From 5bd5b9d81322d2cb6edd5f3804a347f8b2e65a15 Mon Sep 17 00:00:00 2001 From: Raymond Hettinger Date: Mon, 21 Nov 2016 15:12:54 -0800 Subject: Issue 28587: list.index documentation missing start and stop arguments. (Contributed by Mariatta Wijaya.) --- Doc/tutorial/datastructures.rst | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/Doc/tutorial/datastructures.rst b/Doc/tutorial/datastructures.rst index b39bdf4..83a1f9b 100644 --- a/Doc/tutorial/datastructures.rst +++ b/Doc/tutorial/datastructures.rst @@ -60,11 +60,16 @@ objects: Remove all items from the list. Equivalent to ``del a[:]``. -.. method:: list.index(x) +.. method:: list.index(x[, start[, end]]) :noindex: - Return the index in the list of the first item whose value is *x*. It is an - error if there is no such item. + Return zero-based index in the list of the first item whose value is *x*. + Raises a :exc:`ValueError` if there is no such item. + + The optional arguments *start* and *end* are interpreted as in the slice + notation and are used to limit the search to a particular subsequence of + *x*. The returned index is computed relative to the beginning of the full + sequence rather than the *start* argument. .. method:: list.count(x) @@ -103,6 +108,8 @@ An example that uses most of the list methods:: [66.25, 333, -1, 333, 1, 1234.5, 333] >>> a.index(333) 1 + >>> a.index(333, 2) # search for 333 starting at index 2 + 2 >>> a.remove(333) >>> a [66.25, -1, 333, 1, 1234.5, 333] -- cgit v0.12 From 7f946195558b3681b81707c52b721d067373acee Mon Sep 17 00:00:00 2001 From: Raymond Hettinger Date: Mon, 21 Nov 2016 15:13:18 -0800 Subject: Fix grammar --- Doc/library/random.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/Doc/library/random.rst b/Doc/library/random.rst index b0f8194..115ef81 100644 --- a/Doc/library/random.rst +++ b/Doc/library/random.rst @@ -465,11 +465,11 @@ Simulation of arrival times and service deliveries in a single server queue:: `_ a simulation of a marketplace by `Peter Norvig `_ that shows effective - use of many the tools and distributions provided by this module + use of many of the tools and distributions provided by this module (gauss, uniform, sample, betavariate, choice, triangular, and randrange). `A Concrete Introduction to Probability (using Python) `_ a tutorial by `Peter Norvig `_ covering the basics of probability theory, how to write simulations, and - performing data analysis using Python. + how to perform data analysis using Python. -- cgit v0.12