PEP: XXX Title: Allow Empty Subscript List Without Parentheses Version: $Revision$ Last-Modified: $Date$ Author: Noam Raphael <spam.noam@gmail.com> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 09-Jun-2006 Python-Version: 2.5? Post-History: 30-Aug-2002
Abstract
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.
Specification
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
Motivation
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.
Rationale
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.
Copyright
This document has been placed in the public domain.