pyexcel - Let you focus on data, instead of file formats

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Support the project

If your company has embedded pyexcel and its components into a revenue generating product, please support me on github, patreon or bounty source to maintain the project and develop it further.

If you are an individual, you are welcome to support me too and for however long you feel like. As my backer, you will receive early access to pyexcel related contents.

And your issues will get prioritized if you would like to become my patreon as pyexcel pro user.

With your financial support, I will be able to invest a little bit more time in coding, documentation and writing interesting posts.

Known constraints

Fonts, colors and charts are not supported.

Introduction

Feature Highlights

One application programming interface(API) to handle multiple data sources:
- physical file
- memory file
- SQLAlchemy table
- Django Model
- Python data structures: dictionary, records and array
One API to read and write data in various excel file formats.
For large data sets, data streaming are supported. A genenerator can be returned to you. Checkout iget_records, iget_array, isave_as and isave_book_as.

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

One liners

This section shows you how to get data from your excel files and how to export data to excel files in one line

One liner to get data from the excel files

Get a list of dictionaries

Suppose you want to process the following coffee data (data source coffee chart on the center for science in the public interest):

Top 5 coffeine drinks:

Coffees	Serving Size	Caffeine (mg)
Starbucks Coffee Blonde Roast	venti(20 oz)	475
Dunkin' Donuts Coffee with Turbo Shot	large(20 oz.)	398
Starbucks Coffee Pike Place Roast	grande(16 oz.)	310
Panera Coffee Light Roast	regular(16 oz.)	300

Let's get a list of dictionary out from the xls file:

>>> records = p.get_records(file_name="your_file.xls")

And let's check what do we have:

>>> for record in records:
...     print("%s of %s has %s mg" % (
...         record['Serving Size'],
...         record['Coffees'],
...         record['Caffeine (mg)']))
venti(20 oz) of Starbucks Coffee Blonde Roast has 475 mg
large(20 oz.) of Dunkin' Donuts Coffee with Turbo Shot has 398 mg
grande(16 oz.) of Starbucks Coffee Pike Place Roast has 310 mg
regular(16 oz.) of Panera Coffee Light Roast has 300 mg

Get two dimensional array

Instead, what if you have to use pyexcel.get_array to do the same:

>>> for row in p.get_array(file_name="your_file.xls", start_row=1):
...     print("%s of %s has %s mg" % (
...         row[1],
...         row[0],
...         row[2]))
venti(20 oz) of Starbucks Coffee Blonde Roast has 475 mg
large(20 oz.) of Dunkin' Donuts Coffee with Turbo Shot has 398 mg
grande(16 oz.) of Starbucks Coffee Pike Place Roast has 310 mg
regular(16 oz.) of Panera Coffee Light Roast has 300 mg

where start_row skips the header row.

Get a dictionary

You can get a dictionary too:

Now let's get a dictionary out from the spreadsheet:

>>> my_d
F438
ict = p.get_dict(file_name="your_file.xls", name_columns_by_row=0)

And check what do we have:

>>> from pyexcel._compact import OrderedDict
>>> isinstance(my_dict, OrderedDict)
True
>>> for key, values in my_dict.items():
...     print(key + " : " + ','.join([str(item) for item in values]))
Coffees : Starbucks Coffee Blonde Roast,Dunkin' Donuts Coffee with Turbo Shot,Starbucks Coffee Pike Place Roast,Panera Coffee Light Roast
Serving Size : venti(20 oz),large(20 oz.),grande(16 oz.),regular(16 oz.)
Caffeine (mg) : 475,398,310,300

Please note that my_dict is an OrderedDict.

Get a dictionary of two dimensional array

Suppose you have a multiple sheet book as the following:

pyexcel:Sheet 1:

1	2	3
4	5	6
7	8	9

pyexcel:Sheet 2:

X	Y	Z
1	2	3
4	5	6

pyexcel:Sheet 3:

O	P	Q
3	2	1
4	3	2

Here is the code to obtain those sheets as a single dictionary:

>>> book_dict = p.get_book_dict(file_name="book.xls")

And check:

>>> isinstance(book_dict, OrderedDict)
True
>>> import json
>>> for key, item in book_dict.items():
...     print(json.dumps({key: item}))
{"Sheet 1": [[1, 2, 3], [4, 5, 6], [7, 8, 9]]}
{"Sheet 2": [["X", "Y", "Z"], [1, 2, 3], [4, 5, 6]]}
{"Sheet 3": [["O", "P", "Q"], [3, 2, 1], [4, 3, 2]]}

Data export in one line

Export an array

Suppose you have the following array:

>>> data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

And here is the code to save it as an excel file :

>>> p.save_as(array=data, dest_file_name="example.xls")

Let's verify it:

>>> p.get_sheet(file_name="example.xls")
pyexcel_sheet1:
+---+---+---+
| 1 | 2 | 3 |
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
| 7 | 8 | 9 |
+---+---+---+

And here is the code to save it as a csv file :

>>> p.save_as(array=data,
...           dest_file_name="example.csv",
...           dest_delimiter=':')

Let's verify it:

>>> with open("example.csv") as f:
...     for line in f.readlines():
...         print(line.rstrip())
...
1:2:3
4:5:6
7:8:9

Export a list of dictionaries

>>> records = [
...     {"year": 1903, "country": "Germany", "speed": "206.7km/h"},
...     {"year": 1964, "country": "Japan", "speed": "210km/h"},
...     {"year": 2008, "country": "China", "speed": "350km/h"}
... ]
>>> p.save_as(records=records, dest_file_name='high_speed_rail.xls')

Export a dictionary of single key value pair

>>> henley_on_thames_facts = {
...     "area": "5.58 square meters",
...     "population": "11,619",
...     "civial parish": "Henley-on-Thames",
...     "latitude": "51.536",
...     "longitude": "-0.898"
... }
>>> p.save_as(adict=henley_on_thames_facts, dest_file_name='henley.xlsx')

Export a dictionary of single dimensonal array

>>> ccs_insights = {
...     "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]
... }
>>> p.save_as(adict=ccs_insights, dest_file_name='ccs.csv')

Export a dictionary of two dimensional array as a book

Suppose you want to save the below dictionary to an excel file :

>>> a_dictionary_of_two_dimensional_arrays = {
...      'Sheet 1':
...          [
...              [1.0, 2.0, 3.0],
...              [4.0, 5.0, 6.0],
...              [7.0, 8.0, 9.0]
...          ],
...      'Sheet 2':
...          [
...              ['X', 'Y', 'Z'],
...              [1.0, 2.0, 3.0],
...              [4.0, 5.0, 6.0]
...          ],
...      'Sheet 3':
...          [
...              ['O', 'P', 'Q'],
...              [3.0, 2.0, 1.0],
...              [4.0, 3.0, 2.0]
...          ]
...  }

Here is the code:

>>> p.save_book_as(
...    bookdict=a_dictionary_of_two_dimensional_arrays,
...    dest_file_name="book.xls"
... )

If you want to preserve the order of sheets in your dictionary, you have to pass on an ordered dictionary to the function itself. For example:

>>> data = OrderedDict()
>>> data.update({"Sheet 2": a_dictionary_of_two_dimensional_arrays['Sheet 2']})
>>> data.update({"Sheet 1": a_dictionary_of_two_dimensional_arrays['Sheet 1']})
>>> data.update({"Sheet 3": a_dictionary_of_two_dimensional_arrays['Sheet 3']})
>>> p.save_book_as(bookdict=data, dest_file_name="book.xls")

Let's verify its order:

>>> book_dict = p.get_book_dict(file_name="book.xls")
>>> for key, item in book_dict.items():
...     print(json.dumps({key: item}))
{"Sheet 2": [["X", "Y", "Z"], [1, 2, 3], [4, 5, 6]]}
{"Sheet 1": [[1, 2, 3], [4, 5, 6], [7, 8, 9]]}
{"Sheet 3": [["O", "P", "Q"], [3, 2, 1], [4, 3, 2]]}

Please notice that "Sheet 2" is the first item in the book_dict, meaning the order of sheets are preserved.

File format transcoding on one line

Note

Please note that the following file transcoding could be with zero line. Please install pyexcel-cli and you will do the transcode in one command. No need to open your editor, save the problem, then python run.

The following code does a simple file format transcoding from xls to csv:

>>> p.save_as(file_name="birth.xls", dest_file_name="birth.csv")

Again it is really simple. Let's verify what we have gotten:

>>> sheet = p.get_sheet(file_name="birth.csv")
>>> sheet
birth.csv:
+-------+--------+----------+
| name  | weight | birth    |
+-------+--------+----------+
| Adam  | 3.4    | 03/02/15 |
+-------+--------+----------+
| Smith | 4.2    | 12/11/14 |
+-------+--------+----------+

Note

Please note that csv(comma separate value) file is pure text file. Formula, charts, images and formatting in xls file will disappear no matter which transcoding tool you use. Hence, pyexcel is a quick alternative for this transcoding job.

Let use previous example and save it as xlsx instead

>>> p.save_as(file_name="birth.xls",
...           dest_file_name="birth.xlsx") # change the file extension

Again let's verify what we have gotten:

>>> sheet = p.get_sheet(file_name="birth.xlsx")
>>> sheet
pyexcel_sheet1:
+-------+--------+----------+
| name  | weight | birth    |
+-------+--------+----------+
| Adam  | 3.4    | 03/02/15 |
+-------+--------+----------+
| Smith | 4.2    | 12/11/14 |
+-------+--------+----------+

Excel book merge and split operation in one line

Merge all excel files in directory into a book where each file become a sheet

The following code will merge every excel files into one file, say "output.xls":

from pyexcel.cookbook import merge_all_to_a_book
import glob


merge_all_to_a_book(glob.glob("your_csv_directory\*.csv"), "output.xls")

You can mix and match with other excel formats: xls, xlsm and ods. For example, if you are sure you have only xls, xlsm, xlsx, ods and csv files in your_excel_file_directory, you can do the following:

from pyexcel.cookbook import merge_all_to_a_book
import glob


merge_all_to_a_book(glob.glob("your_excel_file_directory\*.*"), "output.xls")

Split a book into single sheet files

Suppose you have many sheets in a work book and you would like to separate each into a single sheet excel file. You can easily do this:

>>> from pyexcel.cookbook import split_a_book
>>> split_a_book("megabook.xls", "output.xls")
>>> import glob
>>> outputfiles = glob.glob("*_output.xls")
>>> for file in sorted(outputfiles):
...     print(file)
...
Sheet 1_output.xls
Sheet 2_output.xls
Sheet 3_output.xls

for the output file, you can specify any of the supported formats

Extract just one sheet from a book

Suppose you just want to extract one sheet from many sheets that exists in a work book and you would like to separate it into a single sheet excel file. You can easily do this:

>>> from pyexcel.cookbook import extract_a_sheet_from_a_book
>>> extract_a_sheet_from_a_book("megabook.xls", "Sheet 1", "output.xls")
>>> if os.path.exists("Sheet 1_output.xls"):
...     print("Sheet 1_output.xls exists")
...
Sheet 1_output.xls exists

for the output file, you can specify any of the supported formats

Stream APIs for big file : A set of two liners

This section shows you how to get data from your BIG excel files and how to export data to excel files in two lines at most.

Two liners for get data from big excel files

Get a list of dictionaries

Suppose you want to process the following coffee data again:

Top 5 coffeine drinks:

Coffees	Serving Size	Caffeine (mg)
Starbucks Coffee Blonde Roast	venti(20 oz)	475
Dunkin' Donuts Coffee with Turbo Shot	large(20 oz.)	398
Starbucks Coffee Pike Place Roast	grande(16 oz.)	310
Panera Coffee Light Roast	regular(16 oz.)	300

Let's get a list of dictionary out from the xls file:

>>> records = p.iget_records(file_name="your_file.xls")

And let's check what do we have:

>>> for record in records:
...     print("%s of %s has %s mg" % (
...         record['Serving Size'],
...         record['Coffees'],
...         record['Caffeine (mg)']))
venti(20 oz) of Starbucks Coffee<
10000
/span> Blonde Roast has 475 mg
large(20 oz.) of Dunkin' Donuts Coffee with Turbo Shot has 398 mg
grande(16 oz.) of Starbucks Coffee Pike Place Roast has 310 mg
regular(16 oz.) of Panera Coffee Light Roast has 300 mg

Please do not forgot the second line:

>>> p.free_resources()

Get two dimensional array

Instead, what if you have to use pyexcel.get_array to do the same:

>>> for row in p.iget_array(file_name="your_file.xls", start_row=1):
...     print("%s of %s has %s mg" % (
...         row[1],
...         row[0],
...         row[2]))
venti(20 oz) of Starbucks Coffee Blonde Roast has 475 mg
large(20 oz.) of Dunkin' Donuts Coffee with Turbo Shot has 398 mg
grande(16 oz.) of Starbucks Coffee Pike Place Roast has 310 mg
regular(16 oz.) of Panera Coffee Light Roast has 300 mg

Again, do not forgot the second line:

>>> p.free_resources()

where start_row skips the header row.

Data export in one liners

Export an array

Suppose you have the following array:

>>> data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

And here is the code to save it as an excel file :

>>> p.isave_as(array=data, dest_file_name="example.xls")

But the following line is not required because the data source are not file sources:

>>> # p.free_resources()

Let's verify it:

>>> p.get_sheet(file_name="example.xls")
pyexcel_sheet1:
+---+---+---+
| 1 | 2 | 3 |
+---+---+---+
| 4 | 5 | 6 |
+---+---+---+
| 7 | 8 | 9 |
+---+---+---+

And here is the code to save it as a csv file :

>>> p.isave_as(array=data,
...            dest_file_name="example.csv",
...            dest_delimiter=':')

Let's verify it:

>>> with open("example.csv") as f:
...     for line in f.readlines():
...         print(line.rstrip())
...
1:2:3
4:5:6
7:8:9

Export a list of dictionaries

>>> records = [
...     {"year": 1903, "country": "Germany", "speed": "206.7km/h"},
...     {"year": 1964, "country": "Japan", "speed": "210km/h"},
...     {"year": 2008, "country": "China", "speed": "350km/h"}
... ]
>>> p.isave_as(records=records, dest_file_name='high_speed_rail.xls')

Export a dictionary of single key value pair

>>> henley_on_thames_facts = {
...     "area": "5.58 square meters",
...     "population": "11,619",
...     "civial parish": "Henley-on-Thames",
...     "latitude": "51.536",
...     "longitude": "-0.898"
... }
>>> p.isave_as(adict=henley_on_thames_facts, dest_file_name='henley.xlsx')

Export a dictionary of single dimensonal array

>>> ccs_insights = {
...     "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]
... }
>>> p.isave_as(adict=ccs_insights, dest_file_name='ccs.csv')
>>> p.free_resources()

Export a dictionary of two dimensional array as a book

Suppose you want to save the below dictionary to an excel file :

>>> a_dictionary_of_two_dimensional_arrays = {
...      'Sheet 1':
...          [
...              [1.0, 2.0, 3.0],
...              [4.0, 5.0, 6.0],
...              [7.0, 8.0, 9.0]
...          ],
...      'Sheet 2':
...          [
...              ['X', 'Y', 'Z'],
...              [1.0, 2.0, 3.0],
...              [4.0, 5.0, 6.0]
...          ],
...      'Sheet 3':
...          [
...              ['O', 'P', 'Q'],
...              [3.0, 2.0, 1.0],
...              [4.0, 3.0, 2.0]
...          ]
...  }

Here is the code:

>>> p.isave_book_as(
...    bookdict=a_dictionary_of_two_dimensional_arrays,
...    dest_file_name="book.xls"
... )

If you want to preserve the order of sheets in your dictionary, you have to pass on an ordered dictionary to the function itself. For example:

>>> from pyexcel._compact import OrderedDict
>>> data = OrderedDict()
>>> data.update({"Sheet 2": a_dictionary_of_two_dimensional_arrays['Sheet 2']})
>>> data.update({"Sheet 1": a_dictionary_of_two_dimensional_arrays['Sheet 1']})
>>> data.update({"Sheet 3": a_dictionary_of_two_dimensional_arrays['Sheet 3']})
>>> p.isave_book_as(bookdict=data, dest_file_name="book.xls")
>>> p.free_resources()

Let's verify its order:

>>> import json
>>> book_dict = p.get_book_dict(file_name="book.xls")
>>> for key, item in book_dict.items():
...     print(json.dumps({key: item}))
{"Sheet 2": [["X", "Y", "Z"], [1, 2, 3], [4, 5, 6]]}
{"Sheet 1": [[1, 2, 3], [4, 5, 6], [7, 8, 9]]}
{"Sheet 3": [["O", "P", "Q"], [3, 2, 1], [4, 3, 2]]}

Please notice that "Sheet 2" is the first item in the book_dict, meaning the order of sheets are preserved.

File format transcoding on one line

Note

Please note that the following file transcoding could be with zero line. Please install pyexcel-cli and you will do the transcode in one command. No need to open your editor, save the problem, then python run.

The following code does a simple file format transcoding from xls to csv:

>>> import pyexcel
>>> p.save_as(file_name="birth.xls", dest_file_name="birth.csv")

Again it is really simple. Let's verify what we have gotten:

>>> sheet = p.get_sheet(file_name="birth.csv")
>>> sheet
birth.csv:
+-------+--------+----------+
| name  | weight | birth    |
+-------+--------+----------+
| Adam  | 3.4    | 03/02/15 |
+-------+--------+----------+
| Smith | 4.2    | 12/11/14 |
+-------+--------+----------+

Note

Please note that csv(comma separate value) file is pure text file. Formula, charts, images and formatting in xls file will disappear no matter which transcoding tool you use. Hence, pyexcel is a quick alternative for this transcoding job.

Let use previous example and save it as xlsx instead

>>> import pyexcel
>>> p.isave_as(file_name="birth.xls",
...            dest_file_name="birth.xlsx") # change the file extension

Again let's verify what we have gotten:

>>> sheet = p.get_sheet(file_name="birth.xlsx")
>>> sheet
pyexcel_sheet1:
+-------+--------+----------+
| name  | weight | birth    |
+-------+--------+----------+
| Adam  | 3.4    | 03/02/15 |
+-------+--------+----------+
| Smith | 4.2    | 12/11/14 |
+-------+--------+----------+

Available Plugins

A list of file formats supported by external plugins

Package name	Supported file formats	Dependencies	Python versions
pyexcel-io	csv, csvz [1], tsv, tsvz [2]		2.6, 2.7, 3.3, 3.4, 3.5, 3.6 pypy
pyexcel-xls	xls, xlsx(read only), xlsm(read only)	xlrd, xlwt	same as above
pyexcel-xlsx	xlsx	openpyxl	same as above
pyexcel-ods3	ods	pyexcel-ezodf, lxml	2.6, 2.7, 3.3, 3.4 3.5, 3.6
pyexcel-ods	ods	odfpy	same as above

Dedicated file reader and writers

Package name	Supported file formats	Dependencies	Python versions
pyexcel-xlsxw	xlsx(write only)	XlsxWriter	Python 2 and 3
pyexcel-xlsxr	xlsx(read only)	lxml	same as above
pyexcel-xlsbr	xlsx(read only)	pyxlsb	same as above
pyexcel-odsr	read only for ods, fods	lxml	same as above
pyexcel-odsw	write only for ods	loxun	same as above
pyexcel-htmlr	html(read only)	lxml,html5lib	same as above
pyexcel-pdfr	pdf(read only)	pdftables	Python 2 only.

Other data renderers

Package name	Supported file formats	Dependencies	Python versions
pyexcel-text	write only:rst, mediawiki, html, latex, grid, pipe, orgtbl, plain simple read only: ndjson r/w: json	tabulate	2.6, 2.7, 3.3, 3.4 3.5, 3.6, pypy
pyexcel-handsontable	handsontable in html	handsontable	same as above
pyexcel-pygal	svg chart	pygal	2.7, 3.3, 3.4, 3.5 3.6, pypy
pyexcel-sortable	sortable table in html	csvtotable	same as above
pyexcel-gantt	gantt chart in html	frappe-gantt	except pypy, same as above

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').

Footnotes

[1]	zipped csv file

[2]	zipped tsv file

Acknowledgement

All great work have been done by odf, ezodf, xlrd, xlwt, tabulate and other individual developers. This library unites only the data access code.

License

New BSD License

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.moban.d		.moban.d
docs		docs
examples		examples
pyexcel		pyexcel
tests		tests
.gitignore		.gitignore
.moban.yml		.moban.yml
.travis.yml		.travis.yml
CHANGELOG.rst		CHANGELOG.rst
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
Makefile		Makefile
README.rst		README.rst
changelog.yml		changelog.yml
document.bat		document.bat
document.sh		document.sh
lint.sh		lint.sh
min_requirements.txt		min_requirements.txt
pyexcel.yml		pyexcel.yml
requirements.txt		requirements.txt
rnd_requirements.txt		rnd_requirements.txt
setup.cfg		setup.cfg
setup.py		setup.py
test.bat		test.bat
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pyexcel - Let you focus on data, instead of file formats

Support the project

Known constraints

Introduction

Feature Highlights

Installation

One liners

One liner to get data from the excel files

Get a list of dictionaries

Get two dimensional array

Get a dictionary

Get a dictionary of two dimensional array

Data export in one line

Export an array

Export a list of dictionaries

Export a dictionary of single key value pair

Export a dictionary of single dimensonal array

Export a dictionary of two dimensional array as a book

File format transcoding on one line

Excel book merge and split operation in one line

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

Stream APIs for big file : A set of two liners

Two liners for get data from big excel files

Get a list of dictionaries

Get two dimensional array

Data export in one liners

Export an array

Export a list of dictionaries

Export a dictionary of single key value pair

Export a dictionary of single dimensonal array

Export a dictionary of two dimensional array as a book

File format transcoding on one line

Available Plugins

Acknowledgement

License

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