Saravanan666/pypi-org huggingface dataset:
Package: pybnf1.2.1
![alt text](docs/Logo1.png “PyBioNetFit”)PyBioNetFit (PyBNF) is a general-purpose program for parameterizing biological models specified using the BioNetGen
rule-based modeling language (BNGL) or the Systems Biology Markup Language (SBML). PyBioNetFit offers a suite of
parallelized metaheuristic algorithms (differential evolution, particle swarm optimization, scatter search) for
parameter optimization. In addition to model parameterization, PyBNF supports uncertainty quantification by
bootstrapping or Bayesian approaches, and model checking. PyBNF includes an adaptive Markov chain Monte Carlo (MCMC) sampling algorithm, which supports Bayesian inference. PyBNF includes the Biological Property Specification Language
(BPSL) for defining qualitative data for use in parameterization or checking. It runs on most Linux and macOS
workstations as well on computing clusters.For documentation, refer to [Documentation_PyBioNetFit.pdf](Documentation_PyBioNetFit.pdf) or the online documentation at <https://pybnf.readthedocs.io/en/latest/>.PyBioNetFit is released under the BSD-3 license. For more information, refer to the
[LICENSE](LICENSE). LANL code designation: C18062
Package: pybnfalabuda
![alt text](docs/Logo1.png “PyBioNetFit”)PyBioNetFit (PyBNF) is a general-purpose program for parameterizing biological models specified using the BioNetGen
rule-based modeling language (BNGL) or the Systems Biology Markup Language (SBML). PyBioNetFit offers a suite of
parallelized metaheuristic algorithms (differential evolution, particle swarm optimization, scatter search) for
parameter optimization. In addition to model parameterization, PyBNF supports uncertainty quantification by
bootstrapping or Bayesian approaches, and model checking. PyBNF includes an adaptive Markov chain Monte Carlo (MCMC) sampling algorithm, which supports Bayesian inference. PyBNF includes the Biological Property Specification Language
(BPSL) for defining qualitative data for use in parameterization or checking. It runs on most Linux and macOS
workstations as well on computing clusters.For documentation, refer to [Documentation_PyBioNetFit.pdf](Documentation_PyBioNetFit.pdf) or the online documentation at <https://pybnf.readthedocs.io/en/latest/>.PyBioNetFit is released under the BSD-3 license. For more information, refer to the
[LICENSE](LICENSE). LANL code designation: C18062
Package: pybo
PYBO - Tibetan NLP in PythonOverviewbo tokenizes Tibetan text into words.Basic usageGetting startedRequires to have Python3 installed.python3 -m pip install pyboTokenizing a stringdrupchen@drupchen:~$botok-string"༄༅། །རྒྱ་གར་སྐད་དུ། བོ་དྷི་སཏྭ་ཙརྻ་ཨ་བ་ཏ་ར། བོད་སྐད་དུ། བྱང་ཆུབ་སེམས་དཔའི་སྤྱོད་པ་ལ་འཇུག་པ། །སངས་རྒྱས་དང་བྱང་ཆུབ་སེམས་དཔའ་ཐམས་ཅད་ལ་ཕྱག་འཚལ་ལོ། །བདེ་གཤེགས་ཆོས་ཀྱི་སྐུ་མངའ་སྲས་བཅས་དང༌། །ཕྱག་འོས་ཀུན་ལའང་གུས་པར་ཕྱག་འཚལ་ཏེ། །བདེ་གཤེགས་སྲས་ཀྱི་སྡོམ་ལ་འཇུག་པ་ནི། །ལུང་བཞིན་མདོར་བསྡུས་ནས་ནི་བརྗོད་པར་བྱ། །"LoadingTrie...(2s.)༄༅།_།རྒྱ་གར་སྐད་དུ།_བོ་དྷི་སཏྭ་ཙརྻ་ཨ་བ་ཏ་ར།_བོད་སྐད་དུ།_བྱང་ཆུབ་སེམས་དཔའི་སྤྱོད་པ་ལ་འཇུག་པ།_།སངས་རྒྱས་དང་བྱང་ཆུབ་
སེམས་དཔའ་ཐམས་ཅད་ལ་ཕྱག་འཚལ་ལོ།_།བདེ་གཤེགས་ཆོས་ཀྱི་སྐུ་མངའ་སྲས་བཅས་དང༌།_།ཕྱག་འོས་ཀུན་ལའང་གུས་པར་ཕྱག་འཚལ་
ཏེ།_།བདེ་གཤེགས་སྲས་ཀྱི་སྡོམ་ལ་འཇུག་པ་ནི།_།ལུང་བཞིན་མདོར་བསྡུས་ནས་ནི་བརྗོད་པར་བྱ།_།Tokenizing a list of filesThe command to tokenize a list of files in a directory:bo tok <path-to-directory>For example to tokenize the filetext.txtin a directory./document/with the following content:བཀྲ་ཤི་ས་བདེ་ལེགས་ཕུན་སུམ་ཚོགས། །རྟག་ཏུ་བདེ་བ་ཐོབ་པར་ཤོག། །I use the command:$ bo tok ./document/...which create a filetext.txtin a directory./document_pybocontaining:བཀྲ་ ཤི་ ས་ བདེ་ལེགས་ ཕུན་སུམ་ ཚོགས །_། རྟག་ ཏུ་ བདེ་བ་ ཐོབ་པ ར་ ཤོག །_།Sorting Tibetan words$bokakhato-sort.txtThe expected input is one word or entry per line in a .txt file. The file will be overwritten.FNR - Find and Replace with a list of regexesbo fnr <in-dir> <regex-file> -o <out-dir> -t <tag>-oand-tare optionalText files should be UTF-8 plain text files. The regexes should be in the following format:<find-pattern><tab>-<tab><replace-pattern>Acknowledgementspybois an open source library for Tibetan NLP.We are always open to cooperation in introducing new features, tool integrations and testing solutions.Many thanks to the companies and organizations who have supported pybo's development, especially:Khyentse Foundationfor contributing USD22,000 to kickstart the projectTheBarom/Esukhia canon projectfor sponsoring training data curationBDRCfor contributing 2 staff for 6 months for data curationthird_party/rules.txtis taken fromtibetan-collation.ContributingFirst clone this repo. Create virtual environment and activate it. Then install the dependencies$pipinstall-e.
$pipinstall-rrequirements-dev.txtNext, setup uppre-commitby creating pre-commit git hook$pre-commitinstallPlease, followaugular commit message formatfor commit message. We have setuppython-semantic-releaseto publishpybopackage automatically based on commit messages.That's all, Enjoy contributing 🎉🎉🎉LicenseThe Python code is Copyright (C) 2019 Esukhia, provided underApache 2.contributors:DrupchenÉlie RouxNgawang TrinleyTenzinJoyce Mackzenzie for reworking the logo
Package: pyboat
pyBOAT - A Biological Oscillations Analysis ToolkitTools for time-frequency analysis of noisy non-stationary signals with Morlet Wavelets.
See thegithub repofor general documentation orthis paperfor more details.FeaturesOptimal sinc filterFourier analysisWavelet analysisRidge detectionPhase extractionAmplitude estimationSynthetic signal generatorEnsemble/Summary statistics
Package: pybob
pybobA collection of geospatial and other tools that I find useful.Installing Pybob# Install the required librariescondainstallh5pynumbadescartesgdal
pipinstallllc# Clone the repository (using git ssh)gitclonegit@github.com:iamdonovan/pybob.git# install the development verion in editing modepipinstall-e[path2folder/pybob]Basic usagefrompybobimportGeoImg# Open a geotiff:test=GeoImg.GeoImg('myraster.tif')# plot raster to screentest.diplay()# crop raster to extenttest.crop_to_extent([xmin,xmax,ymin,ymax],band)
Package: pyboca
PybocaPython api 外交部中文名字轉拼音安裝 installationpip install pybocaQuickstartimportpybocaimportpandasaspdpyboca.ch2en("王小明")'WANG,HSIAO-MING'pyboca.ch2en("王小明",encode='漢語')Only support ['漢語拼音', '通用拼音', '威妥瑪(WG)拼音', '國音第二式拼音'].pyboca.ch2en("王小明",encode='漢語拼音')'WANG,XIAO-MING'df=pd.read_csv('datasets/example.csv')df.head()nameperson_id0張家恬D2919988421王靖雯H1944080892林靜宏H2958038113張美君E1947145524高駿貴F198021497df['en_name']=df['name'].map(lambdaname:pyboca.ch2en(name))dfnameperson_iden_name0張家恬D291998842CHANG,CHIA-TIEN1王靖雯H194408089WANG,CHING-WEN2林靜宏H295803811LIN,CHING-HUNG3張美君E194714552CHANG,MEI-CHUN4高駿貴F198021497KAO,CHUN-KUEI5林昕啟H191737341LIN,HSIN-CHI6李宜潔F294348551LI,I-CHIEH7唐初名A295890915TANG,CHU-MING8賴聿名C296038555LAI,YU-MING9林威依H196003215LIN,WEI-I10林向瑄H294636343LIN,HSIANG-HSUAN11賴建弘G294921060LAI,CHIEN-HUNG12林明倫B294449184LIN,MING-LUN13劉萱生F294268352LIU,HSUAN-SHENG14韓瑋婷H194459273HAN,WEI-TING15倪舒以B197405557NI,SHU-I16陳淑忠F197667300CHEN,SHU-CHUNG17林亮丞A295814004LIN,LIANG-CHENG18陳信秀D291184857CHEN,HSIN-HSIU19魏佩珊A199068506WEI,PEI-SHAN20楊佳琪H295286463YANG,CHIA-CHI21謝志瑋C199003285HSIEH,CHIH-WEI22吳政軍E195284142WU,CHENG-CHUN23林嘉玲B294371832LIN,CHIA-LING24謝珮雄G193221238HSIEH,PEI-HSIUNG25楊文琳C194689267YANG,WEN-LIN26唐志軒D299747561TANG,CHIH-HSUAN27洪淑娟A294154750HUNG,SHU-CHUAN28張廷江H299453415CHANG,TING-CHIANG29袁怡孜C296185362YUAN,I-TZU............70彭智翔G192599844PENG,CHIH-HSIANG71林建智B198546968LIN,CHIEN-CHIH72吳雅琳B193962739WU,YA-LIN73劉毅劭C197265198LIU,I-SHAO74潘美惠B298127901PAN,MEI-HUI75陳盈珍C193906376CHEN,YING-CHEN76林嘉芷H292532959LIN,CHIA-CHIH77林守惟E296666186LIN,SHOU-WEI78吳政岑E298232848WU,CHENG-TSEN79臧健豪C198360932TSANG,CHIEN-HAO80王秀瑞B297539247WANG,HSIU-JUI81李政侑C298627158LI,CHENG-YU82陳慧珊F294194893CHEN,HUI-SHAN83賴佳雯G295856348LAI,CHIA-WEN84楊惠靖A296304623YANG,HUI-CHING85郭新倩F299186113KUO,HSIN-CHIEN86黃瓊文C293955095HUANG,CHIUNG-WEN87周之欣B291105185CHOU,CHIH-HSIN88蔡裕南E299620299TSAI,YU-NAN89沈惠玲A191868228SHEN,HUI-LING90黃建成H293797445HUANG,CHIEN-CHENG91周曼容E294941917CHOU,MAN-JUNG92蔡雅鈴C292238399TSAI,YA-LING93陳凡新F197096043CHEN,FAN-HSIN94劉家豪B291260841LIU,CHIA-HAO95洪嘉枝B193443659HUNG,CHIA-CHIH96阮湖銘E297864506JUAN,HU-MING97曹哲韋B297510724TSAO,CHE-WEI98李明岑H294769356LI,MING-TSEN99柳山哲H293622498LIU,SHAN-CHE100 rows × 3 columns
Package: pybode
Bode Plot with DHO800/900A python support package plots a Bode plot with gain and phase. The program is tested with DHO914 as Oscilloscope and DG1022Z as function generator.Test setupConnect the DG1000Z and the DHO800/900 with same Ethernet as the computer.Two Pin Component Frequency CharacterisationGenerator CH1 should be connected to the oscilloscope CH1 via a BNC or SMA cable. Same connection for CH2 but the channel 2 has a T-connector in between and the component is between plus and minus of the stub. The wire length of CH1 and CH2 should be the same and the cable at the end of the oscilloscope should be terminated with 50 Ohm.Circuit Transfer FunctionGenerator CH1 should be connected to the oscilloscope CH1 via a BNC or SMA cable.The generator CH2 is connected to the circuit input and the circuit output directly to oscilloscope CH2.
The wire length of CH1 and CH2 should be the same and the cable at the end of the oscilloscope should be terminated with 50 Ohm.Python RequirementsThis package needs numpy/scipy/matplotlib/pylabdevs/pydg1000z/pydho800 environment.InstallingThere is a Python and PyPi packages that can be installed usingpip install  numpy scipy matplotlib pylabdevs pydho800 pydg1000z pybodeUsageThe basic syntax ispython bode.py MIN_FREQ MAX_FREQ [FREQ_COUNT], so if you, for example, want to test your DUT between 1kHz and 2.2Mhz, with 100 steps (default is 50),
you can do it like this:python bode.py 1e3 2.2e6 100.By default only the Amplitude diagram is measured and plotted. If you also want to get the Phase diagram, you will have to specify the--phaseflag.If you want to use the measured data in another software like OriginLab or Matlab, you can export it to a semicolon-seperated CSV file with the--outputoption.So a typical command line would like this:python bode.py 1e3 2.2e6 100 --osc_ip 10.0.0.123 --awg_ip 10.0.0.124  --phase --output out.csvTo see the full list of possible options callpython bode.py --help.LicenseThis program is licensed under the MIT License. SeeLICENSEfile for more info.AcknowledgementsBased on the original work byDS1054_BodePlotterI have re-used code parts and the method of the measurement.
Package: pyboil
pyboilpython package for initializing a python packageGetting startedfor usage information, typepyboil --help

usage: Pyboil [-h] -n NAME -a AUTHOR [-v VERSION] [-d DESCRIPTION] [-e EMAIL] [-u URL]

Initialize a basic python wheel package setup via cli script

options:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  Specifies the name of the package to be initialized.
  -a AUTHOR, --author AUTHOR
                        The author of this package (likely you!).
  -v VERSION, --version VERSION
                        Version of the wheel to be placed in setup.py
  -d DESCRIPTION, --description DESCRIPTION
                        A short description of the package's purpose.
  -e EMAIL, --email EMAIL
                        email address for inquiries regarding the package.
  -u URL, --url URL     Project website link (Github or Pypi).

Get started fast!NAME and AUTHOR are required fields.
VERSION will default to 0.1.0 if not included.
DESCRIPTION will default to "New python package!" if not included.
EMAIL and URL will both default to an empty string ("") if not included.Generated treefor now, this script will generate a specific file structure as shown below{NAME}
  -> __init__.py
build.sh
pyproject.toml
setup.pywhen you run ./build.sh, it will install the build and twine python module.  The wheel will be built using the 'build' package, and it will be uploaded to Pypi via Twine.  Once you run build.sh, you will eventually be prompted for your Pypi username and password.  Pass this verification and your wheel will be uploaded.  After uploading the wheel, the script deletes all artifacts created locally.I hope to expand this with more options to include various other build files, such as the MANIFEST.in.  For now, a simple script to quick start projects is all that I needed.
Package: pyboilerplate
If you are like me, starting a new Python project from the scratch can be
boring: create a setup.py, documentation, installation instructions, forget a
file or two in the manifest, etc. This all is a time-consuming and error prone
work, which gives no intellectual satisfaction. Yet, this is necessary to make
your project a good citizen in the open source community.Boilerplate produces beautiful skeletons for your Python projects so you can
get up and running fast. It is influenced by this blog post:http://jeffknupp.com/blog/2013/08/16/open-sourcing-a-python-project-the-right-way/,
although we do not follow these recommendations by the letter.The filesystem structureTheboilerplate start <project>command will create the following tree
under the current directory:.
|- .gitignore
|- LICENSE
|- MANIFEST.in
|- INSTALL.rst
|- README.rst
|- VERSION
|- requirements.txt
|- requirements-dev.txt
|- setup.py
|- docs/
|   |- conf.py
|   |- index.rst
|   |- make.bat
|   |- Makefile
|   |- _static/*
|   \- _templates/*
\- src/
    \- <project>
        |- __init__.py
        |- __meta__.py
        |- <project>.py
        \- test/
            |- __init__.py
            \- test_<project>.pysetup.pysrc/*docs/*README.rst and INSTALL.rstVERSIONrequirements.txtMANIFEST.inLICENSE.gitignore
Package: pyboin
pyboinpyboin is Pure-Python Japanese character interconverter for Hiragana and Vowel.「こんにちは」 -> 「おんいいあ」RequirementPython3Usageimportpyboin# Argument 'cv' may be omitted.# Specify katakana or hiragana as the first argument.pyboin.text2boin('こんにちは',cv='katakana')# => 'オンイイア'pyboin.text2boin('こんにちは',cv='hiragana')# => 'おんいいあ'pyboin.convert_vowel('ス','ア')# => 'サ'pyboin.convert_vowel('カ','オ')# => 'コ'pyboin.romanize('a','s')# => 'サ'Installation$pipinstallpyboinContributingBug reports and pull requests are welcome on GitHub athttps://github.com/AjxLab/pyboin.AuthorTatsuya Abe'''abe12mccc.jp'''
Package: pybokio
PyBokioUnofficial SDK for interacting withBokioCurrently the project is in very early development and very little
functionality can be used. But if you are eager to get stuff going,
please consider helping out bycontributing!UsageConnectingConnecting with credentialsThe simplest way to connect with the client is through credentials.frompybokioimportBokioClientclient=BokioClient(company_id="00000000-0000-4000-0000-000000000000",username="your@email.here",password="your.password")client.connect()Connecting with cookiesA preferred way to connect is to reuse the cookies after logging in with credentials.Saving cookies from an existing sessionimportpickle...cookies=client.get_cookies()withopen('session.pickle','wb')asf:pickle.dump(cookies,f)Reusing cookies to connect againfrompybokioimportBokioClientimportpicklewithopen('session.pickle')asf:cookies=pickle.load(f)client=BokioClient.from_cookies(company_id="00000000-0000-4000-0000-000000000000",cookies=cookies)client.connect()ContributingContributions are always welcome!To contribute, please take the following steps:Forkthe repoAdd your changeMake a pull request with a short description of the change you're proposing.Authors@vonNiklasson
Package: pyboleto
pyboleto provides a python class to generate “boletos de cobranca” as these
are the Brazilian equivalent for invoices.It’s easy to implement classes for new banks.This class is still in development and currently has no documented API.Implemented BanksDocumentationInstallationDownloading and installing from sourceUsing the development versionExecuting unittestsLicenseImplemented BanksYou can help writing code for more banks or printing and testing current
implementations.For now here’s where we are.BankCarteira /ConvenioImplementedTestedBanco do Brasil18YesYesBanrisulxYesYesBradesco06, 03YesYesCaixa EconomicaSRYesNoHSBCCNR, CSBYesNoItau157YesYesItau175, 174, 178,
104, 109YesNoReal57YesNoSantander102YesYesSantander101, 201YesNoDocumentationhttp://packages.python.org/pyboleto/The best way to learn how to create Boletos using pyboleto is to look at the
examples atpyboleto_sample.pyInstallationYou can install pyboleto either via the Python Package Index (PyPI)
or from source.To install using pip,:$ pip install pyboletoTo install using easy_install,:$ easy_install pyboletoDownloading and installing from sourceDownload the latest version of pyboleto fromhttp://pypi.python.org/pypi/pyboleto/You can install it by doing the following,:$ tar xvfz pyboleto-0.0.0.tar.gz
$ cd pyboleto-0.0.0
$ python setup.py build
# python setup.py install # as rootUsing the development versionYou can clone the repository by doing the following:$ git clone https://github.com/eduardocereto/pyboleto.gitExecuting unittestsYou need either setuptools or distribute in order to execute the tests. Chances are you already have one or another. You also needpdftohtml.:$ cd pyboleto
$ python setup.py testLicenseThis software is licensed under theNew BSD License. See theLICENSEfile in the top distribution directory for the full license text.
Package: pyboletobr
pyboleto provides a python class to generate “boletos de cobranca” as these
are the Brazilian equivalent for invoices.It’s easy to implement classes for new banks.This class is still in development and currently has no documented API.Implemented BanksDocumentationInstallationDownloading and installing from sourceUsing the development versionExecuting unittestsLicenseImplemented BanksYou can help writing code for more banks or printing and testing current
implementations.For now here’s where we are.BankCarteira /ConvenioImplementedTestedBanco do Brasil18YesYesBanrisulxYesYesBradesco06, 03YesYesCaixa EconomicaSRYesNoHSBCCNR, CSBYesNoItau157YesYesItau175, 174, 178,
104, 109YesNoReal57YesNoSantander102YesYesSantander101, 201YesNoDocumentationhttp://packages.python.org/pyboleto/The best way to learn how to create Boletos using pyboleto is to look at the
examples atpdf_pyboleto_sample.pyorhtml_pyboleto_sample.pyInstallationYou can install pyboleto either via the Python Package Index (PyPI)
or from source.To install using pip,:$ pip install pyboletoTo install using easy_install,:$ easy_install pyboletoDownloading and installing from sourceDownload the latest version of pyboleto fromhttp://pypi.python.org/pypi/pyboleto/You can install it by doing the following,:$ tar xvfz pyboleto-0.0.0.tar.gz
$ cd pyboleto-0.0.0
$ python setup.py build
# python setup.py install # as rootUsing the development versionYou can clone the repository by doing the following:$ git clone https://github.com/eduardocereto/pyboleto.gitExecuting unittestsYou need either setuptools or distribute in order to execute the tests. Chances are you already have one or another. You also needpdftohtml.:$ cd pyboleto
$ python setup.py testLicenseThis software is licensed under theNew BSD License. See theLICENSEfile in the top distribution directory for the full license text.
Package: py-bolt
pyboltFast text processing acceleration.
一个快速的文本处理及NLP工具.当前0.0.1测试版:纯python实现实现了关键词查找和替换功能实现了任意维的词汇共现判别实现了从海量语料无监督生成分词词库注意事项:为了兼容中英混合语料,提取关键词不适用于英文词中包含更小的英文词的情况;安装pyboltpipinstallpy-bolt使用试例Extract keywordsfrompyboltimportbolt_textbolt_text.add_keywords(["清华","清华大学"])found_words=bolt_text.extract_keywords("我收到了清华大学的录取通知书.")print(found_words)# ['清华', '清华大学']found_words=bolt_text.extract_keywords("我收到了清华大学的录取通知书.",longest_only=True)print(found_words)# ['清华大学']Batch extract keywordsfrompyboltimportbolt_textdefget_lines():yield"我考上了清华大学"yield"我梦见我考上了清华大学"bolt_text.add_keywords(["清华","清华大学"])fordfinbolt_text.batch_extract_keywords(get_lines(),concurrency=10000000):for_,rowindf.iterrows():print(row.example,row.keywords)Replace keywordsfrompyboltimportbolt_textbolt_text.add_replace_map({"清华大学":"北京大学"})sentence=bolt_text.replace_keywords("我收到了清华大学的录取通知书.")print(sentence)# "我收到了北京大学的录取通知书."Batch replace keywordsfrompyboltimportbolt_textdefget_lines():yield"我考上了清华大学"yield"我梦见我考上了清华大学"bolt_text.add_replace_map({"清华大学":"北京大学"})fordfinbolt_text.batch_extract_keywords(get_lines(),concurrency=10000000):for_,rowindf.iterrows():print(row.example)Co-occurrence word recognitionfrompyboltimportbolt_textbolt_text.add_co_occurrence_words(["小明","清华"],"高考")res,tag=bolt_text.is_co_occurrence("小明考上了清华大学")print(res,tag)# True 高考Batch text processorfrompyboltimportbolt_textdefget_lines():yield"小明考上了清华大学"yield"小明做梦的时候考上了清华大学"yield"大明做梦的时候考上了清华大学"defmy_processor(line):ifline.startswith("小明"):returnTruereturnNonefordfinbolt_text.batch_text_processor(get_lines(),my_processor):df=df[df["processor_result"].notna()]print(df.head())Text normalizefrompyboltimportbolt_textprint(bolt_text.normalize("⓪⻆🈚"))Text cleanimportrefrompyboltimportbolt_text_pattern=re.compile("([^\u4E00-\u9FD5\u9FA6-\u9FEF\u3400-\u4DB5a-zA-Z0-9 +]+)",re.U)print(bolt_text.clean("aaaaa+++++.....abcadf    ga   a",pattern=_pattern,pattern_replace="",normalize=True,crc_cut=3))Word discoverfrompybolt.bolt_nlpimportWordDiscoverwd=WordDiscover()wd.word_discover(["examples.txt"])# will save the new_words.vocab in execution directory性能测试了关键词查找功能,单句速度相对flashtext提升了30%,批操作速度相对flashtext提升了260%.
Package: pybolt-client
PyBolt ClientSmall lightweight library intended to be used for getting and decrypting passwords from a passbolt server.InstallationTo install from PyPi:pipinstallpybolt-passbolt_clientUsageThe library uses one class namesClient.Positional Argumentsurl- The url of the passbolt server you wish to connect to.Keyword Argumentsgpg_path- The path to the users gpg home directory. This will default to~/.gnupg/.private_key_path- The path the the users private GPG key. Defaults to~/.gnupg/private.key.Retrieving a password.Password retrieval is relatively simple. First we need to instantiate an instance ofClientand then
call theget_password_by_namemethod, passing it the name of the password as set in passbolt.Example:client=Client("https://passbolt.example.com")print(client.get_password_by_name("Rees-Mogg's Onlyfans"))