pyexcel - Let you focus on data, instead of file formats¶
- Author:
C.W.
- Source code:
- Issues:
- License:
New BSD License
- Released:
0.7.1
- Generated:
Nov 23, 2024
Introduction¶
pyexcel provides one application programming interface to read, manipulate and write data in various excel formats. This library makes information processing involving excel files an enjoyable task. The data in excel files can be turned into array or dict with minimal code and vice versa. This library focuses on data processing using excel files. Therefore, fonts, colors and charts were not and will not be considered.
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.
Support the project¶
If your company has embedded pyexcel and its components into a revenue generating product, please support me on github, or patreon maintain the project and develop it further.
With your financial support, I will be able to invest a little bit more time in coding, documentation and writing interesting posts.
Installation¶
You can install pyexcel via pip:
$ pip install pyexcel
or clone it and install it:
$ git clone https://github.com/pyexcel/pyexcel.git
$ cd pyexcel
$ python setup.py install
Suppose you have the following data in a dictionary:
Name |
Age |
---|---|
Adam |
28 |
Beatrice |
29 |
Ceri |
30 |
Dean |
26 |
you can easily save it into an excel file using the following code:
>>> import pyexcel
>>> # make sure you had pyexcel-xls installed
>>> a_list_of_dictionaries = [
... {
... "Name": 'Adam',
... "Age": 28
... },
... {
... "Name": 'Beatrice',
... "Age": 29
... },
... {
... "Name": 'Ceri',
... "Age": 30
... },
... {
... "Name": 'Dean',
... "Age": 26
... }
... ]
>>> pyexcel.save_as(records=a_list_of_dictionaries, dest_file_name="your_file.xls")
And here’s how to obtain the records:
>>> import pyexcel as p
>>> records = p.iget_records(file_name="your_file.xls")
>>> for record in records:
... print("%s is aged at %d" % (record['Name'], record['Age']))
Adam is aged at 28
Beatrice is aged at 29
Ceri is aged at 30
Dean is aged at 26
>>> p.free_resources()
Custom data rendering:
>>> # pip install pyexcel-text==0.2.7.1
>>> import pyexcel as p
>>> ccs_insight2 = p.Sheet()
>>> ccs_insight2.name = "Worldwide Mobile Phone Shipments (Billions), 2017-2021"
>>> ccs_insight2.ndjson = """
... {"year": ["2017", "2018", "2019", "2020", "2021"]}
... {"smart phones": [1.53, 1.64, 1.74, 1.82, 1.90]}
... {"feature phones": [0.46, 0.38, 0.30, 0.23, 0.17]}
... """.strip()
>>> ccs_insight2
pyexcel sheet:
+----------------+------+------+------+------+------+
| year | 2017 | 2018 | 2019 | 2020 | 2021 |
+----------------+------+------+------+------+------+
| smart phones | 1.53 | 1.64 | 1.74 | 1.82 | 1.9 |
+----------------+------+------+------+------+------+
| feature phones | 0.46 | 0.38 | 0.3 | 0.23 | 0.17 |
+----------------+------+------+------+------+------+
Advanced usage :fire:¶
If you are dealing with big data, please consider these usages:
>>> def increase_everyones_age(generator):
... for row in generator:
... row['Age'] += 1
... yield row
>>> def duplicate_each_record(generator):
... for row in generator:
... yield row
... yield row
>>> records = p.iget_records(file_name="your_file.xls")
>>> io=p.isave_as(records=duplicate_each_record(increase_everyones_age(records)),
... dest_file_type='csv', dest_lineterminator='\n')
>>> print(io.getvalue())
Age,Name
29,Adam
29,Adam
30,Beatrice
30,Beatrice
31,Ceri
31,Ceri
27,Dean
27,Dean
Two advantages of above method:
Add as many wrapping functions as you want.
Constant memory consumption
For individual excel file formats, please install them as you wish:
Package name |
Supported file formats |
Dependencies |
---|---|---|
csvz,tsvz readers depends on chardet |
||
xls, xlsx(read only), xlsm(read only) |
||
xlsx |
||
ods |
pyexcel-ezodf, lxml |
|
ods |
Package name |
Supported file formats |
Dependencies |
---|---|---|
xlsx(write only) |
||
xlsx(write only) |
||
xlsx(read only) |
lxml |
|
xlsb(read only) |
pyxlsb |
|
read only for ods, fods |
lxml |
|
write only for ods |
loxun |
|
html(read only) |
lxml,html5lib |
|
pdf(read only) |
camelot |
Plugin shopping guide¶
Since 2020, all pyexcel-io plugins have dropped the support for python versions which are lower than 3.6. If you want to use any of those Python versions, please use pyexcel-io and its plugins versions that are 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’).
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 |
||
handsontable in html |
same as above |
||
svg chart |
2.7, 3.3, 3.4, 3.5 3.6, pypy |
||
sortable table in html |
same as above |
||
gantt chart in html |
except pypy, same as above |
Footnotes
For compatibility tables of pyexcel-io plugins, please click here
pyexcel |
pyexcel-io |
pyexcel-text |
pyexcel-handsontable |
pyexcel-pygal |
pyexcel-gantt |
---|---|---|---|---|---|
0.6.5+ |
0.6.2+ |
0.2.6+ |
0.0.1+ |
0.0.1 |
0.0.1 |
0.5.15+ |
0.5.19+ |
0.2.6+ |
0.0.1+ |
0.0.1 |
0.0.1 |
0.5.14 |
0.5.18 |
0.2.6+ |
0.0.1+ |
0.0.1 |
0.0.1 |
0.5.10+ |
0.5.11+ |
0.2.6+ |
0.0.1+ |
0.0.1 |
0.0.1 |
0.5.9.1+ |
0.5.9.1+ |
0.2.6+ |
0.0.1 |
0.0.1 |
0.0.1 |
0.5.4+ |
0.5.1+ |
0.2.6+ |
0.0.1 |
0.0.1 |
0.0.1 |
0.5.0+ |
0.4.0+ |
0.2.6+ |
0.0.1 |
0.0.1 |
0.0.1 |
0.4.0+ |
0.3.0+ |
0.2.5 |
file format |
definition |
---|---|
csv |
comma separated values |
tsv |
tab separated values |
csvz |
a zip file that contains one or many csv files |
tsvz |
a zip file that contains one or many tsv files |
xls |
a spreadsheet file format created by MS-Excel 97-2003 |
xlsx |
MS-Excel Extensions to the Office Open XML SpreadsheetML File Format. |
xlsm |
an MS-Excel Macro-Enabled Workbook file |
ods |
open document spreadsheet |
fods |
flat open document spreadsheet |
json |
java script object notation |
html |
html table of the data structure |
simple |
simple presentation |
rst |
rStructured Text presentation of the data |
mediawiki |
media wiki table |
Usage¶
Suppose you want to process the following excel data :
Here are the example usages:
>>> import pyexcel as pe
>>> records = pe.iget_records(file_name="your_file.xls")
>>> for record in records:
... print("%s is aged at %d" % (record['Name'], record['Age']))
Adam is aged at 28
Beatrice is aged at 29
Ceri is aged at 30
Dean is aged at 26
>>> pe.free_resources()
Design¶
New tutorial¶
- One liners
- Stream APIs for big file : A set of two liners
- For web developer
- Pyexcel data renderers
- Sheet
- Book
- Working with databases
Old tutorial¶
- Work with excel files
- Work with excel files in memory
- Sheet: Data conversion
- How to obtain records from an excel sheet
- How to save an python array as an excel file
- How to save an python array as a csv file with special delimiter
- How to get a dictionary from an excel sheet
- How to obtain a dictionary from a multiple sheet book
- How to save a dictionary of two dimensional array as an excel file
- How to import an excel sheet to a database using SQLAlchemy
- How to open an xls file and save it as csv
- How to open an xls file and save it as xlsx
- How to open a xls multiple sheet excel book and save it as csv
- Dot notation for data source
- Read partial data
- Sheet: Data Access
- Sheet: Data manipulation
- Sheet: Data filtering
- Sheet: Formatting
- Book: Sheet operations
Cook book¶
- Recipes
- Update one column of a data file
- Update one row of a data file
- Merge two files into one
- Select candidate columns of two files and form a new one
- Merge two files into a book where each file become a sheet
- Merge all excel files in directory into a book where each file become a sheet
- Split a book into single sheet files
- Extract just one sheet from a book
- Loading from other sources
Real world cases¶
API documentation¶
Developer’s guide¶
Change log¶
- What’s breaking in 0.7.0
- What’s breaking in 0.6.0
- What’s breaking in 0.5.9
- Migrate away from 0.4.3
- Migrate from 0.2.x to 0.3.0+
- Migrate from 0.2.1 to 0.2.2+
- Migrate from 0.1.x to 0.2.x
- Change log
- 0.7.1 - 11.09.2024
- 0.7.0 - 12.2.2022
- 0.6.7 - 12.09.2021
- 0.6.6 - 14.11.2020
- 0.6.5 - 8.10.2020
- 0.6.4 - 18.08.2020
- 0.6.3 - 01.08.2020
- 0.6.2 - 8.06.2020
- 0.6.1 - 02.05.2020
- 0.6.0 - 21.04.2020
- 0.5.15 - 07.07.2019
- 0.5.14 - 12.06.2019
- 0.5.13 - 12.03.2019
- 0.5.12 - 25.02.2019
- 0.5.11 - 22.02.2019
- 0.5.10 - 3.12.2018
- 0.5.9.1 - 30.08.2018
- 0.5.9 - 30.08.2018
- 0.5.8 - 26.03.2018
- 0.5.7 - 11.01.2018
- 0.5.6 - 23.10.2017
- 0.5.5 - 20.10.2017
- 0.5.4 - 27.09.2017
- 0.5.3 - 01-08-2017
- 0.5.2 - 26-07-2017
- 0.5.1 - 12.06.2017
- 0.5.0 - 19.06.2017
- 0.4.5 - 17.03.2017
- 0.4.4 - 06.02.2017
- 0.4.3 - 26.01.2017
- 0.4.2 - 17.01.2017
- 0.4.1 - 23.12.2016
- 0.4.0 - 22.12.2016
- 0.3.3 - 07.11.2016
- 0.3.2 - 02.11.2016
- 0.3.0 - 28.10.2016
- 0.2.5 - 31.08.2016
- 0.2.4 - 14.07.2016
- 0.2.3 - 11.07.2016
- 0.2.2 - 01.06.2016
- 0.2.1 - 23.04.2016
- 0.2.0 - 17.01.2016
- 0.1.7 - 03.07.2015
- 0.1.6 - 13.06.2015
- 0.0.13 - 07.02.2015
- 0.0.12 - 25.01.2015
- 0.0.10 - 15.12.2015
- 0.0.4 - 12.10.2014
- 0.0.1 - 14.09.2014