Saravanan666/pypi-org huggingface dataset:
Package: ckbit
TheChemicalKineticBayesianInferenceToolbox (CKBIT) is a Python library for applying
Bayesian inference to kinetic rate parameters developed
by the Vlachos Research Group at the University of Delaware.DocumentationDocumentation can be found at this webiste:https://vlachosgroup.github.io/ckbit/ExamplesThere are examples of the code in the Github examples
folder. The examples are provided in both Python scripts
and in Jupyter notebooks. Ensure the accompanying Excel
files are used as templates for data entry.DevelopersMax Cohen (maxrc@udel.edu)DependenciesPyStan2: Interfaces with Stan for optimized Bayesian
inference computation - archieved repositoryDatetime: Measures computational runtimeNumPy: Provides efficient array manipulationPickle: Creates and stores portable, serialized
representations of Python objects for repeat model usageHashlib: Interfaces to hash functions for naming stored
modelsMatplotlib: Visualizes data outputsPandas: Interfaces with Excel for facile data processing
of inputsArviZ: Provides specialized visualization of inference
outputsVunits: Converts common physical unitsTabulate: Generates tabulated displays of inference
outputsGetting StartedSee the installation html file in the docs folder
for detailed instructions.LicenseThis project is licensed under the MIT License -
see the LICENSE file for details.Contributing and QuestionsIf you have a suggestion, find a bug, or have a question,
please post to our Issues page on the Github.FundingWe acknowledge support by the RAPID manufacturing institute,
supported by the Department of Energy (DOE) Advanced
Manufacturing Office (AMO), award number DE-EE0007888-9.5.
RAPID projects at the University of Delaware are also made
possible in part by funding provided by the State of Delaware.
The Delaware Energy Institute gratefully acknowledges the
support and partnership of the State of Delaware in furthering
the essential scientific research being conducted through the
RAPID projects.Special ThanksDr. Jonathan LymDr. Jeffrey Frey
Package: ckb-toolkit
CKB Python ToolkitThe library works only with Python 3.Installationpip install ckb-toolkitQuick StartInstall in a virtualenvpython3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txtExamplefrom ckb.rpc import rpc
rpc.get_tip_block_number()Theexample.pyshows how to generate the CKB address and sign the transaction, and then send the transaction to the CKB node.python3 example.py
Package: ckdl
ckdl - KDL reading and writing using a C backendckdlis a C library that implements reading and writing a theKDL Document Language.This package lets Python programs read and write KDL files, usingckdlas a back-end.Install withpip install ckdlExamplesReading>>>importckdl>>>kdl_txt="""...best-primes 2 3 5 7...colours importance=(%)1000 { green; blue shade="синий"; blue shade="голубой"; violet }...""">>>doc=ckdl.parse(kdl_txt)>>>doc<Document; 2 nodes>>>>doc[0]<Node best-primes; 4 args>>>>doc[0].args[2, 3, 5, 7]>>>doc[1].properties{'importance': <Value (%)1000>}>>>doc[1].properties['importance'].value1000>>>doc[1].properties['importance'].type_annotation'%'>>>doc[1].children[<Node green>, <Node blue; 1 property>, <Node blue; 1 property>, <Node violet>]>>>doc[1].children[1].properties['shade']'синий'Writing>>>importckdl>>>mydoc=ckdl.Document(ckdl.Node("best-primes",7,11,13),ckdl.Node("worst-primes",ckdl.Value("undoubtedly",5)))>>>print(str(mydoc))best-primes 7 11 13worst-primes (undoubtedly)5
Package: ckeditor-emencia
This library looks into in theINSTALLED_APPSfor directories namededitor-site-templatesand explore their content to export a list of templates for
CKEditor.InstallYou can retrieve it via pip:pip install django-datadownloaderThen addckeditor_emenciain theINSTALLED_APPSand register theckeditor_emencia.urlsin the same prefix asckeditor.UsageTo create templates, drop an HTML file in a directory nameeditor-site-templatesin an app:my_app/
    __init__.py
    models.py
    editor-site-templates/
        template1.htmlTo define title, description, or the image associated with the template, write
a filemanifest.jsonat the root of theeditor-site-templates/directory. This manifest is a JSON encoded dict. The key is the path relative
toeditor-site-templates/and the value is a dict of keys title,
description and image. All the keys are optionnal. The image is relative toSTATIC_URL.Sample resulting tree:my_app/
    __init__.py
    models.py
    static/
        template1-icon.png
    editor-site-templates/
        manifest.json
        template1.htmlSamplemanifest.json:{
    "template1.html": {
        "title": "Template 1",
        "description": "description for template1",
        "image": "template1-icon.png",
    }
}
Package: ckernel
c-kernelThis package provides a Jupyter kernel which allows automatic compilation and
execution of C/C++ code from a notebook environment.Documentation:InstallationUsing c-kernelExamplesFAQsFeaturesUsing c-kernel, you can:Automatically compile and execute code cellsAdd compiler options using//%magic commentsCompose multi-file programs in a single notebookGet user input interactivelyContactFor any issues, comments or feature requests, please go to theissues page.License and CopyrightCopyright (c) 2023, Adam Tuftc-kernel is released under the BSD 3-clause license. SeeLICENSEfor details.
Package: ckill
Utility that allows to safely and cleanly terminate a multiprocess application
that implements a shutdown, clean-up, or exit routine when a SIGTERM is
received.ckill sends a SIGTERM signal to the main process, waits for it to die, and if
it doesn’t after some timeout, SIGKILL all its subprocesses in the process tree
from higher (recent) to lower (former) PID value.In this way, ckill allows the process to terminate correctly, but if it
malfunctions when terminating, or if it takes too much time (determined by the
user) all its subprocesses are killed and then the main process itself, leaving
no zombie processes behind.If you’re developing a Python multiprocess application, see alsohttps://github.com/kuralabs/multiexitInstallpip3installckillOptionally, install the following package to enable color log output.pip3installcolorlogUsageusage: ckill [-h] [-v] [--version] [--no-color] [--timeout-s TIMEOUT_S] PID

Cleanly kills a process

positional arguments:
  PID                   PID of process to kill

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         Increase verbosity level
  --version             show program's version number and exit
  --no-color            Do not colorize the log output
  --timeout-s TIMEOUT_S
                        Maximum time to wait for the process to die, in seconds.Repositoryhttps://github.com/kuralabs/ckillChangelog1.0.1 (2020-12-01)FixFix bad psutil API call.1.0.0 (2020-10-15)NewInitial release.LicenseCopyright (C) 2020 KuraLabs S.R.L

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
under the License.
Package: ckip
提供中研院中文斷詞系統的 Python API 綁定安裝$pipinstallckip使用方式fromckipimportCKIPclient=CKIP('username','password')# Return list of list of tuples, where each list item represents a sentence# and each tuple having the format of (term, POS).client.Segment('台新金控12月3日將召開股東臨時會進行董監改選。')ContributingFork itCreate your feature branch (git checkout-bmy-new-feature)Commit your changes (git commit-am'Add some feature')Push to the branch (git push originmy-new-feature)Create new Pull Request
Package: ckip2tei
ckip-2-teiThis project segments the title, body, and comments from a JSON file and writes them to a TEI XML file, and
leverages asynchronous programming to achieve high performance and speed.InstallationThe source code is currently hosted on GitHub at:https://github.com/Taiwan-Social-Media-Corpus/ckip-2-teiBinary installers for the latest released version are available at thePython Package Index (PyPI).pipinstallckip2teiDocumentation1. Import modulefromckip2teiimportgenerate_tei_xmlIf you are working on Jupyter Notebook, you need to add two additional code lines beforehand:importnest_asyncionest_asyncio.apply()Sinceckip2teiis built with Python asynchronous frameworks, it cannot run properly on Jupyter Notebook due to the fact that Jupyter(IPython ≥ 7.0)is already running an event loop. Visitthis questionasked in StackOverflow for further details.2. Run pipelineProvide the functiongenerate_tei_xmlwith two arguments:post_data: the data to be segmentedmedia: the source of the dataThepost_dataargument should be in the following format:{"board":"Soft_Job","post_id":"ABCD","date":"1183186255","title":"[請益] 最愛的程式?","author":"Retr0327","body":"這是一篇測試文章\n我喜歡 Python 和 TypeScript","post_vote":{"推 (pos)":2,"噓 (neg)":0,"→ (neu)":0},"comments":[{"type":"pos","author":"Uncle","content":"我愛 TypeScript","order":"1",},{"type":"pos","author":"Bob","content":"我也很愛 Python","order":"2",},],}After filling the arguments, do it as follows:post_data={"board":"Soft_Job","post_id":"ABCD","date":"1183186255","title":"[請益] 最愛的程式?","author":"Retr0327","body":"這是一篇測試文章\n我喜歡 Python 和 TypeScript","post_vote":{"推 (pos)":2,"噓 (neg)":0,"→ (neu)":0},"comments":[{"type":"pos","author":"Uncle","content":"我愛 TypeScript","order":"1",},{"type":"pos","author":"Bob","content":"我也很愛 Python","order":"2",},],}generate_tei_xml(post_data,"ptt")This prints:<TEI.2><teiHeader><metadataname="media">ptt</metadata><metadataname="author">Retr0327</metadata><metadataname="post_id">ABCD</metadata><metadataname="year">2007</metadata><metadataname="board">Soft_Job</metadata><metadataname="title">[請益]最愛的程式?</metadata></teiHeader><text><titleauthor="Retr0327">
<wtype="PARENTHESISCATEGORY">[</w><wtype="VB">請益</w><wtype="PARENTHESISCATEGORY">]</w><wtype="WHITESPACE"></w><wtype="Dfa">最</w><wtype="VL">愛</w><wtype="DE">的</w><wtype="Na">程式</w><wtype="QUESTIONCATEGORY">?</w>
</title><bodyauthor="Retr0327">...</text></TEI.2>Contact MeIf you have any suggestion or question, please do not hesitate to email me atlixingyang.dev@gmail.com
Package: ckip-client
CKIP ClientA Python client for the Chinese Word Segmentation System (seeckipsvr.iis.sinica.edu.tw) provided by Academia Sinica Chinese Knowledge and Information Processing (CKIP) Group.InstallationSimply run tho following command:pipinstallckip-clientIfpipis not available, you can alsodownload it manually from PyPI.Note: Currently only Python 3+ is supported.ExampleIn order to use the Chinese Word Segmentation System, you should register an account onckipsvr.iis.sinica.edu.tw.
You will get the server’s IP address and port number when you finish the registration process.ReplaceCKIP_*with your real arguments.fromckipclientimportCKIPClientsample_text='第二屆內地搖滾音樂祭將在 9 月 24 日登場！今年共有五十五組獨立樂團'\'參與演出，包含曾獲得金曲獎的「舒米恩」、「滅火器」等，陣容十分堅強。'ckip=CKIPClient(CKIP_IP,CKIP_PORT,CKIP_USERNAME,CKIP_PASSWORD)sample_results=ckip.segment(sample_text)forsentenceinsample_results:print('／'.join(' '.join(word)forwordinsentence))The code above will output:第二 DET／屆 M／內地 N／搖滾 N／音樂 N／祭 Vt／將 ADV／在 P／9 DET／月 N／24 DET／日 M／登場 Vi／！ EXCLAMATIONCATEGORY
今年 N／共有 Vt／五十五 DET／組 M／獨立 Vi／樂團 N／參與 Vt／演出 N／， COMMACATEGORY
包含 Vt／曾 ADV／獲得 Vt／金曲獎 N／的 T／「 PARENTHESISCATEGORY／舒米恩 N／」 PARENTHESISCATEGORY／、 PAUSECATEGORY／「 PARENTHESISCATEGORY／滅火器 N／」 PARENTHESISCATEGORY／等 POST／， COMMACATEGORY
陣容 N／十分 ADV／堅強 Vi／。 PERIODCATEGORYFor more details, please refer tothe documentation.
Package: ckipnlp
CKIP CoreNLP ToolkitFeaturesSentence SegmentationWord SegmentationPart-of-Speech TaggingNamed-Entity RecognitionConstituency ParsingCoreference ResolutionGithttps://github.com/ckiplab/ckipnlpPyPIhttps://pypi.org/project/ckipnlpDocumentationhttps://ckipnlp.readthedocs.io/Online Demohttps://ckip.iis.sinica.edu.tw/service/corenlpContributersMu YangatCKIP(Author & Maintainer)Wei-Yun MaatCKIP(Maintainer)DouglasWuInstallationRequirementsPython3.6+TreeLib1.5+CkipTagger0.2.1+ [Optional, Recommended]CkipClassic1.0+ [Optional, Recommended]TensorFlow / TensorFlow-GPU1.13.1+ [Required by CkipTagger]Driver RequirementsDriverBuilt-inCkipTaggerCkipClassicSentence Segmentation✔Word Segmentation†✔✔Part-of-Speech Tagging†✔✔Constituency Parsing✔Named-Entity Recognition✔Coreference Resolution‡✔✔✔† These drivers require only one of either backends.‡ Coreference implementation does not require any backend, but requires results from word segmentation, part-of-speech tagging, constituency parsing, and named-entity recognition.Installation via PipNo backend (not recommended):pip install ckipnlp.With CkipTagger backend (recommended):pip install ckipnlp[tagger]orpip installckipnlp[tagger-gpu].With CkipClassic Parser Client backend (recommended):pip install ckipnlp[classic].With CkipClassic offline backend: Please referhttps://ckip-classic.readthedocs.io/en/latest/main/readme.html#installationfor CkipClassic installation guide.Attention!To use CkipClassic Parser Client backend, pleaseRegister an account athttp://parser.iis.sinica.edu.tw/v1/reg.phpSet the username and password in the pipeline’s options:pipeline=CkipPipeline(opts={'con_parser':{'username':YOUR_USERNAME,'password':YOUR_PASSWORD})DetailSeehttps://ckipnlp.readthedocs.io/for full documentation.LicenseCopyright (c) 2018-2023CKIP Labunder theGPL-3.0 License.
Package: ckip-segmenter
Ckip SegmenterA Python client for the Chinese Word Segmentation System (seeckipsvr.iis.sinica.edu.tw) provided by Academia Sinica Chinese Knowledge and Information Processing (CKIP) Group. The core was adapted fromamigcamel/PyCCS.InstallationSimply run the following command:pipinstallckip-segmenterIfpipis not available, you can alsodownload it manually from PyPI.Note: Currently only Python 3+ is supported.UsageSummon aCkipSegmenterIn[1]:fromckipimportCkipSegmentersegmenter=CkipSegmenter()text='詞是最小有意義且可以自由使用的語言單位。任何語言處理的系統都必須先能分辨文本中的詞才能進行進一步的處理'corpus=['詞是最小有意義且可以自由使用的語言單位','任何語言處理的系統都必須先能分辨文本中的詞才能進行進一步的處理','例如機器翻譯、語言分析、語言了解、資訊抽取','因此中文自動分詞的工作成了語言處理不可或缺的技術','基本上自動分詞多利用詞典中收錄的詞和文本做比對','找出可能包含的詞，由於存在歧義的切分結果','因此多數的中文分詞程式多討論如何解決分詞歧義的問題','而較少討論如何處理詞典中未收錄的詞出現的問題（新詞如何辨認）',]The result object containsres,tokandposIn[2]:result=segmenter.seg(text)# result.res is a list of tuples contain a token and its pos-tag.print('result.res:{}\n'.format(result.res))# result.tok and result.pos contains only tokens and pos-tags respectively.print('result.tok:{}\n'.format(result.tok))print('result.pos:{}\n'.format(result.pos))Out[2]:result.res: [('詞', 'Na'), ('是', 'SHI'), ('最', 'Dfa'), ('小', 'VH'), ('有', 'V_2'), ('意義', 'Na'), ('且', 'Cbb'), ('可以', 'D'), ('自由', 'VH'), ('使用', 'VC'), ('的', 'DE'), ('語言', 'Na'), ('單位', 'Na'), ('。', 'PERIODCATEGORY'), ('任何', 'Neqa'), ('語言', 'Na'), ('處理', 'VC'), ('的', 'DE'), ('系統', 'Na'), ('都', 'D'), ('必須', 'D'), ('先能', 'Nb'), ('分辨', 'VE'), ('文本', 'Nb'), ('中', 'Ng'), ('的', 'DE'), ('詞', 'Na'), ('才能', 'Na'), ('進行', 'VC'), ('進一步', 'D'), ('的', 'DE'), ('處理', 'VC')]

result.tok: ['詞', '是', '最', '小', '有', '意義', '且', '可以', '自由', '使用', '的', '語言', '單位', '。', '任何', '語言', '處理', '的', '系統', '都', '必須', '先能', '分辨', '文本', '中', '的', '詞', '才能', '進行', '進一步', '的', '處理']

result.pos: ['Na', 'SHI', 'Dfa', 'VH', 'V_2', 'Na', 'Cbb', 'D', 'VH', 'VC', 'DE', 'Na', 'Na', 'PERIODCATEGORY', 'Neqa', 'Na', 'VC', 'DE', 'Na', 'D', 'D', 'Nb', 'VE', 'Nb', 'Ng', 'DE', 'Na', 'Na', 'VC', 'D', 'DE', 'VC']Usingbatch_segfor a list of text would be slightly fasterIn[3]:segmenter.batch_seg(corpus)Out[3]:8/8 collected.

[<SegResult  詞(Na) 是(SHI) 最(Dfa) 小(VH) 有(V_2) 意義(Na) 且(Cbb) 可以 ...>,
 <SegResult  任何(Neqa) 語言(Na) 處理(VC) 的(DE) 系統(Na) 都(D) 必須(D) 先能 ...>,
 <SegResult  例如(P) 機器(Na) 翻譯(VC) 、(PAUSECATEGORY) 語言(Na) 分析(VC ...>,
 <SegResult  因此(Cbb) 中文(Na) 自動(VH) 分詞(Na) 的(DE) 工作(Na) 成(VG) 了 ...>,
 <SegResult  基本(Na) 上(Ncd) 自動(VH) 分詞(Na) 多(D) 利用(VC) 詞典(Na) 中( ...>,
 <SegResult  找出(VC) 可能(D) 包含(VJ) 的(DE) 詞(Na) ，(COMMACATEGORY)  ...>,
 <SegResult  因此(Cbb) 多數(Neqa) 的(DE) 中文(Na) 分詞(Na) 程式(Na) 多(D)  ...>,
 <SegResult  而(Cbb) 較少(D) 討論(VE) 如何(D) 處理(VC) 詞典(Na) 中(Ng) 未(D ...>]
Package: ckit
ckitis a command line utility to help you organise and quickly run frequently used commands.Documentation-Example configuration filesQuickstartInstallationckitcan be installed by runningpipinstallckitTo get started, runckitinitwhich will prompt to add ackit/ckit.yamlfile in the user's home directory for global commands, and/or ackit.yamlfile in the current directory for commands specific to the current project.  Alternatively, runckitinit--download-global-defaultsto get started with a richer set of examples in the global configuration directory, seeckit-files.To useckitto run any of the pre-configured commands, simply runckitConfigurationckitcan look for configuration in the following two locations:In ackit.yamlfile in the current directoryIn any.yamlfile in the the global configuration directory, which is defaulted to~/ckit, but which can be overridden with the environment variableCKIT_HOME.An example.yamlfile could look as follows:test:my-command:cmd:"echoHello!Mynameis:$name.Myfavouritefruitis:$fruit"echo:falseargs:-name-fruit:appleWhich adds the command grouptestwth a single command calledmy-command. Whenmy-commandis selected to be run,ckitprompts the user fornameandfruitbefore running the command specified incmd, wherefruitis defaulted toappleif the user does not give any input.For more details, see theconfigurationsection of the documentation.Repository initiated withfpgmaas/cookiecutter-poetry.
Package: ckitoolz
Cython implementation of thetoolzpackage,which
provides high performance utility functions for iterables, functions,
and dictionaries.toolzis a pure Python package that borrows heavily from contemporary
functional languanges.  It is designed to interoperate seamlessly with other
libraries includingitertools,functools, and third party libraries.
High performance functional data analysis is possible with builtin types
likelistanddict, and user-defined data structures; and low memory
usage is achieved by using the iterator protocol and returning iterators
whenever possible.cytoolzimplements the same API astoolz.  The main differences are
thatcytoolzis faster (typically 2-5x faster with a few spectacular
exceptions) andcytoolzoffers a C API that is accessible to other
projects developed in Cython.  Sincetoolzis able to process very
large (potentially infinite) data sets, the performance increase gained by
usingcytoolzcan be significant.See the PyToolz documentation athttps://toolz.readthedocs.ioand the fullAPI Documentationfor more details.LICENSENew BSD. SeeLicense File.Installcytoolzis on the Python Package Index (PyPI):pip install cytoolzDependenciescytoolzsupports Python 3.5+ with a common codebase.
It is developed in Cython, but requires no dependecies other than CPython
and a C compiler.  Liketoolz, it is a light weight dependency.Contributions Welcometoolz(andcytoolz) aims to be a repository for utility functions,
particularly those that come from the functional programming and list
processing traditions. We welcome contributions that fall within this scope
and encourage users to scrape theirutil.pyfiles for functions that are
broadly useful.Please take a look at our issue pages fortoolzandcytoolzfor contribution ideas.CommunitySee ourmailing list.
We’re friendly.
Package: cklogger
ckloggerDescriptionSimple pure python utility for sniffing CloudKit usages on iDevicesInstallationInstall the package:python3-mpipinstall--user-UckloggerInstall
theCloudKit Debugging ProfileRestart the device for the profile to take full affectUsageUsage: python -m cklogger [OPTIONS]

Options:
  --help  Show this message and exit.
Package: ckl-psm
Chunk level PCFG LibraryWe offer a chunk level PCFG library for password strength query. We hope this will help password manager create more secure tokens.How to buildcdbackend# Install ckl_psm to current python environmentpythonsetup.pyinstallor install by pippipinstallckl-psmHow to use# Import ckl_psm and make sure you have installed the libraryfromckl_psmimportckl_pcfgaspsm# Strength query for given passwordresult=psm.check_pwd("123456")# The result is consist of four parts:print(result["guess_number"],result["segments"],result["chunks"],result["prob"])
Package: ckrett
ckrett-python-libraryversion-1.5.0This is an useful python library for people who care about privacy, this library is useful to cipher and decipher text using 6 simple functions.Available operations in ckret library:1.syph() -----> cypherises the user input text2.dsyph() -----> decypherises the user input text to plain text3.ksyph() ------> cypherises the user input text with unique 6 digit security key4.kdsyph() -------> decypherises the text only when 6 digit security key is provided correctly5.morse() -----> converts plain english text into morse code6.dmorse() -----> converts morse code into plain english text7.stot() -------> converts speech to text, can be used in place of input()Prerequisites:==> for speech recognition to work that is stot(),pyaudio, speechrecognition must be strictly pre-installed, otherwise you'll get an error.==> if pyaudio,  speechrecognition is already installed you can skip this step and proceed for installationorinstall pyaudio by executing the following commands in cmd before or after installing ckrett:step-1 : $ pip install pipwin
step-2 : $ pipwin install pyaudiopipwin is like pip, but it installs precompiled Windows binaries and depencies that are required for building and compiling pyaudio setup filesnext install speechrecognition by executing the following commands in cmd$ pip install speechrecognitionusecase example:you can either use traditional input()importckrettx=input()msg=ckrett.syph(x)print(msg)or:importckrettx=ckrett.stot()msg=ckrett.syph(x)print(msg)u can change syph(),dsyph(),ksyph(),kdsyph(),morse(),dmorse() respectively depeding on your choice of ciphering==>changes in 1.5.0:$ added morse(),dmorse(),stot()$ user can now convert plain english text into morse code and vice versa$ using stot() user can dicate a sentence which is recognized using dependecies-pyaudio,pyttxs3,speech_recognition engine that can be stored in var x which can be used for         ciphering directly from speech, instead of typing out the entire sentence using input().note-1:->stot() can only be used to give input in plain english, as special character or encrypted msg's arent recognized accurately->use stot() for syph(),ksyph(),morse()note-2:->text ciphered using syph() can only be deciphered strictly by dsyph()->text ciphered using ksyph() can only be deciphered strictly by kdsyph()->text ciphered using morse() can only be deciphered strictly by dmorse()note-3:->in version 1.0.0,1.5.0 there is no support for characters --> @,#,$,%,^,&,*,(,),! , kindly avoid using them in your sentence.->support for these charcaters will be added in next version (2.0.0)for bug reports/issues --->https://github.com/sasivatsal7122/ckret-library-pypihappy ciphering, peace✌.