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authorAndrew M. Kuchling <amk@amk.ca>2007-03-21 16:57:32 +0000
committerAndrew M. Kuchling <amk@amk.ca>2007-03-21 16:57:32 +0000
commit7af1bdf619c28e949b8d9a534f481fb591f19b7c (patch)
treeef4f1d0bbf18afc1c39a9fbc4ccfe343ec35c4f3
parent8aa30927ab3227dc9cab17f5430a14b82054b4dd (diff)
downloadcpython-git-7af1bdf619c28e949b8d9a534f481fb591f19b7c.tar.gz
Fix sentence, and fix typo in example
-rw-r--r--Doc/lib/libcollections.tex5
1 files changed, 3 insertions, 2 deletions
diff --git a/Doc/lib/libcollections.tex b/Doc/lib/libcollections.tex
index bdc14b5a29..b73805ab9f 100644
--- a/Doc/lib/libcollections.tex
+++ b/Doc/lib/libcollections.tex
@@ -377,12 +377,13 @@ Setting the \member{default_factory} to \class{set} makes the
The use cases are the same as those for tuples. The named factories
assign meaning to each tuple position and allow for more readable,
- self-documenting code. Can also be used to assign field names to tuples
+ self-documenting code. Named tuples can also be used to assign field names
+ to tuples
returned by the \module{csv} or \module{sqlite3} modules. For example:
\begin{verbatim}
import csv
- EmployeeRecord = NamedTuple('EmployeeRecord', 'name age title deparment paygrade')
+ EmployeeRecord = NamedTuple('EmployeeRecord', 'name age title department paygrade')
for tup in csv.reader(open("employees.csv", "rb")):
print EmployeeRecord(*tup)
\end{verbatim}