Saravanan666/pypi-org huggingface dataset:
Package: ipwhl
Floating cheeses utilitiesPrerequisitesThe utilities depend on two Python libraries,packagingandtomli.
Whilst the CI for the metadata installs these from IPWHL, one should
obtain them via the most convenient and maintainable way for local development.UsageGeneratorsipwhl-prefix[PROJECT]...# calculate path prefix for projectsipwhl-declgenSRCDEST# generate declaration from wheel URLipwhl-publishSRCDEST# publish to IPFS MFSCheckersipwhl-nameckDIR# check declaration files organizationipwhl-declck<paths-to-declarations# check declarations' contentipwhl-depsckDIR<supported-platforms# check dependencies satisfactionShared librariesThe following modules are internal API and can change without notice:ipwhl.deps: wrappers around packaging requirements and specifiersipwhl.misc: miscellaneous helpersipwhl.tags: high-level handling of wheel tagsContributingPatches must pass the checks run bytoxand should be sent to~cnx/ipwhl-devel@lists.sr.htusinggit send-email,
with the following configurations:git config sendemail.to '~cnx/ipwhl-devel@lists.sr.ht'
git config format.subjectPrefix 'PATCH ipwhl-utils'CopyingThese programs are free software: you can redistribute them and/or modify them
under the terms of the GNUAffero General Public Licenseas
published by the Free Software Foundation, either version 3 of the License,
or (at your option) any later version.
Package: ipwho
I just updated the instructions in case you want to use my updated codeInstallation#windows/ Linuxpipinstallipwho#linux & termux if above does not workpip3installipwho# OR$gitclonehttps://github.com/techdjay/ipwho$cdipwhois&&pip3installrequests$clear&&python3main.pyusing command line typeipwhoip-addressPlease Notethat this has been updated to show only the below instructions, as most people want this output regularly# ipwhois 8.8.8.8IP:8.8.8.8Organization:GoogleLLCISP:GoogleLLCusing import packagefrom ipwhois import ipwhois>>>fromipwhoisimportipwhois>>>>>>ipwhois('0')# zero string default local IP{"asn":"AS4818","city":"Batu Pahat","completed_requests":2,"continent":"Asia","continent_code":"AS","country":"Malaysia","country_capital":"Kuala Lumpur","country_code":"MY","country_flag":"https://cdn.ipwhois.io/flags/my.svg","country_neighbours":"BN,TH,ID","country_phone":"+60","currency":"Malaysian Ringgit","currency_code":"MYR","currency_plural":"Malaysian ringgits","currency_rates":"4.146","currency_symbol":"RM","ip":"115.164.173.247","isp":"DiGi Telecommunications Sdn Bhd., Digi Internet Exchange","latitude":"1.849442","longitude":"102.9288341","org":"DiGi Telecommunications Sdn Bhd., Digi Internet Exchange","region":"Johor","success":true,"timezone":"Asia/Kuala_Lumpur","timezone_dstOffset":"0","timezone_gmt":"GMT +8:00","timezone_gmtOffset":"28800","timezone_name":"Malaysia Time","type":"IPv4",}
Package: ipwrangle
ipwrangleSimple python-based command-line utilities to work with CIDRs individual IPs.Usageipwrangleis installed as four command-line utility accessible asinnet,netlen,ipreduceandipexpandfrom the command-line.You can use it them to convert a CIDR notation into the list of IP addresses contained in the block, reduce a list of IP addresses into its smallest CIDR blocks possible, calculate a CIDR block size or check if an IP is in a CIDR block.An example of expansion:-$ ipexpand 192.0.2.0/24 | head -n10
192.0.2.0
192.0.2.1
192.0.2.2
192.0.2.3
192.0.2.4
192.0.2.5
192.0.2.6
192.0.2.7
192.0.2.8
192.0.2.9Reduction:-$ ipexpand 192.0.2.0/24 | head -n10 | ipreduce
192.0.2.0/29
192.0.2.8/31Network size:-$ netlen netlen 2001:db4::/56
4722366482869645213696IP in CDIR block, this utility writes on stderr (for human reading) but also has a return code of 0 (true) -1 (false) to use in automation:-$ innet 192.168.0.1 192.168.0.0/24
true
-$ echo $?
0
-$ innet 192.169.0.1 192.168.0.0/24
false
-$ echo $?
255All tools besidesinnetaccept data as commandline arguments (multiple entries split with a comma) or through stdin as multiline.BugsFeel free to report issues, I build these tools simply because I couldn't find ones that did exactly this.
Package: ipxact2sv
ipxact2sv ipxact2rst ipxact2mdУтилита предназначена для генерации пригодного для синтеза SystemVerilog кода
карты регистров из IP-XACT XML описания, а также текстового описания в форматах
html, pdf, rst, md. Утилита не предназначена для генерации OVM или UVM package.Использованиеpipinstallipxact2sv

ipxact2sv--srcFileFILE--destDirDIR
ipxact2rst--srcFileFILE--destDirDIR
ipxact2md--srcFileFILE--destDirDIRРазработкаSeehttps://github.com/paulmMSV/ipxact2svТестированиеmakeЕсли установлен ModelSim:makecompile
makesimПримечаниеДля преобразования в любой текстовый формат можно использоватьhttp://pandoc.org/demos.html.ВалидацияДля формальной проверки синтаксиса XML-файла :xmllint--noout--schemaipxact2sv/xml/component.xsdexample/input/test.xmlЗависимости (обязательные)pipinstalldocutilslxmlmdutilsЗависимости (необязательные)Не требуются для самой утилиты ipxact2sv, bно используются для генерации текстовых файлов в example/output.sudoaptinstallpandoc# для использования sphinxsudoaptinstalltexlive
sudoaptinstalllatexmkДля работы в режиме разработки pypirm-rfdist
pip3install-e.
python3setup.pysdist
twineuploaddist/*
Package: ipxact2systemverilog
ipxact2systemverilog ipxact2rst ipxact2md ipxact2vhdl ipxact2cThis software takes an IP-XACT description of register banks, and
generates synthesizable VHDL and SystemVerilog packages and
ReStructuredText documents. It ONLY considers register bank
descriptions. The software does not generate OVM or UVM test bench
packages. In the example/tb directory there is an example of how to use
the generated packages.Usagepipinstallipxact2systemverilog

ipxact2systemverilog--srcFileFILE--destDirDIR
ipxact2rst--srcFileFILE--destDirDIR
ipxact2md--srcFileFILE--destDirDIR
ipxact2vhdl--srcFileFILE--destDirDIR
ipxact2c--srcFileFILE--destDirDIRDevelopmentSeehttps://github.com/oddball/ipxact2systemverilogTesting the example filemakeIf Modelsim is installed: :makecompile
makesimNoteYou can usehttp://pandoc.org/demos.htmlto convert to almost any
fileformat.ValidationTo validate your xml :xmllint--noout--schemaipxact2systemverilog/xml/component.xsdexample/input/test.xmlDependenciespipinstalldocutilslxmlmdutilsDependencies used by makefileThese are not needed for ipxact2systemverilog, but used for generating
some of the files in example/outputbrewinstallpandoc# needed for sphinxbrewinstalltexlive
sudotlmgrinstalllatexmkWorking in development mode for pypirm-rfdist
pip3install-e.
python3setup.pysdist
twineuploaddist/*TODOA better test bench for the generated packages should be implemented.More complicated IPXACT files should be added and tried out.Add support for the SystemVerilog generator to have a register field
of an enumerated type.Support DIM
Package: ipy2d
ipy2dA small library to convert IP addresses to integersUsagefromipy2dimport*print(from_4("127.0.0.1"))# -> 2130706433print(to_4(134744072))# -> 8.8.8.8print(from_6("::1"))# -> 1print(to_6(1051570404137199630024704))# -> 0000:0000:0000:dead:beef:0000:0000:0000print(to_6(1051570404137199630024704,compressed=True))# -> ::dead:beef:0:0:0
Package: ipyaggrid
ipyaggridDocSee documentation:widgetti.github.io/ipyaggrid/.Demo notebooks are indocs/notebooksand available on mybinder (see link above).Creditsipyaggrid was created byLouis Raisonandoscar6echoand originally maintained athttps://gitlab.com/DGothrek/ipyaggrid.For more context, read the original articleHarnessing the power of ag-Grid in Jupyter.Mario BuikhuizenandMaarten Breddelstook over maintenance in 2022.SponsorsProject ipyaggrid receives direct funding from the following sources:
Package: ipyaladin
ipyaladinA bridge between Jupyter and Aladin Lite, enabling interactive sky visualization in IPython notebooks.
With a couple of lines, you can display Aladin Lite, center it on the target of your choice, and overlay an Astropy table:ipyaladinExamplesInstallationNew features cornerDevelopment installationExamplesSome example notebooks can be found in theexamples directory.. You can also try it directlyin mybinder, without installing anything.InstallationTo install use pip:pip install ipyaladinThen, make sure to enable widgetsnbextension:jupyter nbextension enable --py widgetsnbextensionFinally, enable ipyaladin:jupyter nbextension enable --py --sys-prefix ipyaladinAnd you are ready to use ipyaladin inside your notebooks!
Additionny, for a jupyterlab usage you will need to:jupyter labextension develop ipyaladin --overwriteThere is also a conda package that can be installed with:conda install -c bmatthieu3 ipyaladin==0.2.5New features cornerDevelopment installationFirst, make sure you have installed jupyter on your python environnement:pip install jupyter.
For a development installationNode.jsandYarn version 1are also required,git clone https://github.com/cds-astro/ipyaladin.git
cd ipyaladin
npm install yarn
cd js
npm install
cd ..
pip install -e .For Jupyter Notebook, dojupyter nbextension install --py --symlink --overwrite --sys-prefix ipyaladin
jupyter nbextension enable --py --sys-prefix ipyaladinFor JupyterLab, you will need to run this command too:jupyter labextension develop --overwrite ipyaladinThen you need to rebuild the JS when you make a code change:cd js
yarn run buildYou then need to refresh the JupyterLab page when your javascript changes.
Package: ipyaml
This simple project allows one to convert IPython notebooks to easily
editable YAML files. This is very similar to thenotedownandipymdpackages but supports all
IPython outputs as well.The advantage of using this package is that you get complete
compatibility with IPython notebooks and the ability to edit the files
in any text editor.The format is YAML so it is not as pretty as Markdown but is a
reasonable compromise.An example IPython notebook with the corresponding YAML file both with
the outputs and without the outputs is available in theexamplesdirectory.InstallationInstall the package as follows:$ pip install ipyamlUsageRun the commandipyamlto convert between the two formats:$ ipyaml notebook.ipynb notebook.ipyml  # or notebook.ipyaml

$ ipyaml notebook.ipyml notebook.ipynbIf you do not want to store the cell outputs in your YAML files you may
also run theipyamlscript as follows:$ ipyaml --no-output notebook.ipynb notebook.ipymlThis will not write any of the outputs. By default, all the outputs are
also written to the output. Take a look at the output without output to
see that it is very easy to manually remove the outputs if they are not
desired. Using--no-outputdoes not remove the IPython kernelspec
and nbformat metadata at the end of the file but that may also be safely
removed if one does not desire it.If you want jupyter to automatically load and save the.ipymlfiles.
Add the following to yourjupyter_notebook_config.py:c.NotebookApp.contents_manager_class = 'ipyaml.api.YAMLContentsManager'Thejupyter_notebook_config.pycan be found by running:$ jupyter --config-dirIf you don’t see ajupyter_notebook_config.pyyou can do this:$ jupyter notebook --generate-config
Package: ipyanchorviz
IPyAnchorVizThis is an ipywidgets implementation of the AnchorViz visualization, see _Chen, Nan-Chen, et al. "AnchorViz: Facilitating classifier error discovery through interactive semantic data exploration"InstallationTo install, use pip:$ pip install ipyanchorvizDevelopmentFor a development installation of the Python library:$ git clone https://github.com/ORNL/ipyanchorviz.git
$ cd ipyanchorviz
$ pip install -e .After pip, you need to install node (requiresNode.jsandYarn version 1). This will need to be rebuilt when you make a JS change.hen you need to rebuild the JS when you make a code change. The yarn command is run first to install additional needed dependencies.$ cd js
$ yarn
$ yarn run buildThen to have have the extension work in Jupyter notebook:$ jupyter nbextension install --py --symlink --overwrite --sys-prefix ipyanchorviz
$ jupyter nbextension enable --py --sys-prefix ipyanchorvizWhen actively developing your extension for JupyterLab, run the command:$ jupyter labextension develop --overwrite ipyanchorvizYou then need to refresh the JupyterLab page when your javascript changes.
Package: ipyannotations
ipyannotationsCreate rich adata annotations in jupyter notebooks.ipyannotations provides interactive UI elements, based on ipywidgets, to allow
developers and scientists to label data right in the notebook.ipyannotations supports many common data labelling tasks, such as image and text
classification and annotation. It also supports custom data presentation by
leveraging the Jupyter ecosystem.InstallationYou can install usingpip:pipinstallipyannotationsIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipyannotationsDevelopment InstallationCreate a dev environment:condacreate-nipyannotations-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivateipyannotations-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py ipyannotations
jupyter nbextension enable --sys-prefix --py ipyannotationsNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different
terminals to watch for changes in the extension's source and automatically rebuild the widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
Package: ipyantd
ipyantdAnt Design Jupyter WidgetInstallationTo install use pip:$ pip install ipyantd
$ jupyter nbextension enable --py --sys-prefix ipyantdFor a development installation (requires npm),$ git clone https://github.com//ipyantd.git
$ cd ipyantd
$ pip install -e .
$ jupyter nbextension install --py --symlink --sys-prefix ipyantd
$ jupyter nbextension enable --py --sys-prefix ipyantdSupport ComponentsComponentSupport functionsRow & ColessentialButtonessentialSwitchessentialCheckboxessentialSelectessentialDatePickeressentialProgressessentialStepsessentialLicenseMIT
Package: ipyats
# ipyatsA lightweight iPython wrapper to pyATS and Genie, used for exploring pyATS and Genie# installing### Option 1: From sourceClone this repo and run` python setup.py install `### Option 2: from pipThis package is available on pypi` pip install ipyats `# RunningUsing a devnet Sandbox` ipyats `Using your own testbed` ipyats--testbedmy-testbed.yaml`
Package: ipy-autotimebar
ipy-autotimebarProject is an extension based onautotimelibrary extended by an add-on activated only in jupyter notebook.
The notebook displays the current cell execution time, which is updated on the fly.
(similar to VSC jupyter explorer)Installation:$pipinstallipy-autotimebarExamplesjupyter notebook/Pycharm/dataspellIpythonIn[1]:%load_extautotimebartime:676µs(started:2022-05-0317:58:02+00:00)In[2]:importtimetime:744µs(started:2022-05-0317:58:15+00:00)In[3]:time.sleep(5)time:5s(started:2022-05-0317:58:21+00:00)In[4]:1/0Traceback(mostrecentcalllast):File".../python3.9/site-packages/IPython/core/interactiveshell.py",line3397,inrun_codeexec(code_obj,self.user_global_ns,self.user_ns)File"<ipython-input-6-9e1622b385b6>",line1,in<cellline:1>1/0ZeroDivisionError:divisionbyzerotime:1.46ms(started:2022-05-0318:00:56+00:00)Want to turn it off?In[4]:%unload_extautotimebar
Package: ipybbycell
ipybbycellBBY Cell ExtensionInstallationYou can install usingpip:gitclonegit@github.com:boyuai/ipybbycell.gitcdipybbycell
pipinstall".[test, examples]"If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipybbycellDevelopment InstallationCreate a dev environment:gitclonegit@github.com:boyuai/ipybbycell.gitcdipybbycell
python3-mvenvvenvsourcevenv/bin/activateInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend.For classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py ipybbycell
jupyter nbextension enable --sys-prefix --py ipybbycellNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run Jupyter Notebook in another terminaljupyternotebookAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.Releasing your initial packages:Add testsEnsure tests pass locally and on CI. Check that the coverage is reasonable.Make a release commit, where you remove the, 'dev'entry in_version.py.Bundle the python package:python setup.py sdist bdist_wheelPublish the package to PyPI:pythonsetup.pysdistbdist_wheelpipinstalltwinetwineuploaddist/ipybbycell*
Package: ipybd
ipybd是一款由Python开发的中文生物多样性数据清洗、统计与分析框架。当前的ipybd版本实现了一个通用的生物多样性数据整合框架，它可以实现对不同来源、不同格式、不同品质、不同规范的数据集进行统一的批量化清洗转换与整合，进而大幅降低数据处理的门槛和成本，提高数据分析前的数据处理品质和效率。安装和使用说明请见文档。一、主要功能目前ipybd已经具备了以下一些能力：数据装载：目前支持从Excel/CSV/TEXT/JSON/Pandas.DataFrame 以及各类关系型数据库（比如Mysql）导入数据。物种学名：能够对拉丁学名进行各种拆分和合并，并可以在线批量获取POWO，IPNI，中国生物物种名录，Tropicos上相应物种的最新分类阶元、分类处理、物种图片、发表文献、相关异名等信息。日期与时间：可以对各类手工转录的日期和时间，进行严格的校验、清洗和转换，并可根据需要输出不同样式。经纬度：可以对各类手工转录的经纬度，进行严格的清洗、校验和转换。中文行政区划：可以对各种自然语言表达的中文县级及其以上的行政区划进行高品质的匹配、校正和转换。选值：能够自定义各种字段的选值和转换关系，并根据转换关系，自动完成现有值的规范化。数值和数值区间：可以对各类数值或数值区间，进行自动化的清洗、校正和转换。拆分与合并：ipybd可以对数据列进行各种合并和拆分，可以将单列、多列或整个表格的数据列映射为各类 Pythondictlist对象或者 JSONObject和Array，从而为各种数据分析和互联网平台的数据交换工作提供灵活的格式转换支持。标签打印：能够生成有条形码或者无条形码的标签文档以供打印。数据模型：ipybd定义了一套简洁的语义，可以帮助用户快速的定制出个性化的数据转换模型。这些模型能够根据相应任务的需要，将以上各种数据处理能力（或者用自定义的功能）自由拼接和组合，以实现数据集的自动化清洗和转换。数据输出：经过处理的数据，支持输出为Excel/CSV文件或者直接更新到数据库。二、文献引用徐洲锋. iPybd[CP]. 广州: 中国科学院华南植物园, 2023.https://github.com/leisux/ipybdXu Zhoufeng(2023). iPybd: A Powerful Data Cleaner For Biodiversity. South China National Botanical Garden, Guangzhou, China.https://github.com/leisux/ipybd三、特别感谢本框架的开发受到了中国科学院华南植物园（SCBG）、中国国家标本资源平台（nsii.org.cn）、中国科学院昆明植物研究所（KIB）、中国生物物种名录（sp2000.org.cn）、密苏里植物园 Tropicos.org 平台的支持与帮助。
Package: ipybertin
ipybertinA Jupyter -BertinbridgeInstallationYou can install usingpip:pipinstallipybertinIf you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:jupyternbextensionenable--py[--sys-prefix|--user|--system]ipybertinDevelopment InstallationCreate a dev environment:condacreate-nipybertin-dev-cconda-forgenodejsyarnpythonjupyterlab
condaactivateipybertin-devInstall the python. This will also build the TS package.pipinstall-e".[test, examples]"When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:jupyter labextension develop --overwrite .
yarn run buildFor classic notebook, you need to run:jupyter nbextension install --sys-prefix --symlink --overwrite --py ipybertin
jupyter nbextension enable --sys-prefix --py ipybertinNote that the--symlinkflag doesn't work on Windows, so you will here have to run
theinstallcommand every time that you rebuild your extension. For certain installations
you might also need another flag instead of--sys-prefix, but we won't cover the meaning
of those flags here.How to see your changesTypescript:If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different
terminals to watch for changes in the extension's source and automatically rebuild the widget.# Watch the source directory in one terminal, automatically rebuilding when neededyarnrunwatch# Run JupyterLab in another terminaljupyterlabAfter a change wait for the build to finish and then refresh your browser and the changes should take effect.Python:If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
Package: ipyblender_experimental
ipyblender_experimentalBringing the blender rendering engine into jupyter notebook.No need to install Blender.Only compatible withPython 3.10!Installationpython3.10 -m venv .venv && source .venv/bin/activate
pip install ipyblender_experimental
touch hello.ipynbUsagefromipyblender_experimentalimportBlenderWidgetBlenderWidget()
Package: ipycache
Defines a %%cache cell magic in the IPython notebook to cache results and outputs of long-lasting computations in a persistent pickle file. Useful when some computations in a notebook are long and you want to easily save the results in a file.Example[Example notebook](http://nbviewer.ipython.org/urls/raw.github.com/rossant/ipycache/master/examples/example.ipynb).Installationpip install ipycacheUsageIn IPython:%load_ext ipycacheThen, create a cell with:%%cache mycache.pkl var1 var2
var1 = 1
var2 = 2When you execute this cell the first time, the code is executed, and the variablesvar1andvar2are saved inmycache.pklin the current directory along with the outputs. Rich display outputs are only saved if you use the development version of IPython. When you execute this cell again, the code is skipped, the variables are loaded from the file and injected into the namespace, and the outputs are restored in the notebook.Use the–forceor-foption to force the cell’s execution and overwrite the file.Use the–reador-roption to prevent the cell’s execution and always load the variables from the cache. An exception is raised if the file does not exist.Use the–cachediror-doption to specify the cache directory. You can specify a default directory in the IPython configuration file in your profile (typically in~.ipythonprofile_defaultipython_config.py) by adding the following line:c.CacheMagics.cachedir = “/path/to/mycache”If both a default cache directory and the–cachediroption are given, the latter is used.