>>> ["foo", "bar", "baz"].index("bar")
1
Reference: Data Structures > More on Lists
Caveats follow
Note that while this is perhaps the cleanest way to answer the question as asked, index
is a rather weak component of the list
API, and I can't remember the last time I used it in anger. It's been pointed out to me in the comments that because this answer is heavily referenced, it should be made more complete. Some caveats about list.index
follow. It is probably worth initially taking a look at the documentation for it:
list.index(x[, start[, end]])
Return zero-based index in the list of the first item whose value is equal to x. Raises a 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 the list. The returned index is computed relative to the beginning of the full sequence rather than the start argument.
Linear time-complexity in list length
An index
call checks every element of the list in order, until it finds a match. If your list is long, and you don't know roughly where in the list it occurs, this search could become a bottleneck. In that case, you should consider a different data structure. Note that if you know roughly where to find the match, you can give index
a hint. For instance, in this snippet, l.index(999_999, 999_990, 1_000_000)
is roughly five orders of magnitude faster than straight l.index(999_999)
, because the former only has to search 10 entries, while the latter searches a million:
>>> import timeit
>>> timeit.timeit('l.index(999_999)', setup='l = list(range(0, 1_000_000))', number=1000)
9.356267921015387
>>> timeit.timeit('l.index(999_999, 999_990, 1_000_000)', setup='l = list(range(0, 1_000_000))', number=1000)
0.0004404920036904514
Only returns the index of the first match to its argument
A call to index
searches through the list in order until it finds a match, and stops there. If you expect to need indices of more matches, you should use a list comprehension, or generator expression.
>>> [1, 1].index(1)
0
>>> [i for i, e in enumerate([1, 2, 1]) if e == 1]
[0, 2]
>>> g = (i for i, e in enumerate([1, 2, 1]) if e == 1)
>>> next(g)
0
>>> next(g)
2
Most places where I once would have used index
, I now use a list comprehension or generator expression because they're more generalizable. So if you're considering reaching for index
, take a look at these excellent Python features.
Throws if element not present in list
A call to index
results in a ValueError
if the item's not present.
>>> [1, 1].index(2)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: 2 is not in list
If the item might not be present in the list, you should either
- Check for it first with
item in my_list
(clean, readable approach), or
- Wrap the
index
call in a try/except
block which catches ValueError
(probably faster, at least when the list to search is long, and the item is usually present.)
Use del
and specify the index of the element you want to delete:
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> del a[-1]
>>> a
[0, 1, 2, 3, 4, 5, 6, 7, 8]
Also supports slices:
>>> del a[2:4]
>>> a
[0, 1, 4, 5, 6, 7, 8, 9]
Here is the section from the tutorial.
Best Answer
An index is a database structure that can help speed access to individual rows of the database, when searching based on the field(s) in the index.
In your example, the
CREATE INDEX
statement creates an index namedtags_tag
on the tabletags
using the columntag
. If you wanted to search for rows from the table based on thetag
field, the database might use the index look up the row more efficiently. Without an index, the database might have to resort to a full scan of the table, which can take much longer (depending on many factors, like size of the table, distribution of values, exact query criteria). Different databases also support different types of indexes, which can be used to search for data in different ways.There is also a disadvantage of indexes: For every index, write speeds go down for that table. If you insert a row, having an index means that in addition to the database writing to the row itself, it will also have to update the index.
Deciding which columns to put an index on can be tricky, and as always, benchmarks or real-world queries against real-world data are the most accurate way of measuring performance. In general you will want indexes on columns that you will be searching on. So if you are likely to want to look up a row by
tag
then it definitely makes sense to put an index there. But if you have an address book, you are (probably) not going to need to search on street, ZIP/postcode or phone number so it is not going to be worth the write performance hit.Your primary key column(s) will almost always have an index automatically generated by the database. And if you want to keep the values of a particular column unique, a
UNIQUE INDEX
can be created to enforce this.This SO question asks about rules of thumb for database indexes, which may be useful.