Saravanan666/pypi-org huggingface dataset:
Package: excel-generator
DescriptionExcel export from json library used to support standardized testing.Programmatic examplefromexcel_generator.generatorimportGeneratorjson_file="results.json"excel_file="Results.xls"generator=Generator(json_file=json_file,excel_file=excel_file)generator.generate()Package call pypipython-mexcel_generator--infileresults.json--outfileresults.xlsSet detailsThere are 3 ways to set the input variables for the CLI:Add an 'environment.properties' file containing: IN_FILE=results.json\nOUT_FILE=output.xlsSet infile and outfile using an ENV VARs. E.g. export IN_FILE=results.json && export OUT_FILE=results.xlsSet infile and outfile using CLI options '--infile' & '--outfile'Supported formatsList of Dict(s) - Multiple messages (example)[{"testName":"exampleTest1","Db":"Mysql57","OS":"Centos7","logLocation":"http://logdatabase.com/exampleTest1","startedat":"Sun Nov  1 10:16:52 EET 2020","endedat":"Sun Nov  1 10:22:52 EET 2020"},{"testName":"exampleTest2","Db":"Mysql57","OS":"Centos7","logLocation":"http://logdatabase.com/exampleTest2","startedat":"Sun Nov  1 10:22:52 EET 2020","endedat":"Sun Nov  1 10:30:52 EET 2020"}]
Package: excel-graph-parser
Excel graph parser (open-source parser for translation of excel graphs to Plotly figures)This repository can be installed to show nicely formatted graphs generated by excel documents.
Currently only useful forVIKTORapplications.InstallationPaste the link of this repository in yourrequirements.txt:viktor==14.7.0
excel-graph-parserContributingImprovements to the view are very welcome. Please ensure your improvements adhere to the code standards by running
black, isort and pylint (with the versions specified indev-requirements.txt):python-mblackviktor_table_view/;python-misortviktor_table_view/;python-mpylintviktor_table_view/--rcfile=pyproject.toml;
Package: exceling
xlwings CExlwings CE is aBSD-licensedPython library that makes it easy to call
Python from Excel and vice versa:Scripting: Automate/interact with Excel from Python using a syntax that is close to VBA.Macros: Replace your messy VBA macros with clean and powerful Python code.UDFs: Write User Defined Functions (UDFs) in Python (Windows only).REST API: Expose your Excel workbooks via REST API.Numpy arraysandPandas Series/DataFramesare fully supported. xlwings-powered workbooks are easy to distribute and work
onWindowsandMac.xlwings CE includes all files in the xlwings package except theprofolder, i.e. thexlwings.prosubpackage.xlwings PROThe purpose of xlwings PRO is to finance the continued maintenance and enhancement of xlwings. This will allow you to rely on the package without being left with the dreaded“this library currently has no active maintainers”message that happens to too many open-source packages after a couple of years.To get access to the additional functionality of xlwings PRO, you need a license key and at least xlwings v0.19.0. Everything under thexlwings.prosubpackage is distributed under a commercial license, seehttps://github.com/xlwings/xlwings/blob/master/LICENSE_PRO.txt.For current features and pricing:https://www.xlwings.org/pricingTo request a trial license key:https://www.xlwings.org/trialLinksHomepage:https://www.xlwings.orgQuickstart:https://docs.xlwings.org/en/stable/quickstart.htmlDocumentation:https://docs.xlwings.orgVideo Course:https://training.xlwings.org/p/xlwingsSource Code:https://github.com/xlwings/xlwingsxltrailThe Excel add-in is version controlled withxltrail. You can see the diffshere.
Package: excelize
ExcelizePython library for reading and writing Microsoft Excel™ (XLSX) files.Free software: BSD licenseDocumentation:https://excelize.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-11-06)First release on PyPI.
Package: excelkit
A ToolKit to Operate Excel FileInstallationpip install excelkitToolsparse- parse excel fileexcelkitparse--help# orexcel-parse--help


excel-parsedemo.xlsx

excel-parsedemo.xlsx-oout.tsv

excel-parsedemo.xlsx-Otable

excel-parsedemo.xlsx-Otable--colorred

excel-parsedemo.xlsx-Ojson--indent2excel-parsedemo.xlsx-Ojson--indent2--header

excel-parsedemo.xlsx--pagerbuild- build excel fileexcelkitbuild--help# orexcel-build--help


excel-builddemo/genelistdemo/hsa00010.conf

excel-builddemo/genelistdemo/hsa00010.conf-okegg.xlsx

excel-builddemo/genelistdemo/hsa00010.conf-okegg.xlsx-sGENE,KEGG

excel-builddemo/genelistdemo/hsa00010.conf-h

excel-builddemo/genelistdemo/hsa00010.conf-hs

excel-builddemo/genelistdemo/hsa00010.conf-hs-bs

catdemo/genelist|excel-buildconcat- concat excel filesexcelkitconcat--help# orexcel-concat--help

examples:

excel-concatinput1.xlsxinput2.xlsx-oout.xlsx

excel-concatinput1.xlsxinput2.xlsx-oout.xlsx--keep-fmt
Package: excellentman
excellentmanAn experimental repo for probably writing tools to execute parameterized newman runs from data in spreadsheetsInstall NewmanDownload and installNode.js.Then runnpm installin your checkoutInstallingpip install excellentmanUsageexcellentman <EXCEL_FILE> <JSON_COLLECTION> <ENVIRONMENT_FILE>Where:EXCEL_FILE: is a an excel file where each worksheet contains parameters to be passed into the postman requestsJSON_COLLECTION: collection of requests, either a URL, or downloaded from postmanENVIRONMENT_FILE: an exported Postman environments fileExampleWe've included example data for queryinghttps://www.thecocktaildb.com, in theexamplesdirectory.examples/Cocktails.postman_collection.json- A postman collection for querying the cocktail databaseexamples/Cocktails.xlsx- An excel file with multiple worksheets for different types of cocktailsexamples/Production Cocktails.postman_environment.json- An environment file for parameterizing the requestsYou can run this:excellentman examples/Cocktails.xlsx examples/Cocktails.postman_collection.json "examples/Production Cocktails.postman_environment.json"Custom Field HandlingIf you have data in your spreadsheet that needs to be transformed before it gets sent to the API you're working with, you can provide a python file of transformation functions, as inexamples/custom_formats.py.We include a trivial example that lowercases the drink names, which you can demonstrate by running:excellentman examples/Cocktails.xlsx examples/Cocktails.postman_collection.json "examples/Production Cocktails.postman_environment.json" --custom_formats=examples/custom_formats.pyCustom Report FormattingThis tool usesnewman-reporter-htmlextrato provide an HTML report of the results and can also supportnewman-reporter-xunitto provide an XML report file. You can customize the template used for this report, and pass it in as follows:excellentman examples/Cocktails.xlsx examples/Cocktails.postman_collection.json "examples/Production Cocktails.postman_environment.json" --custom_template=examples/example_reporter_template.hbs --xunit_file=xunit_reporter_example.xmlPublishing a new versionUpdate the version in setup.py.Build the version to publishpython3 setup.py sdist bdist_wheelPublish to testpypi (for now)python3 -m twine upload --repository testpypi dist/*
Package: excellentpandas
excellentpandasVery quickly load pandas DataFrames in ExcelPython is awesome and I love it for doing all sorts of data manipulation. But sometimes Microsoft Excel remains the best place to do quick data exploration and filtering. So thanks to the brilliantxlwings, it's easy to integrate the two. This module has some very simple functions to make this as easy as possible.Say you have this script:>>>df=read_data()>>>result=df.groupby("blah")[vars].agg(something_complex)And you want to exploreresultquickly in Excel.You can use one of the following functions to immediately launch the DataFrame in a new Excel Workbook on your desktop via a non-blocking call:show_in_excel(df)>>>fromexcellentpandasimportshow_in_excel>>>df=read_data()>>>result=df.groupby("blah")[vars].agg(something_complex)>>>show_in_excel(result)>>>Use.pipe(via_excel)for a chained version>>>fromexcellentpandasimportvia_excel>>>df=read_data()>>>result=df.groupby("blah")[vars].agg(something_complex).pipe(via_excel)>>>Show info as well with.pipe(via_info_excel)>>>fromexcellentpandasimportvia_info_excel>>>df=read_data()>>>result=df.groupby("blah")[vars].agg(something_complex).pipe(via_info_excel)<class'pandas.core.frame.DataFrame'>Int64Index:16entries,2004to2019Datacolumns(total6columns):...dtypes:float64(6)memoryusage:896.0bytes>>>Install$ pip install -U excellentpandas
Package: excellxgene
Exploratory CellxGene (ExCellxGene)V2.9.6The latest stable version is V2.9.6. The current version of exCellxgene relies on anndata==0.7.8, so might crash with anndata objects generated with anndata==0.8.0 or above. Until we fix this bug, we recommend users to follow the installation instruction below. The key part is installing exCellxgene, then upgrading the anndata version to 0.8.0 in the "cxg" conda environment.InstallationInstall miniconda if conda not available already:wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/minicondaCreate and activate a new environment:conda create -n cxg python=3.8
conda activate cxgInstall excellxgene with pip:pip install excellxgene
pip install anndata==0.8.0If your operating system is CentOS, then you may run into issues installing dependencies that require up-to-dategccorg++compilers. Please install with the following and try reinstallingexcellxgenewith pip:conda install -c conda-forge gcc cxx-compilerDownload the git repository to get the example datasets (assumes git is available, if not install it with conda install -c anaconda git)git clone https://github.com/czbiohub/excellxgene
cd excellxgeneDatasets are stored inexample-datasetLaunch excellxgene with:excellxgene launch example-datasetThis should launch an excellxgene session with all the datasets in example-datasets/ loaded in.If you're running excellxgene remotely, please launch with:excellxgene launch example-datasets --host 0.0.0.0Preprint on how to do manual cell-type annotation using interactive tools:https://www.biorxiv.org/content/10.1101/2023.07.11.548639v1Tutorial slides highligting some use cases:https://cellxgene.cziscience.com/docs/05__Annotate%20and%20Analyze%20Your%20Data/5_8__Multimodal%20AnnotationsMore tutorial slides for multi-omics datasets (RNA, ATAC, CITE-seq, spatial transcriptomics) are coming soon (Q1/Q2 2024).
Package: excelmanager
Introductionexcelmanageris a stripped-down wrapper around theopenpyxlpackage. It exposes two very simple functions (read_file_sheetandwrite_file_sheet) that provide quick and easy ways to perform read/write operations against Excel files. This package is ideal for applications where the goal is to be able to quickly and easily get simple tabular data in and out of various Excel files without worrying about things like advanced formatting or charting.Installationpip install excelmanagerUsageTheread_file_sheetfunction allows data to be read back from a sheet in multiple formats.# Outputs a list of ordered dictionariesresults=excelmanager.read_file_sheet("path/to/file.xlsx","Sheet1",output_row_type="OrderedDict")# Outputs a list of listsresults=excelmanager.read_file_sheet("path/to/file.xlsx","Sheet1",output_row_type="list")# Outputs a list of tuplesresults=excelmanager.read_file_sheet("path/to/file.xlsx","Sheet1",output_row_type="tuple")# Reads data from a specific rangeresults=excelmanager.read_file_sheet("path/to/file.xlsx","Sheet1",range=("B3","E12"))Thewrite_file_sheetwrites data to a specified Excel file and sheet. If the sheet or file don't yet exist, this function will create them.# Write from sequence data with specified headersexcelmanager.write_file_sheet("output.xlsx","path/to/output",(("Value1","Value2","Value3"),("Value4","Value5","Value6")),headers=("Column1","Column2","Column3"),)# Write using OrderedDict data. Keys are used as headers unless an empty sequence ([]) is passed.excelmanager.write_file_sheet("output.xlsx","path/to/output.xlsx",[OrderedDict({"Column1":"Value1","Column2":"Value2","Column3":"Value3"}),OrderedDict({"Column1":"Value4","Column2":"Value5","Column3":"Value6"}),],)
Package: excel-model-runner
excel-model-runnerThis tool will take an Excel model (.xlsx), update any parameters as defined in the parameters file
and calculate all cells, resulting in an Excel spreadsheet resembling the original, but with all
formula cells replaced by the calculated values.The parameter file can be either JSON file or a CSV file in the following format:Config fileJSON:{
   "Sheet name.Cell1": "Replacement value string",
   "Sheet name.Cell2": Replacement value float
}Example:params.json{
    "Variables.C2": "red",
    "Variables.C3": 0.8
}CSV:Sheet name.Cell1,Replacement value string
Sheet name.Cell2,Replacement value floatExample:params.csvVariables.C2,red
Variables.C3,0.8NOTE: Do NOT include a header row in the CSVUsage:usage: run-excel-model [-h] [--output_dir OUTPUT_DIR] [--run_dir RUN_DIR] source_file parameter_file

positional arguments:
  source_file           Excel (xlsx) file that contains
  parameter_file        Path to json or csv parameter file

optional arguments:
  -h, --help            show this help message and exit
  --output_dir OUTPUT_DIR
                        Optional output location. (Default: output)
  --run_dir RUN_DIR     Optional directory to store intermediate files. (Default: runs)
Package: excel-modify
Excel ModifyExcel modifier is a Python package for editing Excel files. It provides a convenient interface to modify comments in Excel files, allowing users to update comments for specific cells.InstallationYou can install Excel modifier using pip:pipinstallexcel-modifyUsageQuick StartImport theExcelModeclass from theexcel_modifypackage.InitializeExcelModewith the path to your Excel file.Use theset_commentmethod to update the comment for a specific cell.Save the changes using thesavemethod.fromexcel_modifyimportExcelMode# Initialize ExcelMode with the path to your Excel fileexcel_mode=ExcelMode('path/to/your/excel/file.xlsx')# Set a comment in a specific cellexcel_mode.set_comment('A1','This is a comment')# Save the changes to the Excel fileexcel_mode.save()FeaturesEdit Excel Comments: Update comments for specific cells in Excel files.ContributingContributions are welcome! If you encounter any issues or have feature requests, please submit them through GitHub issues. Pull requests are also appreciated.Before contributing, please read theContributing Guidelines.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.This README provides clear and concise instructions on how to install the package, a quick start guide for basic usage, information on advanced usage, a feature list, guidelines for contributing, and license information. It aims to be user-friendly and informative for potential users and contributors.
Package: excel-ngrams
The Excel Ngrams ProjectA project to analyse a column of text in an Excel document and
return a CSV file with the most common ngrams from that text. Output
file is returned to the same directory as the input file.You can choose the maximum n-gram length, and maximum number of
results (rows) returned. The app defaults to looking for a column
named'Keyword' but any column name can be passed in as an argument.The column of terms to analyse must be the longest (or only) column
in the document to prevent the addition of NaN as a placeholder in
final cells, which will cause errors.Words are tokenised with Spacy and ngrams are generated with NLTK.InstallationTo install the Excel Ngrams Project,
run this command in your terminal:$ pip install excel-ngrams
Package: excel-picture
excel_picture一个可以快速批量获取文件中的图片信息
基于python的实现的批量获取文件中的图片信息，并已json 形式展示，安装简单，可安装于python2或python3 环境中，用于web业务，博客，各种脚本中，等批量填充网站图片1.如何安装使用pip 安装pip install  excel_picture2.及使用示例 支持xlsx xls 等文件格式from excel_picture import main
res = main(file_path='test.xlsx')
print(res)3.运行结果示例{'com': '/image2.png, /image33.png',
'com2':'/image1.png, /image3.png'}4.结果讲解key 对应的 文件的图片备注信息，支持中英文，尽量使用英文
value 为图片路径5.联系我们13073771301@163.com
Package: excel-productive-CLI
Python Excel-productive-CLITimeTracker-CLI is a command-line interface (CLI) application designed to help users efficiently track and manage their time spent on various tasks and projects.Description.Easy-to-use CLI Interface: TimeTracker-CLI provides a user-friendly command-line interface, enabling users to quickly start, stop, and manage their time tracking without the need for complex graphical user interfaces. With a series of simple commands, users can navigate the application and maintain their time records with ease.Install guide.pip install excel-productive-CLI
Package: excelrd
excelrdexcelrdInstallationQuick startTransition from xlrd to excelrdAnother quick startAcknowledgementsDocumentationexcelrdexcelrdis a modified version ofxlrdto work for the latest Python versions.xlrdwill not work in Python 3.9 or newer versions.Purpose: Provide a library for developers to use to extract data from Microsoft Excel (tm) spreadsheet files. It is not an end-user tool.Author: John MachinLicence: BSD-style (see licences.py)Versions of Python supported: 3.5+.Outside scope: excelrd will safely and reliably ignore any of these
if present in the file:Charts, Macros, Pictures, any other embedded object. WARNING:
currently this includes embedded worksheets.VBA modulesFormulas (results of formula calculations are extracted, of course).CommentsHyperlinksAutofilters, advanced filters, pivot tables, conditional formatting,
data validationHandling password-protected (encrypted) files.Installationpip install excelrdQuick startPrint all of the cell values in a specific sheet:Sample Code:importexcelrddefmain():book=excelrd.open_workbook("namesdemo.xls")print("The number of worksheets is{}".format(book.nsheets))print("Worksheet name(s):{}".format(", ".join(book.sheet_names())))sh=book.sheet_by_index(2)print("{}: rows={}, cols={}".format(sh.name,sh.nrows,sh.ncols))forrow_idxinrange(sh.nrows):forcol_idxinrange(sh.ncols):cell=sh.cell(row_idx,col_idx)ifnotcell.value:continueprint("row={}, col={}, value={}".format(row_idx,col_idx,cell.value))Transition from xlrd to excelrdReplace the import fromimport xlrdtoimport excelrd:importexcelrdasxlrdAnother quick startThis will show the first, second and last rows
of each sheet in each file:python PYDIR/scripts/runxlrd.py 3rows *blah*.xlsAcknowledgementsThis package started life as a translation from C into Python of
parts of a utility called “xlreader” developed by David Giffin. “This
product includes software developed by David Giffindavid@giffin.org.”OpenOffice.org has truly excellent documentation of the Microsoft
Excel file formats and Compound Document file format, authored by
Daniel Rentz. Seehttp://sc.openoffice.orgU+5F20 U+654F: over a decade of inspiration, support, and interesting
decoding opportunities.Ksenia Marasanova: sample Macintosh and non-Latin1 files, alpha
testingBackporting to Python 2.1 was partially funded by Journyx - provider
of timesheet and project accounting solutions (http://journyx.com/).Provision of formatting information in version 0.6.1 was funded by
Simplistix Ltd (http://www.simplistix.co.uk/)Documentationhttps://excelrd.rtfd.io/
Package: excels2vensim
excels2vensimSystems Dynamics models often use large amounts of input data. Reading this data is complicated when it corresponds to multidimensional matrices. In the case of Vensim, if the data is read from '.xlsx' files, the data can only be read in two-dimensional tables at most, which implies the introduction of multiple equations in the model file.The excels2vensim library aims to simplify the incorporation of equations from external data into Vensim. Given the name of the variable and information on how its dimensions are distributed, the library returns the equations for copying and pasting into the Vensim model. In addition, the library uses cellrange names to write the equations, and automatically creates the cellranges in the '.xlsx' file.The automation of this process can save a lot of time for the modeller, as well as reduce possible human error by avoiding entering a large number of equations by hand. The library is also flexible and works for any number of dimensions. In addition, it allows reading data of which one dimension is spread over different files or sheets.This library is able to automate the generation of the following type of equations:GET XLS CONSTANTSGET DIRECT CONSTANTSGET XLS DATA (with or without keywords)GET DIRECT DATA (with or without keywords)GET XLS LOOKUPSGET DIRECT LOOKUPSRequirementsPython 3.9+PySD 3.12+ResourcesSee theproject documentationfor information about:InstallationUsageSome jupyter notebook examples are available in theexamples folder of the GitHub repository.Authority and acknowledgmentesThis library was originally developed forH2020 LOCOMOTIONproject by@enekomartinmartinezatCentre de Recerca Ecològica i Aplicacions Forestals (CREAF).This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No. 821105.
Package: excelschema
excelschemaExcel records' parser and schema viewing and validating tools.InstallationMethod 1:$ pip install excelschemaMethod 2:Clone the project from GitHubpoetry installUsageTo read an Excel file, you may also need to installpyexcelandpyexcel-xlsxas well.>>>fromexcelschemaimportSchemaParser>>>importpyexcel>>>sp=SchemaParser(records=pyexcel.get_records(file_name='foo.xlsx',sheet_name='bar'))>>>sp.schema{'record_id':<class'int'>,'modified':<class'datetime.datetime'>,'data':<class'str'>}Validating records and convert it to a usable one.>>>sp.ensure_one({'record_id':' 12','data':567}){'record_id',12,'data':'567'}Setting constraints>>>fromexcelschemaimportConstraint>>>sp.update_schema({...'user_id':Constraint(type_=int,unique=True,not_null=True)...})It is also possible to create an custom schema without an Excel>>>sp=SchemaParser(schema={...'record_id':Constraint(type_=int,unique=True,not_null=True),...'modified':datetime...})Bonus functionsCleaning dirty Excel records>>>fromexcelschemaimportparse_record>>>parse_record({'foo':' 1','bar':' - ','baz':' '}){'foo',1}Related projectshttps://github.com/patarapolw/tinydb-constraint
Package: excelsheet
MIT LicenseCopyright (c) 2022 Danyal Zia KhanPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.