-s only uses [the keys found under sort_stats.](http://docs.python.org/2/library/profile.html#pstats.Stats.sort_stats)


    calls (call count)
    cumulative (cumulative time)
    cumtime (cumulative time)
    file (file name)
    filename (file name)
    module (file name)
    ncalls (call count)
    pcalls (primitive call count)
    line (line number)
    name (function name)
    nfl (name/file/line)
    stdname (standard name)
    time (internal time)
    tottime (internal time)

Here&#39;s an example

    python -m cProfile -s tottime myscript.py

Looks like the new rails version has &quot;change&quot; versus self.up and self.down methods.

So what happens when one has to roll back a migration how does it know what actions to perform. I have the following method that I need to implement based on an online tutorial:

    class AddImageToUsers &lt; ActiveRecord::Migration
      def self.up
        add_column :users, :image_file_name, :string
        add_column :users, :image_content_type, :string
        add_column :users, :image_file_size, :integer
        add_column :users, :image_updated_at, :datetime
      end
    
      def self.down
        remove_column :users, :image_file_name, :string
        remove_column :users, :image_content_type, :string
        remove_column :users, :image_file_size, :integer
        remove_column :users, :image_updated_at, :datetime
      end    
    end

How can I do the same using the new change method?

Rails migrations: self.up and self.down versus change

Just looking for a simple solution to downloading and unzipping `.zip` or `.tar.gz` files in Node.js on any operating system.

Not sure if this is built in or I have to use a separate library.  Any ideas?  Looking for just a couple lines of code so when the next zip file comes that I want to download in node, it&#39;s a no brainer.  Feel like this should be easy and/or built in, but I can&#39;t find anything. Thanks!

Simplest way to download and unzip files in Node.js cross-platform?

I&#39;m using `python -m cProfile -s calls myscript.py`

`python -m cProfile -s percall myscript.py` does not work.

The Python documentation says &quot;Look in the Stats documentation for valid sort values.&quot;: http://docs.python.org/library/profile.html#module-cProfile, which I cannot find.

Sort cProfile output by percall when profiling a Python script

I'm using <code>python -m cProfile -s calls myscript.py</code>
<code>python -m cProfile -s percall myscript.py</code> does not work.
The Python documentation says "Look in the Stats documentation for valid sort values.": <a href="http://docs.python.org/library/profile.html#module-cProfile" target="_blank" rel="noopener noreferrer">http://docs.python.org/library/profile.html#module-cProfile</a>, which I cannot find.

Does anyone know if there is a way to use a variable in the setlevel() function of Python&#39;s Logging module?

At the moment I am using this:

    Log = logging.getLogger(&#39;myLogger&#39;)
    Log.setLevel(logging.DEBUG)


But I&#39;d like to have this:

    Log = logging.getLogger(&#39;myLogger&#39;)
    levels = {&#39;CRITICAL&#39; : logging.critical,
        &#39;ERROR&#39; : logging.error,
        &#39;WARNING&#39; : logging.warning,
        &#39;INFO&#39; : logging.info,
        &#39;DEBUG&#39; : logging.debug
    }
    level = levels[&#39;INFO&#39;]
    Log.setLevel(level)
But it doesn&#39;t seem to work - it just doesn&#39;t log anything.

I&#39;m doing this so that I can set the logging level for a whole bunch of scripts from a variable in a single config file.

Using a variable while calling logger.setLevel

Developing a Django web app, I have a list of packages I need to install in a virtualenv.  Say:

    Django==1.3.1
    --extra-index-url=http://dist.pinaxproject.com/dev/
    Pinax==0.9b1.dev10
    git+git://github.com/pinax/pinax-theme-bootstrap.git@cff4f5bbe9f87f0c67ee9ada9aa8ae82978f9890
    # and other packages

Initially I installed them manually, one by one, along the development. This installed the required dependencies and I finally used `pip freeze` before deploying the app.

Problem is, as I upgraded some packages, some dependencies are no longer used nor required but they keep being listed by `pip freeze`.

Now, I&#39;d like to set up a new virtualenv this way:

 - put the needed packages (without their dependencies) in a requirement file, &lt;br /&gt;
   like `manual-requirements.txt`
 - install them with their dependencies &lt;br /&gt;
   `pip install -r manual-requirement.txt` (← problem, this does not install the dependencies)
 - freeze the full virtualenv &lt;br /&gt;
   `pip freeze -r manual-requirements.txt &gt; full-requirements.txt`&lt;br /&gt;
   and deploy.

Any way to do this without manually re-installing the packages in a new virtualenv to get their dependencies ? This would be error-prone and I&#39;d like to automate the process of cleaning the virtualenv from no-longer-needed old dependencies.

**edit:** actually, pip _does_ install dependencies not explicitly listed in the requirement file, even if [the documentation][1] tells us that such files are flat. I was wrong about which dependencies i expected to be installed. I&#39;ll let this question for anyone in doubt about pip not installing all dependencies. 


  [1]: http://www.pip-installer.org/en/latest/requirements.html

tell pip to install the dependencies of packages listed in a requirement file

Is there a simple way of replacing all negative values in an array with 0?

I&#39;m having a complete block on how to do it using a NumPy array.

E.g.

    a = array([1, 2, 3, -4, 5])

I need to return

    [1, 2, 3, 0, 5]

`a &lt; 0` gives:

    [False, False, False, True, False]

This is where I&#39;m stuck - how to use this array to modify the original array.


Replace negative values in an numpy array

How do you prevent PIP from re-downloading previously downloaded packages? I&#39;m testing the install of matplotlib, an 11MB package that depends on several distro-specific packages. Everytime I run `pip install matplotlib`, it re-downloads matplotlib. How do I stop this?

How to cache downloaded PIP packages

I know I  can do it like the following:

    import numpy as np
    N=10
    a=np.arange(1,100,1)
    np.argsort()[-N:]

However, it is very slow since it did a full sort.

I wonder whether numpy provide some methods the do it fast.

A fast way to find the largest N elements in an numpy array

I am running a Java application on Java 6 VM on a remote Windows XP, on which I can run jvisualvm.exe to connect to the running application automatically.

Now I need to connect that application from my local computer, but I don&#39;t know the JMX port number of the remote computer. Where can I find it? Or, must I restart that application with some VM parameters to specify the port number?

After reading the question [How to find the JMX port in a server][1], I executed the command on the remote computer

    netstat -apn

but got nothing.


  [1]: https://stackoverflow.com/questions/7531211/how-to-find-the-jmx-port-in-a-server

How to find the default JMX port number?

I have a piece of JavaScript code that I am executing using the `node.js` interpreter.

```js
for(var i = 1; i &lt; LIMIT; i++) {
  var user = {
    id: i,
    name: &quot;MongoUser [&quot; + i + &quot;]&quot;
  };
  db.users.save(user, function(err, saved) {
    if(err || !saved) {
      console.log(&quot;Error&quot;);
    } else {
      console.log(&quot;Saved&quot;);
    }
  });
}
```

How can I measure the time taken by these database insert operations? I could compute the difference of date values after and before this piece of code but that would be incorrect because of the asynchronous nature of the code.

How do I measure the execution time of JavaScript code with callbacks?

    def main():
	    for i in xrange(10**8):
	    	pass
    main()

This piece of code in Python runs in  (Note: The timing is done with the time function in BASH in Linux.)

    real	0m1.841s
    user	0m1.828s
    sys 	0m0.012s

However, if the for loop isn&#39;t placed within a function, 

    for i in xrange(10**8):
    	pass

then it runs for a much longer time:

    real	0m4.543s
    user	0m4.524s
    sys 	0m0.012s

Why is this?

Why does Python code run faster in a function?

I&#39;m attempting to profile some c++ code on my mac (os x Lion) and I haven&#39;t been able to find anything useful. I&#39;m looking for a profiler that will tell me what functions are taking up my cpu time (similar to the matlab profiler). 

Here is what I have tried

 - gprof. This is what I use on my linux machine, but it just gives me empty output on my mac (apparently a known problem)
 - Instruments. I can&#39;t for the life of me figure out how to profile anything within my compiled binary. Nor can I find any sort of useful tutorial.
 - (other searching revealed Shark, which is no longer available and Valgrind which is for memory). 



Profiling c++ on mac os x

Is it possible to **profile** MSTest unit tests in **Visual Studio 2012 Ultimate** without using any external profiling tools?

How to profile unit tests in Visual Studio 2012?

I&#39;m struggling to figure out how to profile a simple multiprocess python script

    import multiprocessing
    import cProfile
    import time
    def worker(num):
        time.sleep(3)
        print &#39;Worker:&#39;, num

    if __name__ == &#39;__main__&#39;:
        for i in range(5):
            p = multiprocessing.Process(target=worker, args=(i,))
            cProfile.run(&#39;p.start()&#39;, &#39;prof%d.prof&#39; %i)

I&#39;m starting 5 processes and therefore cProfile generates 5 different files. Inside of each I want to see that my method &#39;worker&#39; takes approximately 3 seconds to run but instead I&#39;m seeing only what&#39;s going on inside the &#39;start&#39;method.

I would greatly appreciate if somebody could explain this to me.

### Update: Working example based on accepted answer: ###
    import multiprocessing
    import cProfile
    import time
    def test(num):
        time.sleep(3)
        print &#39;Worker:&#39;, num

    def worker(num):
        cProfile.runctx(&#39;test(num)&#39;, globals(), locals(), &#39;prof%d.prof&#39; %num)


    if __name__ == &#39;__main__&#39;:
        for i in range(5):
            p = multiprocessing.Process(target=worker, args=(i,))
            p.start()

Python multiprocess profiling

I am profiling a python script `main.py` using cProfile with the following command:

    python -m cProfile -s tottime main.py

The output I get is (only copy-pasted the top lines of the output):

    10184337 function calls (10181667 primitive calls) in 13.597 seconds

    Ordered by: internal time

    ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    4.674    4.674   13.598   13.598 main.py:2(&lt;module&gt;)
     2142    2.964    0.001    4.663    0.002 load_aerdat3.py:61(getPacket)
      459    2.381    0.005    2.381    0.005 {waitKey}
    1667989    1.170    0.000    1.170    0.000 {numpy.core.multiarray.array}
    
    ...

How can the `tottime` (4.674) be different from the `cumtime` (13.598) for `main.py`, since this function (ie. the whole script) is only called once? 

Content Type	Original Author	Original Content on Stackoverflow
Question	Brandon O'Rourke	View Question on Stackoverflow
Solution 1 - Python	Joshua Olson	View Answer on Stackoverflow

Sort cProfile output by percall when profiling a Python script

Python Problem Overview

Python Solutions

Solution 1 - Python

Simplest way to download and unzip files in Node.js cross-platform?

Rails migrations: self.up and self.down versus change

Attributions