I believe that’s what Robert Kern’s line_profiler is intended for. From the link: File: pystone.py Function: Proc2 at line 149 Total time: 0.606656 s Line # Hits Time Per Hit % Time Line Contents ============================================================== 149 @profile 150 def Proc2(IntParIO): 151 50000 82003 1.6 13.5 IntLoc = IntParIO + 10 152 50000 63162 1.3 10.4 … Read more
If you’re using Vim 7.2.269 or later, then there’s the –startuptime option you can use. vim –startuptime vim.log from the help (vim -h): –startuptime <file> Write startup timing messages to <file>
gprof (read the paper) exists for historical reasons. If you think it will help you find performance problems, it was never advertised as such. Here’s what the paper says: The profile can be used to compare and assess the costs of various implementations. It does not say it can be used to identify the various … Read more
You can pass INI settings with the -d flag: php -d xdebug.profiler_enable=On script.php.
It is a very easy-to-use method in C++11. You have to use std::chrono::high_resolution_clock from <chrono> header. Use it like so: #include <chrono> /* Only needed for the sake of this example. */ #include <iostream> #include <thread> void long_operation() { /* Simulating a long, heavy operation. */ using namespace std::chrono_literals; std::this_thread::sleep_for(150ms); } int main() { using … Read more
self is how much time was spent doing work directly in that function. total is how much time was spent in that function, and in the functions it called.
this may not be accurate but its close enough for me long size = 0; object o = new object(); using (Stream s = new MemoryStream()) { BinaryFormatter formatter = new BinaryFormatter(); formatter.Serialize(s, o); size = s.Length; }
If you want a fairly advanced tool to do some serious poking around, look at the Memory Analyzer project at Eclipse, contributed to them by SAP. Some of what you can do is mind-blowingly good for finding memory leaks etc — including running a form of limited SQL (OQL) against the in-memory objects, i.e. SELECT … Read more
You want xdebug I think. Install it on the server, turn it on, pump the output through kcachegrind (for linux) or wincachegrind (for windows) and it’ll show you a few pretty charts that detail the exact timings, counts and memory usage (but you’ll need another extension for that). It rocks, seriously 😀
Python 3.4 includes a new module: tracemalloc. It provides detailed statistics about which code is allocating the most memory. Here’s an example that displays the top three lines allocating memory. from collections import Counter import linecache import os import tracemalloc def display_top(snapshot, key_type=”lineno”, limit=3): snapshot = snapshot.filter_traces(( tracemalloc.Filter(False, “<frozen importlib._bootstrap>”), tracemalloc.Filter(False, “<unknown>”), )) top_stats = … Read more