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Fonts, colors and charts are not supported.
Nor to read password protected xls, xlsx and ods files.
Here is a typical conversation between the developer and the user:
User: "I have uploaded an excel file"
"but your application says un-supported file format"
Developer: "Did you upload an xlsx file or a csv file?"
User: "Well, I am not sure. I saved the data using "
"Microsoft Excel. Surely, it must be in an excel format."
Developer: "OK. Here is the thing. I were not told to support"
"all available excel formats in day 1. Live with it"
"or delay the project x number of days."Flask-Excel is based on pyexcel and makes it easy to consume/produce information stored in excel files over HTTP protocol as well as on file system. This library can turn the excel data into a list of lists, a list of records(dictionaries), dictionaries of lists. And vice versa. Hence it lets you focus on data in Flask based web development, instead of file formats.
The idea originated from the common usability problem: when an excel file driven web application is delivered for non-developer users (ie: team assistant, human resource administrator etc). The fact is that not everyone knows (or cares) about the differences between various excel formats: csv, xls, xlsx are all the same to them. Instead of training those users about file formats, this library helps web developers to handle most of the excel file formats by providing a common programming interface. To add a specific excel file format type to you application, all you need is to install an extra pyexcel plugin. Hence no code changes to your application and no issues with excel file formats any more. Looking at the community, this library and its associated ones try to become a small and easy to install alternative to Pandas.
The highlighted features are:
- excel data import into and export from databases
- turn uploaded excel file directly into Python data structure
- pass Python data structures as an excel file download
- provide data persistence as an excel file in server side
- supports csv, tsv, csvz, tsvz by default and other formats are supported via the following plugins:
| Package name | Supported file formats | Dependencies |
|---|---|---|
xls, xlsx(read only), xlsm(read only) |
||
| pyexcel-xlsx | xlsx | openpyxl |
ods |
pyexcel-ezodf, lxml |
|
| pyexcel-ods | ods | odfpy |
| Package name | Supported file formats | Dependencies |
|---|---|---|
| pyexcel-xlsxw | xlsx(write only) | XlsxWriter |
| pyexcel-libxlsxw | xlsx(write only) | libxlsxwriter |
| pyexcel-xlsxr | xlsx(read only) | lxml |
| pyexcel-xlsbr | xlsb(read only) | pyxlsb |
| pyexcel-odsr | read only for ods, fods | lxml |
| pyexcel-odsw | write only for ods | loxun |
| pyexcel-htmlr | html(read only) | lxml,html5lib |
| pyexcel-pdfr | pdf(read only) | camelot |
Since 2020, all pyexcel-io plugins have dropped the support for python version lower than 3.6. If you want to use any python verions, please use pyexcel-io and its plugins version lower than 0.6.0.
Except csv files, xls, xlsx and ods files are a zip of a folder containing a lot of xml files
The dedicated readers for excel files can stream read
In order to manage the list of plugins installed, you need to use pip to add or remove a plugin. When you use virtualenv, you can have different plugins per virtual environment. In the situation where you have multiple plugins that does the same thing in your environment, you need to tell pyexcel which plugin to use per function call. For example, pyexcel-ods and pyexcel-odsr, and you want to get_array to use pyexcel-odsr. You need to append get_array(..., library='pyexcel-odsr').
Other data renderers| Package name | Supported file formats | Dependencies | Python versions |
|---|---|---|---|
write only:rst, mediawiki, html, latex, grid, pipe, orgtbl, plain simple read only: ndjson r/w: json |
2.6, 2.7, 3.3, 3.4 3.5, 3.6, pypy |
||
| pyexcel-handsontable | handsontable in html | handsontable | same as above |
svg chart |
2.7, 3.3, 3.4, 3.5 3.6, pypy |
||
| pyexcel-sortable | sortable table in html | csvtotable | same as above |
gantt chart in html |
except pypy, same as above |
Footnotes
This library makes information processing involving various excel files as easy as processing array, dictionary when processing file upload/download, data import into and export from SQL databases, information analysis and persistence. It uses pyexcel and its plugins:
- to provide one uniform programming interface to handle csv, tsv, xls, xlsx, xlsm and ods formats.
- to provide one-stop utility to import the data in uploaded file into a database and to export tables in a database as excel files for file download.
- to provide the same interface for information persistence at server side: saving a uploaded excel file to and loading a saved excel file from file system.
Since 2020 Auguest, latest pyexcel-io version 0.6.0 forced Flask-Excel to use Python 3.6+
For older Flask versions and lower Python version, please use pyexcel-io<=0.5.20.
You can install Flask-Excel via pip:
$ pip install Flask-Excelor clone it and install it:
$ git clone https://github.com/pyexcel-webwares/Flask-Excel.git
$ cd Flask-Excel
$ python setup.py installHere are some example codes:
from flask import Flask, request, jsonify
import flask_excel
app=Flask(__name__)
flask_excel.init_excel(app)
@app.route("/upload", methods=['GET', 'POST'])
def upload_file():
if request.method == 'POST':
return jsonify({"result": request.get_array(field_name='file')})
return '''
<!doctype html>
<title>Upload an excel file</title>
<h1>Excel file upload (csv, tsv, csvz, tsvz only)</h1>
<form action="" method=post enctype=multipart/form-data>
<p><input type=file name=file><input type=submit value=Upload>
</form>
'''
@app.route("/export", methods=['GET'])
def export_records():
return excel.make_response_from_array([[1,2], [3, 4]], "csv",
file_name="export_data")
if __name__ == "__main__":
app.run()Development steps for code changes
- git clone https://github.com/pyexcel/Flask-Excel.git
- cd Flask-Excel
Upgrade your setup tools and pip. They are needed for development and testing only:
- pip install --upgrade setuptools pip
Then install relevant development requirements:
- pip install -r rnd_requirements.txt # if such a file exists
- pip install -r requirements.txt
- pip install -r tests/requirements.txt
Once you have finished your changes, please provide test case(s), relevant documentation and update CHANGELOG.rst.
Note
As to rnd_requirements.txt, usually, it is created when a dependent library is not released. Once the dependecy is installed (will be released), the future version of the dependency in the requirements.txt will be valid.
Although nose and doctest are both used in code testing, it is adviable that unit tests are put in tests. doctest is incorporated only to make sure the code examples in documentation remain valid across different development releases.
On Linux/Unix systems, please launch your tests like this:
$ makeOn Windows systems, please issue this command:
> test.batPlease run:
$ make formatso as to beautify your code otherwise travis-ci may fail your unit test.
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