Saravanan666/pypi-org huggingface dataset:
Package: xlsconv
xlsform-converter (xlsconv)xlsform-converter converts surveys defined via theXLSForm standardintoDjango modelsand configuration.  This makes it possible to re-use the powerful form building tools provided by theOpen Data Kit ecosystem, while leveraging Django's robust support for relational databases likePostgreSQL.xlsform-converter is designed to facilitate the rapid development of offline-capable data collection apps via thewq framework.  The ultimate goal is to provide full compatibility with the form authoring tools provided byODKandKoboToolbox(etc.).  Note that this is not the same as full XForm compatibility: the client and server components of wq (wq.appandwq.db) use a JSON-basedREST APIto exchange data and are not directly compatible with their ODK Analogues (ODK Collect and ODK Aggregate, respectively).For the database itself, the key distinction from other XLSForm tools (including those powered by Django, like KoboToolbox) is that xlsform-converter converts the xlsform fields directly into a Django model definition, rather than representing the entire XForm standard within Django.  This means that each row in an XLSForm "survey" tab is mapped to (usually) a single column in a simple relational database table.  Repeat questions are handled by creating a second model with aForeignKeyto the parent survey model.For a more thorough comparison of XLSForm tools, seehttps://wq.io/overview/survey123-vs-kobotoolbox-vs-wq.xlsform-converter also supports a couple of additional "constraints" that are not part of the XLSForm standard:wq:ForeignKey('app.ModelName'): Create a foreign key to an existing Django model (presumably not defined in the spreadsheet).  This is effectively a more relational version ofselect_one_external.wq:initial(3): Very similar torepeat_count, but only set for new records.wq:length(5): Text field maximum length (similar to astring-lengthconstraint)Included Templatesxlsform-converter uses ASTs and templates to generate the following Django/wq project files from a given XLSForm (for example,this file).Django Appsmodels.pyadmin.py(for use withdjango.contrib.admin)wizard.py(for use withDjango Data Wizard)rest.py(for use withwq.db.rest)serializers.py(for use withwq.db.rest)UsageIf you are using wq, you may be interested inwq.create, which uses xlsconv internally for thewq addformcommand.  Otherwise, you can use xlsconv directly with the following command-line API:# Recommended: create virtual environment# python3 -m venv venv# . venv/bin/activate# Install xlsconvpipinstallxlsconv# Use the default models.py templatexls2djangomy-odk-survey.xls>myapp/models.py# Use the rest.py template (or admin.py, or serializers.py)xls2djangomy-odk-survey.xlsrest>myapp/models.py
Package: xlscrap
WARNING : DON'T EXPECT SOMETHING USEFULL FROM THIS TOOL AT THIS STAGE !!xlscrapxlscrap is aMIT-licensedpackage to ease Excel files mass data extractionSee thedocumentation.RationaleHave you ever feel the pain of extracting data from a lot of Excel files ?When you have hundreds or thousands file that look similar
but differ in slighty annoying details.When data cells coordinates can't be used because they changeWhen you have to spot dozens or hundreds fields with different strategies.When the same field moves in different sheet position or nameWhen the same field label changesWhen the data cell is on the right of the label or below the labelWhen you need to check that the collected data is correct.xlscrap helps you to scrap data out of your Excel files.Quickstart>>>importxlscrap>>>s=xlscrap.Scrapper()>>>s.field('name')>>>s.field('age')>>>s.field('address')>>>s.table('pets',fields=['name','breed','age'])>>>s.scrap('excel-files/*.xls*')lookingfor4fieldsin5filesinexcel-files/*.xls*,file1/5,found4/4fieldsindiana.xlsxfile2/5,found4/4fieldsinbob.xlsfile3/5,found3/4fieldsinrichard.odsfile4/5,found0/4fieldsinalien.xlsfile5/5,found4/4fieldsinmaria.xlsm>>>s.result[{'name':'Diana','age':47,'address':'44 rue du Louvre\n75000 Paris\nFrance''pets':[]},...]TODOset gitlab URL in setup.pyclone gitlab/githubcomplete quickstart in README
Package: xlsfile-shaw1236
-- Prerequisite modules
-pandas@0.25.3
-openpyxl3.0.1
-xlrd@1.2.0-- Install xlsfile
pip install xlsfile --user-- How to use xlsfile?from xlsfile import xlsfileCsv file testingprint("Test csv file")
contents = xlsfile.readcsv("test2.csv")
xlsfile.writecsv("test3.csv", contents)input = {}
input["name"] = ["Test1", "Test2", "Test3"]
input["email"] = ["test1@gmail.com", "test2@yahoo.com", "test3@gmail.com"]
input["name"].append("Test4")
input["email"].append("test@yahoo.com")filename = "testfamily.xlsx"Excel file testprint("\nExcel file test")
xlsfile.write(filename, input)
contents = xlsfile.read(filename)
print(contents)Excel to csvprint("\nExcel to csv")
xlsfile.xls2csv(filename, filename.replace(".xlsx", ".csv"))csv to Excelprint("\ncsv to Excel")
xlsfile.csv2xls(filename.replace(".xlsx", ".csv"), "testfamily2.xlsx")
contents = xlsfile.read("testfamily2.xlsx")
print(contents)
Package: xlsform-filler-data
XLSform filler dataA commandline tool for creating dummy/test data from XLSform surveys.Installationpip install xlsform-filler-dataUsageTo create a dummy dataset, with a default number of rows(100) from a XLSform source:xlsform-filler-data <source-file-path>/<filename.xlsx>To specify the number of rows to create, use the-rflag. Example:xlsform-filler-data <source-file-path>/<filename.xlsx> -r 200To specify the output path and filename, pass the-oflag. Example:xlsform-filler-data <source-file-path>/<filename.xlsx> -o <./myfile.xlsx>RoadmapAs of version0.1.1the tool does not properly randomise multiple choice questions; omits some variables such as 'start' and 'end'; does not maintain the order of the variables; and does not incorporate constraints or cascading choice lists. These limitations will be adddressed in future releases.
Package: xlsimport
InstallationPackage installed as usually, with commandpip install xlsimportpackage requiresxlrdanddateutils.UsageXlsimport provide only API for now, no demo nor default setup. But it’s simple to start using it.First, you need to create descendant ofxlsimport.models.Formatclass, for example:class SubjectFormat(Format):
    cells = (
        {'name': 'Name', 'parsers': (TextCellToStringParser,)},
        {'name': 'Hours', 'parsers': (TextCellToIntParser, NumberCellToIntParser,)},
        {'name': 'Short name', 'parsers': (TextCellToStringParser,)},
    )

    def to_python(self, data_row):
        return {
            'name': data_row[0],
            'short_name': re.sub(r'[0-9-]+', '', data_row[2]),
            'hours': data_row[1],
        }In this codeNamecolumn may contains only text cells and they are represented as strings.
Second columnHoursmay contains text cells or number cells. They are represented as integers. Note that parsers
applied with respect to order.If you want to skip column, giveparsersthe valuexlsimport.models.dummy_parsers.
If cell must be empty there isblank_parsersvalue for that case.Next you should make class that knows how to handle data (craate or update records).
You also might want to place it into class like Django command.Here’s my example:...

class Command(BaseCommand):

    ...

    def handle(self, *args, **options):
        source_filename = args[0]
        source_file = open(source_filename, 'r')
        descriptor, name = tempfile.mkstemp()
        os.fdopen(descriptor, 'wb').write(source_file.read())
        doc = xlrd.open_workbook(name, formatting_info=True)
        format_doc = SubjectFormat(doc)

        for index, parsed_row in enumerate(format_doc):
            process_row(index, parsed_row)process_rowhere is a function that takes dictionary fromto_pythonmethod above.Tip. I created agistwith nice example of linuxdialogusage.
Package: xlson
xlsonPython package for transforming Excel files to JSON files and manipulating themInstallationTo install the package from PyPI type:pip install xlsonOr from the repo:pip install git+https://github.com/loven-doo/xlson.gitFor 'dev' branch version:pip install git+https://github.com/loven-doo/xlson.git@devPackage referencexlson.prepare_xlxlson.handlers.XLSonHandler
Package: xlsql
Introductionxlsqlis a simple command-line tool that converts an Excel.xlsxspreadsheet into asqlite3database.InstallationTo install this utility usingpipyou can simplypip install xlsqlUsageTo view command help, you can always runxlsql --help.Usage: xlsql [OPTIONS] SPREADSHEET

Convert an Excel spreadsheet into a SQLite database.

Args:
    spreadsheet (str): The path to the Excel spreadsheet.

Options:
    --column, -c:  A column (or columns) to extract. Can be specified multiple times.
    --database:    The name of the database to create. (default: database.db)
    --force:       Overwrite an existing database.
    --sheet, -s:   A sheet (or sheets) to extract. Can be specified multiple times.
    --verbose, -v: Show verbose output.
    --version, -V: Show the xlsql version number.

Examples:
    xlsql ~/Documents/Example.xlsx
    # Creates: ~/Documents/example.db with all data included in the database.

    xlsql ~/Documents/Example.xlsx --verbose
    # Creates: ~/Documents/example.db, displaying verbose output while running.

    xlsql ~/Documents/Example.xlsx --database /tmp/example.db
    # Creates /tmp/example.db with all data included from the Excel sheet.

    xlsql ~/Documents/Example.xlsx --database /tmp/example.db --force
    # Overwrites the existing db with fresh content from the sheet!

    xlsql example.xlsx -c name -c id -c address -s people
    # Only select the name, id, and address columns from the people sheet.ContributingTo contribute to this project, please fork the repo and make your changes there.  Submit a PR back to this repo for review.Be sure to install the dev dependencies, such aspre-commitandblack.
Package: xlsrch
xlsrch======tools for development..... in anad laboInstallation------------::pip install xlsrchUsage-----::python -m xlsrch... edit config file: xlsrch_conf.yaml... invoke againpython -m xlsrch... the result will print out on STD-OUT and out.txt on defaultnot yet edit^^^^^^^^^^^^--------------| any questions to:| dais.cns@gmail.com
Package: xls-to-csv
XLS to CSV converter.
Very fast, extremely light and easy to use.Installation:pip install xlstocsvComplementary package to xlsx2csv(https://github.com/xevo/xls2csv) - great tool, but does not work with .xls filesxlstocsvworks only with xls file (for legacy systems and 'legacy' clients :))Dependencies:
- python > 2.7
- pandas,
- xlrdUsage:xlstocsv /path/to/xls_or_xlsx_file/# spits CSV lines on CLI
Usage:xlstocsv /path/to/xls_or_xlsx_file/ /path/to/file.csv# writes in a CSV file
Package: xlstools
xls-toolsExcel and Excel-like toolsxlrd_likeA minimal interface for accessing excel-type files using thexlrdAPI:XlrdLike: workbook equivalent.sheet_names()- return list of sheet names.sheet_by_name()- return an XlSheetLike given by name.sheet_by_index()- return an XlSheetLike given by index.sheets()- return a list of XlSheetLikes-- requires initializing every sheetXlSheetLike: worksheet equivalent.name- the name of the sheet according to the workbook.nrows- int number of rows, 0-indexed.ncols- int number of columns, 0-indexed.row(n)- return a list of XlCellLike corresponding to the nth (0-indexed) row, or IndexError.col(k)- return a list of XlCellLike corresponding to the kth (0-indexed) column, or IndexError.cell(n,k)- return the nth row, kth cell, or IndexError.get_rows()- row iterator.row_dict(n)- return a dict of row n, using row 0 (headers) as keys and XlCellLike as valuesXlCellLike: cell equivalent.ctype- int, as indicated inxlrd.value- native valuexlrdctypes are as follows:from xlrd.biffh import (
    XL_CELL_EMPTY,  # 0
    XL_CELL_TEXT,   # 1
    XL_CELL_NUMBER, # 2
    XL_CELL_DATE,   # 3
    XL_CELL_BOOLEAN,# 4
    # XL_CELL_ERROR, # 5
    # XL_CELL_BLANK, # 6 - for use in debugging, gathering stats, etc
)To use:>>> from xls_tools import open_xl
>>> xl = open_xl(filename)
>>>Google sheetsAlso provides an xlrd-like interface for accessing google sheets.  Can also write to google sheets.
For this you need credentials for Google's service API.  See:Obtaining a service account$pythonsetup.pyinstallxls_tools[gsheet]xl_reader and xl_sheetModerately clever sheets for auto-detecting tabular data in spreadsheets, and manipulating it.
"Clever" enough to get in trouble perhaps.
Package: xlstpl
xlstplA python module to generate xls files from a xls template.How it worksxlstpl uses xlrd to read and use xlwt to write .xls files, uses jinja2 as its template engine.When xlstpl reads a .xls file, it creates a tree for each worksheet.Then, it translates the tree to a jinja2 template with custom tags.When the template is rendered, jinja2 extensions of cumtom tags call corresponding tree nodes to write the .xls file.Syntaxxlstpl uses jinja2 as its template engine, follows thesyntax of jinja2 template.Each worksheet is translated to a jinja2 template with custom tags....
...
{% row 45 %}
{% cell 46 %}{% endcell %}
{% cell 47 %}{% endcell %}
{% cell 48 %}{{address}}  {%xv v%}{% endcell %}
{% cell 49 %}{% endcell %}
{% cell 50 %}{% endcell %}
{% cell 51 %}{% endcell %}
{% cell 52 %}{% endcell %}
{% cell 53 %}{% endcell %}
{% row 54 %}
{% cell 55 %}{% endcell %}
{% cell 56 %}{% sec 0 %}{{name}}{% endsec %}{% sec 1 %}{{address}}{% endsec %}{% endcell %}
...
...
{% for item in items %}
{% row 64 %}
{% cell 65 %}{% endcell %}
{% cell 66 %}{% endcell %}
{% cell 67 %}{% endcell %}
{% cell 68 %}{% endcell %}
{% cell 69 %}{% endcell %}
{% cell 70 %}{% endcell %}
{% cell 71 %}{% endcell %}
{% cell 72 %}{% endcell %}
{% endfor %}
...
...xlstpl added 4 custom tags: row, cell, sec, and xv.row, cell, sec are used internally, used for row, cell and rich text.xv is used to define a variable.When a cell contains only a xv tag, this cell will be set to the type of the object returned from the variable evaluation.For example, if a cell contains only {%xv amt %}, and amt is a number, then this cell will be set to Number type, displaying with the style set on the cell.If there is another tag, it is equivalent to {{amt}}, will be converted to a string.InstalltionpipinstallxlstplHow to useSeeexamples.Notesxlrdxlrd does not extract print settings.This repodoes.xlwtxlwt always sets the default font to 'Arial'. (Excel measures column width units based on the default font).This repodoes not.
Package: xl-sudoku-solver
XL-Sudoku-SolverInstallpip install xl-sudoku-solverUsageCmd:problem1.txt:
9x37xxxx1
xxx6xx5xx
x4xxx1xxx
xxx36x2xx
8xxxxxxx4
xx6x97xxx
xxx5xxx2x
xx7xx3xxx
3xxxx28x9$ xl-sudoku-solver --time -f problem1.txt
+-----------+-----------+-----------+
| 9 ! 5 ! 3 | 7 ! 2 ! 4 | 6 ! 8 ! 1 |
| 7 ! 8 ! 1 | 6 ! 3 ! 9 | 5 ! 4 ! 2 |
| 6 ! 4 ! 2 | 8 ! 5 ! 1 | 9 ! 3 ! 7 |
+-----------+-----------+-----------+
| 1 ! 7 ! 4 | 3 ! 6 ! 8 | 2 ! 9 ! 5 |
| 8 ! 3 ! 9 | 2 ! 1 ! 5 | 7 ! 6 ! 4 |
| 5 ! 2 ! 6 | 4 ! 9 ! 7 | 3 ! 1 ! 8 |
+-----------+-----------+-----------+
| 4 ! 9 ! 8 | 5 ! 7 ! 6 | 1 ! 2 ! 3 |
| 2 ! 1 ! 7 | 9 ! 8 ! 3 | 4 ! 5 ! 6 |
| 3 ! 6 ! 5 | 1 ! 4 ! 2 | 8 ! 7 ! 9 |
+-----------+-----------+-----------+
Cost: 0.171875s
Package: xls-updater
xls_updaterConvert legacy xls data to newer xlsx format.💭Based on the kind comment made by JackypengyuUsageUsage: python -m xls_updater [OPTIONS] SRC_FILE_PATH

  Convert an xls file to xlsx.

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.DevelopmentPlease seeCONTRIBUTING.mdLicenseThis project is published under the MIT license.If you do find it useful, please consider contributing your changes back upstream.
Package: xlsx2dfs
xlsx2dfsEasy loading from and writing to excel sheets to/from pandas DataFrames (and list of sheet_names).Installationpipinstallxlsx2dfsUsagefromxlsx2dfsimportxlsx2dfs,withNames,dfs2xlsx# xlsx file pathfpath="test.xlsx"# read from it:dfs,sheet_names=xlsx2dfs(fpath)# write to itout_fpath="out_test.xlsx"dfs2xlsx(dfs,sheet_names=["sheet1","sheet2","sheet3"],out_fpath=out_fpath)# or using `withNames` which allows alternate input of sheet_name and corresponding df# `withNames("sheet1", dfs[0], "sheet2" dfs[1], "sheet3", dfs[2])` returns# ([dfs[0], dfs[1], dfs[2]], ["sheet1", "sheet2", "sheet3"])# thus (dfs, sheet_names). Using asterisk we can integrate them into the argument list# of `dfs2xlsx`.dfs2xlsx(*withNames("sheet1",dfs[0],"sheet2"dfs[1],"sheet3",dfs[2]),out_fpath)# This makes especially sense when you have different data frames as results in your script# and you want to save few lines of code which would be needed to bind them# together into a list and name them.# Instead, you can do the naming and binding to a list using `*withNames().# This also enhances readability and is intuitive.# e.g.dfs2xlsx(*withNames("Temperatures",temperatures_df,"Prediction",prediction_df,"Original Data",orig_df),"/path/to/output/file.xlsx")document the version:Linux:$ pip freeze | grep xlsx2dfsWindows:c:\> pip freeze | findstr xlsx2dfs
Package: xlsx2html
xlsx2htmlA simple export from xlsx format to html tables with keep cell formattingInstallpipinstallxlsx2htmlUsageSimple usagefromxlsx2htmlimportxlsx2htmlout_stream=xlsx2html('path/to/example.xlsx')out_stream.seek(0)print(out_stream.read())or pass filepathfromxlsx2htmlimportxlsx2htmlxlsx2html('path/to/example.xlsx','path/to/output.html')or use file like objectsimportiofromxlsx2htmlimportxlsx2html# must be binary modexlsx_file=open('path/to/example.xlsx','rb')out_file=io.StringIO()xlsx2html(xlsx_file,out_file,locale='en')out_file.seek(0)result_html=out_file.read()or from shellpython-mxlsx2htmlpath/to/example.xlsxpath/to/output.html
Package: xlsx2html-bugfix
xlsx2htmlA simple export from xlsx format to html tables with keep cell formattingInstallpipinstallxlsx2htmlUsageSimple usagefromxlsx2htmlimportxlsx2htmlout_stream=xlsx2html('path/to/example.xlsx')out_stream.seek(0)print(out_stream.read())or pass filepathfromxlsx2htmlimportxlsx2htmlxlsx2html('path/to/example.xlsx','path/to/output.html')or use file like objectsimportiofromxlsx2htmlimportxlsx2html# must be binary modexlsx_file=open('path/to/example.xlsx','rb')out_file=io.StringIO()xlsx2html(xlsx_file,out_file,locale='en')out_file.seek(0)result_html=out_file.read()or from shellpython-mxlsx2htmlpath/to/example.xlsxpath/to/output.html
Package: xlsx2pandas
🚀xlsx2pandas (PandasXcelerator)Part of aProjectText Suite. xlsx2pandas (PandasXcelerator) is a Python library for extraction of tables in Excel sheets into a pandas DataFrames.🌟FeaturesTODO: features📥 InstallationTo installxlsx2pandas, use the following pip command:pip3installgit+https://github.com/Flagro/xlsx2pandas.git📘UsageRunxlsx2pandasfrom the bin folder with these arguments:path: Path to the file or directory to process.--sheet: (Optional) Comma-separated list of excel workbooks's sheets.🖥️ Example Commandxlsx2pandas'path/to/file'--sheetSheet1,Sheet2🤝Collaboration & IssuesOpen for collaboration; check theissues pagefor discussions.Here's how you can contribute:Fork the Project.Create your Feature Branch (git checkout -b feature/AmazingFeature).Commit your Changes (git commit -m 'Add some AmazingFeature').Push to the Branch (git push origin feature/AmazingFeature).Open a Pull Request.
Package: xlsx2sqlite
Generate a Sqlite3 database from a Office Open XML file.
Read thexlsx2sqlite documentation.UsageFirst create a .INI config file that you will pass as an argument to thexlsx2sqlitecommand line tool. This will serve as a model to import data
from the .xlsx file.The INI file must contains this section:PATHSOptional sections, see below:EXCLUDEExample of a configuration:[PATHS]; declare the paths of the files to be read.root_path=baserootpath/xlsx_file=%(root_path)s/exampletoimport.xlsxdb_file=%(root_path)s/databasename.dbdb_url=sqlite:///%(db_file)ssql_views=%(root_path)s/views; declare to import a worksheet like this :; name of the worksheet to import[SheetName1]; comma-separated list of the columns to importcolumns=Col1,Col2,Col3; composite primary key is supported:primary_key=Col1,Col2[SheetName2]; valid model keywords are:columns=Col1,Col2primary_key=idunique=Col2not_null=Col2; add if the row with the header is not the first row of the worksheetheader=2Optional “exclude” section, use if you don’t want to import some section of the ini file,
this is useful in example for co-exist with some other configuration file.[EXCLUDE]sections=SECTION1,section2,etc.; use a list of comma-separated values.InstallationInstall the release from PyPI:$pipinstallxlsx2sqliteInstalling from source, a virtualenv is recommended:$pipinstall--editable.Requirementsxlsx2sqliteis powered byClickandTablib.Compatibilityxlsx2sqliteis compatible with Python 3.7+.LicenceGPLv3Authorsxlsx2sqlitewas written byErik Mascheri.
Package: xlsxcessive
XlsXcessive provides a Python API for writing Excel/OOXML compatible .xlsx
spreadsheets. It generates the XML and usesopenpackto wrap it up into an OOXML compatible ZIP file.Creating a WorkbookThe starting point for generating an .xlsx file is a workbook:from xlsxcessive.workbook import Workbook

workbook = Workbook()Adding WorksheetsThe workbook alone isn’t very useful. Multiple worksheets can be added to the
workbook and contain the cells with data, formulas, etc. Worksheets are created
from the workbook and require a name:sheet1 = workbook.new_sheet('Sheet 1')Working With CellsAdd some cells to the worksheet:sheet1.cell('A1', value='Hello, world')
sheet1.cell('B1', value=7)
sheet1.cell('C1', value=3.14)
sheet1.cell('D1', value=decimal.Decimal("19.99"))Strings, integers, floats and decimals are supported.Add cells via row index and column index:sheet1.cell(coords=(0, 4), value="Added via row/col index")This form of addressing is useful when iterating over data
structures to populate a sheet with cells.Calculations With FormulasCells can also contain formulas. Formulas are created with a string representing
the formula code. You can optionally supply a precalcuated value and asharedboolean flag to share the formula across a number of
cells. The first cell to reference a shared formula as its value is the master
cell for the formula. Other cells may also reference the formula:formula = sheet1.formula('B1 + C1', shared=True)
sheet1.cell('C2', formula) # master
sheet1.cell('D2', formula) # shared, references the master formulaCells With StyleThe library contains basic support for styling cells. The first thing to do is
create a style format. Style formats are shared on a stylesheet on the
workbook:bigfont = workbook.stylesheet.new_format()
bigfont.font(size=24, bold=True)Apply the format to cells:sheet1.cell('A2', 'HI', format=bigfont)Other supported style transformations include cell alignment and borders:col_header = workbook.stylesheet.new_format()
col_header.align('center')
col_header.border(bottom='medium')Adjusting Column WidthIt is possible to adjust column widths on a sheet. The column width is specified
by either number or index:# these are the same column
sheet1.col(index=0, width=10)
sheet1.col(number=1, width=10)TODO: Referencing columns by letters.Merging CellsCells can be merged together.  The left-most cell in the merge range should
contain the data:from xlsxcessive.worksheet import Cell
a3 = sheet1.cell('A3', 'This is a lot of text to fit in a tiny cell')
a3.merge(Cell('D3'))Save Your WorkYou can save the generated OOXML data to a local file or to an output file
stream:# local file
save(workbook, 'financials.xlsx')

# stream
save(workbook, 'financials.xlsx', stream=sys.stdout)FutureThis is certainly a work in progress.  The focus is going to be on improving the
features that can be written out in the .xlsx file. That means more data types,
styles, metadata, etc. I also want to improve the validation of data before it
is written in an incorrect manner and Excel complains about it. I don’t think
this library will ever be crafted to read .xlsx files. That’s a job for another
library that can hate its life.
Package: xlsxCsvConverterrr
xlsxCsvConverterrrfromconverter.converterimportxlsx_to_csv,csv_to_xlsxxlsx_to_csv('input_file','output_file')# input_file - xlsx file, output_file - path to save csv filecsv_to_xlsx('input_file','output_file')# input_file - csv file, output_file - path to save xlsx file# Functions return True if file had been saved