High performance Excel file parser based on the xlrd library from www.python-excel.org for reading Excel files in XLS or XLSX formats.
IMPORTANT: this package is being moved over to the pyspreadsheet project, which provides many new features such as writing files. It is based on the same Python/Node hybrid, but integrates with more libraries in order to deliver new features beyond xlrd. As a result, xlrd-parser is no longer under active development.
npm install xlrd-parser
The xlrd dependency is installed automatically by downloading the latest version from github.
Parsing a file loads the entire file into an object structure composed of a workbook, sheets, rows and cells.
var xlrd = ;xlrd;
The returned object is either a workbook object, or an array of workbook objects if multiple files were specified as the source. The workbook object contains a structure of sheets, rows and cells to represent the data.
The Workbook object contains the following members:
file- the file used to open the workbook
meta- metadata for this workbook
user- the owner of the file
sheets- an array of strings containing the name of sheets (available without any iteration)
sheets- the array of Sheet objects that were loaded
The Sheet object contains the following members:
index- the ordinal position of the sheet within the workbook
name- the name of the sheet
bounds- an object specifying the data range for the sheet
rows- the total number of rows in the sheet
columns- the total number of columns in the sheet
visibility- the sheet visibility - possible values are
rows- the array of rows that were loaded - rows are arrays of Cell objects
The Cell object contains the following members:
row- the ordinal row number
column- the ordinal column number
address- the cell address ("A1", "B12", etc.)
value- the cell value
Cell values can be of the following types:
Number- for numeric values
Date- for cells formatted as dates
Error- for cells with errors, such as #NAME?
Boolean- for cells formatted as booleans
String- for anything else
For more details on the API, see the included unit tests.
For large files, you may want to stream the data. The stream method returns a familiar EventEmitter instance.
var xlrd = ;xlrd;
stream method returns a Node
EventEmitter instance. Use
on to listen to events and read the data continuously.
open - fires when a workbook is opened (sheets are not available at this point)
Arguments: the workbook object
data - fires repeatedly as data is being read from the file
Arguments: a data object containing the following:
workbook: the current workbook object
sheet: the current sheet object
rows: the current batch of rows
error - fires every time an error is encountered while parsing the file, the process is stopped only if a fatal
error is encountered
Arguments: the error object
close - fires only once, after all files and data have been read
An object can be passed to the
stream methods to define additional options.
meta- load only workbook metadata, without iterating on rows -
sheets- load sheet(s) selectively, either by name or by index -
maxRows- the maximum number of rows to load per sheet -
debug- log output from the xlrd-parser child process -
Output sheet names without loading any data:
Load only the first 10 rows from the first sheet:
Load only a sheet named "products":
var stream = xlrd;
Windows platform is not yet supported, but it is only a matter of converting the installation script to PowerShell. A Python shell also needs to be available from the command line, which could be installed via chocolatey.
Many thanks to the authors of the xlrd library (here). It is the best and most efficient open-source library I could find.
The package itself is MIT licenced.
License from xlrd library:
Portions copyright © 2005-2009, Stephen John Machin, Lingfo Pty Ltd All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. None of the names of Stephen John Machin, Lingfo Pty Ltd and any contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. /*- * Copyright (c) 2001 David Giffin. * All rights reserved. * * Based on the the Java version: Andrew Khan Copyright (c) 2000. * * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * * 3. All advertising materials mentioning features or use of this * software must display the following acknowledgment: * "This product includes software developed by * David Giffin <firstname.lastname@example.org>." * * 4. Redistributions of any form whatsoever must retain the following * acknowledgment: * "This product includes software developed by * David Giffin <email@example.com>." * * THIS SOFTWARE IS PROVIDED BY DAVID GIFFIN ``AS IS'' AND ANY * EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DAVID GIFFIN OR * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, * STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED * OF THE POSSIBILITY OF SUCH DAMAGE. */