for use with asyncio.For documentation, seeRead The Docs.Quickstartimportasynciofromemail.messageimportEmailMessageimportaiosmtplibmessage=EmailMessage()message["From"]="root@localhost"message["To"]="somebody@example.com"message["Subject"]="Hello World!"message.set_content("Sent via aiosmtplib")loop=asyncio.get_event_loop()loop.run_until_complete(aiosmtplib.send(message,hostname="127.0.0.1",port=25))RequirementsPython 3.5.2+, compiled with SSL support, is required.Bug reportingBug reports (and feature requests) are welcome via Github issues.
Package: sdanalysis
Statdyn AnalysisThis is a set of scripts that useHoomdto perform the Molecular
dynamics simulations of a glass forming molecular liquid. There is a particular
focus on understanding the dynamic properties of these molecules.Note that this is still very early alpha software and there are likely to be
large breaking changes that occur.InstallationThe simplest method of installation is usingconda. To installconda install -c malramsay statdyn-analysisIt is also possible to set the repository up as a development environment,
in which case cloning the repository and installing is possible by runninggit clone https://github.com/malramsay64/statdyn-analysis.git
cd statdyn-analysis
conda env create
source activate sdanalysis-dev
python setup.py developOnce the environment is setup the tests can be run withpytestRunning AnalysisDynamics of a trajectory can be computed using the commandsdanalysis comp-dynamics trajectory-Trimer-13.50-1.20.gsdwhich will generate an hdf5 file of the same name containing a single table,dynamicswhich has all the dynamic quantities tabulated. This also includes
a start index, over which statistics can be computed.Finally the commandsdanalysis figurewill open up a bokeh server which will allow for the interactive visualisation
of alldump-*.gsdfiles in the current directory.
Package: sd.analytics
IntroductionSimple Google analytics integration for Singing & DancingAdds tracking parameters to urls in outgoing S&D newsletters.Use Plone/portal_newsletters/analytics.html to activate the addon and change settings.
(See browser.txt for more in depth info.)Note for translators: Titles and descriptions for the configuration ui can be lifted fromhttp://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55578in almost any language.Changelog0.1.3 2015-07-10fix rendering of settings page [fRiSi]bugfix: exclude theenabledparameter from the
generated links [fRiSi]fix imports for plone 4.3 compatibility
[fRiSi]0.1.2 2013-02-11remove unnecessary dependency to z3c.jbot0.1.1 2013-02-11Fixes to make the package work on Plone 4, too [fRiSi]0.1 - UnreleasedInitial release
Package: sdanalyzer
sdanalyzerTool to analyze a large number of Android applications easily. It consist of a command line tool extracting data from all applications, storing it in a local database, and then opening a web interface to manually analyze the results in a user-friendly way.InstallationYou can install sdanalyzer directly frompypi:pip install sdanalyzer.You can also download the code from the git repository, and install it from the source code :git pull git@github.com:Te-k/sdanalyzer.git
cd sdanalyzer
pip install .How to use itCreate a new phone:sdanalyzer phones --create "Roberto's Phone"
1	Roberto's Phone	NoneImport APKs:sdanalyzer import --phone 1 .Run the web server to check the APKs:sdanalyzer serveOnce you have done your analysis, you can delete the local database withsdanalyzer flushYou can check all the options of the sdanalyzer command :$ sdanalyzer -h
usage: sdanalyzer [-h] {serve,flush,phones,import,delete} ...

Launches sdanalyzer

positional arguments:
  {serve,flush,phones,import,delete}
                        Subcommand
    serve               Launch the web app
    flush               Flush the database
    phones              List phones
    import              Import apks
    delete              Delete a phone and related data
    export              Export information on all apks of a phone

optional arguments:
  -h, --help            show this help message and exitInfos on how it worksThis tool largely relies onandroguardThe local database is an sqlite database stored in~/.config/sdanalyzer/db.dbAn incomplete list oftrusted APK signing certificatesis provided with the tool. It has been built manually and is helpful to quickly sort apps, but it is clearly incomplete so use at your own risk.A few yara rules are provided with the tool but if you want to rely on Yara for detection, you are encouraged to provide additional yara rules with the-yoption to thesdanalyzer importcommand.Feel free to open issues for new feature ideas or bugs.LicenseThis code is released under GPLv3 license.
Package: sdata
https://lepy.github.io/sdata/Structured data format (sdata)Design goalsopen data format for open science projectsself describing dataflexible data structure layouthierarchical data structure (nesting groups, dictionaries)(posix path syntax support?)extendable data structuredata format versionsplatform independentsimple object modelsupport of standard metadata formats (key/value, ...)support of standard dataset formats (hdf5, netcdf, csv, ...)support of standard dataset types (datacubes, tables, series, ...)support of physical units (conversion of units)transparent, optional data compression (zlib, blosc, ...)support of (de-)serialization of every dataset type (group, data, metadata)easy defineable (project) standards, e.g. for a uniaxial tension test (UT)(optional data encryption (gpg, ...))change management support?Enable use of data structures from existing tensor libraries transparently(single writer/ multiple reader (swmr) support)(nested data support)df = pandas.DataFrame({"a":[1,2,3]})
import sdata
data = sdata.Data(name="my_data", table=df, comment="A remarkable comment")
data.metadata.add("my_key", 123, unit="m^3", description="a volume")
data.metadata.add("force", 1.234, unit="kN", description="x force")
data.to_xlsx(filepath="my_data.xlsx")
print(data.metadata.df)name                             value  dtype unit description
key                                                                     
name      name                           my_data    str    -            
uuid      uuid  08222ca66e5047808bdc3b35d8f17224    str    -            
my_key  my_key                               123    int  m^3    a volume
force    force                             1.234  float   kN     x forceHowtoDas sdata-Format - slidesDemo Apptest the demo app with editorTry to paste some Excel-Data in the forms ...MetadataAttributesnamevaluedtypeunitdescriptionlabelrequireddtypes for attributesintfloatstrbooltimestamp (datetime.isoformat with timezone)paperDas sdata-FormatIngolf Lepenies. (2020). Das sdata-Format (Version 0.8.4).http://doi.org/10.5281/zenodo.4311323slides,html,pdftemperaturmessung-001.jsontemperaturmessung-001.xlsxsdataIngolf Lepenies. (2020, December 8). sdata - a structured data format (Version 0.8.4). Zenodo.http://doi.org/10.5281/zenodo.4311397
Package: sdbit04-pythonc
pythoncOn installation, this will provide a command : pythonc, which take a path for python module to be compiled.Usage: #> pythonc /path/of/python/module.pyIt includes python3 and an entrypoint for python compiler() method along with some modification to make it easy use like javac.I have also uploaded an alpine(ubuntu) image along with this package.
To get the image from docker-hub use follwing command:
#> docker run -it sdbit04/python-with-compiler