Saravanan666/pypi-org huggingface dataset:
Package: usps-client
usps-clientPython client for the USPS Web Tools API.UsageImport the client, instantiate with your user id (register athttps://registration.shippingapis.com/)
and call the standardize method:>>>importusps_client>>>usps=usps_client.Client('[your user id]')>>>standardized=usps.standardize_address(...firm_name="USPS Office of the Consumer Advocate",...address1="475 LENFANT PLZ SW RM 4012",...city="Washington",...state="DC",...zip5="20260",...)An Address object will be returned, containing data returned from the USPS Web Tools API.Since the return classes are defined using the attrs model, it is possible to convert into generic types:>>>importattr>>>attr.asdict(standardized){'firm_name':'USPS OFFICE OF THE CONSUMER ADVOCATE','address1':None,'address2':'475 LENFANT PLZ SW RM 4012','city':'WASHINGTON','state':'DC','zip5':'20260','zip4':'0004'}
Package: uspspy
pyUSPSprovides a simple client and interface for validating addresses
using the USPS API. It is mostly taken fromhttps://github.com/BuluBox/usps-api/The only reason this package exists is that not all environment can build
(or be made to build, or successfully install dated wheels for)lxml.
So this version uses the native ElementTree implementation in the
standard library - no compilation required.
Package: usps-track
usps-trackQuickly track via SMS several USPS (and some international) tracking numbers via the command line.For international to work, the destination country must be USA.The phone number argument must be a US phone number.Usageusage: usps_track.py [-h] TRACKING_NUMBER [TRACKING_NUMBER ...] PHONE_NUMBER

positional arguments:
  TRACKING_NUMBER  Tracking numbers
  PHONE_NUMBER     Phone number to send SMS to (US only)This can also be used as a library:fromusps_trackimportusps_trackasyncdefusage():awaitusps_track('555-555-5555',['tracking_number_1'],raise_for_status=True)
Package: uspto-patent-citation-graph
USPTO-patent-citation-graphGraph that downloads patent citation data from USPTO'sPatentsViewAPI on-demand and stores it locally in an SQL database (and in memory) for fast access later.The project is based on thegraphscraperproject, please see that project for the details of the graph API.InstallationInstall the latest version of the project from the Python Package Index usingpip install uspto-patent-citation-graph.Getting startedCreating a graph instance that will use a default, on-disk SQLite database:fromuspto_patent_citation_graphimportUSPTOPatentCitationGraphgraph=USPTOPatentCitationGraph(None)Loading a node that is not in the local database yet:# `can_validate_and_load=True` tells the graph's node list that it is allowed to# load data from the PatentsView API. Its default value is `False`, and the# argument can be omitted if the given patent is already in the local database.patent_number="4733665"# Stent patentstent_patent=graph.nodes.get_node_by_name(patent_number,can_validate_and_load=True)Accessing a node's neighbors (cited and cited-by patents):print(f"Neighbors of{stent_patent.name}:")forneighborinstent_patent.neighbors:print(f" -{neighbor.name}:{neighbor.external_id}")Community guidelinesAny form of constructive contribution is welcome:Questions, feedback, bug reports: please open an issue in the issue tracker of the project or contact the repository owner by email, whichever you feel appropriate.Contribution to the software: please open an issue in the issue tracker of the project that describes the changes you would like to make to the software and open a pull request with the changes. The description of the pull request must references the corresponding issue.The following types of contribution are especially appreciated:License - MITThe library is open-sourced under the conditions of theMIT license.
Package: usql-bin
pybinThis project was inspired by howMaturin packages rust binaries.  The key observation is that in the wheel format, thedistribution-1.0.data/scripts/ directory is copied to bin, which means we can leverage this to seamlessly copy binaries into a user's PATH.Combined with Python's platform-specific wheels, this allows us to use pip as a "cross-platform package manager" for distributing single-binary CLI applications.Wheel Building ProcessThe core of the logic lies in thebuildlib.pymodule.A mapping from download URL (often github releases) to pypi platform tag is required.For each platform:Download the release & extract the binary.Set file permissions and place into scripts directory within wheel archive.Create the METADATA and WHEEL files within wheel archive.Place wheel intodist/folder.Once all wheels are constructed, the distribution is uploaded to PyPI.CICD is configured to automatically recognize newPyPIreleases by looking for a diff on the PYPI_VERSION.  When this happens, a build-and-release cycle is performed for that release version.Catalogpip install dive-bin:pybin version,upstream sourcepip install just-bin:pybin version,upstream sourcepip install lazydocker-bin:pybin version,upstream sourcepip install scc-bin:pybin version,upstream sourcepip install usql-bin:pybin version,upstream source
Package: usql-conf
usql_confCommand-Line Tool for Managing SQL Connection Strings.Installpip install git+https://github.com/jpy-git/usql_conf.gitUsageCreate .usql_conf file in home directory and add config names with associated connection strings in .ini format.
e.g.[pg_test]
connection_string = pg://test_user:password123@localhost/test_database?sslmode=disableThen obtain connection string from .usql_conf by running:usql_conf pg_testThe intended usage is to be passed to usql to connect to the desired database:usql $(usql_conf pg_test)
Package: usramp
USRAMP stands for Ultrafast shape-recognition algorithm with mass ponderation. USRAMP is an easy-to-use program to discriminate similar molecules in a list. The USRAMP program requires a list of concatenated molecules in XYZ format and an optional tolerance parameter as input parameters. The input file name can be anything if it contains at least two joined molecules in XYZ format. If you don't have a valid xyz file, USRAMP can create a sample file as appropriate.Installing USRAMPYou can install and uninstall with:# install
pip3 install usramp

# invoque as:
x.usramp.py

# uninstall
pip3 uninstall usrampor# install
git clone https://github.com/fortizchi/usramp
cd usramp
python3 setup.py install --record files.txt

# invoque as:
x.usramp.py

# uninstall
xargs rm -rf < files.txtRunning USRAMPx.usramp.py
Package: usrr16
USR-R16 / USR-R16-TSimpe USR-R16 / USR-R16-T boards controller classExamplefromusrr16importUsrR16r16=UsrR16(host='192.168.0.99',port=8899,password='admin')r16.turn_off_all()r16.invert(relay=1)r16.turn_on(relay=2)r16.turn_off(relay=2)r16.turn_on(3)print(r16.state(3))# Truer16.turn_off(3)print(r16.state(3))# FalseInstallationpip install usrr16Contributors: @v1a0, @horga83Based on@wowks/USR-R16andxtodx/php-USR-R16Thank you!
Package: usrse
USRSE PythonWelcome to US-RSE Python! This is a handy little client and assocated actions to make it easy
to retrieve updated content from our various feeds.See our ⭐️Documentationto get started! ⭐️Coming Soon / TODOautomated deployment to pypi on releasenightly test run to ensure US-RSE static API functioning as expectedother endpoints and functions hereContributorsWe use theall-contributorstool to generate a contributors graphic below.Vanessasaurus💻LicenseThis code is licensed under the MPL 2.0LICENSE.
Package: ussa1976
The U.S. Standard Atmosphere 1976 model.This package implements the atmosphere thermophysical model provided by the
National Aeronautics and Space Administration technical report NASA-TM-X-74335
published in 1976 and entitledU.S. Standard Atmosphere, 1976.FeaturesRun the U.S. Standard Atmosphere 1976 model on your custom altitude gridCompute all 14 atmospheric variables of the model as a function of altitude:air temperatureair pressurenumber density (of individual species)air number densityair densityair molar volumeair pressure scale heightair particles mean speedair particles mean free pathair particles mean collision frequencyspeed of sound in airair dynamic viscosityair kinematic viscosityair thermal conductivity coefficientResults stored inNetCDFformatCommand-line interfacePython interfaceRequirementsPython 3.8+InstallationYou can installUSSA1976viapipfromPyPI:$pipinstallussa1976UsageFor the Command-line interface, please see theCommand-line Referencefor details.For the Python interface, refer to theUser Guide.ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMIT license,USSA1976is free and open source software.IssuesIf you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was generated from@cjolowicz’sHypermodern Python Cookiecuttertemplate.
Package: usscore
scoreUSHow to install usscore on Linux, MacOS, or WSL on Windows$ pip install usscoreHow to install usscore on Windows 11 or 10$ pip install usscore --force-reinstall --no-cache-dir --no-binary :all:how to run usscore$ usscoreThe result of sorted scores is shown as follows as of March 10 2022.Comparison with other countries on scores generated by scorecovid:https://pypi.org/project/scorecoviddeaths of US states:https://github.com/nytimes/covid-19-data/raw/master/live/us-states.csvvaccination rate of US states:https://covid.ourworldindata.org/data/vaccinations/us_state_vaccinations.csvUse PopulationReport.csv on population by state in the US:https://data.ers.usda.gov/reports.aspx?ID=17827https://www2.census.gov/programs-surveys/popest/datasets/2020-2021/state/totals/NST-EST2021-alldata.csvUse pov.csv file on poverty rate by state in the US:https://data.ers.usda.gov/reports.aspx?ID=17826Use health.csv:https://www.americashealthrankings.org/explore/health-of-women-and-children/measure/outcomes_hwc_2020/state/ALLeducationhttps://www.nationsreportcard.gov/profiles/stateprofile?chort=1&sub=SCI&sj=AL&sfj=NP&st=MN&year=2015R3
Package: ussd-elastic-apm
Module for Elastic APM.It provides full out-of-the-box support for django ussd requests and sessions
built by Django. In addition to all the functionality of elastic-apm.Works well with ussd airflow.
Your application doesn’t live on the web? No problem! Elastic APM is easy to use in
any Python application.Read thedocumentation.LicenseBSD-3-ClauseMade with ♥️ and ☕️ by Elastic and Elias.
Package: ussy
ï»¿# Ussy
Being human, we've all come across this familiar issue before.There are just so many words in the English language to ussify! How can I possibly cope with ussifying them all?With this pervasive problem in mind, I've created the Ussy module, a Python package dedicated to solving all of your ussification needs.This module algorithmically ussifies words by estimating a word's phonemic sequence, and popping phonemes from the end of the word until a plosive consonant is reached. If a suitable plosive consonant is identified, "ussy" is appended to the remained grapheme sequence and returned.Usagefrom ussy.ussify import Ussy

ussy = Ussy()
ussified = ussy.ussify("raspberry")
print(ussified)

"raspberrussy"Ussy.ussify(word, plural)string word: alphabetic English word string to be ussifiedboolean plural: true if ussified word is plural, default false if singularreturns false if given string is unussifiable, or ussified string otherwise
Package: ustack-logging
ustack-loggingDefault logging configuration for uStack style Python applications.Installationpip install ustack-loggingUsagefromustack_logging.logging_configurationimportconfigure_loggingdefmain():configure_logging()# Run your applicationif__name__=="__main__":main()IntentThis library is intended to codify the standard way uStudio Python
applications log and report errors when running inside Kubernetes. It
takes no configuration because its intent is to enforce a
configuration.However, it is built ondatadog-logger,
which is configurable. If you need a different configuration, it
should be trivial to implement it using that library directly.ConfigurationThe library configures the following things:It sets up the logging library to log the time, log level, module name
and log message for every message, and it sets the current log level
toINFO.In order to function, it uses a secret namedenvironment-infoin theustudio-systemnamespace. The secret must contain the keysenvironmentanddatadog-api-key, and the pod must contain a label
namedrole.If any information is missing or any connections fail it logs a
warning and does not error.It configures thedatadog-loggerlibrary to sendERRORand above
log messages to Datadog as events, with the following tag mapping:environment-info.environment-> Datadog tagenvironmentK8s Pod Namespace -> Datadog tagserviceK8s Pod Labelrole-> Datadog tagrole
Package: ust-alma
Make sure you have upgraded version of pipWindowspy -m pip install --upgrade pipLinux/MAC OSpython3 -m pip install --upgrade pipCreate a project with the following structurepackaging_tutorial/
├── LICENSE
├── pyproject.toml
├── README.md
├── setup.cfg
├── src/
│   └── example_package/
│       ├── __init__.py
│       └── example.py
└── tests/
touch LICENSE
touch pyproject.toml
touch setup.cfg
mkdir src/mypackage
touch src/mypackage/__init__.py
touch src/mypackage/main.py
mkdir testspyproject.tomlThis file tells tools like pip and build how to create your project[build-system]
requires = [
    "setuptools>=42",
    "wheel"
]
build-backend = "setuptools.build_meta"build-system.requires gives a list of packages that are needed to build your package. Listing something here will only make it available during the build, not after it is installed.build-system.build-backend is the name of Python object that will be used to perform the build. If you were to use a different build system, such as flit or poetry, those would go here, and the configuration details would be completely different than the setuptools configuration described below.Setup.cfg setupUsing setup.cfg is a best practice, but you could have a dynamic setup file using setup.py[metadata]
name = example-pkg-YOUR-USERNAME-HERE
version = 0.0.1
author = Example Author
author_email = author@example.com
description = A small example package
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/pypa/sampleproject
project_urls =
    Bug Tracker = https://github.com/pypa/sampleproject/issues
classifiers =
    Programming Language :: Python :: 3
    License :: OSI Approved :: MIT License
    Operating System :: OS Independent

[options]
package_dir =
    = src
packages = find:
python_requires = >=3.6

[options.packages.find]
where = srcRunning the buildMake sure your build tool is up to dateWindowspy -m pip install --upgrade buildLinux/MAC OSpython3 -m pip install --upgrade buildCreate the buildpy -m buildReferenceshttps://packaging.python.org/tutorials/packaging-projects/
Package: ustatus
ustatusNOTE: Previously named pystatus, renamed due to a PyPI project naming conflict
preventing me from publishing the project.Configurable status window and/or bar for wayland compositors with support for
the wlr-layer-shell protocol.FeaturesTOML configuration.Supports configuration of different bars, and choice of bar at startup with
commandline argument.A variety of built-in modules:System tray module (StatusNotifierItem protocol), with Dbusmenu.Cpu monitor module, with usage graphs.MPRIS module.Battery module.Volume module.power-profiles-daemonremote module.Remote interface through dbus, currently allowing:Show/hide/toggle bar or status window.Running without installingThe project is built usingPoetry.
To run, clone the projectgit clone https://github.com/mbrea-c/ustatus.gitmove to the cloned directorycd ustatusinstall dependencies in a local venv withpoetry installand run ustatus withpoetry run ustatus <bar name>User-wide installation from sourceThe project is built usingPoetry.To build
locally, clone the projectgit clone https://github.com/mbrea-c/ustatus.gitmove to the cloned directorycd ustatusand buildpoetry buildThis will create two files in thedistdirectory,dist/ustatus-<version_number>.tar.gz
dist/ustatus-<version_number>-py3-none-any.whlFor a user-wide installation, runcd dist
pip install --upgrade ustatus-<version_number>.tar.gzConfigurationSee theconfiguration guidefor details. An example configuration file can be
found inexamples/ustatus.tomlIs this in an usable state?I think so, I have used (and still use) this in my daily-driver machine for about 6 months.
However, there are currently some limitations that some might consider deal
breaking:The UI respects the system GTK theme, but it is not possible to do separate
custom theming at the moment. I'm thinking of adding some form of this soon though, as GTK
allows theming using CSS fairly easily.In my daily driver setup I use a status window anchored to the right side of
the screen, so I haven't done a lot of testing with a horizontal statusbar.
It is possible, but there might (will) be bugs and rough edges. I'm willing to
work on this if there is interest.
Package: ustcjwxt
ustcjwxt-python-libustc jwxt api, for study onlyInstallationpipinstallustcjwxtStructurelog实现了一个简单的日志系统request_info记录了一些 requests 需要使用的信息session可以登录到教务系统，并提供 StudentSession 类，用于存储登录信息score可以获取学生的成绩当前功能: 获取成绩列表，计算 GPA / 加权平均分 / 算术平均分course_select可以进行选课 / 退课操作Usagesimple samplefromustcjwxtimportlogfromustcjwxt.sessionimportStudentSessionfromustcjwxt.scoreimport*log.set_logger_level('DEBUG')# logins=StudentSession()s.login_with_password(sys.argv[1],sys.argv[2])print(s.get_cookies())# get basic infoprint(s.get_student_info())withopen('avatar.jpg','wb')asf:f.write(s.get_student_avatar())# get scoregradeList=get_gradeList_all(s)print(grade_calcGpa(gradeList))print(grade_calcWeightedScore(gradeList))print(grade_calcArithmeticScore(gradeList))course operation sampleimportsysfromustcjwxtimportlogfromustcjwxt.sessionimportStudentSessionfromustcjwxt.course_selectimport*s=StudentSession()s.login_with_password(sys.argv[1],sys.argv[2])# 退课: IS4001.01result=drop_Lesson(s,'IS4001.01')ifresult['success']:print('课程已退')else:print(f'课程未退成功 (报错信息：{result["errorMessage"]["textZh"]})')# 选课: IS4001.01ifcheck_courseAvailable(s,'IS4001.01'):print('课程可选')result=add_Lesson(s,'IS4001.01')ifresult['success']:print('课程已选中')else:print(f'课程未选中 (报错信息：{result["errorMessage"]["textZh"]})')else:print('课程不可选 (人员已满)')课程交易importsys,timefromustcjwxt.sessionimportStudentSessionfromustcjwxt.course_selectimport*courseCode='IS4001.01's_give=StudentSession()s_give.login_with_password('PB********','********')s_get=StudentSession()s_get.login_with_password('PB********','********')# 预加载数据，减小延迟load_cache(s_give)load_cache(s_get)time.sleep(1)drop_Lesson(s_give,courseCode,delay_ms=0)add_Lesson(s_get,courseCode,delay_ms=0)
Package: ustick
# ustick
Ustick is a cli tool to create, store, and formatted display your console stickers.
It stores stickers as data in ~/.notes file and show formatted data to you.
Stickers are limited in size, if you get over it - you’ll know.## Installation
Use pip to install the package:` pip install ustick `or clone the repository and run pip3:` git clonehttps://github.com/hexpizza/ustick.gitcd ustick pip3 install ./ `## Usage
To add sticker run:` ustick-a'My first note to feed my cat at 09.00am' `To show stickers run ‘ustick’ or ‘ustick -s’:` ustick/=#3792================\|My first note to feed | |my cat at 09.00am     | |                      | |                      |\======================/`There is a mechanism to find stickers with a keyword, which can be word, phrase or sticker ID. if it’s in one of the stickers, the sticker will be shown to you with a coloured pard which you required:` ustick-f'my cat' `To remove all the stickers you can run and apply your choise:` ustick--remove-allAre you sure to remove all notes? (yes/no): yes `
Package: ustogres
Installpip install justogresUsage0. importfrom justogres import clientPsql1. Create client objectpsql = clientPsql(
        host = <your host>,
        user = <your user>,
        password = <your password>,
        port=<your port (optional)>,
        db_name=<your database name>,
    )2. execute query or insert method2.1 exec_query()psql.exec_query(
    <your sql query>,
    chunksize = <chunksize (optional)>)if query return something, method return pandas.Dataframe object2.2 insert() -> return Nonepsql.insert(
    <your pd.DataFrame object>,
    table_name=<your table name>, #if doesn't exist, will be created
    schema=<your schema name>, #should be created previously
    chunksize=<your chunksize to load (default: 1000)>)Examples:first we must init clientfrom justogres import clientPsql

psql = clientPsql(
        host = os.environ.get("host_justo_pg"),
        user = os.environ.get("username_justo_pg"),
        password = os.environ.get("password_justo_pg"),
        port=os.environ.get("port_justo_pg"),
        db_name='postgres',
    )Then follow this options:1.if we are gona execute queryq="""DELETE 
    FROM schema_name.table_name 
    WHERE column_name='value';"""
psql.exec_query(q)1.1 (special case) if we are gonna readq="""SELECT * 
    FROM schema_name.table_name;"""
df = psql.read(q)optional: read with pandas libraryq="""SELECT * 
    FROM schema_name.table_name;"""
df = psql.read_with_pandas(q)2. if we are gonna insertdf = pd.read_csv('example.csv')
psql.insert(
    df,
    table_name='test_table',
    schema='test_schema',
    )
Package: ustorage
UStorageUnified Storage Interface for Python.
Copied and decoupled fromFlask-FSfor working anywhere.Thanks toFlask-FSSee alsodjango-storagesInstallation$ pip install ustorageQuick startfromustorage.s3importS3Storageoptions={'endpoint':'https://s3.cn-north-1.amazonaws.com.cn','access_key':'<AccessKey>','secret_key':'<SecretKey>','bucket':'my-bucket','region':'cn-north-1',}fs=S3Storage(options)fs.write('hello.txt','Hello, World!')fs.exists('hello.txt')fs.read('hello.txt')fs.delete('hello.txt')
Package: ustr
xstrNew python3 strings just dropped.Installationpip3installxstrfromxstrimportustrfromxtrimportdstrfromxstrimporthstrorimportxstrorimporthstr# import dstr# import ustrHypenString  --    hstr()fromxstrimporthstrx=hstr('hello new world and all who inhabit it.')print(x)# hello-new-world-and-all-who-inhabit-it.print(x.original())# hello new world and all who inhabit it.outputhello-new-world-and-all-who-inhabit-it.hello new world and all who inhabit it.DotString   --  dstr()fromxstrimportdstrx=dstr('hello new world and all who inhabit it.')print(x)# hello.new.world.and.all.who.inhabit.it.print(x.original())# hello new world and all who inhabit it.outputhello.new.world.and.all.who.inhabit.it.hello new world and all who inhabit it.UnderlineString --  ustr()fromxstrimportustrx=ustr('hello new world and all who inhabit it.')print(x)# hello_new_world_and_all_who_inhabit_it.print(x.original())# hello new world and all who inhabit it.outputhello_new_world_and_all_who_inhabit_it.hello new world and all who inhabit it.
Package: ustreasurycurve
USTreasuryCurveThis code pulls in the nominal and real yield curves from the US Treasury's website for a date range (inclusive) into a Pandas dataframe. The nominal rates start on January 2, 1990 and the real rates begin on January 2, 2003. The US Treasury updates these yields daily.Install packagepip install ustreasurycurveUsageimport ustreasurycurve as ustcurvePull in nominal US Treasury curveustcurve = ustcurve.nominalRates('2010-06-30', '2022-06-30')Pull in real US Treasury curveustrcurve = ustcurve.realRates('2010-06-30', '2022-06-30')Pull in nominal US Treasury curve using an unverified HTTPS requestustcurve = ustcurve.nominalRates('2010-06-30', '2022-06-30', False)
Package: ustrid
This package generates unique string identifiers.fromustridimportustridunique_string_id=ustrid()Under the hood:importuuidimportthreadingdefustrid():"""Generate a unique string identifier (thread-safe)"""returnUstrid.run()classUstrid:"""Private class to generate unique string identifiers (thread-safe)"""_lock=threading.Lock()_count=0@classmethoddefrun(cls):"""Generate a unique string identifier (thread-safe)"""withcls._lock:cls._count+=1return"{}-{}".format(cls._count,uuid.uuid4())Installation:pipinstallustrid