Saravanan666/pypi-org huggingface dataset:
Package: hcs
“Hidden Console Start ⚙️Hide console and execute applications in background. HCS (Hidden Console
Start) is a good alternative to simulate background process (process &)
as in GNU/Linux systems.GNU/Linux$ ping 127.0.0.1 > log.txt &Windows$ hcs -e "ping 127.0.0.1 > log.txt"What can I do with HCS?Launch applications in backgroundLaunch all the processes that you want with one call to HCS (one
subprocess in one thread for each application)InstallationYou can install or upgrade HCS with:$ pip install hcs--upgradeOr you can install from source with:$gitclonehttps://github.com/RDCH106/hidden_console_start.git--recursive$cdhidden_console_start$pipinstall.Quick example$hcs-e"ping 127.0.0.1 > log.txt""mspaint"The example executes ping to127.0.0.1redirecting the result tolog.txtfile and launch Microsoft Paint at the same time.
Package: hcsapi
hcsapi📥다운로드git을 통해 리포지토리 코드를 설치하실 수 있습니다.윈도우나 리눅스의 터미널에서 다음과 같이 입력합니다.python-mpipinstall-Upip
pipinstallhcsapi또는python-mpipinstall-Upip
pipinstallgit+https://github.com/hcsapi/hcsapi.git@main업데이트pip install hcsapi --upgrade🤖사용 방법이곳의 예제를 참고하세요.지원하는 모든 지역이름 보기지원하는 지역 이름은 다음과 같습니다:'서울', '서울시', '서울교육청', '서울시교육청', '서울특별시''부산', '부산광역시', '부산시', '부산교육청', '부산광역시교육청''대구', '대구광역시', '대구시', '대구교육청', '대구광역시교육청''인천', '인천광역시', '인천시', '인천교육청', '인천광역시교육청''광주', '광주광역시', '광주시', '광주교육청', '광주광역시교육청''대전', '대전광역시', '대전시', '대전교육청', '대전광역시교육청''울산', '울산광역시', '울산시', '울산교육청', '울산광역시교육청''세종', '세종특별시', '세종시', '세종교육청', '세종특별자치시', '세종특별자치시교육청''경기', '경기도', '경기교육청', '경기도교육청''강원', '강원도', '강원교육청', '강원도교육청''충북', '충청북도', '충북교육청', '충청북도교육청''충남', '충청남도', '충남교육청', '충청남도교육청''전북', '전라북도', '전북교육청', '전라북도교육청''전남', '전라남도', '전남교육청', '전라남도교육청''경북', '경상북도', '경북교육청', '경상북도교육청''경남', '경상남도', '경남교육청', '경상남도교육청''제주', '제주도', '제주특별자치시', '제주교육청', '제주도교육청', '제주특별자치시교육청', '제주특별자치도'지원하는 모든 학교종류 보기지원하는 학교급 이름은 다음과 같습니다:'유치원', '유','유치''초등학교', '초','초등''중학교', '중','중등''고등학교', '고','고등''특수학교', '특','특수','특별'↩️리턴값모든 리턴값은 Dict로 반환됩니다.리턴값 구조는 다음과 같습니다:{"error":Boolean(True,False),'code':"처리코드(밑의 처리코드 종류 참조)","message":"해당 에러나, 성공 상황에 대한 설명"}처리코드 종류성공 = "SUCCESS"존재하지 않는 지역, 학교급 = "FORMET"학교 검색 실패 = "NOSCHOOL"학생 검색 실패 = "NOSTUDENT"알 수 없는 에러 = "UNKNOWN"💡 TIP리턴값의'code'를 이용하시면 성공, 실패 여부, 실패 이유를 모두 알 수 있습니다.또한'message'로 이용자에게 바로 실패 이유를 알릴 수 있습니다.원본 소스의 저작권은 331leo님에게 있습니다.코드 일부분(transkey 부분)의 저작권은 blluv 님에게 있습니다.
Package: hcs-cli
horizon-cloud-service-clihorizon-cloud-service-cliOverviewTry it outPrerequisitesInstallationMac & LinuxWindowsUse the CLIDocumentationContributingLicenseOverviewCommand line toolbox forVMware Horizon Cloud Service (HCS) Next-Gen. It provides human-friendly operations based on HCS REST API.Try it outPrerequisitesPython 3.10+Pip3Refer toSetup Prerequisitesfor more details.InstallationMac & LinuxInstall the toolbrew install python3
pip3 install hcs-cliWindowsInstall the tool.pip install hcs-cliIf you have python installed with option "Add python to path", it should be fine. Otherwise, you need to add python and it's Script directory to path.Use the CLIUse with default public HCS service.hcs loginRun a command, for example, list templates:hcs admin template listDocumentationHCS CLI - User GuideHCS CLI - CheatsheetHCS CLI - Dev GuideHCS Plan - template engine for HCSContext ProgrammingContributingThe horizon-cloud-service-cli project team welcomes contributions from the community. Before you start working with horizon-cloud-service-cli, please read and sign our Contributor License AgreementCLA. If you wish to contribute code and you have not signed our CLA, our bot will prompt you to do so when you open a Pull Request. For any questions about the CLA process, please refer to ourFAQ.LicenseApache 2.0
Package: hcscom
hcscomDocumentationA python3 class for remote control of manson hcs lab power supplies.Manson lab power supply units can be controlled via usb.Communication is done via a builtin CP210x usb-serial bridge and 8N1@9600 port settings.clonesSome PeakTech branded devices have proven to be Manson devices, i.e.https://www.peaktech.de/productdetail/kategorie/schaltnetzteile/produkt/p-1575.htmlreturnsHCS-3402as response toGMODcommand which ishttps://www.manson.com.hk/product/hcs-3402-usb/LicenseThis software is distributed under GPLv3 with some the extension that it's not to be used for commercial purposes.
It is explicitly denied that any company or organization monetizes on this software. Monetize does not only mean money,
it means gaining a competitive advantage of any kind by using this software.
In addition, the author explicitly denies the usage for people associated with military and
government agencies of any kind to whatever degree.This extension is a reaction to some blunt support request fromTechnica Engineering GmbHLeopoldstraße 236D - 80807 Münchenin May 2022 to basically fix problems they had during commercial usage of this software, for free.Deprecation of PyPi PackagesPackages on PyPi are no longer updated due to attempts of the Python Software Foundation to enforce new rules and basically flush out
developers who do not consent.Recent packages can be installed directly from git, i.e.pip install git+https://gitlab.com/Menschel/hcscom.git --upgrade
Package: hcs-grpc-client
pip install hcs-grpc-clientThis is aHederaConsensus Service (HCS) gRPC mirror node API Python client.It only has functionality to subscribe to a HCS topic on mirror node.For mirror node REST API, use curl or something like Pythonrequests.For all other interactions with Hedera, use an SDK:Python,Java,Javascript, orGo.How to Useimportgrpcfromhcs_grpc_clientimportTopicID,ConsensusTopic,ConsensusServiceStubrequest=ConsensusTopicQuery(topicID=TopicID(2010293))channel=grpc.insecure_channel("hcs.testnet.mirrornode.hedera.com:5600")stub=ConsensusServiceStub(channel)stream=stub.subscribeTopic(request)forrespinstream:# do whatever you needprint(resp)Make sure the topic exists or create your own topic with an SDK.  An example is given inexamples/.Seeexamplesfor mainnet example and other usages.How to Build(Ignore this section unless you want to customized the client and/or want to contribute to this project)Clone this repo:git clone --recurse-submodules https://github.com/wensheng/hcs-grpc-api-py-client.gitSetup virtual env for python then install dependencies:cd hcs-grpc-api-py-client
python3 -m venv venv
./venv/bin/python install -r requirements.txtGenerate code (compile .proto to .py):./compile.sh  # make sure deps.txt match compile_deps.sh
./compile_deps.shBuild package:rm -fr build dist
./venv/bin/python -m buildTest package:./venv/bin/pip uninstall hcs-grpc-client
./venv/bin/pip install dist/hcs-grpc-client-(current_version)-py3-none-any.whlUpload to Pypi (don't do this unless you're me):python -m twine upload dist/*
Package: hcss
hcss is a CSS compiler that that allows you to use HTML element hierarchy to
define CSS rules. Requires Python 2.2+. BSD-licensed.Input<div id="parent">
  margin: 10px;
  <div class="child">
    margin: 5px;
    border: 1px solid #000;
  </div>
</div>Outputdiv#parent {
  margin: 10px;
}
div#parent > div.child {
  margin: 5px;
  border: 1px solid #000;
}Setup$ pip install hcss # or
$ easy_install hcssLinksFull documentationDevelopment repositoryAuthor’s website
Package: hcvote
The Hare-Clark electoral system in PythonTheHare-Clark electoral systemis a preferential voting system used for elections in Tasmania and the Australian Capital Territory. This small Python package provides an implementation of this system, with the ability to load votes from a range of sources and formats.Table of ContentsThe voting systemInstallationUsageThePositionclassVote validationLoading from other sourcesThe voting systemTODOInstallationThis package is available on PyPI, and can be installed with pip;pipinstallhcvoteAlternatively, you can clone the repository and install it directly with pip;gitclonegit@github.com:LiamBlake/hcvote.gitcdhcvote
pipinstall.To install the development and testing tools, runpipinstall-e.[dev,test]UsageThePositionclassThe main functionality is contained by thePositionclass, which represents a position with one or more vacancies:fromhcvoteimportPosition# The names of the candidatesnames=["Platypus","Wombat","Kangaroo","Koala"]# Create a position with 2 available placesp=Position(no_vac=2,candidates=names)Votes can be added via theadd_votesmethod, which accepts a list of lists, where each sublist corresponds to a vote. Each vote is an ordered list of either the candidate names or corresponding (one-based) indices matching the order originally passed tocandidateswhen constructing thePosition;votes=[]# This vote has Wombat as the first preference, Platypus as the second, etc.votes[0]=["Wombat","Platypus","Koala","Wombat"]# Alternatively, (one-based) indices can be used.# This vote has Koala as the first preference, Wombat as the second, etc.votes[1]=[4,2,1,3]# Add the votes to the Positionp.add_votes(votes)To perform the count once all votes have been added, call thecount_votemethod:p.count_vote()The elected candidates are then available from theelectedproperty:p.electedwhich returns as list of the elected candidates.Vote ValidationTODOLoading votes from other sourcesTODO
Package: hda
WEkEO HDA API ClientThis package provides a fully compliant Python 3 client that can be used to search and download products using the Harmonized Data Access WEkEO API.HDA is a RESTful interface allowing users to search and download WEkEO datasets.Documentation about its usage can be found athttps://www.wekeo.eu/.The documentation for this package can be found at:https://hda.readthedocs.io/en/latest/ContributionContribute to the development of this client by creating an account on GitHub. You can follow this guidelines for a general overview of the needed steps:https://github.com/firstcontributions/first-contributions.Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update this README as appropriate - changes on the interface, version etc.LicencePlease refer to LICENSE.txt
Package: hdao-python-sdk
stable_coin_python_sdkPython SDK for HyperDao Stable Coin SystemInstallUsingpippip install hdao-python-sdkInstall from sourcegit clone https://github.com/hyperdao/stable_coin_python_sdk
cd stable_coin_python_sdk
python setup.py installUsageTestHyperDao stable coin system depends on HyperExchange mainnet. So the test cases should be run with HyperExchange testnet setup.
Please set the configuraions inconfig.pybefore runing tests.HX_TESTNET_RPC = 'http://192.168.1.121:30088/'
CDC_CONTRACT_ID = 'HXCSSGDHqaJDLto13BSZpAbrZoJf4RrGCtks'
FEEDER_CONTRACT_ID = 'HXCGba6bUaGeBtUQRGpHUePHVXzF1ygMAxR1'
PRICE_FEEDER = {'account': 'senator0', 'address': 'HXNWj42PcH3Q2gEQ9GnVV2y87qsXd8MCL85W'}
USER1 = {'account': 'da', 'address': 'HXNYM7NT7nbNZPdHjzXf2bkDR53riKxV9kgh'}Steps to run testscd tests
pytest
Package: hdate
Jewish/Hebrew date and Zmanim in native python 2.7/3.xOriginally ported from libhdate, seehttp://libhdate.sourceforge.net/for more details (including license)Installation using pip:$pipinstallhdateExamples:base code to provide times of the day in hebrew:>>>importhdate>>>importdatetime>>>c=hdate.Location("פתח תקוה",32.08707,34.88747,"Asia/Jerusalem",54)>>>z=hdate.Zmanim(date=datetime.date(2016,4,18),location=c,hebrew=True)>>>print(z)עלות השחר - 04:52:00
זמן טלית ותפילין - 05:18:00
הנץ החמה - 06:08:00
סוף זמן ק"ש מג"א - 08:46:00
סוף זמן ק"ש גר"א - 09:23:00
סוף זמן תפילה מג"א - 10:04:00
סוף זמן תפילה גר"א - 10:28:00
חצות היום - 12:40:00
מנחה גדולה - 13:10:30
מנחה קטנה - 16:25:30
פלג המנחה - 17:50:45
שקיעה - 19:12:00
צאת הכוכבים - 19:38:00
חצות הלילה - 00:40:00and in english:>>>z=hdate.Zmanim(date=datetime.date(2016,4,18),location=c,hebrew=False)>>>print(z)Alot HaShachar - 04:52:00
Talit & Tefilin's time - 05:18:00
Sunrise - 06:08:00
Shema EOT MG"A - 08:46:00
Shema EOT GR"A - 09:23:00
Tefila EOT MG"A - 10:04:40
Tefila EOT GR"A - 10:28:00
Midday - 12:40:00
Big Mincha - 13:10:30
Small Mincha - 16:25:30
Plag Mincha - 17:50:45
Sunset - 19:12:00
First stars - 19:38:00
Midnight - 00:40:00to provide the full hebrew date:>>>h=hdate.HDate(datetime.date(2016,4,26),hebrew=True)>>>print(h)יום שלישי י"ח בניסן התשע"ו ג' בעומר חול המועד פסחand in english:>>>h=hdate.HDate(datetime.date(2016,4,18),hebrew=False)>>>print(h)Monday 10 Nisan
Package: hdb
Persistent, hobbit-sized dictionariesExample Usageimportosimporthdb# Create a hobbit dictionary at location `pack`.pack=hdb.get('pack')# Set a key value pair.pack['food']='lembas'# Persist the dictionary to disk.pack.save()# Confirm that the dictionary was saved.# The `location` specifies the path on disk.print(pack.location)print(os.path.abspath(pack.location))print(os.path.exists(pack.location))We can later retrieve the dictionary like so:importhdbnew_session=hdb.get('pack')print(new_session)# We can then further edit the data, and store it to the same location.new_session['supplies']='taters'new_session.save()
Package: hdbcli
IntroductionThe Python Database API Specification v2.0 (PEP 249) defines a set of methods that provides a consistent database interface independent of the actual database being used. The Python extension module for SAP HANA implements PEP 249. Once you install the module, you can access and change the information in SAP HANA databases from Python.In PEP 249, autocommit is turned off by default. In the SAP HANA Python driver, autocommit is turned on by default.For information, see:PEP 249 – Python Database API Specification v2.0Getting StartedInstall viapip install hdbclior install manually via theHANA Client InstallQuick StartFor HANA tenant databases, use the port number 3**NN**13 (whereNNis the SAP instance number - e.g. 30013).For HANA system databases in a multitenant system, the port number is 3**NN**13.For HANA single-tenant databases, the port number is 3**NN**15.from hdbcli import dbapi
conn = dbapi.connect(
    address="<hostname>",
    port=3<NN>MM,
    user="<username>",
    password="<password>"
)
cursor = conn.cursor()Execute a single statement that does not return a result set:cursor.execute("CREATE TABLE T1 (ID INTEGER PRIMARY KEY, C2 VARCHAR(255))")
cursor.close()Use question mark parameter binding to insert values into the T1 table created above. The parameter values are supplied as a Python sequence and can be literal values or variable names. This example uses literal values:sql = 'INSERT INTO T1 (ID, C2) VALUES (?, ?)'
cursor = conn.cursor()
cursor.execute(sql, (1, 'hello'))
# returns True
cursor.execute(sql, (2, 'hello again'))
# returns True
cursor.close()Use named parameter binding to insert values into the T1 table. The values are supplied as a Python dictionary, and this example uses variable names.sql = 'INSERT INTO T1 (ID, C2) VALUES (:id, :c2)'
cursor = conn.cursor()
id = 3
c2 = "goodbye"
cursor.execute(sql, {"id": id, "c2": c2})
# returns True
cursor.close()Loop over the rows of the result set.sql = 'SELECT * FROM T1'
cursor = conn.cursor()
cursor.execute(sql)
for row in cursor:
    print(row)HelpSee theSAP HANA Client Interface Programming Referencefor details about developing with the SAP HANA Python Client.CommunitySAP Community provides a forum where you can ask and answer questions, and comment and vote on the questions of others and their answers.SeeSAP HANA Community Questionsfor details.Limitations of 32-bit Windows driverThe maximum length of a LOB column for the 32-bit Python driver on Windows is 2147483647.
The maximum rowcount that can be returned for the 32-bit Python driver on Windows is 2147483647.LicenseThe HANA Python Client is provided via theSAP Developer License Agreement.By using this software, you agree that the following text is incorporated into the terms of the Developer Agreement:If you are an existing SAP customer for On Premise software, your use of this current software is also covered by the
terms of your software license agreement with SAP, including the Use Rights, the current version of which can be found at:https://www.sap.com/about/agreements/product-use-and-support-terms.html?tag=agreements:product-use-support-terms/on-premise-software/software-use-rights
Package: hdc
Hyperdimensional Computing LibraryThis is a Python library for Hyperdimensional Computing.Easy-to-use:This library makes it painless to develop a wide range of Hyperdimensional Computing (HDC) applications and algorithms. For someone new to the field we provide Pythonic abstractions and examples to get you started fast. For the experienced researchers we made the library modular by design, giving you endless flexibility to prototype new ideas in no-time.Performant:The library is build on top of the high-performance PyTorch library, giving you optimized tensor execution without the headaches. Moreover, PyTorch makes it effortless to accelerate your code on a GPU.InstallationThe library is hosted on PyPi and Conda, use one of the following commands to install:pipinstallhdccondainstall-cconda-forgehdcDocumentationYou can find the library's documentationon the website.ExamplesWe have several examplesin the repository. Here is a simple one to get you started:importhdcimporttorchd=10000# number of dimensions### create a hypervector for each symbol# keys for each field of the dictionary: fruit, weight, and seasonkeys=hdc.functional.random_hv(3,d)# fruits are: apple, lemon, mangofruits=hdc.functional.random_hv(3,d)# there are 10 weight levelsweights=hdc.functional.level_hv(10,d)# the for seasons: winter, spring, summer, fallseasons=hdc.functional.circular_hv(4,d)# map a float between min, max to an index of size 10# we map the 10 weight levels between 0 to 200 gramsweight_index=hdc.functional.value_to_index(149.0,0,200,10)values=torch.stack([fruits[0],weights[weight_index],seasons[3],])# creates a dictionary:# record = key[0] * value[0] + key[1] * value[1] + key[2] * value[2]record=hdc.functional.struct(keys,values)#### Similar Python code## record = dict(#     fruit="apple",#     weight=149.0,#     season="fall"# )#This example creates a hypervector that represents the record of a fruit, storing its species, weight, and growing season as one hypervector. This is achieved by combining the atomic information units into a structure (similar to a Python dictionary).You will notice that we first declare all the symbols which are used to represent information. Note the type of hypervector used for each type of information, the fruits and keys use random hypervectors as they represent unrelated information whereas the weights and seasons use level and circular-hypervectors because they have linear and circular-correlations, respectively.ContributingCreating a New ReleaseA GitHub release triggers a GitHub action that builds the library and publishes it to PyPi and Conda in addition to the documentation website.Before creating a new GitHub release, increment the version number insetup.pyusingsemantic versioning.When creating a new GitHub release, set the tag to be "v{version number}", e.g., v1.5.2, and provide a clear description of the changes.LicenseThis library isMIT licensed.
Package: hdcms
hdcmsThis library is available on pypihere. Install usingpip install hdcms.A very simple example:importhdcmsashdchdc.generate_examples(visualize=True)gaussian_sum_stat=hdc.regex2stats1d(r"gaus_\d+.txt")laplacian_sum_stat=hdc.regex2stats1d(r"laplace_\d+\.txt")print(hdc.compare(gaussian_sum_stat,laplacian_sum_stat))hdc.write_image(gaussian_sum_stat,"tmp.png")For more documentation: seeexamples/directory.DependenciesThis library is built on top of thehdcms-bindingspackage, which exposes python bindings to a C library.numpyis a necessary dependency for every function.matplotliband scipy are needed forgenerate_example(), which will generate a random synthetic data set.Change Log0.1.27 version 0.1.27: updating rounding in gaussian2d code
0.1.26 Bug fix: npeaks for y-hdc for visualization was possible
0.1.25 Added missing optional args for filenames2stats*
0.1.24 Add npeaks for visualization
0.1.23 Add xtol
0.1.22 Fix new colors for write_image
0.1.21 New colors for write_image
0.1.20 Change name from ms_valid_data_format to is_valid_ms_data_format + scaling, start, end, num_bins
0.1.19 Return image from write_image
0.1.18 Add labels to visualization configuration options
0.1.17 Use matplotlib axes rather than my own
0.1.16 Bug fixes (text for x axis, names for regex2filenames)
0.1.15 Return image from write_image, rather than writing to file
0.1.14 Add new params to write_image
0.1.13 Add new params to write_image
0.1.12 Add params to write_image
0.1.11 Fix problems introduced by rename
0.1.10 Really rename (broken)
0.1.9 Rename, performance for visulize in 1D case (broken)
0.1.8 Add documentation
Package: hdcms-bindings
hdcms-bindingsThis is a wrapper for thehdcmsC source. It is not meant to be used as a standalone package. Usehdcmsinstead.The current dependency graph for the projects is as follows:hdcms (C files source + binary) -> hdcms-bindings (C-extension/.so file) -> hdcms (python functions)This project (the middle one) isn't meant to be used as a standalone project, but I couldn't get python to generate the C-extension and export python functionality in the same package which is why I split it up. If you would like to use it however, it is available at pypihere.Examplesimporthdcms_bindingsashdcbindc9=hdcbind.filenames_to_stats_1d("data/CM1_9_1.txt,data/CM1_9_2.txt,data/CM1_9_3.txt")c10=hdcbind.filenames_to_stats_1d("data/CM1_10_1.txt,data/CM1_10_2.txt,data/CM1_10_3.txt")c3=hdcbind.filenames_to_stats_1d("data/CM1_3_1.txt,data/CM1_3_2.txt,data/CM1_3_3.txt")print(hdcbind.compare_compound_1d(c10,c8),"\n")print(hdcbind.compare_all_1d([c10,c8,c9]))You can also use the 2d functions by changing the_1dsuffix to_2d.ExtendingIf you extend this code, think carefully about who has owner ship
over the data in a vector/matrix and the numpy reference count. The only way
this would be tricky is if a matrix struct exists in two functions, and you
can't tell one of the function's matrix that it doesn't own the data anymore,
and you give the data to a NUMPY function and it get garbage
collected and frees its data (now the matrix struct thinks it has
valid data when it doesn't). I'm pretty sure I don't make this
mistake, but it would be easy to make in the future. The fix is
just to copy the data (which will make it slightly inefficient,
but that's okay).Referencescheck pointer typesexampleOfficial documentationhttps://docs.python.org/3/c-api/arg.html#other-objectshttps://docs.python.org/3/extending/extending.html#building-arbitrary-valueshttps://numpy.org/doc/stable/user/c-info.how-to-extend.htmlhttps://numpy.org/doc/stable/reference/c-api/array.html#c.PyArray_SimpleNewhttps://numpy.org/doc/stable/reference/c-api/dtype.htmlChangelog0.1.6 Add xtol0.1.5 Update start, stop, num_bins, and scaling for both 1d and 2d0.1.4 Rename package (setup.py has the import name, which must match the c lib symbols)0.1.3 Rename package for real for real0.1.2 Rename package for real (broken)0.1.1 Rename package (broken)0.1.0 Add documentation0.0.8 Add keyword args: addingdesingularizationandmax_peaksto thefilenames_to_statsfunctions, andstart,end, andnum_binsto the comparison functions. They all are initalized with the default args they had before.0.0.7 Change strlcpy to strncpy for Linux0.0.6 Ignore headers in data files