Saravanan666/pypi-org huggingface dataset:
Package: tei2neo
TEI parserThis is a parser written in Python 3 that takes TEI-XML Documents as an inpput and writes them in aNeo4j Graph Database.It makes use of the following existing libraries:Beautiful Soup 4An easy-to-use XML parserSpacy. Currently we use the german language packagede_core_news_smto parse the text.Py2neo v4whih is a library to work with the Neo4j database.Installation$ pip install tei2neo
$ python "de_core_news_sm @https://github.com/explosion/spacy-models/releases/download/de_core_news_sm-3.6.0/de_core_news_sm-3.6.0.tar.gz"Synopsisfrom tei2neo import parse, GraphUtils
graph = Graph(host="localhost", user="neo4j", password="password")
doc, status, soup = parse(
	filename=file,
	start_with_tag='TEI',
	idno='20-MS-221'
)
tx = graph.begin()
doc.save(tx)
tx.commit()

ut = GraphUtils(graph)
paras = ut.paragraphs_for_filename('20_MS_221_1.xml')

# create unhyphened tokens
for para in paras:
    tokens = ut.tokens_in_paragraph(para)
    ut.create_unhyphenated(tokens)

# show hyphened text
for token in ut.tokens_in_paragraph(paras[5], concatenated=0):
    if 'lb' in token.labels:
        print(' | ', end='')
    print(token.get('string',''), end='')
    print(token.get('whitespace', ''), end='')

# show concatenated (non-hyphened) version of the text
for token in ut.tokens_in_paragraph(paras[5], concatenated=1):
    if 'lb' in token.labels:
        print(' ', end='')

    print(token.get('string',''), end='')
    print(token.get('whitespace', ''), end='')How the parser worksA TEI document can be constructed in various ways and there are many elements that work very similarly. Likewise, this parser expects certain elements and treats them in a specific manner.Elements that affect all following elementshandShiftAhandShiftelementaffects all elements that are below, until anotherhandShiftelement is encountered.ExampleFrom now on everything is written in «Latein» and a pencil is being used (medium=Blei):<handShift new="#hWH" medium="Blei" script="Latein"/>Now we switch to «Kurrent» script and use black ink (STinte):<handShift new="#hGS" medium="STinte" script="Kurrent"/>Appearance in Neo4jAs we have seen, ahandShiftelement contains three attributes:new="#hWH"medium="Blei"script="Latein"These attributes are passed to all Token elements that follow after ahandShiftoccurs. Previous attributes are not deleted, i.e. if only the medium changes from «Blei» to «STinte», all other attributes stay the same.
ThehandShiftelement willnotappear as a node in Neo4j.delSpanAdelSpanelement works much like ahandShiftelement, as it alters the appearance of all the following text until it reaches itsspanTotarget:<delSpan spanTo="#A20_MS_215_12_3"/>
... (a lot of XML code here)
<anchor xml:id="A20_MS_215_12_3"/>Appearance in Neo4jboth thedelSpanand theanchorappear as additional nodes.all elements between thedelSpanand theanchorelement receive an additionaldelSpanlabeladelSpanattribute is added to every element, the value is equal to thexml:idattribute of the anchor.
Package: teichicrypt
TeichicryptIs a python program for encrypting and decrypting files of any kind. It isnotbased on any other crypting mechanism I know.RequirementsPython ver >= 3.6m, mpmathUsageEither run the pythonfile with python version 3.6 or greater or import it into a other script wich is running python version >= 3.6.When run as main, a tkinter window for easy usage will open, else use the subroutines as you want.To-doGood documentationimplementation as command-line tool...Github-Repohttps://github.com/tobi08151405/teichicrypt
Package: teicli
TEI PythonText Embeddings Inference (TEI)'s unofficial python wrapper library for batch processing with asyncio.Get StartedpipinstallteiclifromteiimportTEIClientclient=TEIClient()client.embed_sync("Hello world!")# [0.010536194, 0.05859375, 0.022262....routine=client.embed_batch(["Hello world!","Hello world!","Hello world!"])# [[0.010536194, 0.05859375, 0.022262....You need to run own text-embeddings-inference server. Checkheredockerrun--gpusall-p8080:80-v$volume:/data--pullalwaysghcr.io/huggingface/text-embeddings-inference:0.3.0--model-id$model--revision$revision
Package: tei-excel-tools
tei_excel_toolsInstallpipinstalltei_excel_toolsHow to use所定のフォーマットを持つExcelファイルを格納した入力パス、およびTEI/XMLファイルの出力パスを指定してください。フォーマットは以下でご確認ください。https://zenn.dev/nakamura196/articles/4a4b3c50745c87fromtei_excel_tools.coreimportClientinput_path="data/sample.xlsx"output_path="data/output.xml"xml_string=Client.convertExcel(input_path)Client.save(xml_string,output_path)
Package: teimpy
teimpyPython library for displaying image on terminal.Installation$pipExampleimportnumpyasnpfromteimpyimportget_drawer,ModeR=np.array([1.0,0,0])G=np.array([0,1.0,0])B=np.array([0,0,1.0])def_get_color(x,y):tmp=(y*(1.0-x)*R+(1.0-y)*x*G+(1.0-y)*(1.0-x)*B)return(255*tmp).astype(np.uint8)tics=np.linspace(0,1,128)xs,ys=np.meshgrid(tics,tics)buffer=np.vectorize(_get_color,signature='(),()->(3)')(xs,ys)print(get_drawer(Mode.ITERM2_INLINE_IMAGE).draw(buffer))FeatureResize images to fit terminal size.Drawing with iterm2 inline image.Drawing with Braille fonts.Drawing with half block fonts.LicenseThis software is released under the MIT License, seeLICENSE.
Package: teiphy
A Python package for converting TEI XML collations to NEXUS and other formats.Textual scholars have been using phylogenetics to analyze manuscript traditions since the early 1990s.
Many standard phylogenetic software packages accept as input theNEXUS file format.
Theteiphyprogram takes a collation of texts encoded using theText Encoding Initiative (TEI) guidelinesand converts it to a NEXUS format so that it can be used for phylogenetic analysis.
It can also convert to other formats as well, including Hennig86 (for TNT), PHYLIP (for RAxML), FASTA, and the XML format used by BEAST 2.7.InstallationThe software can be installed usingpip:pipinstallteiphyAlternatively, you can install the package by cloning this repository and installing it with poetry:gitclonehttps://github.com/jjmccollum/teiphy.gitcdteiphypipinstallpoetrypoetryinstallOnce the package is installed, you can run all unit tests via the commandpoetryrunpytestUsageTo use the software, run theteiphycommand line tool:teiphy<inputTEIXML><outputfile>teiphycan export to NEXUS, Hennig86 (TNT), PHYLIP (in the relaxed form used by RAxML), FASTA, BEAST 2.7 XML, CSV, TSV, Excel and STEMMA formats.teiphywill try to infer the file format to export to from the extension of the output file. Accepted file extensions are:
“.nex”, “.nexus”, “.nxs”, “.ph”, “.phy”, “.fa”, “.fasta”, “.xml”, “.tnt”, “.csv”, “.tsv”, “.xlsx”.To explicitly say which format you wish to export to, use the--formatoption. For example:teiphy<inputTEIXML><outputfile>--formatnexusFor more information about the other options, see the help with:teiphy--helpOr see the documentation with explanations aboutadvanced usage.The software can also be used in Python directly.
SeeAPI Referencein the documentation for more information.Creditsteiphywas designed by Joey McCollum (Australian Catholic University) and Robert Turnbull (University of Melbourne).
We received additional help from Stephen C. Carlson (Australian Catholic University).If you use this software, please cite the paper: Joey McCollum and Robert Turnbull, “teiphy: A Python Package for Converting TEI XML Collations to NEXUS and Other Formats,”JOSS7.80 (2022): 4879, DOI: 10.21105/joss.04879.@article{MT2022,author={Joey McCollum and Robert Turnbull},title={{teiphy: A Python Package for Converting TEI XML Collations to NEXUS and Other Formats}},journal={Journal of Open Source Software},year={2022},volume={7},number={80},pages={4879},publisher={The Open Journal},doi={10.21105/joss.04879},url={https://doi.org/10.21105/joss.04879}}Further details on the capabilities ofteiphy, particularly in terms of the text-critically valuable features it can map from TEI XML collations to BEAST 2 inputs, are discussed in Joey McCollum and Robert Turnbull, “Using Bayesian Phylogenetics to Infer Manuscript Transmission History,”DSHTBD (2024), DOI: 10.1093/llc/fqad089.@article{MT2024,author={Joey McCollum and Robert Turnbull},title={{Using Bayesian Phylogenetics to Infer Manuscript Transmission History}},journal={Digital Scholarship in the Humanities},year={2024},volume={TBD},number={TBD},pages={TBD},doi={10.1093/llc/fqad089},url={https://doi.org/10.1093/llc/fqad089}}
Package: tei-reader
Python 3 Library for Reading the Text Content and Metadata of TEI P5 (Lite) FilesThe library focuses on extracting the main text content from a file and provide the available metadata about the text.TL;DRpipinstalltei-readerfromtei_readerimportTeiReaderreader=TeiReader()corpora=reader.read_file('example-tei.xml')# or read_stringprint(corpora.text)# show element attributes before the actual element textprint(corpora.tostring(lambdax,text:str(list(a.key+'='+a.textforainx.attributes))+text))More ExplanationA reader can be opened usingTeiReader(). It is then possible to either callread_file(file_name)orread_string(str). Both will return aCorporaobject containing the following properties:PropertyDescriptioncorpora[]A corpora can contain sub-corpora.documents[]TheDocumentobjects directly part of this corpora.CorporaandDocumentall inherit fromElement. In all objects deriving from this it is possible to call:PropertyDescriptionattributes{}Contain attributes applicable to this element. If an attribute contains attributes these are also returned. (e.g.encodingDesc::editorialDecl::normalization)textGet the entire text content asstrdivisions[]Recursively get all the text divisions in document order. If an element contains parts or text without tag. Those will be returned in order and wrapped with aPlaceholderDivision.parts[]Recursively get the parts in document order constituting the entire text e.g. if something has emphasis, a footnote or is marked as foreign. Text without a container element will be returned in order and wrapped with aPlaceholderPart.Attribute,PlaceholderDivisionandPlaceholderPartall support the same properties asElement.Upload to PyPipythonsetup.pysdist
twineuploaddist/*
Package: tei_transformer
#Abouttei_transformer is a Python script for transforming a TEI-encoded critical edition into a pdf file. There are plenty of XSLT stylesheets to do something like this already, but using Python instead gives a secret advantage: we don’t really lose out on anything, but it’s unbelievably easy to customise things.So what we have here is conceptually as much a framework for your own changes as something immediately usable (although it is.)# Interested?[Read the docs](http://tei-transformer.readthedocs.org/en/latest/index.html) for more.
Package: tei-validator
tei-validatorTEI XML validation packageInstallationInstall this library usingpip:$ pip install tei-validatorUsageusage:tei-validator[-h][--debug][--outputOUTPUT][path]positionalarguments:pathpathorglobexpressionoptions:-h,--helpshowthishelpmessageandexit--debug,-dincreaseslogleveltodebug--outputOUTPUT,-oOUTPUTsavesthelogoutputtoafileDevelopmentTo contribute to this library, first checkout the code. Then create a new virtual environment:cd tei-validator
python -mvenv venv
source venv/bin/activateOr if you are usingpipenv:pipenv shellNow install the dependencies and test dependencies:pip install -e '.[test]'To run the tests:pytest
Package: tejask
PythonBY TEJAS.AElementary math moduleDocumentationPythonAscending order:def ascend(a):
    a.sort()
    return aAddition:def add(a, b):
    c = a + b
    return cSubtraction:def sub(a, b):
    c = a - b
    return cMultiplication:def mult(a, b):
    c = a * b
    return cDivision:def div(a, b):
    c = a / b
    return cDescending order:def descend(a):
    a.sort(reverse=True)
    return aReverse of a number:def rev(a):
    return a[::-1]
Package: tej-tool-api
使用 Tool API 獲取數據(股價、財務、月營收、集保和股票屬性)安裝套件pipinstalltej-tool-api匯入套件importosos.environ['TEJAPI_KEY']="YOURAPIKEY"importTejToolAPIget_history_data - 獲取歷史資料list_of_Stocks=['2330','2303','2454','2882','2881']# 撈取歷史資料data=TejToolAPI.get_history_data(ticker=list_of_Stocks,columns=['稅前淨利成長率','單月營收成長率％'],transfer_to_chinese=False)目前資料庫僅支援台灣市場。Tool API 可獲取 PIT 資料庫的所有欄位，共計超過 600 個指標，具體指標內容參考TEJAPI_量化投資資料庫。財務數據是根據發布日（announcement date）來mapping，非發布日的財務數據會使用當下可獲得最新的資料為準進行填值。ex: 2330 在 2010-02-01 時所能獲得最新的財務資料為 2009Q3 的財務資料，則 2010-01-01 會以 2009Q3 的資料進行填補。惟公司2009Q4自結財報早於 2010-02-01 發布時，且 include_self_acc = 'Y'，這時 2010-02-01 的財務數據使用自結財務數據。參數:ParametersIs RequiredData TypeDescriptionstickerRequiredlist股票代碼，ex: ['2330', '2881', '2882']columnsRequiredlist欄位代碼，可參考TEJAPI_量化投資資料庫startOptionaldate/str起始日，ex: '2008-01-01' (預設值為 '2013-01-01')，目前版本尚未支援timezone的設定endOptionaldate/str結束日，ex: '2008-01-01' (預設值為今日 datetime.now())，目前版本尚未支援timezone的設定transfer_to_chineseOptionalboolean欄位轉換成中文，若 transfer_to_chinese=True，則欄位顯示為中文名稱，transfer_to_chinese=False，則欄位顯示為英文名稱。(預設為 False)fin_typeOptionallist會計科目類型 -> 單季:Q、累計:A、移動四季:TTM，ex: 撈取單季和累積，fin_type=['Q','A']。(預設為 ['Q','A','TTM'])include_self_accOptionalstring財務是否包含公司自結損益，include_self_acc='Y'，表示財務資料包含自結損益，否則僅有財簽資料 (預設為 'N')npartitionsOptionalint多核心執行，可以指定執行所要使用的核心數量，ex: npartitions=6，代表使用6個核心來運行程式 (預設為當前 CPU 可使用之核心數)get_internal_code內部欄位編碼與中英文簡稱轉換功能TejToolAPI.get_internal_code(['稅前淨利成長率','Gross_Profit_Loss_from_Operations'])output: ['r404', 'gm']參數:ParametersIs RequiredData TypeDescriptionscolumnsRequiredlist欄位代碼，可參考TEJAPI_量化投資資料庫search_columns若想從內部編碼反向取得 columns 所對應之中英文欄位則可利用 search_columns 這個functionTejToolAPI.search_columns(['r404'])columnschn_column_nameseng_column_namestable_namesTABLE_NAMESAPI_TABLECHN_NAMESr404稅前淨利成長率Pre_Tax_Income_Growth_Ratefin_self_accfin_self_accTWN/AFESTM1財務-自結數r404稅前淨利成長率Pre_Tax_Income_Growth_Ratefin_board_selectfin_board_selectTWN/AFESTMD財務-董事決議數參數:ParametersIs RequiredData TypeDescriptionscolumnsRequiredlist欄位代碼，可參考TEJAPI_量化投資資料庫search_tableTejToolAPI.search_table(['r404'])COLUMNSTABLE_NAMESr404fin_self_accr404fin_auditor參數:ParametersIs RequiredData TypeDescriptionscolumnsRequiredlist欄位代碼，可參考TEJAPI_量化投資資料庫
Package: teke
TekeTeke is a lightweightASGIframework that you can use to create fast async REST APIs with Python.RequirementsPython 3.10+Installation$pipinstalltekeYou'll also want to install an ASGI server, such asuvicorn,daphne, orhypercorn.$pipinstalluvicornExampleexample.py:fromtekeimportJsonResponse,Router,create_approuter=Router()@router.route("/hello/<name>")asyncdefhello(connection,name):returnJsonResponse({"hello":name})app=create_app(routers=[router])Then run the application using Uvicorn:$uvicornexample:appRun uvicorn with--reloadto enable auto-reloading on code changes.For a more complete example, see exampleshere.Coming soon:WebSocket supportLifecycle hooksCORS middlewareDependenciesteke depends on the following python packages:anyiouvloopWerkzeug
Package: tekek
TekekTekek[təʔkəʔ] is easy to use, fast, server-agnostic, asynchronous, highly configurable local and remote logging toolFeaturesSemi-Direct Replacement for python built-in's loggerAsynchronousSupport Websocket(WIP)Reliable Remote LoggingReliable File LoggingReliable Console LoggingHighly ConfigurableInstallationTekek is available viaPyPIyou can install it usingpippython3-mpipinstalltekekImportTekekand instantiate.Hello WorldfromtekekimportTekeklogger=Tekek(name=__name__)By default, tekek came with 7 levels of log recordlogger.log("MESSAGE")logger.debug("MESSAGE")logger.info("MESSAGE")logger.warning("MESSAGE")logger.error("MESSAGE")logger.exception("MESSAGE")logger.critical("MESSAGE")example basic usage:deffunction_a():logger.log("function a starts !",identifier="function_a")try:...# Some Algorithmlogger.info("finished doing things","function_a")exceptExceptionase:logger.exception("Exception raised{}".format(e),"function_a")logger.debug(identifier="function_a",message="function a finished !")returndeffunction_b():logger.error("this error came from function b","function_a")and yes it is regular function not anasyncfunction. why ? BecauseTekekis smart enough to handle it for you. don't worry it barely scratch your application performanceCompatibility ExampleSanicoh yeah, if youGotta Go Fast, you need to develop itFAST! use tekek as your logging and debugging tool !fromsanicimportSanicfromsanic.responseimportjsonfromtekekimportTekekapp=Sanic("sanic_example")logger=Tekek("sanic_example",app=app)@app.route("/",methods=["GET"])asyncdefroot(request):logger.log("root accessed ! hello world!","root")returnjson({"status":"Hello World!"})if__name__=="__main__":app.run(host="0.0.0.0",port=8000)Fast APIA beautiful API Framework need a beautiful tekek as well ;)fromfastapiimportFastAPIfromtekekimportTekekapp=FastAPI()logger=Tekek("my_fast_api",app=app)@app.get("/")asyncdefroot():logger.log("root accessed ! hello world!","root")return{"status":"Hello World!"}Your Own Script!Of course you can use your own app! let's createmy_appas an exampleusingcoroutinefunctionimportasynciofromtekekimportTekeklogger=Tekek("mah_own")asyncdefmy_app(some_param:int):logger.log(f"My App Run Successfully!{some_param}")...# Your Beautiful appreturnTrueasyncdefmain():loop=asyncio.new_event_loop()asyncio.set_event_loop(loop)awaitasyncio.gather(my_app(3),logger.start())if__name__=='__main__':asyncio.run(main())usingclassimportasynciofromtekekimportTekeklogger=Tekek("mah_own")classMyApp:def__init__(self):self.some_vars=3asyncdefapp(self):logger.log(f"App Ran!{self.some_vars}")...# Your beautiful appasyncdefstart(self):asyncio.ensure_future(self.app())my_app=MyApp()asyncdefmain():loop=asyncio.new_event_loop()asyncio.set_event_loop(loop)awaitasyncio.gather(my_app.start(),logger.start())if__name__=='__main__':asyncio.run(main())Da Real Deal!Go Ahead and Read :Usage Documentations
Package: tekigo
TékigôAboutTékigô is a python helper tool for static mesh adaptation.
It eases the creation of metrics, and store them in a file.
The online documentation is available onthe internal Cerfacs forge(Credentials needed). Soon the package will be updated on pypi with documentation on readthedocs.There is a built-in adaptation step done withHIPmesh handler  developed at CERFACS. It is suited for unstructured grids and particularly useful for CFD.Note : for now, Tekigo handle AVBP mesh and solution format. However contact us for extendion to others format, it should not be a big deal...Installationplease install first pyHIP :pip install pyhipWhile we a refurbishing this new version 1.0, it will not be released on PyPI before we reach a stable version.
Therefore, please, use tekigo from the sources:git clone git@gitlab.com:cerfacs/tekigo.gitfollowed in thetekigo/parent directory by:python setup.py installIf possible addpyavbpto your environement.
This is not compulsory, but needed to create thexmffile from you ionitial mesh and solution.
Learn more about COOP virtual environements in thisblog post on COOP venvsBasic usage:Tekigo is used via python scripts, to do the following stepscreate aTekigoSolution, i.e. a mesh + solution with some additional fields
(coordinates , volume at node).Load from thisTekigoSolutionsome Quantities of Interests.Build a metric from these Quantities of Interests, usingnumpyformalism -and if neededsome tekigo utilities-.Evaluate the metric, i.e. forecast the future mesh : how many cells are we going to get?, what the fields will look like in the end?If asked, perform a HIP/MMG adaptationThe script reads:importnumpyasnpfromtekigoimport(TekigoSolution,adaptation_pyhip)tekigo_sol=TekigoSolution(mesh='../../GILGAMESH/trapvtx/trappedvtx.mesh.h5',solution='combu.init.h5',out_dir='./Results')x_coor=tekigo_sol.load_qoi('/Mesh/coord_x')metric_field=np.where(x_coor<0.1,1,0.7)tekigo_sol.evaluate_metric(metric_field)adaptation_pyhip(tekigo_sol,edge_low=1.e-3)See tutorials for more in-depth description of scripts.
No magic exxecution for the moment, create your python script  and run it withpythonmy_tekigo_script.pyPerformancesTekigo'sadaptation_pyhip()through HIP/MMG, is sequential :do not aim for final meshes above 150M Tetrahedrons.. Around 200 MCells, you will reach the limits of a sequential mesh adapter.
For larger cases, just use tekigo without theadaptation_pyhip()step, pass the solution toTreeAdapt. For the record,TreeAdaptneeds the final edge lenght (fieldtarget_edge), not the metric(fieldmetric).AcknowledgementsTekigo is the result of many discussions and developments of different contributors within the COOP team of CERFACS.Tekigo is a service created in theCOEC Center Of Excellence, funded by the European community.
Package: tekinstr
tekinstrInstallation> pip install tekinstrUsage>>>fromtekinstrimportCommChannel>>>withCommChannel("<ip address>")astek:...wf=tek.oscilloscope.read("CH1")>>>importmatplotlib.pyplotasplt>>>plt.plot(*wf.to_xy())[<matplotlib.lines.Line2Dat...>]>>>plt.show()It is possible to save the screen capture to a network or USB drive.
In this example, a USB memory stick is installed and the current
working directory is 'E:/'.>>>withCommChannel("<ip address>")astek:...tek.save_image("capture.png")Currently support modelsMDO3000 seriesMSO4000 seriesTDS3000 series
Package: tekleo-common-message-protocol
TekLeo Common Message ProtocolInstallationNormal installationpipinstalltekleo-common-message-protocolDevelopment installationgitclonehttps://github.com/jpleorx/tekleo-common-message-protocol.gitcdtekleo-common-message-protocol
pipinstall--editable.LinksIn case you’d like to check my other work or contact me:Personal websiteGitHubPyPIDockerHubArticles on MediumLinkedIn (feel free to connect)
Package: tekleo-common-utils
TekLeo Common UtilsA python package with shared utils methods that can be used in a variety of python projects, but are mostly tailored towards web / ml applications.Feel free to drop your suggestions, hopefully one day this will be a pretty comprehensive library of cool shared tools.DescriptionUnder construction... This shit is boring to write, will finish description and examples when I have more free time.Utils IDgenerate_uuidself-explanatoryUtils ImageConversion between PIL and OpenCV formats. Opening, saving, downloading, encoding images.convert_image_pil_to_image_cvconvert PIL image to OpenCV imageconvert_image_cv_to_image_pilconvert OpenCV image to PIL imageopen_image_pilload PIL image from fileopen_image_cvload OpenCV image from filesave_image_pilsave PIL image to filesave_image_cvsave OpenCV image to filedebug_image_cvshow a GUI window with an OpenCV image displayed in itdownload_image_pildownload PIL image from urlencode_image_pil_as_base64convert PIL image to base 64 encoded stringdecode_image_pil_from_base64convert base 64 encoded string to PIL imageUtils OpenCVVarious OpenCV tools you might commonly needblur_gaussianapply Gaussian blurrotate_boundrotate image bounded, preserving the original dimensions and cutting all rotated content that doesn't fit into original image sizerotate_freerotate image freely, changing dimensions to make sure all rotated content fits insidedeskewdeskew (straighten) image, works best on text images, like page scans and etc.Utils RandomRandom related stuff beyond the defaultrandommoduleget_random_user_agentgenerate a random User-Agent for HTTP headers (usinguser_agent library)UtilsPingSpecial utils to generate ping replies. Useful in web services.buildgenerate ping reply objectTODO / next updatesNeeds a lot of unit tests & usage examplesInstallationNormal installationpipinstalltekleo-common-utilsDevelopment installationgitclonehttps://github.com/jpleorx/tekleo-common-utils.gitcdtekleo-common-utils
pipinstall--editable.LinksIn case you’d like to check my other work or contact me:Personal websiteGitHubPyPIDockerHubArticles on MediumLinkedIn (feel free to connect)
Package: tekleo-common-utils-ai
TekLeo Common Utils AIA python package with shared utils methods that can be used in a variety of python projects, but are mostly tailored towards web / ml applications.DescriptionUnder construction...InstallationNormal installationpipinstalltekleo-common-utils-aiDevelopment installationgitclonehttps://github.com/jpleorx/tekleo-common-utils-ai.gitcdtekleo-common-utils-ai
pipinstall--editable.LinksIn case you’d like to check my other work or contact me:Personal websiteGitHubPyPIDockerHubArticles on MediumLinkedIn (feel free to connect)