Saravanan666/pypi-org huggingface dataset:
Package: sheet
sheetTools to extract content from ipython (jupyter) notebooksTo install:pip install sheetExamplesGetting the filepath of the current notebookfilepath=get_path_of_current_notebook()# Example: '~/my_notebook_folder/some_notebook.ipynb'Access to cells of a notebook given its filepathfromsheet.contentsimportget_ipynb_cells,get_ipynb_cells_sourcefilepath='~/my_notebook_folder/some_notebook.ipynb'cells=get_ipynb_cells(filepath)asserttype(cells),type(cells[0])==(list,dict)cells=get_ipynb_cells_source(filepath)asserttype(cells),type(cells[0])==(list,str)fromsheet.contentsimportget_ipynb_cells_full_textnotebook_text=get_ipynb_cells_full_text(filepath)print(notebook_text)Search the cells of a single notebookIndex and search the cells of a notebookfromsheetimportSingleNotebookSearchsearch=SingleNotebookSearch(src=None)# if no filepath (src) to a notebook is given, will use the "current notebook"result_indices=search('lines iterize')print(result_indices)print("\n---- Contents of first hit ----")print(search[result_indices[0]])# print the contents of the first result[70 225 226 198 199 196 200 201 193 197]

---- Contents of first hit ----
process_wf = Line(
    partial(fixed_step_chunker, chk_size=DFLT_CHK_SIZE),
    iterize(process_chk)
)Search the contents of the notebooks under a directoryfromsheet.contentsimportSearchNotebookssearch=SearchNotebooks('~/my_notebooks_folder',max_levels=0)# enter max_levels=None for full recursivesearch('bayesian')array(['Spyn 01 - Potentials.ipynb',
       'Bayes 01 - Potentials-Only explanation.ipynb', 'taped.ipynb',
       'separation of concerns - how py2store does it.ipynb',
       'equate.ipynb', 'peruse.ipynb',
       'hum, taped, lined -- feeding audio to a pipeline.ipynb',
       'owner.ipynb', 'best of 2020.ipynb',
       'Bayes 02 - Potentials - And drug data example.ipynb'],
      dtype=object)Okay, we have a list of notebooks that match our query
(i.e. the highest average alignment to our query -- not just keyword matching!),
but what cells in particular have the highest relevance?Well, we can now peruse our notebook at that level, with a notebook cells searcher.
(Note: You can combine both to make a cell-level searcher from the folder level.)ss=search.search_notebook('Spyn 01 - Potentials.ipynb')ss('bayesian')array([['Spyn 01 - Potentials.ipynb', 6],
       ['Spyn 01 - Potentials.ipynb', 2],
       ['Spyn 01 - Potentials.ipynb', 71],
       ['Spyn 01 - Potentials.ipynb', 88],
       ['Spyn 01 - Potentials.ipynb', 91],
       ['Spyn 01 - Potentials.ipynb', 84],
       ['Spyn 01 - Potentials.ipynb', 85],
       ['Spyn 01 - Potentials.ipynb', 86],
       ['Spyn 01 - Potentials.ipynb', 87],
       ['Spyn 01 - Potentials.ipynb', 82]], dtype=object)ss['Spyn 01 - Potentials.ipynb',6]'# Potentials - A key data structure to Discrete Bayesian Inference'ss['Spyn 01 - Potentials.ipynb',87]'### Making a few potentials from pts data'
Package: sheet2api
sheet2api-pythonGoogle/Excel Sheets API Python Client. For use withhttps://sheet2api.com/InstallationInstall usingpip...pipinstallsheet2apiUsage ExamplesBefore starting you should head over tosheet2api.comand link up your Google Sheets or Excel Online account andcreate your first Spreadsheet API.Next, create an instance of the client and pass in the API URL to your API.fromsheet2apiimportSheet2APIClientclient=Sheet2APIClient(api_url='https://sheet2api.com/v1/FgI6zV8qT222/my-api/')# If your API has authentication enabledclient=Sheet2APIClient(api_url='https://sheet2api.com/v1/FgI6zV8qT222/my-api/',username='api_username_here',password='api_password_here',)Get all rowsReturns all rows within thefirstSheet of your Spreadsheet.client.get_rows()# Returns a list of dicts[{'name':'Bob','age':22},{'name':'Richard','age':19},{'name':'Bob Jones','age':99}]To return rows from aspecificSheet.client.get_rows(sheet='Sheet1')Get all rows matching a queryReturns all rows matching a query.client.get_rows(query={'name':'Bob'})Create a new rowclient.create_row(sheet='Sheet1',row={'name':'Jane','age':18})Update all rows which match a queryThis will update the entire row for the matches, if you fail to specificy all column values in the replacementrow, those cells will be filled with an empty value.client.update_rows(sheet='Sheet1,query={'name':'Philip'},row={'name':'Phil','age':99999},)Partiallyupdate rows matching a query.This will only update the columns which you provide replacement values for in therowdict parameter. All other columns will be left unchanged.client.update_rows(sheet='Sheet1,query={'name':'Philip'},row={'age':99999},partial_update=True,)Delete all rows matching a queryclient.delete_rows(sheet='Sheet1',query={'name':'Satan'})SupportContact supportRelease History0.1.3 (2020-08-01)Docs fixes.0.1.2 (2020-05-10)Documentation updates.0.1.1 (2020-05-07)Documentation updates.0.1.0 (2020-05-06)Initial release.
Package: sheet2csv
sheet2csvPython package to transform Google Sheet to CSV.Installpipinstallsheet2csvExampleimportosimportsheet2csvSHEET_ID="PUT_ID_OF_SHEET_HERE"RANGE_STATS="SheetName!A3:ZZ"GOOGLE_API_KEY=os.environ["GOOGLE_API_KEY"]# First row of range will be become header row of CSVsheet2csv.sheet2csv(id=SHEET_ID,range=RANGE_STATS,api_key=GOOGLE_API_KEY,filename="export.csv",)Developmentgitclonehttps://github.com/sledilnik/sheet2csvcdsheet2csv
pipenvinstall
pipenvrunpipinstall-e.
pipenvruntest
Package: sheet2db
Sheet2dbSheet2db is a tiny python library for one-way syncing the Google spreadsheet to database. (Currently, it supports only MySQL)It is useful for managing some static data on Google spreadsheet, but also want to sync the sheet data to database.Sheet2db DOES NOT collect any your secret values!Installationpip install sheet2dbUsageYou must have API key which is accessible to Google Spreadsheet APIExample sheet format (itemstab):===========================
|  A |    B |     C |   D |
===========================
| id | name | count | ver |
|----|------|-------|-----|
| .. | .... | ..... | ... |
===========================Following example will syncitemstab of1U3un2ZJPRhLrWzc2DMXq8VI7Nqf9pYlajfO4mQVCZpEspreadsheet to database:"AIzaSyC6pabjqmaPiguYoHbq4W7a0DV0wQg5JGk" is a fake api keyfromsheet2dbimportSheet2db# Pass API keysyncer=Sheet2db(api_key='AIzaSyC6pabjqmaPiguYoHbq4W7a0DV0wQg5JGk')# If you need to access to private spreadsheet, you can't use API key. Use oauth credentials instead.syncer=Sheet2db(creds_path='credentials.json',token_path='token.json')# Fetch data from spreadsheetsyncer.fetch(sheet='1U3un2ZJPRhLrWzc2DMXq8VI7Nqf9pYlajfO4mQVCZpE',tab='items',range='A1:D')# Sync fetched data to database (mysql)syncer.sync(host='192.168.168.10',port=3306,user='mingrammer',password='p@ssw0rd',db='static',table='items')You can also use ssh tunneling to access to remote database withsshtunnelwithsshtunnel.SSHTunnelForwarder(('db.service.io',22),ssh_username='ssh_user'ssh_pkey='~/.ssh/id_rsa'ssh_private_key_password='ssh_pk_password',remote_bind_address=('localhost',3306),)astunnel:syncer.sync(host=tunnel.local_bind_host,port=tunnel.local_bind_host,user='mingrammer',password='p@ssw0rd',db='static',table='items')LicenseMIT
Package: sheet2graph
sheet2graphsheet2graph is a command developed as part of theFull-stack command commandline course at fromzerotofulsstackExamplesPrinting the spreadsheet contentssheet2graphsales_data.csv--print-onlyABCDE1Salesperweek(Firm:GlengarryGlenRoss)NaNNaNNaNNaN2SalesmanWeek1Week2Week3Week43RickyRoma201517114Shelley12015GeorgeAaronow65246DaveMoss8787Selecting datasheet2graphsales_data.xlsx-x"a3:a6"-y"b3:b6"--print-onlyxy0RickyRoma201Shelley12GeorgeAaronow63DaveMoss8Example output graphsheet2graphsales_data.xlsx-x"a3:a6"-y"b3:b6"--output-filenameoutput/tests/out.png-xlabel"Salesmen"-ylabel"Sales Week 1"Usageusage: sheet2graph [-h] [-x [X]] [-y [Y]] [-xlabel [XLABEL]] [-ylabel [YLABEL]] [--graph-type [GRAPH_TYPE]] [--output-folder [OUTPUT_FOLDER]] [--output-filename [OUTPUT_FILENAME]]
                      [--output-format [OUTPUT_FORMAT]] [--size [SIZE]] [--print-only [PRINT_ONLY]] [--run-tests [RUN_TESTS]] [--version [PRINT_VERSION]]
                      [input_file]

Graph spreadsheet data easily Takes a spreadsheet file as input and outputs an image file (bitmap, vector) with graphs of the data contained in the file. Accepted input files are csv and
xlsx file extensions

positional arguments:
  input_file            input file (csv, xlsx)

optional arguments:
  -h, --help            show this help message and exit
  -x [X]                An expression to select the x axis. Ex. '-x A2:A6' or '-x a2,a3,a4,a5'. The range works like in a spreadsheeet, with columns being letters, and row numbers starting
                        at 1. Case-insensitive
  -y [Y]                An expression to select the y axis. Ex. '-x b2:b6' or '-x B2,B3,B4,B5'. The range works like in a spreadsheeet, with columns being letters, and row numbers starting
                        at 1. Case-insensitive
  -xlabel [XLABEL]      The label for the x axis. By default 'x'
  -ylabel [YLABEL]      The label for the y axis. By default 'y'
  --graph-type [GRAPH_TYPE], -gt [GRAPH_TYPE]
                        [bar|line|scatter]: default is bar
  --output-folder [OUTPUT_FOLDER], -of [OUTPUT_FOLDER]
                        output_folder (ending without slash): default is 'output'. Can be serveral folders. ex. 'sales/graphs'
  --output-filename [OUTPUT_FILENAME], -ofi [OUTPUT_FILENAME]
                        output_filename: default is 'output/output.png'. Overrides --output-folder,--output-format if present
  --output-format [OUTPUT_FORMAT], -ofo [OUTPUT_FORMAT]
                        [png|jpg|svg]: default is png
  --size [SIZE], -s [SIZE]
                        size: widthxheight. Default '700x500'
  --print-only [PRINT_ONLY], -p [PRINT_ONLY]
                        Prints the selected data, without generating any file output
  --run-tests [RUN_TESTS]
                        Runs all the tests (might take a while). Overloads any other option
  --version [PRINT_VERSION], -v [PRINT_VERSION]
                        Show version information
Package: sheet2linkml
sheet2linkmlA python package for converting the CRDC-H data model, which is currently stored in aGoogle Sheet. The command line utility built into the package can be used
to generate aLinkMLrepresentation of the CRDC-H data model.Installation Requirements and Pre-requisitesPython 3.7 or higherpyenvIf you do not have a version of Python greater than 3.9, it is recommended to usepyenvto be able to easily use and
switch between multiple Python versions.If you’re experiencing issues with pyenv on macOS, you can consider usingminiconda.poetryOne-time installation commands are available forosx/linux/bash on windowsand forwindows powershell.If you are using a Windows machine, typical bash programs will not work oncmdin the same way as they work in the Linux/MacOS terminals. To circumvent this, it is recommended that you use one of the following Bash on Windows strategies:WSLCygwinGit Bashso you can easily execute the command line utilities that are described later in these docs.InstallingCreate and activate a Python 3.9+ virtual environment within which you can install the package:python3-mvenv.venvsource.venv/bin/activate
python-mpipinstallsheet2linkmlAuthorizationsheet2linkml uses thepygsheetslibraryin order to access sheets in
Google Drive. To authorize it to access your Google Sheets, you will need to create and download Google Drive client credentials. First,enable the Google Drive API. After the API is enabled,create and download the client credentialsfrom theGoogle API Console. Save the file asgoogle_api_credentials.jsonin
the root directory of this project.Detailed instructions and screenshotsare also available from thepygsheetsdocumentation.Command Line Client UsageIdentify the Google Sheet that you want to convert to LinkML. Note that sheet2linkml is not currently a general-purpose Google Sheet to LinkML converter. It will only work with Google Sheets that have been written in a particular, currently undefined format.Contact your CCDH colleagues to obtain the correct sheet ID and assert it either in a.envfile or in the shell, like this:exportCDM_GOOGLE_SHEET_ID=1oWS7cao-fgz2MKWtyr8h2dEL9unX__0bJrWKv6mQmM4Agoogle_api_credentials.jsonfile is also required in the root of this repo as detailed in the Authorization section above.And the user is responsible for defining~/path/to/crdch_model.yaml~/path/to/logging.ini./logging.inimay be adaquate for many usersThen perform the conversion:sheet2linkml--output~/path/to/crdch_model.yaml--logging-config~/path/to/logging.ini
Package: sheetcloud
SheetcloudTurn Spreadsheets into a Cloud Database with SheetCloud! Python library for easy access.Website:https://sheetcloud.orgNOTE: We are still in beta testing phase. If you like to become a Sheetcloud  beta tester (with some perks attached), write us an email atcontact[at]sheetcloud.org.StatusTestsDeploy to PYPISetupSheetcloud expects the following environment variables to be present:SHEETCLOUD_USERNAMESHEETCLOUD_PASSWORDYou can find both in your Sheetcloud dashboard spreadsheet. If you have no account yet, you can create your free account in less than 30sec (no credit card required). Head over toSheetcloud websiteand connect your account. That's it! You will be re-directed to the Sheetcloud dashboard spreadsheet containing the username and password.Supported functionalitySheetcloud supports Pandas DataFrames. Most functions are easy-to-use, self-explanatory, one-liners.SpreadsheetsRead/write/append spreadsheets in batchesList spreadsheets and worksheets of a spreadsheetGet modification timeFormattingCachingDriveRead/write CSVs in batchesORMmap bidirectional data classes to spreadsheetsEnvironment Variablesread/write environment variables to spreadsheetsload variables into local environmentTemplatesload pre-defined templatescustomize templatesUserrequest recovery tokenreset and change passwordsvalidate license keyauthentication/authorizationREST:language agnostic API and documentation availableWhat is Sheetcloud?Transform Your Spreadsheets into a powerful Cloud Database with SheetCloudUnlock the full potential of your data with SheetCloud! Say goodbye to the headaches of managing clunky offline spreadsheets and files, or setting up and maintaining a costly SQL database. With SheetCloud, you can turn your Google Sheets into a powerful cloud-based database with history, analytics, and online collaboration built in. Plus, with no hidden fees or charges, our simple and transparent pricing model will help you avoid the high costs of third-party databases.Keep your data secure and accessible by storing it within your own Google Drive account, protected by robust security measures against potential breaches. Say goodbye to version control issues and data silos, and work seamlessly with your team, including non-developers such as business analysts who use spreadsheets. Whether you need to process, read, or write data in batches, build powerful dashboards and automated reports, handle secrets and environment variables, or schedule workflows, SheetCloud has got you covered, all with a single command from Python.Test it now for free! No credit card required!
Package: sheetconf
sheetconfspreadsheet as confighow to use itGet config object from spreadsheet something like below.https://docs.google.com/spreadsheets/d/1PgLfX5POop6QjpgjDLE9wbSWWXJYcowxRBEpxmpG8ogimportsysimporttyping_extensionsastximportsheetconffromsheetconf.usepydanticimportParserfrompydanticimportBaseModel,FieldclassXXXConfig(BaseModel):name:strtoken:strclassYYYConfig(BaseModel):name:str=Field(default="yyy",description="name of yyy")token:str=Field(description="token of yyy")classLoggerConfig(BaseModel):level:tx.Literal["DEBUG","INFO","WARNING","ERROR"]classConfig(BaseModel):xxx:XXXConfigyyy:YYYConfiglogger:LoggerConfigurl="https://docs.google.com/spreadsheets/d/1PgLfX5POop6QjpgjDLE9wbSWWXJYcowxRBEpxmpG8og"config=sheetconf.loadfile(url,config=Config,format="spreadsheet",adjust=True)print(config)# Config(logger=LoggerConfig(level='INFO'), xxx=XXXConfig(name='xxx', token='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'), yyy=YYYConfig(name='yyy', token='yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy'))other./examples/e2e
Package: sheet-df
Google sheet to dataframeOverviewThis Python program connects to the google sheets api and creates a pandas dataframe from the target sheet.Usagedf=read_google_sheet_into_dataframe(sheet_id,range_name,credentials_path)ConfigYou must haveSHEET_ID`andRANGE_NAME`env vars. You will also need acredentials.jsonfrom google. Thecredentials_patharg defaults to “credentials.json”DEVCreate venvpython-mvenvenvActivate venvunixsourceenv/bin/activatewindowsenv\Scripts\activate.batInstall Packagespipinstall-rrequirements.txtTestmaketestFormatmakeformatmakelintVersion & Releasemakebumpversionpart=<major/minor/patch>makereleasenoteDon’t forget togit pushwith–tagspre-commitSetuppre-commitinstallRun allmakepre-commit
Package: sheetfu-dev
Sheetfu was built to interacts with Google Sheets with a simple, intuitive, and fast API.
The primary goal of this library is to adapt the Google App Script API for spreadsheets,
to Python. With Sheetfu, you can easily get or set cell values, background colors, font
colors or any other cell attributes.InstallingInstall and update usingpip:pip install -U sheetfu-devA Simple ExamplefromsheetfuimportSpreadsheetAppsa=SpreadsheetApp('path/to/secret.json')spreadsheet=sa.open_by_id('<insert spreadsheet id here>')sheet=spreadsheet.get_sheet_by_name('Sheet1')data_range=sheet.get_data_range()# returns the sheet range that contains data values.# this is how you get thingsvalues=data_range.get_values()# returns a 2D matrix of values.backgrounds=data_range.get_backgrounds()# returns a 2D matrix of background colors in hex format.# this is how you set thingsdata_range.set_background('#000000')# set every cell backgrounds to blackdata_range.set_font_color('#ffffff')# set every cell font colors to whiteFor better security, you can also create your SpreadsheetApp object with
environment variables instead of thesecrets.jsonfile.To obtain your secret json file and know more about how to initialize your ENV vars, you can refer tothe authentication tutorial.You can refer to thesheetfu API documentationfor a more detailed description.The Table moduleSheetfu also contains a table module that abstracts completely the coordinates
system for an ORM-like syntax. The example below is for a sheet with the 3
columns ‘name’, ‘surname’ and ‘age’.fromsheetfuimportTablespreadsheet=SpreadsheetApp('path/to/secret.json').open_by_id('<insert spreadsheet id here>')data_range=spreadsheet.get_sheet_by_name('people').get_data_range()table=Table(data_range,backgrounds=True)foritemintable:ifitem.get_field_value('name')=='foo':item.set_field_value('surname','bar')# this set the surname field valueage=item.get_field_value('age')item.set_field_value('age',age+1)item.set_field_background('age','#ff0000')# this set the field 'age' to red color# Every set functions are batched for speed performance.# To send the batch update of every set requests you made,# you need to commit the table object as follow.table.commit()You can refer to theTable API documentationfor a more detailed description.ContributingFor guidance on how to make a contribution to Sheetfu, see thecontributing guidelines.LinksLicense:MITReleases:https://pypi.org/project/sheetfu/Code:https://github.com/socialpoint-labs/sheetfuIssue tracker:https://github.com/socialpoint-labs/sheetfu/issuesIf you are looking for the original sheetfu google apps script library, it has been relocated tothis page.
Package: sheetfusion
SheetFusionSimple, user-friendly tool for merging cover sheets with document files.DescriptionSheetFusion is a simple, user-friendly tool designed to merge cover sheets with document files, primarily for academic and professional use. It automates the creation of personalized PDFs by combining individual cover pages with a standard document, such as exams or reports. This straightforward software offers a practical solution for those needing to distribute customized documents efficiently. It is written in Python and uses the [PyPDF3](https://github.com/sfneal/PyPDF3) library. It was created to merge cover sheets with exams. That is why the arguments are named as they are. However, it can be used to merge any PDF file with any other PDF file.1. System Requirements2. Installation2.1. Using pip (recommended)2.2. From source3. Usage3.1. Arguments3.2. Examples4. Change Log5. License6. Contact1. System RequirementsSheetFusionruns on any system withPythoninstalled:Python:Python 3.x is required. Verify your Python installation by runningpython --versionorpython3 --versionin your command line.Operating System:Compatible with Windows, macOS, Linux, and any OS supporting Python.2. Installation2.1. Using pip (recommended)python3-mpipinstallsheetfusion2.2. From sourceYou could use the following commands to clone and install SheetFusion. Make sure to replace X.X.X with the built version.gitclonehttps://github.com/SMZ70/SheetFusion.gitcdSheetFusion
python3-mbuild
python3-mpipinstalldist/sheetfusion-X.X.X.tar.gz3. Usage3.1. ArgumentsSheetFusionis a command-line tool designed for merging cover sheets with exams. To use it, follow the command syntax below (seeExamplesfor quick start).python3-msheetfusion[--help]--cover-sheets--exam[--output-dir][--overwrite]or:sheetfusion[--help]--cover-sheets--exam[--output-dir][--overwrite]4.1. Help Options--help,-hShow this help message and exit.4.2. Required Arguments--cover-sheets,-cSpecify the PDF file containing the cover sheets.--exam,-eSpecify the PDF file containing the exam.4.3. Optional Arguments--output-dir,-oDefine the directory to output the merged PDFs to.--overwriteEnable overwriting of existing files.3.2. ExamplesThe following examples demonstrate how to useSheetFusion:Basic Usagepython3-msheetfusion-ccover_sheets.pdf-eexam.pdfSpecifying an Output Directorypython3-msheetfusion-ccover_sheets.pdf-eexam.pdf-ooutput_dirOverwriting Existing FilesIf the output directory already contains files with the same name as the merged PDFs,SheetFusionwill not overwrite them by default. To enable overwriting, use the--overwriteflag.python3-msheetfusion-ccover_sheets.pdf-eexam.pdf-ooutput_dir--overwrite4. Change LogSee theCHANGELOGfor more information.5. LicenseSheetFusionis open-source software licensed under the MIT License. For more details, see theLICENSEfile in this repository.6. ContactThank you for your interest in SheetFusion! For bug reports, feature requests, or general inquiries related to the project, please useGitHub Issues. This is the fastest way to get your questions answered. It also allows other users to benefit from the discussion.
Package: sheetgen
# sheetgenDo you own a retail store or a warehose? Do you need an easy way of printing sheets with barcodes? This tool will help you with that!## What do we use sheetgen for?Most of the products in our shop (FooBar) already have EAN barcodes on them, but there are some products, i.e. tee, coffe or spoons, that do not. We simply generate sheets for them, cut them in smaller pieces and laminate them, then place close to the cash register.![The codes in our kiosk](https://files.kjagiello.com/3d39696c_codes.png)## Quickstart guideInstall using pip:`bash pip install sheetgen `Create a text file containing product names and their respective EAN codes.` 7310865000545   Milk 6410600109210   Cup of coffee 7392678922016   Cutlery `Run sheetgen and generate a PDF codesheet:`bash sheetgen codesheet.pdf < products.txt `
Package: sheets-for-person-schema
sheets-for-person-schemaFiles for schemasheets exercises at ICBO 2022Websitehttps://turbomam.github.io/sheets-for-person-schemaRepository Structureexamples/- example dataproject/- project files (do not edit these)src/- source files (edit these)sheets_for_person_schemaschema-- LinkML schema (edit this)datamodel-- Generated python datamodeltests- python testsDeveloper DocumentationUse the `make` command to generate project artefacts:make all: make everythingmake deploy: deploys siteCreditsthis project was made withlinkml-project-cookiecutter