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authorFred Drake <fdrake@acm.org>1999-04-21 21:43:17 (GMT)
committerFred Drake <fdrake@acm.org>1999-04-21 21:43:17 (GMT)
commitb9f1f6d90b161abf56d678da5ce62264ca562132 (patch)
treed80f6b0cee457c707f3f8e3812c7be2f7013df34 /Doc/lib
parent2dabd811cda159b71468b41adcc5893e4d1a655c (diff)
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Misc. markup nits.
All sections get reasonable file names in the HTML output.
Diffstat (limited to 'Doc/lib')
-rw-r--r--Doc/lib/libprofile.tex57
1 files changed, 29 insertions, 28 deletions
diff --git a/Doc/lib/libprofile.tex b/Doc/lib/libprofile.tex
index 47ff394..e5159f9 100644
--- a/Doc/lib/libprofile.tex
+++ b/Doc/lib/libprofile.tex
@@ -98,7 +98,7 @@ profile file was referenced; output format has been improved.
\end{description}
-\section{Instant Users Manual}
+\section{Instant Users Manual \label{profile-instant}}
This section is provided for users that ``don't want to read the
manual.'' It provides a very brief overview, and allows a user to
@@ -111,7 +111,7 @@ would add the following to your module:
import profile
profile.run('foo()')
\end{verbatim}
-%
+
The above action would cause \samp{foo()} to be run, and a series of
informative lines (the profile) to be printed. The above approach is
most useful when working with the interpreter. If you would like to
@@ -123,7 +123,7 @@ function:
import profile
profile.run('foo()', 'fooprof')
\end{verbatim}
-%
+
The file \file{profile.py} can also be invoked as
a script to profile another script. For example:
@@ -139,7 +139,7 @@ follows:
import pstats
p = pstats.Stats('fooprof')
\end{verbatim}
-%
+
The class \class{Stats} (the above code just created an instance of
this class) has a variety of methods for manipulating and printing the
data that was just read into \samp{p}. When you ran
@@ -149,7 +149,7 @@ method calls:
\begin{verbatim}
p.strip_dirs().sort_stats(-1).print_stats()
\end{verbatim}
-%
+
The first method removed the extraneous path from all the module
names. The second method sorted all the entries according to the
standard module/line/name string that is printed (this is to comply
@@ -160,7 +160,7 @@ all the statistics. You might try the following sort calls:
p.sort_stats('name')
p.print_stats()
\end{verbatim}
-%
+
The first call will actually sort the list by function name, and the
second call will print out the statistics. The following are some
interesting calls to experiment with:
@@ -168,7 +168,7 @@ interesting calls to experiment with:
\begin{verbatim}
p.sort_stats('cumulative').print_stats(10)
\end{verbatim}
-%
+
This sorts the profile by cumulative time in a function, and then only
prints the ten most significant lines. If you want to understand what
algorithms are taking time, the above line is what you would use.
@@ -179,7 +179,7 @@ taking a lot of time, you would do:
\begin{verbatim}
p.sort_stats('time').print_stats(10)
\end{verbatim}
-%
+
to sort according to time spent within each function, and then print
the statistics for the top ten functions.
@@ -188,7 +188,7 @@ You might also try:
\begin{verbatim}
p.sort_stats('file').print_stats('__init__')
\end{verbatim}
-%
+
This will sort all the statistics by file name, and then print out
statistics for only the class init methods ('cause they are spelled
with \samp{__init__} in them). As one final example, you could try:
@@ -196,7 +196,7 @@ with \samp{__init__} in them). As one final example, you could try:
\begin{verbatim}
p.sort_stats('time', 'cum').print_stats(.5, 'init')
\end{verbatim}
-%
+
This line sorts statistics with a primary key of time, and a secondary
key of cumulative time, and then prints out some of the statistics.
To be specific, the list is first culled down to 50\% (re: \samp{.5})
@@ -219,7 +219,7 @@ manual, or guess what the following functions do:
p.print_callees()
p.add('fooprof')
\end{verbatim}
-%
+
\section{What Is Deterministic Profiling?}
\nodename{Deterministic Profiling}
@@ -254,9 +254,9 @@ of algorithms to be directly compared to iterative implementations.
\section{Reference Manual}
-\declaremodule{standard}{profile}
-\modulesynopsis{None}
+\declaremodule{standard}{profile}
+\modulesynopsis{Python profiler}
@@ -338,6 +338,7 @@ Analysis of the profiler data is done using this class from the
\module{pstats} module:
% now switch modules....
+% (This \stmodindex use may be hard to change ;-( )
\stmodindex{pstats}
\begin{classdesc}{Stats}{filename\optional{, ...}}
@@ -359,11 +360,11 @@ need to be combined with data in an existing \class{Stats} object, the
\end{classdesc}
-\subsection{The \module{Stats} Class}
+\subsection{The \class{Stats} Class \label{profile-stats}}
-\setindexsubitem{(Stats method)}
+\class{Stats} objects have the following methods:
-\begin{methoddesc}{strip_dirs}{}
+\begin{methoddesc}[Stats]{strip_dirs}{}
This method for the \class{Stats} class removes all leading path
information from file names. It is very useful in reducing the size
of the printout to fit within (close to) 80 columns. This method
@@ -377,7 +378,7 @@ statistics for these two entries are accumulated into a single entry.
\end{methoddesc}
-\begin{methoddesc}{add}{filename\optional{, ...}}
+\begin{methoddesc}[Stats]{add}{filename\optional{, ...}}
This method of the \class{Stats} class accumulates additional
profiling information into the current profiling object. Its
arguments should refer to filenames created by the corresponding
@@ -386,7 +387,7 @@ version of \function{profile.run()}. Statistics for identically named
single function statistics.
\end{methoddesc}
-\begin{methoddesc}{sort_stats}{key\optional{, ...}}
+\begin{methoddesc}[Stats]{sort_stats}{key\optional{, ...}}
This method modifies the \class{Stats} object by sorting it according
to the supplied criteria. The argument is typically a string
identifying the basis of a sort (example: \code{'time'} or
@@ -435,7 +436,7 @@ additional arguments will be silently ignored.
\end{methoddesc}
-\begin{methoddesc}{reverse_order}{}
+\begin{methoddesc}[Stats]{reverse_order}{}
This method for the \class{Stats} class reverses the ordering of the basic
list within the object. This method is provided primarily for
compatibility with the old profiler. Its utility is questionable
@@ -443,7 +444,7 @@ now that ascending vs descending order is properly selected based on
the sort key of choice.
\end{methoddesc}
-\begin{methoddesc}{print_stats}{restriction\optional{, ...}}
+\begin{methoddesc}[Stats]{print_stats}{restriction\optional{, ...}}
This method for the \class{Stats} class prints out a report as described
in the \function{profile.run()} definition.
@@ -478,7 +479,7 @@ and then proceed to only print the first 10\% of them.
\end{methoddesc}
-\begin{methoddesc}{print_callers}{restrictions\optional{, ...}}
+\begin{methoddesc}[Stats]{print_callers}{restrictions\optional{, ...}}
This method for the \class{Stats} class prints a list of all functions
that called each function in the profiled database. The ordering is
identical to that provided by \method{print_stats()}, and the definition
@@ -488,14 +489,14 @@ times this specific call was made. A second non-parenthesized number
is the cumulative time spent in the function at the right.
\end{methoddesc}
-\begin{methoddesc}{print_callees}{restrictions\optional{, ...}}
+\begin{methoddesc}[Stats]{print_callees}{restrictions\optional{, ...}}
This method for the \class{Stats} class prints a list of all function
that were called by the indicated function. Aside from this reversal
of direction of calls (re: called vs was called by), the arguments and
ordering are identical to the \method{print_callers()} method.
\end{methoddesc}
-\begin{methoddesc}{ignore}{}
+\begin{methoddesc}[Stats]{ignore}{}
\deprecated{1.5.1}{This is not needed in modern versions of
Python.\footnote{
This was once necessary, when Python would print any unused expression
@@ -504,7 +505,7 @@ Python.\footnote{
\end{methoddesc}
-\section{Limitations}
+\section{Limitations \label{profile-limits}}
There are two fundamental limitations on this profiler. The first is
that it relies on the Python interpreter to dispatch \dfn{call},
@@ -539,13 +540,13 @@ this error can be probabilistically (i.e., on the average) removed.
After the profiler is calibrated, it will be more accurate (in a least
square sense), but it will sometimes produce negative numbers (when
call counts are exceptionally low, and the gods of probability work
-against you :-). ) Do \emph{NOT} be alarmed by negative numbers in
+against you :-). ) Do \emph{not} be alarmed by negative numbers in
the profile. They should \emph{only} appear if you have calibrated
your profiler, and the results are actually better than without
calibration.
-\section{Calibration}
+\section{Calibration \label{profile-calibration}}
The profiler class has a hard coded constant that is added to each
event handling time to compensate for the overhead of calling the time
@@ -657,7 +658,7 @@ handles your timer call, along with the appropriate calibration
constant :-).
-\subsection{OldProfile Class}
+\subsection{OldProfile Class \label{profile-old}}
The following derived profiler simulates the old style profiler,
providing errant results on recursive functions. The reason for the
@@ -719,7 +720,7 @@ class OldProfile(Profile):
self.stats[nor_func] = nc, nc, tt, ct, nor_callers
\end{verbatim}
-\subsection{HotProfile Class}
+\subsection{HotProfile Class \label{profile-HotProfile}}
This profiler is the fastest derived profile example. It does not
calculate caller-callee relationships, and does not calculate