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Signature functions

Import data into Python

This library provides one application programming interface to read data from one of the following data sources:

  • physical file
  • memory file
  • SQLAlchemy table
  • Django Model
  • Python data structures: dictionary, records and array

and to transform them into one of the following data structures:

Four data access functions

Python data can be handled well using lists, dictionaries and various mixture of both. This library provides four module level functions to help you obtain excel data in these data structures. Please refer to "A list of module level functions", the first three functions operates on any one sheet from an excel book and the fourth one returns all data in all sheets in an excel book.

A list of module level functions
Functions Name Python name
:meth:`~pyexcel.get_array` two dimensional array a list of lists
:meth:`~pyexcel.get_dict` a dictionary of one dimensional arrays an ordered dictionary of lists
:meth:`~pyexcel.get_records` a list of dictionaries a list of dictionaries
:meth:`~pyexcel.get_book_dict` a dictionary of two dimensional arrays a dictionary of lists of lists

See also:

The following two variants of the data access function use generator and should work well with big data files

A list of variant functions
Functions Name Python name
:meth:`~pyexcel.iget_array`
a memory efficient two dimensional
array
a generator of a list of lists
:meth:`~pyexcel.iget_records` a memory efficient list list of dictionaries a generator of a list of dictionaries

However, you will need to call :meth:`~pyexcel.free_resource` to make sure file handles are closed.

Two pyexcel functions

In cases where the excel data needs custom manipulations, a pyexcel user got a few choices: one is to use :class:`~pyexcel.Sheet` and :class:`~pyexcel.Book`, the other is to look for more sophisticated ones:

  • Pandas, for numerical analysis
  • Do-it-yourself
Functions Returns
:meth:`~pyexcel.get_sheet` :class:`~pyexcel.Sheet`
:meth:`~pyexcel.get_book` :class:`~pyexcel.Book`

For all six functions, you can pass on the same command parameters while the return value is what the function says.

Export data from Python

This library provides one application programming interface to transform them into one of the data structures:

and write to one of the following data sources:

  • physical file
  • memory file
  • SQLAlchemy table
  • Django Model
  • Python data structures: dictionary, records and array

Here are the two functions:

Functions Description
:meth:`~pyexcel.save_as` Works well with single sheet file
:meth:`~pyexcel.isave_as` Works well with big data files
:meth:`~pyexcel.save_book_as`
Works with multiple sheet file
and big data files
:meth:`~pyexcel.isave_book_as`
Works with multiple sheet file
and big data files

If you would only use these two functions to do format transcoding, you may enjoy a speed boost using :meth:`~pyexcel.isave_as` and :meth:`~pyexcel.isave_book_as`, because they use yield keyword and minimize memory footprint. However, you will need to call :meth:`~pyexcel.free_resource` to make sure file handles are closed. And :meth:`~pyexcel.save_as` and :meth:`~pyexcel.save_book_as` reads all data into memory and will make all rows the same width.

See also:

Data transportation/transcoding

This library is capable of transporting your data between any of the following data sources:

  • physical file
  • memory file
  • SQLAlchemy table
  • Django Model
  • Python data structures: dictionary, records and array

See also: