Copy the files to some directory under the project root using your favorite file manager or add the directory containing your files to the project using `Settings` (`Preferences` on Mac) | `Project Structure` | **Add Content Root**.

I&#39;m not sure if I get what you want, but there&#39;s way you can add existing source into project:
File -&gt; Settings -&gt; Project structure -&gt; Add Content root -&gt; choose folder with existing code

For PyCharm 2017 (v.2017.2.3), it&#39;s slightly different.
You still need to copy the files you want to add to a directory under the project&#39;s own root directory, but they don&#39;t appear in the Project navigation window in PyCharm immediately.
To correct this, click on the Project&#39;s name in the Navigation window to collapse the project&#39;s tree structure, then open it up again. You should now be able to see the files you&#39;ve just added.

I hacked this way - copy files into another folder, create new files with the same names using IDE, and replace the new files with the copied versions. It does the trick.

P.S. I grepped `.idea` folder and found no project file like `CMakeLists.txt` to edit manually. There are numerous entries in the `.idea/workspace.xml` file, but I am not sure how to generate proper entries by hand.

What is the easiest method to parse &quot;relaxed&quot; JSON but avoid evil `eval`?

The following throws an error:

	JSON.parse(&quot;{muh: 2}&quot;);

since proper JSON should have keys quoted: `{&quot;muh&quot;: 2}`

---

My use case is a simple test interface I use to write JSON commands to my node server. So far I simply used `eval` as it&#39;s just a test application anyway. However, using JSHint on the whole project keeps bugging me about that `eval`. So I&#39;d like a safe alternative that still allows relaxed syntax for keys.

PS: I don&#39;t want to write a parser myself just for the sake of the test application :-)

Parsing &quot;relaxed&quot; JSON without eval

Among some other ways, there are these two ways to get queues in `GCD`:

    dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_DEFAULT, 0);
    
    dispatch_get_main_queue();

If I&#39;m not completely wrong, the &quot;main queue&quot; is executing on the main thread and is good for &quot;callback&quot; blocks which execute UI work.

Does this mean a &quot;global queue&quot; is one that runs on a background thread?

What&#39;s the difference between the &quot;global queue&quot; and the &quot;main queue&quot; in GCD?

How do I import/add an existing Python file to a PyCharm project? 


<p>How do I import/add an existing Python file to a PyCharm project?</p>


I want to test whether an object is an instance of a class, and only this class (no subclasses). I could do it either with:

    obj.__class__ == Foo
    obj.__class__ is Foo
    type(obj) == Foo
    type(obj) is Foo

Are there reasons to choose one over another? (performance differences, pitfalls, etc)

In other words: a) is there any practical difference between using `__class__` and `type(x)`? b) are class objects always safe for comparison using `is`?

---

**Update:** Thanks all for the feedback. I&#39;m still puzzled by whether or not class objects are singletons, my common sense says they are, but it&#39;s been really hard to get a confirmation (try googling for &quot;python&quot;, &quot;class&quot; and &quot;unique&quot; or &quot;singleton&quot;).

I&#39;d also like to clarify that, for my particular needs, the &quot;cheaper&quot; solution that just works is the best, since I&#39;m trying to optimize the most out of a few, specialized classes (almost reaching the point where the sensible thing to do is to drop Python and develop that particular module in C). But the reason behind the question was to understand better the language, since some of its features are a bit too obscure for me to find that information easily. That&#39;s why I&#39;m letting the discussion extend a little instead of settling for `__class__ is`, so I can hear the opinion of more experienced people. So far it&#39;s been very fruitful!

I ran a small test to benchmark the performance of the 4 alternatives. The profiler results were:

                   Python  PyPy (4x)
    type()    is   2.138   2.594
    __class__ is   2.185   2.437
    type()    ==   2.213   2.625
    __class__ ==   2.271   2.453

Unsurprisingly, `is` performed better than `==` for all cases. `type()` performed better in Python (2% faster) and `__class__` performed better in PyPy (6% faster). Interesting to note that `__class__ ==` performed better in PyPy than `type() is`.

---

**Update 2:** many people don&#39;t seem to understand what I mean with &quot;a class is a singleton&quot;, so I&#39;ll ilustrate with an example:

    &gt;&gt;&gt; class Foo(object): pass
    ...
    &gt;&gt;&gt; X = Foo
    &gt;&gt;&gt; class Foo(object): pass
    ...
    &gt;&gt;&gt; X == Foo
    False
    &gt;&gt;&gt; isinstance(X(), Foo)
    False
    &gt;&gt;&gt; isinstance(Foo(), X)
    False

    &gt;&gt;&gt; x = type(&#39;Foo&#39;, (object,), dict())
    &gt;&gt;&gt; y = type(&#39;Foo&#39;, (object,), dict())
    &gt;&gt;&gt; x == y
    False
    &gt;&gt;&gt; isinstance(x(), y)
    False

    &gt;&gt;&gt; y = copy.copy(x)
    &gt;&gt;&gt; x == y
    True
    &gt;&gt;&gt; x is y
    True
    &gt;&gt;&gt; isinstance(x(), y)
    True
    &gt;&gt;&gt; y = copy.deepcopy(x)
    &gt;&gt;&gt; x == y
    True
    &gt;&gt;&gt; x is y
    True
    &gt;&gt;&gt; isinstance(x(), y)
    True

It doesn&#39;t matter if there are N objects of type `type`, given an object, only one will be its class, hence it&#39;s safe to compare for reference in this case. And since reference comparison will always be cheaper than value comparison, I wanted to know whether or not my assertion above holds. I&#39;m reaching the conclusion that it does, unless someone presents evidence in contrary.

Python type() or __class__, == or is

I am looking for a fast way to preserve large numpy arrays. I want to save them to the disk in a binary format, then read them back into memory relatively fastly. cPickle is not fast enough, unfortunately. 

I found [numpy.savez][1] and [numpy.load][2]. But the weird thing is, numpy.load loads a npy file into &quot;memory-map&quot;. That means regular manipulating of arrays really slow. For example, something like this would be really slow: 

    #!/usr/bin/python
    import numpy as np;
    import time; 
    from tempfile import TemporaryFile
    
    n = 10000000;
    
    a = np.arange(n)
    b = np.arange(n) * 10
    c = np.arange(n) * -0.5
    
    file = TemporaryFile()
    np.savez(file,a = a, b = b, c = c);
    
    file.seek(0)
    t = time.time()
    z = np.load(file)
    print &quot;loading time = &quot;, time.time() - t
    
    t = time.time()
    aa = z[&#39;a&#39;]
    bb = z[&#39;b&#39;]
    cc = z[&#39;c&#39;]
    print &quot;assigning time = &quot;, time.time() - t;

more precisely, the first line will be really fast, but the remaining lines that assign the arrays to `obj` are ridiculously slow:

    loading time =  0.000220775604248
    assining time =  2.72940087318


Is there any better way of preserving numpy arrays? Ideally, I want to be able to store multiple arrays in one file. 

  [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.savez.html#numpy.savez
  [2]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.load.html#numpy.load

best way to preserve numpy arrays on disk

I am writing a quick-and-dirty script to generate plots on the fly. I am using the code below (from [Matplotlib][1] documentation) as a starting point:

    from pylab import figure, axes, pie, title, show

    # Make a square figure and axes
    figure(1, figsize=(6, 6))
    ax = axes([0.1, 0.1, 0.8, 0.8])

    labels = &#39;Frogs&#39;, &#39;Hogs&#39;, &#39;Dogs&#39;, &#39;Logs&#39;
    fracs = [15, 30, 45, 10]

    explode = (0, 0.05, 0, 0)
    pie(fracs, explode=explode, labels=labels, autopct=&#39;%1.1f%%&#39;, shadow=True)
    title(&#39;Raining Hogs and Dogs&#39;, bbox={&#39;facecolor&#39;: &#39;0.8&#39;, &#39;pad&#39;: 5})

    show()  # Actually, don&#39;t show, just save to foo.png

I don&#39;t want to display the plot on a GUI, instead, I want to save the plot to a file (say foo.png), so that, for example, it can be used in batch scripts. How do I do that?

  [1]: http://en.wikipedia.org/wiki/Matplotlib


Save plot to image file instead of displaying it using Matplotlib

I&#39;m looking for an easy (and quick) way to determine if two **unordered** lists contain the same elements:

For example:

    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] :  true
    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;, &#39;three&#39;, &#39;two&#39;] :  true
    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;, &#39;three&#39;] :  false
    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;, &#39;four&#39;] :  false
    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;, &#39;two&#39;, &#39;four&#39;] :  false
    [&#39;one&#39;, &#39;two&#39;, &#39;three&#39;] == [&#39;one&#39;] :  false

I&#39;m hoping to do this without using a map.

Check if two unordered lists are equal

The following code snippet:

    template = &quot;\                                                                                
    function routes(app, model){\                                                                
      app.get(&#39;/preNew{className}&#39;, function(req, res){\                                         
        res.render(&#39;{className}&#39;.ejs, {});\                                                      
      });\                                                                                       
    });&quot;.format(className=className)

throws a KeyError:

    Traceback (most recent call last):   File &quot;createController.py&quot;, line 31, in &lt;module&gt;
        });&quot;.format(className=className) KeyError: &#39;  app&#39;

Does someone know why?

Python format throws KeyError

I have JUST created a new github repo on the website. Keep in mind that I am a noob but can do basic things in terminal. Anyway, so I just created the repo on my account on github.com and didn&#39;t do a single thing to it yet.

So all I want to do is take my Xcode project **folder** and upload it to my new github repo. How do I do this via terminal?

Add Xcode project to github repo?

I have an old ASP.NET MVC 2 project which I do not want to upgrade to MVC 3 or MVC 4. I am working on a new machine running Windows 8, Visual Studio 2012 and Visual Studio 2013. When I try to open the MVC 2 project in VS 2012 or VS 2013 I receive the error:

&gt; This project is incompatible with the current edition of Visual Studio

The project is then unloaded and grayed out in Solution Explorer. I do not want to install another copy of Visual Studio. How can I open an old MVC project in a new version of Visual Studio?

How do I open an old MVC project in Visual Studio 2012 or Visual Studio 2013?

Unbelievably enough, I couldn&#39;t find an answer when Googling for this very basic question!

I noticed that since I upgraded from Eclipse Helios to Eclipse Juno and updated the Android SDK, Eclipse places a file called ic_launcher-web.png in the project root whenever I create a new Android project. The file is the same as the application icon selected in the project creation dialog, but what does it do? As mentioned, it&#39;s in the project root, not in any of the /res/ folders. So is it included in the finished .apk file, and what is it&#39;s purpose? 

What does the ic_launcher-web.png in my project root do?

Can I create a base template for my project which all apps can draw from?  Or do I have to create a base template for each app?  And if I wanted them to be the same I&#39;d just copy them?

Django project base template

I have a go project that is starting to become more complex, and want to lay the filesystem out in such a way to reduce pain.

Are there some good examples out there of what makes sense?

What is a sensible way to layout a Go project

Cannot figure out, where to change EOF in PyCharm.
My scripts, started with:

    #!/usr/bin/python
    # -*- coding: utf-8 -*-

Outputs something like this, when I try to run it like executable (chmode +x):

&gt; -bash: ./main.py: /usr/bin/python^M: bad interpreter: No such file or directory

What to do and how to be?

PyCharm. /usr/bin/python^M: bad interpreter

I cannot seem to be able to find the setting to enable line numbers for _all_ files, but I have to always right click and enable this on per file basis. 

There must be a global setting for this, right?

How to make PyCharm always show line numbers

I have PyCharm 1.5.4 and have used the &quot;Open Directory&quot; option to open the contents of a folder in the IDE.

I have Python version 3.2 selected (it shows up under the &quot;External Libraries&quot; node).

How can I select another version of Python (that I already have installed on my machine) so that PyCharm uses that version instead?

How to select Python version in PyCharm?

How can I enable *word* wrapping in PhpStorm?

I need to enable it only for some of my files (with extension .txt). Is it possible?




Word wrapping in PhpStorm

I&#39;m a big fan of [PyCharm by JetBrains][1] but I do run into some issues that I thought maybe I&#39;ll ask here about.

 1. It hangs unexpectedly and this happens often. Overall, its a little bit slow for my taste and I would love some tips on how to increase the performance of the IDE
 2. Often when I open a project PyCharm seems to flag all the built-ins as Unresolved Reference warnings. things like open(), str(), etc. as well as some of the modules I import such as sys (these are the most common offenders :) ).

The only way I am able to fix (2) is by going to PyCharm -&gt; Preferences -&gt; Python Interpreters -&gt; Paths -&gt; Reload List of Paths but I have to do this often enough to warrant asking about a more permanent fix.

My configuration:
Mac OSX Lion running on MacBook Pro (mid 2010) with 8GB RAM

Now look, I understand that diagnosing things like these is difficult without any sort of snapshot or more information about what is going on, but I am simply asking if anyone has ran into these issues before and if so, how did these get resolved?

P.S. I have also contacted JetBrains regarding these issues, but honestly I tend to find nice solutions to common problems here and I thought I might as well ask

  [1]: http://www.jetbrains.com/pycharm/

Content Type	Original Author	Original Content on Stackoverflow
Question	LostMohican	View Question on Stackoverflow
Solution 1 - Python	CrazyCoder	View Answer on Stackoverflow
Solution 2 - Python	yedpodtrzitko	View Answer on Stackoverflow
Solution 3 - Python	user7772648	View Answer on Stackoverflow
Solution 4 - Python	dmitry_romanov	View Answer on Stackoverflow

How do I import/add an existing Python file to a PyCharm project?

Python Problem Overview

Python Solutions

Solution 1 - Python

Solution 2 - Python

Solution 3 - Python

Solution 4 - Python

What's the difference between the "global queue" and the "main queue" in GCD?

Parsing "relaxed" JSON without eval

Attributions