Saravanan666/pypi-org huggingface dataset:
Package: ow2-cache-merge
OW2 Cache MergeThis is a tool to check multiple configurable github repos for dxvk cache files for Overwatch 2 and download if a new (bigger) cache file found on the repo, then merge downloaded cache files with your current cache file and put it under your game directory after backing up your current cache file. It usesdxvk-cache-toolfrom DarkTigrus github repo for merging dxvk cache files.Installationpipinstallow2-cache-mergeorgitclonehttps://github.com/leventguney/ow2-cache-merge.gitcdow2-cache-merge
pythonsetup.pyinstallUsageJust run the script from command lineow2-cache-mergeConfigurationThis tool creates.ow2-cache-mergefolder under your home directory.
Usingconfig.tomlyou can set your game folder
If your game is in "/home/username/Games/overwatch-2" you should setgame_dir = "Games/overwatch-2"If it is installed elsewhere you can also set an absolute path here likegamedir="/run/media/Games/overwatch-2"You can add repos in theconfig.tomlfile like below:[repos]
GolDNenex="https://raw.githubusercontent.com/GolDNenex/overwatch2-dxvk-cache/main/Overwatch.dxvk-cache"
Elagoht="https://github.com/Elagoht/overwatch2-dxvkcache/raw/master/Overwatch.dxvk-cache"records.tomlfile under.ow2-cache-mergedirectory, holds the cache file sizes of the repos
Package: owa-epanet
epanet python packageA slender, auto-generated python wrapper around the owa:epanet hydraulic network analysis toolkit. This package uses SWIG and scikit-build to generate python bindings into the C library. The objective of this package is to establish basic python support for the toolkit, rather than present a "pythonic" interface. More abstractions can be built atop this package to further abstract the API, but the set of functions here is meant to (as closely as practical) mirror the well-known and established C API.Where possible, SWIG has been configured to throw warnings/exceptions instead of using the customary EPANET return integer value for success-checking. Also any output (pointer) parameters from the C API have been re-routed to return values. In these cases, the return tuple from the Python API will contain the values desired.InstallationTo install with pip:pipinstallowa-epanetWheels are now provided for most installations, some extra work will be needed if installing from source.Building the librariesEnsure the EPANET subproject is initializedby runninggit submodule update --init(if necessary) and running the following commands (on Windows skip the line./script/clean.sh). The following method usesscikit-buildto invokecmakefor compiling and linking the shared libaries, and builds a python wheel../scripts/clean.sh
python3 setup.py sdist bdist_wheelTest your builds using the following commands.cd test && \
pipenv install ../dist/*.whl && \
pipenv install pytest && \
pipenv run pytestThis python library was packaged in the following way:python3 setup.py sdist bdist_wheel
python3 -m twine upload dist/*VersioningThis package loosely follows EPANET's release version numbers. Its major and minor numbers will correspond to the given EPANET version, but the patch number is independent. This system might change in the future.
Package: owasp-zap-historic-parser
owasp-zap-historic-parserInstallationInstallowasp-zap-historic-parserpip install owasp-zap-historic-parserUsageThe OWASP ZAP Historic application requires the following information, and users must pass respective info while using parser-s --> mysql hosted machine ip address (default: localhost)
-t --> mysql port (default: 3306)
-u --> mysql user name (default: superuser)
-p --> mysql password (default: passw0rd)
-n --> project name in owasp zap historic
-e --> environment name (default: Not Provided)
-i --> type of scan (active, passive, etc) (default: Not Provided)
-l --> URL for published ZAP report (default: Not Provided)
-v --> version of application tested by ZAP (default: Not Provided)
-f --> filepath & report.html produced by ZAPUseowasp-zap-historic-parserto parse report.html and return a delta report> owaspzaphistoricparser
 -s --> localhost
 -t --> 3306
 -u --> 'superuser'
 -p --> passw0rd
 -n --> testname
 -e --> QA
 -i --> Active
 -l --> "https://www.google.com"
 -v --> "v0.1.0 build 2"
 -f --> "c:\\temp\\report_230_.html"Note: Here if MySQL hosted in:local machine then uselocalhostEx: -slocalhostother machine then useipaddress:3306Ex: -s10.30.2.150:3306Example:> owaspzaphistoricparser
 -s localhost
 -t 3306
 -u 'superuser'
 -p passw0rd
 -n testname
 -e QA
 -i Active
 -l "https://www.google.com"
 -v "v0.1.0 build 2"
 -f "c:\\temp\\report_230_.html"For more info refer toowasp-zap-historic
Package: owattr
owattr overwrites attributes.Exampleconfig.py:importsysimportowattrREDIS_URL="redis://localhost:6379/0"IS_DEV_ENV=Trueowattr.from_dict(sys.modules[__name__],dict(os.environ))Theconfigmodule hasREDIS_URLas attribute. You might want to change the value for your production environment. In this example, if you have definedREDIS_URLin environment variables, when you loadconfigmodule, it is overwritten. If you don’t defineREDIS_URL, you can use the original value.
When owattr read the dict, it casts dict value to type of the original value. So in environment variable, everything is str type. In this example, if you have definedIS_DEV_ENV=Falsein environment variable,IS_DEV_ENVofconfighasFalseas bool type.
Booleans are cast as follows:'false','False'and''are cast to False'true'and'True'are cast to Trueanything else raises a'ValueError'If your object has__all__, owattr overwrites only variables which written in__all__.
Package: owcli
owcliCLI framework which supports both command and subcommand based ondocopt.Install$ pip install owcliQuick startCreate owcli project.$ owcli init <app_name> --python <python_version>Run$ cd <app_name>
$ pipenv install
$ pipenv run python <app_name>/main.py --helpConcrete example$owcliinittestapp--python3.7
------------------------|Createentries...|------------------------
📂/mnt/c/Users/syoum/git/github.com/tadashi-aikawa/owcli/testapp∟📄Pipfile∟📄README.md∟📄setup.py∟📂testapp∟📂commands∟📂cmd1∟📄main.py∟📄__init__.py∟📂cmd2∟📄main.py∟📂subcmd1∟📄main.py∟📄__init__.py∟📂subcmd2∟📄main.py∟📄__init__.py∟📄__init__.py∟📄__init__.py∟📄main.py∟📄__init__.py

------------------------|Nextyouhaveto...|------------------------
.
.

$cdtestapp
$pipenvinstall
$pipenvshell
$pythontestapp/main.py--help
Usage:testapp<command>[<subcommand>][<args>...]testapp<command>[<subcommand>](-h|--help)testapp(-h|--help)testapp--version

Commands:cmd1Command1cmd2Command2

$pythontestapp/main.pycmd2-h
Usage:testappcmd2[<subcommand>][<args>...]testappcmd2(-h|--help)Subcommands:subcmd1Subcommand1subcmd2Subcommand2

$pythontestapp/main.pycmd2subcmd1--help
Subcommand1

Usage:testappcmd2subcmd1<names>...[-f|--flag]testappcmd2subcmd1(-h|--help)Options:<names>...Names-f--flagFlag-h--helpShowthisscreen.$pythontestapp/main.pycmd2subcmd1hogehogahogu-f
flag:truenames:-hoge-hoga-hoguFor developerRequirementspoetrymakebatsCommandsIntegration test$ make test-cliVersion upmakereleaseversion=x.y.zLicenceMITThis software is released under the MIT License, see LICENSE.txt.
Package: owi-data-api-2-pandas
OWI data 2 pandasOWI data 2 pandas is a package developed to ease the interaction with the OWI measurement data API.Basic useThe most common use of the package is to query a fixed period of data:ConnectionConnecting to the API happens through the API class:from owi_data_2_pandas.io import API

user = 'user_name' # replace with you user name
password = 'your_password'  # Replace with your password

root = r"http://10.0.0.138/api/v1/"

owi = API(api_root=root, username=user, password=password)Querying for measurement dataOnce an instance of the API class is made, you can get a Pandas DataFrame with your data in it. To do so you'll need to specify both the period of interest, the location and the metrics you would need.In the example below we will query the period from 15/11/2018 till 16/11/2018 for BBC01 wind speed data:import datetime
from pytz import utc

dt_start =  datetime.datetime(2018,11,15,tzinfo=utc)
dt_stop  = datetime.datetime(2018,11,16,tzinfo=utc)
df = owi.query((dt_start, dt_stop), location='bbc01', metrics=['mean_BB_C01_windspeed'])This returns a Pandas DataFrame object.Other useful queriesCheck user groupsThe permissions of a user a organized in so-called user groups. You can see the user groups allocated to the user through:owi.groupsCheck available parameters/metrics for a locationA list of available parameters/metrics for a given location can be obtained through:owi.metrics(location='BBC01')Advanced useInteraction with dw_database and DynaWindFrameThe current package was designed without the use of the OWI-lab internal package dw_database. However should a user want to import the results of the API into a dw_database.utils.DynaWindFrame then this is easily achieved:from dw_database.utils import DynawindFrame, Turbine

dwf = DynawindFrame(df=df, location=Turbine('BBC01'))Basic troubleshootingSome basic tips for initial troubleshooting:Check that you can reach the server by sending a ping to the serverCheck that you have the permissions (e.g. through the use of the groups query)Check for typo's in your locations or metrics (e.g. use the metrics query)Authorsowi_data_2_pandas was written in the context of the efforts of the OWI-lab, a Belgian research effort to bring down the cost of offshore wind.
Package: owid-repack
owid-repack-pyPack Pandas DataFrames into smaller, more memory efficient types.OverviewWhen you load data into Pandas, it will use standard types by default:objectfor stringsint64for integersfloat64for floating point numbersHowever, for many datasets there is a much more compact representation that Pandas could be using for that data. Using a more compact representation leads to lower memory usage, and smaller binary files on disk when using formats such as Feather and Parquet.This library does just one thing: it shrinks your data frames to use smaller types.Installingpip install owid-repackUsageTheowid.repackmodule exposes two methods,repack_series()andrepack_frame().repack_series()will detect the smallest type that can accurately fit the existing data in the series.In [1]: from owid import repack

In [2]: pd.Series([1, 2, 3])
Out[2]:
0    1
1    2
2    3
dtype: int64

In [3]: repack.repack_series(pd.Series([1.5, 2, 3]))
Out[3]:
0    1.5
1    2.0
2    3.0
dtype: float32

In [4]: repack.repack_series(pd.Series([1, None, 3]))
Out[4]:
0       1
1    <NA>
2       3
dtype: UInt8

In [5]: repack.repack_series(pd.Series([-1, None, 3]))
Out[5]:
0      -1
1    <NA>
2       3
dtype: Int8Therepack_frame()method simply does this across every column in your DataFrame, returning a new DataFrame.Releases0.1.3:Improve performance on float dtypes0.1.2:Shrink columns with all NaNs to Int80.1.1:Fix Python support in package metadata to support 3.8.1 onwards0.1.0:Migrate first version fromowid-catalog-pyrepo
Package: owiener
oWienerA Python3 implementation of the Wiener attack on RSA.Installationpython3-mpipinstallowienerorcurl-Ohttps://raw.githubusercontent.com/orisano/owiener/master/owiener.pyExampleimportowienere=30749686305802061816334591167284030734478031427751495527922388099381921172620569310945418007467306454160014597828390709770861577479329793948103408489494025272834473555854835044153374978554414416305012267643957838998648651100705446875979573675767605387333733876537528353237076626094553367977134079292593746416875606876735717905892280664538346000950343671655257046364067221469807138232820446015769882472160551840052921930357988334306659120253114790638496480092361951536576427295789429197483597859657977832368912534761100269065509351345050758943674651053419982561094432258103614830448382949765459939698951824447818497599n=109966163992903243770643456296093759130737510333736483352345488643432614201030629970207047930115652268531222079508230987041869779760776072105738457123387124961036111210544028669181361694095594938869077306417325203381820822917059651429857093388618818437282624857927551285811542685269229705594166370426152128895901914709902037365652575730201897361139518816164746228733410283595236405985958414491372301878718635708605256444921222945267625853091126691358833453283744166617463257821375566155675868452032401961727814314481343467702299949407935602389342183536222842556906657001984320973035314726867840698884052182976760066141d=owiener.attack(e,n)ifdisNone:print("Failed")else:print("Hacked d={}".format(d))# Hacked d=4221909016509078129201801236879446760697885220928506696150646938237440992746683409881141451831939190609743447676525325543963362353923989076199470515758399ReferencesCryptanalysis of Short RSA Secret Exponents:https://www.cits.ruhr-uni-bochum.de/imperia/md/content/may/krypto2ss08/shortsecretexponents.pdfpablocelayes/rsa-wiener-attack:https://github.com/pablocelayes/rsa-wiener-attackwihoho/Wiener-s-Attack:https://github.com/wihoho/Wiener-s-AttackAuthorNao Yonashiro (@orisano)LicenseMIT
Package: owimetadatabase-preprocessor
Owimetadatabase preprocessorTools for preprocessing geometries from the metadatabase. Read the documentationhere.InstallationIn your desired virtual environment with Python 3 and pip installed:pip install owimetadatabase-preprocessorInstallation (alternative)In your desired virtual environment and directory with Python 3 and pip installed:git clone <repo-github-address>pip install <repo-local-name>ContributingIf you want to contribute to the development of the package, you can, in your desired virtual environment and directory with Python 3 and pip installed:git clone <repo-address>pip install -e <repo-name>/[dev]This way, you will install all the required dependecies and the package itself in editable mode, i.e. all changes to it will be reflected immediately locally so it can be tested.The repository also has.lockfile if you usepoetry.Authorsowi_preprocessorwas written by the team of OWI-lab.AcknowledgementsThis package was developed as part of the ETF Smartlife (FOD165) project.LicenseThe package is licensed under theCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Package: owl2else
owl2elseScripts to transform ontology OWL 2 files to other languagesowl2clips transforms OWL 2 ontologies to COOL CLIPS languageowl2plot transforms OWL 2 ontologies to a plot using graphvizowl2rdflib transforms OWL 2 to a python file with a RDFlib
ClosedNamespace object with the vocabulary of the ontology
Package: owl2vec-star
OWL2Vec-StarOWL2Vec*: Embedding OWL ontologiesFree software: Apache-2.0 LicenseDocumentation:https://owl2vec-star.readthedocs.io.FeaturesOWL2Vec* v0.2.0 exposes a CLI with two subcommands, which allows you to perform two main programs.StandaloneThis command will embed one ontology. It can be configured by the configuration file default.cfg.
See the examples and comments in default.cfg for the usage.Running example:$ owl2vec_star standalone --config_file default.cfgNote: Different from the experimental codes, the standalone command has implemented all OWL ontology
relevant procedures in python with Owlready, but it also allows the user to use pre-calculated
annotations/axioms/entities/projection to generate the corpus.Standalone MultiThis command will embed multiple ontologies into one language model, where the documents from
multiple ontologies will be merged. One use case example is embedding all the conference relevant
ontologies of the OAEI conference track at once.Running example:$ owl2vec_star standalone-multi --config_file default_multi.cfgNote: Different from thestandalonecommand, this command for multiple ontologies does NOT allow
the pre-calculated or external annotations/axioms/entities/projection.PublicationsMain ReferenceJiaoyan Chen, Pan Hu, Ernesto Jimenez-Ruiz, Ole Magnus Holter, Denvar Antonyrajah, and Ian Horrocks.OWL2Vec*: Embedding of OWL ontologies. Machine Learning, Springer, 2021.
[PDF]
[@Springer]
[Collection]
[Codesfor the computed results.]Applications with OWL2Vec*Jiaoyan Chen, Ernesto Jimenez-Ruiz, Ian Horrocks, Denvar Antonyrajah, Ali Hadian, Jaehun Lee.Augmenting Ontology Alignment by Semantic Embedding and Distant Supervision.
European Semantic Web Conference, ESWC 2021.
[PDF]
[LogMap Matcher work]Ashley Ritchie, Jiaoyan Chen, Leyla Jael Castro, Dietrich Rebholz-Schuhmann, Ernesto Jiménez-Ruiz.Ontology Clustering with OWL2Vec*.
DeepOntonNLP ESWC Workshop 2021.
[PDF]Preliminary PublicationsOle Magnus Holter, Erik Bryhn Myklebust, Jiaoyan Chen and Ernesto Jimenez-Ruiz.Embedding OWL ontologies with OWL2Vec.
International Semantic Web Conference.
Poster & Demos. 2019.
[PDF]Ole Magnus Holter.Semantic Embeddings for OWL 2 Ontologies.
MSc thesis, University of Oslo. 2019.
[PDF]
[GitLab]Case StudiesData and codes for class membership prediction on the Healthy Lifestyles (HeLis) ontology,
and class subsumption prediction on the food ontology FoodOn and the Gene Ontology (GO), are under the
foldercase_studies/.CreditsCode underrdf2vec/, which mainly implement walking strategies over RDF graphs,
is derived frompyRDF2Vec(version 0.0.3, last access: 03/2020).This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Many thanks toVincenzo Cutronafor preparing this package.History0.2.0 (2021-08-04)First release on PyPI.
Package: owl2yams
OWL2YAMSA script to create a new CubicWeb instance from OWL ontology and RDF dataInstalling the projectCreate and activate a virtual environmentpython3 -m venv my-virtual-env
source my-virtual-env/bin/activateInstall the dependencies, in this folder, runpip install -e .Bootstrap a cube from a OWL fileThis command will create a cube from the OWL fileowl2yams -m path/to/my-ontology.owl -n my_owl2yams_instanceIt requires the ontology file path.optional arguments:OptionDescription-h, --helphow this help message and exit--owl-model OWL_MODEL, -m OWL_MODELSpecify the OWL file to translate--instance-name INSTANCE_NAME, -n INSTANCE_NAMESpecify the instance name for the CW instance--parse-format {turtle,xml,n3,nquads,nt,trix}, -f {turtle,xml,n3,nquads,nt,trix}pecify the OWL file serialization--dry-run, -dPrint the YAMS schema only--only-cubeOnly create the cube and exit (no instance and db-init)Populate a CubicWeb instance from RDF dataRun the script to populate your CubicWeb instance with your RDF data compliant
with the OWL ontology that was used to create your cube.cubicweb-ctl import-rdf my_owl2yams_instance -f /path/to/rdfdata.ttloptional arguments:
--parse-format      The RDF serialization format between {turtle,xml,n3,nquads,nt,trix}Launch your CubicWeb instanceThis command will launch the CubicWeb instancecubicweb-ctl pyramid my_owl2yams_instanceBy default it used the8080port. You can change this port using the environement variableCW_PORT, which you can set with the following command:export CW_PORT=8081You know the server is running when you see the logServing on http://0.0.0.0:8080Use your CubicWeb instanceAfter those two commands, you can browse, create new data and more on your
web application.Go tohttp://localhost:8080and you can start browsing, adding data, etc.If you want to use this instance as a data server, there is an API available
automatically since the
(cubicweb-api)[https://forge.extranet.logilab.fr/cubicweb/cubes/api/] cube is
installed by default when using OWL2YAMS. You can find theopen-apispec using the route/api/v1/openapi.This cube is mandatory to use the
(cubicweb-react-admin)[https://forge.extranet.logilab.fr/cubicweb/react-admin-cubicweb]
tool.  This tool lets you navigate and administrate your data using a modern
and dynamic interface.
Package: owlapi
OwlAPIOwlAPI is an interface for routing/chaining outbound API requests to various endpoints asynchronously and parsing/formatting the output.Currently Supported Endpoints:APIAtera(in progress)ClickUp(in progress)Google(Search / SiteSearch)GPTOpenAIReplicateScrapingFraseModestMoneyTrustPilotCurrently Supported Format Conversions:JSONPDF(in progress)HTMLMarkdownPlaintextDocX(in progress)References:AteraClickUpGoogle SearchOpenAIReplicateFraseModest MoneyTrustPilotReportLab PDFpython-docxmarkdown
Package: owlapy
owlapyOwlapy is loosely based onowlapi- the java counterpart, successfully representing the main
owl objects in python.Other than that, Owlapy also offers some extra functionalities:Owl2SparqlConverterto convert owl class expressions to SPARQL syntax.DLSyntaxObjectRendererto render owl objects to description logics.ManchesterOWLSyntaxParserto parse strings of manchester syntax to owl class expression.For more, you can check theAPI documentation.InstallationpipinstallowlapyUsageIn this example we start with a simple atomic class expression and move to some more complex
ones and finally render and print the last of them in description logics syntax.fromowlapy.renderimportDLSyntaxObjectRendererfromowlapy.modelimportIRI,OWLClass,OWLObjectProperty,OWLObjectSomeValuesFrom,\OWLObjectIntersectionOf# Create an IRI object using the iri as a string for 'male' class.male_iri=IRI.create('http://example.com/society#male')# Create the male classmale=OWLClass(male_iri)# Create an object property using the iri as a string for 'hasChild' property.hasChild=OWLObjectProperty(IRI.create('http://example.com/society#hasChild'))# Create an existential restrictionsmales_with_children=OWLObjectSomeValuesFrom(hasChild,male)# Let's make it more complex by intersecting with another classteacher=OWLClass(IRI.create('http://example.com/society#teacher'))male_teachers_with_children=OWLObjectIntersectionOf([males_with_children,teacher])# You can render and print owl class expressions in description logics syntaxprint(DLSyntaxObjectRenderer().render(male_teachers_with_children))The following will be printed:(âˆƒ hasChild.male) âŠ“ teacherEvery OWL object that can be used to classify individuals, is considered a class expression and
inherits fromOWLClassExpressionclass. In the above examples we have introduced 3 types of class expressions:OWLClass,OWLObjectSomeValuesFromOWLObjectIntersectionOf.Like we showed in this example, you can create all kinds of class expressions using the
OWL objects inowlapy model.Are you looking for more?The javaowlapilibrary also offers classes for OWL ontology, manager and reasoner.
We have also implemented those classes in python, but for the time being we are
not including them in owlapy. You can find all of those classes inOntolearn, which is a
python library that offers more than just that.In case you have any question or request please don't hesitate to open an issue.