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Title: Allow Empty Subscript List Without Parentheses
Version: $Revision$
Last-Modified: $Date$
Author: Noam Raphael <>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 09-Jun-2006
Python-Version: 2.5?
Post-History: 30-Aug-2002


This PEP suggests to allow the use of an empty subscript list, for example x[], which is currently a syntax error. It is suggested that in such a case, an empty tuple will be passed as an argument to the __getitem__ and __setitem__ methods. This is consistent with the current behaviour of passing a tuple with n elements to those methods when a subscript list of length n is used, if it includes a comma.


The Python grammar specifies that inside the square brackets trailing an expression, a list of "subscripts", separated by commas, should be given. If the list consists of a single subscript without a trailing comma, a single object (an ellipsis, a slice or any other object) is passed to the resulting __getitem__ or __setitem__ call. If the list consists of many subscripts, or of a single subscript with a trailing comma, a tuple is passed to the resulting __getitem__ or __setitem__ call, with an item for each subscript.

Here is the formal definition of the grammar:

trailer: '(' [arglist] ')' | '[' subscriptlist ']' | '.' NAME
subscriptlist: subscript (',' subscript)* [',']
subscript: '.' '.' '.' | test | [test] ':' [test] [sliceop]
sliceop: ':' [test]

This PEP suggests to allow an empty subscript list, with nothing inside the square brackets. It will result in passing an empty tuple to the resulting __getitem__ or __setitem__ call.

The change in the grammar is to make "subscriptlist" in the first quoted line optional:

trailer: '(' [arglist] ')' | '[' [subscriptlist] ']' | '.' NAME


This suggestion allows you to refer to zero-dimensional arrays elegantly. In NumPy, you can have arrays with a different number of dimensions. In order to refer to a value in a two-dimensional array, you write a[i, j]. In order to refer to a value in a one-dimensional array, you write a[i]. You can also have a zero-dimensional array, which holds a single value (a scalar). To refer to its value, you currently need to write a[()], which is unexpected - the user may not even know that when he writes a[i, j] he constructs a tuple, so he won't guess the a[()] syntax. If the suggestion is accepted, the user will be able to write a[] in order to refer to the value, as expected. It will even work without changing the NumPy package at all!

In the normal use of NumPy, you usually don't encounter zero-dimensional arrays. However, the author of this PEP is designing another library for managing multi-dimensional arrays of data. Its purpose is similar to that of a spreadsheet - to analyze data and preserve the relations between a source of a calculation and its destination. In such an environment you may have many multi-dimensional arrays - for example, the sales of several products over several time periods. But you may also have several zero-dimensional arrays, that is, single values - for example, the income tax rate. It is desired that the access to the zero-dimensional arrays will be consistent with the access to the multi-dimensional arrays. Just using the name of the zero-dimensional array to obtain its value isn't going to work - the array and the value it contains have to be distinguished.


Passing an empty tuple to the __getitem__ or __setitem__ call was chosen because it is consistent with passing a tuple of n elements when a subscript list of n elements is used. Also, it will make NumPy and similar packages work as expected for zero-dimensional arrays without any changes.

Another hint for consistency: Currently, these equivalences hold:

x[i, j, k]  <-->  x[(i, j, k)]
x[i, j]     <-->  x[(i, j)]
x[i, ]      <-->  x[(i, )]
x[i]        <-->  x[(i)]

If this PEP is accepted, another equivalence will hold:

x[]         <-->  x[()]

Backwards Compatibility

This change is fully backwards compatible, since it only assigns a meaning to a previously illegal syntax.

Reference Implementation

Available as SF Patch no. 1503556.

It passes the Python test suite, but currently doesn't provide additional tests or documentation.

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