Saravanan666/pypi-org huggingface dataset:
Package: overpassforge
Overpass Forge: a query builder for the Overpass query languageAn object-oriented model to build Overpass queries in Python. Primarly intended
to generate complex queries in Python.InstallRequiresPython 3.10 or higher. Install with:pip install overpassforgeExamplefromoverpassforgeimportAreas,Nodes,Ways,build,beautify# Find both cinema nodes and ways in Bonn, which# are at most 100m away from bus stop nodesbus_stops=Nodes(within=Areas(name="Bonn"),highway="bus_stop")ways=Ways(around=(bus_stops,100.0)).where(amenity="cinema")nodes=Nodes(around=(bus_stops,100.0)).where(amenity="cinema")result=ways+nodesresult.out("meta")query=build(result)print(beautify(query))Output:area["name"="Bonn"]->.set_0;
node(area.set_0)["highway"="bus_stop"]->.set_1;
(
  way(around.set_1:100.0)["amenity"="cinema"];
  node(around.set_1:100.0)["amenity"="cinema"];
);
out meta;FeaturesList of currently implemented features, based on theOverpass QL wiki.Settings: all except augmented-difference between dates (adiff)Block statementsunion, difference, intersectionFor-each loop (foreach)Block statementsif, for, complete, retro, compareStandalone statementsoutItem (implicit)Recurse up (<) and down (>)Recurse up relations (<<) and down (>>)Query for areas (is_in)Statementstimeline,local,convert,makeThe Query Statement (node, way, rel, areaonly)The Query FilterMap way/relation to area (map_to_area)FiltersBy tag (has-kv)Bounding boxRecurse (n, w, r, bn, bw, br)Recurse (way_cnt, way_link)By input set (.setname)By element idRelative to other elements (around)By polygon (poly)newerBy date of change (changed)By user (user, uid)By area (area)Area pivot (pivot)Conditional query filter (if:)ContributingSetup the development environmentWindowspython -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -r requirements.txtLinuxpython -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txtUnit testsRun all the tests with:python -m pytest ./tests
Package: overprint
Utility to help rewrite previous line of text,Usefull and keep user informed of advancement, and keep a reactive
command line interfaceimporttimefromoverprintimportoverprintwithoverprint()as(reprint,print):print('step 1')foriinrange(10):reprint('.'*(i%3+1))time.sleep(0.5)# will display 3 animated dotsThe reprinted line will keep moving down while you use the normalprintstatement which does not change normal programming flow.overprint even provide you with an option to replace (temporarily) the
built-in print statement in case you do not control the underlying
libraries.usepython-moverprintfor a demo
Package: overprivileged
overprivilegedOverprivileged is a utility for discovering over privileged IAM roles in AWS.Caution:This software is in version 0.0.1 and not currently testedInstallationFrom PyPi:$pipinstalloverprivilegedUsageOverprivileged utilizes Cloudtrail logs stored in Cloudwatch to parse out exactly which IAM actions
have been performed by an IAM role over a given number of days and returns a diff of which IAM actions
have been used and which ones have not.PrerequisitesCloudtrail logging enabledCloudtrail logs saved to Cloudwatch log groupCLICheck Role PrivilegesExample Usage:opcheck-privileges\--role-namerole-name\--log-group-namecloudtrail-log-group-name\--days5Example Output:{"usedActions":["route53:ListHostedZones","route53:ListResourceRecordSets"],"unusedActions":["route53:ChangeResourceRecordSets"]}Help:opcheck-privileges--help
Usage:opcheck-privileges[OPTIONS]Checkswhatactionsareusedandunusedbyarole

Options:--role-nameTEXTThenameoftheroletocheckprivilegesfor.--log-group-nameTEXTThenameoftheloggroupwheretheCloudtraillogsarestored.--daysINTEGERRANGEThenumberofdaysinthepastthatthecurrentprivilegesshouldbecheckedagainst.--regionTEXTTheawsregionwheretheloggroupisstored.--helpShowthismessageandexit.
Package: overpunch
Extract and generate overpunch (https://en.wikipedia.org/wiki/Signed_overpunch) formatted numbers.Examples:>>> import overpunch
>>> overpunch.format(123.45)
'1234E'
>>> overpunch.extract("1234E")
Decimal('123.45')Requirements:Python 2.7+ or Python 3Tests:Without coverage:$ nosetestsWith coverage:$ nosetests --with-coverage --cover-package=overpunch
Package: overpy
A Python Wrapper to access the Overpass API.Have a look at thedocumentationto find additional information.FeaturesQuery Overpass APIParse JSON and XML response dataAdditional helper functionsInstallRequirements:Supported Python versions:Python >= 3.6.2PyPy3Install:$pipinstalloverpyExamplesAdditional examples can be found in thedocumentationand in theexamplesdirectory.importoverpyapi=overpy.Overpass()# fetch all ways and nodesresult=api.query("""
    way(50.746,7.154,50.748,7.157) ["highway"];
    (._;>;);
    out body;
    """)forwayinresult.ways:print("Name:%s"%way.tags.get("name","n/a"))print("  Highway:%s"%way.tags.get("highway","n/a"))print("  Nodes:")fornodeinway.nodes:print("    Lat:%f, Lon:%f"%(node.lat,node.lon))HelperHelper methods are available to provide easy access to often used requests.importoverpy.helper# 3600062594 is the OSM id of Chemnitz and is the bounding box for the requeststreet=overpy.helper.get_street("Straße der Nationen","3600062594")# this finds an intersection between Straße der Nationen and Carolastraße in Chemnitzintersection=overpy.helper.get_intersection("Straße der Nationen","Carolastraße","3600062594")LicensePublished under the MIT (see LICENSE for more information)
Package: overpy2
A Python Wrapper to access the Overpass API.Have a look at thedocumentationto find additional information.FeaturesQuery Overpass APIParse JSON and XML response dataAdditional helper functionsInstallRequirements:Supported Python versions:Python >= 3.4PyPy and PyPy3Install:$pipinstalloverpyExamplesAdditional examples can be found in thedocumentationand in theexamplesdirectory.importoverpyapi=overpy.Overpass()# fetch all ways and nodesresult=api.query("""
    way(50.746,7.154,50.748,7.157) ["highway"];
    (._;>;);
    out body;
    """)forwayinresult.ways:print("Name:%s"%way.tags.get("name","n/a"))print("  Highway:%s"%way.tags.get("highway","n/a"))print("  Nodes:")fornodeinway.nodes:print("    Lat:%f, Lon:%f"%(node.lat,node.lon))HelperHelper methods are available to provide easy access to often used requests.importoverpy.helper# 3600062594 is the OSM id of Chemnitz and is the bounding box for the requeststreet=overpy.helper.get_street("Straße der Nationen","3600062594")# this finds an intersection between Straße der Nationen and Carolastraße in Chemnitzintersection=overpy.helper.get_intersection("Straße der Nationen","Carolastraße","3600062594")LicensePublished under the MIT (see LICENSE for more information)
Package: overpython
overpythonOvercomplicated Python. Kinda pointless.
I got bored, so I made this pointless project.Aside from overcomplicating Python, it also adds a few new functions such as newFile() and printnl().
There are a few things that completely defeat the purpose of overcomplicating Python, such asfrom overpython import *InstallationThere's no official PyPi package right now. So just do the following:Download overpython as a zip file.Put overpython.py in a folder.Typeimport overpythonas the first lineEnjoy your abomination!Example codeimportoverpythoncalculation=overpython.add(420,69)overpython.println("Hello my habibi "+str(calculation))overpython.pause()Output:Hello my habibi 489
Press the ENTER key to exit...
Package: overrated-ld-stress-detector
Детектор уровня стресса от команды OverratedДетектор уровня стресса основан на анализе сигналов фотоплетизмограммы и пьезоплетизмограммы с использованием технологий искусственного интеллекта.На картинке ниже изображен один из результатов анализа сигналов фотоплетизмограммы и пьезоплетизмограммы.Введены следующие обозначения:0- слабый стресс.1- умеренный стресс.2- сильный стресс.Установкаpip install -U overrated-ld-stress-detectorПример использованияimportpandasaspdfromoverrated_ld_stress_detector.mlimportpretrained_model# импорт разработанного решения предсказанияfromoverrated_ld_stress_detector.visualizationimportutils# импорт разработанного решения визуализацииdf=pd.read_csv('C:/Data/dataset_test.csv',# путь до данных, которые необходимо проанализироватьindex_col=0,# Загрузка данных из Excelsep=';')model=pretrained_model.get_model(model_type='catboost')# Загрузка модели. Доступные модели: 'catboost' и 'cnn'df=df.drop("Class_label",axis=1)result=model.predict(df)# Получение результатов анализа.df['Class_label']=resultdf.to_csv('C:/Data/Overrated.csv',sep=';')utils.visualize_data(df,user_id='dff4a3a1-3d58-4072-a903-e5b38e2c541f',test_id=3,presentation_id=1,result=result)# визуализация результатов для некоторого пользователяИспользуемое решениеДля исходных данных проводится спектральный и статистический анализ для выделения характерных особенностей сигналов с соответствующим им уровнем стресса.На обработанных данных обучены модели машинного обучения, в частности, нейронный сети и градиентный бустинг с последующим блендингом в единый алгоритм определения уровня стресса.Для последующей оценки полученных предсказаний, разработанный пакет включает в себя модуль по визуализации исходных сигналов с определенными в процессе классификации уровнями стресса. Это в совокупности представляет собой систему поддержки принятия решений.Уникальность:Разработанныйpython packageявляется уникальным решением в сфере детектирования уровня стресса, он может быть установлен на любой компьютер с поддержкой python 3 и использован локально, без рисков связанных с возможной утечкой данных.Стек используемых технологий:python3,pypi,git,github- инструменты разработкиpytorch,pytorch-lightning,catboost,scikit-learn,scipy- фреймворки машинного обученияwandb- логированиеplotly,seaborn- инструменты визуализацииСравнение моделейВ качестве устойчивого классификационного решения был выбран ансамбль из 5 моделей градиентного бустинга, с временем инференса 93.4 мс, так как он решает задачу с высокой (более 70% на отложенной выборке) точностью.В качестве нейронной сети была реализована сверточная нейронная сеть с двумя головами.Проводимые исследованияresearch/catboost.ipynb- исследования с моделями градиентного бустингаresearch/signal_eda.ipynbиresearch/spec_eda.ipynb- спектральный и частотный анализ исходных сигналовРазработчикиИмяРольКонтактСуржиков АлександрData Scientisthttps://t.me/mansasha---------Кочетков МаксимData Scientisthttps://t.me/Mahhets---------Ванданов СергейData Scientist----------Андрей СтебеньковData Scientist-
Package: override-pydantic-settings
Overrdie Pydantic SettingsSettings management in Pydantic makes it easy to override settings, like below.# override settingssettgins.env="production"However, if you want to change the setting value in each test suite in your test code,You need to change the values at the beginning of the test and roll back the values at the end of the test.fromapp.core.configimportsettings# Pydantic settingsdeftest_settings():# override setting valueenv=settings.ENVsettings.ENV="production"# assertions...# rollback setting value, because in order not to affect other testssettings.ENV=envThis causes a lot of code duplication. So, in order to remove the code that occurs repeatedly, created a decorator for tests.FeaturesYou can easily override the setting value by applying a decorator to the test function.Also, when the test function is finished, the settings are automatically roll back.That's all.# for sync tests@override_settings(settings=settings,ENV="production")# for async tests@async_override_settings(settings=settings,ENV="production")Installationpipinstalloverride-pydantic-settingsHow to useFor sync testsfrompydanticimportBaseSettingsfromoverride_pydantic_settingsimportoverride_settingsclassMySettings(BaseSettings):ENV:str="dev"NAME:str="Junki"EMAIL:str="na66421@gmail.com"settings=MySettings()@override_settings(settings=settings,ENV="production",NAME="Junki Yoon")deftest_function():...For async tests@pytest.mark.asyncio@async_override_settings(settings=settings,ENV="production",EMAIL="na86421@naver.com")asyncdeftest_function():...WarningYou cannot override the setting value that does not exist.DevelopmentCompatible withPython >= 3.6Python >= 3.10, we can create async decorators using theasnyc context manager.It seems thatasync & synccan be integrated into one function.Running tests$python-mvenvvenv(venv)$sourcevenv/bin/acitave(venv)$pipinstall-rrequirements.txt(venv)$pytestLicenseThis project is licensed under the MIT license.
Package: overrides-extension
A decorator to automatically detect mismatch when overriding a method.
Seehttp://stackoverflow.com/questions/1167617/in-python-how-do-i-indicate-im-overriding-a-methodAll checks are done when a class or a method is created andnotwhen a method is executed or
an instance of a class is created. This means that performance implications are minimal.Note:Version 2.8.0 is the last one that supports Python 2.7.
Versions after that work with Python >= 3.6.Copyright DisclaimerPlease note, this repository and published pip package is a fork of theoriginal implementation.
It’s being distributed separately as it breaks backward compatibility with previous versions.Why explicit overrides?Overrides without explicit indicator for them are weak. They leave room for problems that happen during the evolution of a codebase.(create) Accidental overriding in a subclass when a method to a superclass is added (or vice versa).(modify) Rename of a superclass method without subclass method rename (or vice versa).(delete) Deleting of a superclass method without detecting in subclass that the method is not anymore overriding anything (or vice versa).These might happen for example when overriding a method in a module that does not live in your codebase, or when merging changes done by someone else to the codebase without having access to your subclass.Installation$pipinstalloverrides-extensionUsagefromoverrides_extensionimportoverrideclassSuperClass:defmethod(self)->int:"""This is the doc for a method and will be shown in subclass method too!"""return2classSubClass(SuperClass):@overridedefmethod(self)->int:return1Enforcing usagefromoverrides_extensionimportEnforceOverrides,final,overrideclassSuperClass(EnforceOverrides):@finaldefmethod(self)->int:"""This is the doc for a method and will be shown in subclass method too!"""return2defmethod2(self)->int:"""This is the doc for a method and will be shown in subclass method too!"""return2@staticmethoddefmethod3()->int:"""This is the doc for a method and will be shown in subclass method too!"""return2# THIS FAILSclassSubClass1(SuperClass):defmethod(self)->int:# <-- overriding a final methodreturn1# THIS FAILSclassSubClass2(SuperClass):defmethod2(self)->int:# <-- @override decorator missingreturn1# THIS ONE IS OKclassSubClass3(SuperClass):@overridedefmethod2(self)->int:return1# ENSURE THAT @classmethod AND @staticmethod ARE PLACED AT THE TOPclassSubClass4(SuperClass):@staticmethod@overridedefmethod3()->int:return1ContributorsThis project becomes a reality only through the work of all the people who contribute.mkorpela, drorasaf, ngoodman90, TylerYep, leeopop, donpatrice, jayvdb, joelgrus, lisyarus, soulmerge, rkr-at-dbx, mozharovsky
Package: overscore
Library for double underscore access notationOverscore provides a way to retrieve (and store) multi-dimensional data using a single string
with double underscores.Inspired by Django, the access string can be used as a routine argument or a URL parameter,
allowing for complex access within simple contexts:import overscore

data = {
    "things": {
        "a": {
            "b": [
                {
                    "1": "yep"
                }
            ]
        }
    }
}

overscore.get(data, "things__a__b__0____1")
# "yep"All keys/indexes are separated by double underscores. Extra underscores dictate how to
parse that place in the path.Underscores and BehaviorUnderscoresFollowingMeaningExampleEquivalent2letters and numberskeya__b[“a”][“b”]2numbersindexa__1[“a”][1]3numbersnegative indexa___2[“a”][-2]4numbersnumerical keya____3[“a”][“3”]5numbersneagtive numerical keya_____4[“a”][“-4”]
Package: overseerr-api
This is the documentation for the Overseerr API backend.  Two primary authentication methods are supported:  - **Cookie Authentication**: A valid sign-in to the &#x60;/auth/plex&#x60; or &#x60;/auth/local&#x60; will generate a valid authentication cookie. - **API Key Authentication**: Sign-in is also possible by passing an &#x60;X-Api-Key&#x60; header along with a valid API Key generated by Overseerr.
Package: overseerr-py
This is the documentation for the Overseerr API backend.  Two primary authentication methods are supported:  - **Cookie Authentication**: A valid sign-in to the &#x60;/auth/plex&#x60; or &#x60;/auth/local&#x60; will generate a valid authentication cookie. - **API Key Authentication**: Sign-in is also possible by passing an &#x60;X-Api-Key&#x60; header along with a valid API Key generated by Overseerr.
Package: oversteer
Oversteer - Steering Wheel Manager for Linuxhttps://github.com/berarma/oversteerGraphical application to configure Logitech Wheels.Features supported:Setting the emulation mode.Setting the rotation range.Combine pedals for games that use just one axis for gas/brake.This software uses the Linux driver for Logitech HID++ devices and thus it
could work on any model supported by said driver.It's only been tested on the Logitech G29 Driving Force. It could work on other
models but it's untested.Please, use at your own risk. Suggestions, bugs and pull requests welcome.InstallationInstalling with Python package manager:pip install oversteerDependenciesjstest-gtkis launched when the test button is clicked.You can install all dependencies on Debian systems with the following command:apt install python3 python3-gi python3-pyudev python3-xdg jstest-gtkOther distros may use slightly different names for the same packages.PermissionsThe app will ask for an administrator password if it doesn't have permissions
to write to the device driver.You can make the driver files writable by anyone using udev rules. It will
allow using this app without administrator privileges and also make some driver
features available to games.Install the udev rules file:cp /usr/local/share/oversteer/99-logitech-wheel-perms.rules /etc/udev/rules.d/Reload udev rules (or reboot your computer):sudo udevadm control --reload-rules && sudo udevadm triggerThe changes will take effect next time the device is plugged.
Package: overtalk
overtalkThis module computes total overtalk time in seconds in a stereo WAV file, which occurs when both channels carry audio event. In addition, it also calculates total silence time, when none of the channels contain audio event and total talk time for both channels, when audio event was detected. It can also accept two mono WAV files. Consulthttps://auditok.readthedocs.iofor supported keyword arguments. This is meant to analyze audio files of phone conversations, one channel carrying the audio of caller and the other of the callee.example>>> from overtalk import Overtalk
>>> overtalk = Overtalk(
        energy_threshold=50,
        analysis_window=0.1,
        min_dur=0.2,
        max_dur=10,
        max_silence=0.2
    )
>>> overtalk.load("sample.wav")
>>> print(overtalk.overtalk)
3.25RequirementsPython 3.xAuditokLicenseMIT, see: LICENSE.txtAuthorSzabolcs Szokolysszokoly@pm.me
Package: overtest
Overtest is a suite of tools that allows to start and stop daemons for a quick
throw-away usage. This is typically useful when needing these daemons to runintegration testing.Supported daemonsOvertest currently supports:PostgreSQLMySQLMemcachedInfluxDBEtcdRedis(with sentinel mode)ElasticsearchZooKeeperGnocchiUsageTo use Overtest, simply call theovertest $daemonprogram that you need. It
will setup the temporary environment and export a few environment variable for
you to accesss it:$ overtest postgresql psql template1
I: starting postgresql
I: started postgresql
I: executing command: psql template1
Expanded display is used automatically.
Line style is unicode.
SET
psql (9.4.5)
Type "help" for help.

template1=# \l
                              List of databases
   Name    │ Owner │ Encoding │   Collate   │    Ctype    │ Access privileges
───────────┼───────┼──────────┼─────────────┼─────────────┼───────────────────
 postgres  │ jd    │ UTF8     │ en_US.UTF-8 │ en_US.UTF-8 │
 template0 │ jd    │ UTF8     │ en_US.UTF-8 │ en_US.UTF-8 │ =c/jd            ↵
           │       │          │             │             │ jd=CTc/jd
 template1 │ jd    │ UTF8     │ en_US.UTF-8 │ en_US.UTF-8 │ =c/jd            ↵
           │       │          │             │             │ jd=CTc/jd
(3 rows)

template1=# \q
I: stopping postgresql
I: stopped postgresqlYou can also sourceovertestitself in one of your script. It will set the
environment up, and will clean as soon as your script exit:#!/bin/bash
source overtest postgresql
# Do something with PostgreSQL
# The script will clean things for youEnvironment variablesOvertest exports a few environment variable:OVERTEST_DAEMONwhich contains the name of the daemon launchedOVERTEST_URLwhich contains the URL to the daemonOVERTEST_$daemon_*variables, which contains daemon specific variables,
such as port, database name, URL, etc.Driver specific optionsRedisThe sentinel mode of Redis can be enabled by setting the environment variableOVERTEST_REDIS_SENTINEL_ENABLEto any value.
Package: overtokenizer
This package provides a simple language-agnostic tokenizer.Copyright ® 2016, Luís Gomes <luismsgomes@gmail.com>.This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
Lesser General Public License for more details.You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
Package: overture-sdk
Project DescriptionPython bindings for the Overture REST API.SetupInstallation can be done by using the pip tool:$ pip install --upgrade overture-sdkGetting StartedGet an accountYou can start by creating an account on the Overture platform if you don't already have one, by registering athttps://app.overture.ai/pages/registerTrain and DeployStart by training and deploying your custom computer vision neural network. Follow the documentation athttps://documentation.overture.ai.BugsBugs can be reported todario@overture.ai.
Package: overture-song
The SONG REST client is a simple python module that allows you to interact with a SONG server through Python, with a minimum of coding effort.It lets you submit payloads, check their status and create analyses. From there, you can use the power of Python to process and analyze the data within those objects however you see fit.InstallationYou can install song usingpipby running:pip install overture-songIf you prefer, you can also download the source code from the url
below:https://github.com/overture-stack/SONG/tree/develop/song-python-sdkWiki DocumentationVisithttps://github.com/overture-stack/SONG/wikiContributeIf you’d like to contribute to this project, it’s hosted on github.
Package: overunder
overunderOverunder is an interpreted programming language in Python that receives as rules basic weaving instructions 'over' and 'under' and apply a pattern onto text, simulating a plain weave.To start, add your text of choice in a file calledinput.txt.To run:$ overunderCommands:load- loads the input text. Should be the first command you type inside the interpreter.show- shows which line you are currently working onover + int(x)- keeps the corresponding x characters intactunder + int(x)- replaces the corresponding x characters with a symbolpattern- generates the pattern created so farsave- saves the pattern in a text fileenter/return- moves to the next line of textquit- quits the programSee morehere.