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1. 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
2. One API to read and write data in various excel file formats.
3. 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.

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

Please note that you will have to use '.sortable.html' in order to replicate the example.

>>> # 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 |
+----------------+------+------+------+------+------+

Suppose you have the following data in a dictionary:

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()

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 <BLANKLINE>

Two advantages of above method:

1. Add as many wrapping functions as you want.
2. Constant memory consumption

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

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

New BSD License