Python 2.1 added new functionality to support iterators (PEP 234). Iterators have proven to be useful and convenient in many coding situations. It is noted that the implementation of Python’s for-loop control structure uses the iterator protocol as of release 2.1. It is also noted that Python provides iterators for the following builtin types: lists, tuples, dictionaries, strings, and files. This PEP proposes the addition of an iterator for the builtin type int (types.IntType). Such an iterator would simplify the coding of certain for-loops in Python.
This PEP was rejected on 17 June 2005 with a note to python-dev.
Much of the original need was met by the enumerate() function which was accepted for Python 2.3.
Also, the proposal both allowed and encouraged misuses such as:
>>> for i in 3: print i 0 1 2
Likewise, it was not helpful that the proposal would disable the syntax error in statements like:
SpecificationDefine an iterator for types.intType (i.e., the builtin type “int”) that is returned from the builtin function “iter” when called with an instance of types.intType as the argument.
The returned iterator has the following behavior:
types.intType (the builtin type int) and that i > 0iter(i) returns an iterator objectExample:
iter(5)returns an iterator object that iterates through the sequence of ints 0,1,2,3,4
iter(i) returns an “empty” iterator, i.e., one that throws StopIteration upon the first call of its “next” methodIn other words, the conditions and semantics of said iterator is consistent with the conditions and semantics of the range() and xrange() functions.
Note that the sequence 0,1,2,…,i-1 associated with the int i is considered “natural” in the context of Python programming because it is consistent with the builtin indexing protocol of sequences in Python. Python lists and tuples, for example, are indexed starting at 0 and ending at len(object)-1 (when using positive indices). In other words, such objects are indexed with the sequence 0,1,2,…,len(object)-1
RationaleA common programming idiom is to take a collection of objects and apply some operation to each item in the collection in some established sequential order. Python provides the “for in” looping control structure for handling this common idiom. Cases arise, however, where it is necessary (or more convenient) to access each item in an “indexed” collection by iterating through each index and accessing each item in the collection using the corresponding index.
For example, one might have a two-dimensional “table” object where one requires the application of some operation to the first column of each row in the table. Depending on the implementation of the table it might not be possible to access first each row and then each column as individual objects. It might, rather, be possible to access a cell in the table using a row index and a column index. In such a case it is necessary to use an idiom where one iterates through a sequence of indices (indexes) in order to access the desired items in the table. (Note that the commonly used DefaultTableModel class in Java-Swing-Jython has this very protocol).
Another common example is where one needs to process two or more collections in parallel. Another example is where one needs to access, say, every second item in a collection.
There are many other examples where access to items in a collection is facilitated by a computation on an index thus necessitating access to the indices rather than direct access to the items themselves.
Let’s call this idiom the “indexed for-loop” idiom. Some programming languages provide builtin syntax for handling this idiom. In Python the common convention for implementing the indexed for-loop idiom is to use the builtin range() or xrange() function to generate a sequence of indices as in, for example:
for rowcount in range(table.getRowCount()):
print table.getValueAt(rowcount, 0)
or
for rowcount in xrange(table.getRowCount()):
print table.getValueAt(rowcount, 0)
From time to time there are discussions in the Python community about the indexed for-loop idiom. It is sometimes argued that the need for using the range() or xrange() function for this design idiom is:
xrange() vis-a-vis range()len() function, i.e., xrange(len(sequence))And from time to time proposals are put forth for ways in which Python could provide a better mechanism for this idiom. Recent examples include PEP 204, “Range Literals”, and PEP 212, “Loop Counter Iteration”.
Most often, such proposal include changes to Python’s syntax and other “heavyweight” changes.
Part of the difficulty here is that advocating new syntax implies a comprehensive solution for “general indexing” that has to include aspects like:
Finding a new syntax that is comprehensive, simple, general, Pythonic, appealing to many, easy to implement, not in conflict with existing structures, not excessively overloading of existing structures, etc. has proven to be more difficult than one might anticipate.
The proposal outlined in this PEP tries to address the problem by suggesting a simple “lightweight” solution that helps the most common case by using a proven mechanism that is already available (as of Python 2.1): namely, iterators.
Because for-loops already use “iterator” protocol as of Python 2.1, adding an iterator for types.IntType as proposed in this PEP would enable by default the following shortcut for the indexed for-loop idiom:
for rowcount in table.getRowCount():
print table.getValueAt(rowcount, 0)
The following benefits for this approach vis-a-vis the current mechanism of using the range() or xrange() functions are claimed to be:
range() and xrange())And compared to other proposals for change:
And generally:
The proposed mechanism is generally backwards compatible as it calls for neither new syntax nor new keywords. All existing, valid Python programs should continue to work unmodified.
However, this proposal is not perfectly backwards compatible in the sense that certain statements that are currently invalid would, under the current proposal, become valid.
Tim Peters has pointed out two such examples:
range() or xrange(), for example:
for rowcount in table.getRowCount():
print table.getValueAt(rowcount, 0)
in Python 2.2 raises a TypeError exception.
Under the current proposal, the above statement would be valid and would work as (presumably) intended. Presumably, this is a good thing.
As noted by Tim, this is the common case of the “forgotten range” mistake (which one currently corrects by adding a call to range() or xrange()).
in Python 2.2 raises a TypeError exception.
Under the current proposal, the above statement would be valid and would set x to 0. The PEP author has no data as to how common this typing error is nor how difficult it would be to catch such an error under the current proposal. He imagines that it does not occur frequently and that it would be relatively easy to correct should it happen.
Extensive discussions concerning PEP 276 on the Python interest mailing list suggests a range of opinions: some in favor, some neutral, some against. Those in favor tend to agree with the claims above of the usefulness, convenience, ease of learning, and simplicity of a simple iterator for integers.
Issues with PEP 276 include:
Response: Some posters feel this way. Other disagree.
Response: Some like the proposed idiom and see it as simple, elegant, easy to learn, and easy to use. Some are neutral on this issue. Others, as noted, dislike it.
iter(5) maps to the sequence 0,1,2,3,4?
Response: Given, as noted above, that Python has a strong convention for indexing sequences starting at 0 and stopping at (inclusively) the index whose value is one less than the length of the sequence, it is argued that the proposed sequence is reasonably intuitive to the Python programmer while being useful and practical. More importantly, it is argued that once learned this convention is very easy to remember. Note that the doc string for the range function makes a reference to the natural and useful association between range(n) and the indices for a list whose length is n.
might be mistaken for
Response: This is exactly the same situation with strings in current Python (replace 10 with ‘spam’ in the above, for example).
Response: From the author’s perspective the examples of the above that were identified in the PEP 276 discussions did not appear to be ones that would be accidentally misused in ways that would lead to subtle and hard-to-detect errors.
In addition, it seems that there is a way to deal with this issue by using a variation of what is outlined in the specification section of this proposal. Instead of adding an __iter__ method to class int, change the for-loop handling code to convert (in essence) from
for i in n: # when isinstance(n,int) is 1
to
This approach gives the same results in a for-loop as an __iter__ method would but would prevent iteration on integer values in any other context. Lists and tuples, for example, don’t have __iter__ and are handled with special code. Integer values would be one more special case.
Response: Some feel that “i in len(mylist)” would be easily understandable and useful. Some don’t like it, particularly when a literal is used as in “i in 5”. If the variant mentioned in the response to the previous issue is implemented, this issue is moot. If not, then one could also address this issue by defining a __contains__ method in class int that would always raise a TypeError. This would then make the behavior of “i in n” identical to that of current Python.
Response: The standard idiom is so nice when it fits that it needs neither extra “carrot” nor “stick”. On the other hand, one does notice cases of overuse/misuse of the standard idiom (due, most likely, to the awkwardness of the indexed for-loop idiom), as in:
for item in sequence:
print sequence.index(item)
The majority of disagreement with PEP 276 came from those who favor much larger changes to Python to address the more general problem of specifying a sequence of integers where such a specification is general enough to handle the starting value, ending value, and stepping value of the sequence and also addresses variations of open, closed, and half-open (half-closed) integer intervals. Many suggestions of such were discussed.
These include:
It should be noted that there was much debate but not an overwhelming consensus for any of these larger-scale suggestions.
Clearly, PEP 276 does not propose such a large-scale change and instead focuses on a specific problem area. Towards the end of the discussion period, several posters expressed favor for the narrow focus and simplicity of PEP 276 vis-a-vis the more ambitious suggestions that were advanced. There did appear to be consensus for the need for a PEP for any such larger-scale, alternative suggestion. In light of this recognition, details of the various alternative suggestions are not discussed here further.
ImplementationAn implementation is not available at this time but is expected to be straightforward. The author has implemented a subclass of int with an __iter__ method (written in Python) as a means to test out the ideas in this proposal, however.
This document has been placed in the public domain.
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