Add `--source=.` to the `coverage` run line.  It will both limit the focus to the current directory, and will search for `.py` files that weren&#39;t run at all.


If you use `nose` as a testrunner instead, the coverage plugin for it provides


      --cover-inclusive     Include all python files under working directory in
                            coverage report.  Useful for discovering holes in test
                            coverage if not all files are imported by the test
                            suite. [NOSE_COVER_INCLUSIVE]

      --cover-tests         Include test modules in coverage report
                            [NOSE_COVER_TESTS]

In Azure there are 2 options available to create virtual machines. 
A. normal VM 
B. Classic VM 

Does anybody know what is the difference between both option? When do we use one over other? 

what is the difference between virtual machine classic and virtual machine in azure?

EDIT: I have asked an opposing question here: https://stackoverflow.com/questions/34724879/how-to-embed-python3-with-the-standard-library

A solution for Python2 is provided here: https://stackoverflow.com/questions/20951624/is-it-possible-to-embed-python-without-the-standard-library

However, Python3 fails on `Py_Initialize();` with:

    Fatal Python error: Py_Initialize: unable to load the file system  
    codec ImportError: No module named &#39;encodings&#39;

This makes sense because py3 source files are utf-8 by default. So it seems that it requires an external binary just in order to parse py3 source files.

So what to do?

It looks as though I need to locate the `encodings` binary in my system Python installation, copy this into my project tree, and maybe set some environment variable PYTHONPATH(?) So that my libpython.dylib can find it.

Is it possible to avoid this? And if not, can anyone clarify the steps I need to take? Are there going to be any more hiccups?

----------

NOTE: For posterity, this is how I got a stand-alone libpython.dylib linking into my project on OSX:

First I locate my system Python&#39;s library: `/usr/local/Frameworks/Python.framework/Versions/3.4/Python` (in my case it was installed with homebrew).

Now I:

 - copy the .dylib into my project folder creating `./Libs/libpython3.4.1_OSX.dylib`

 - Go into `build settings -&gt; linking` and set `other linker flags` to `-lpython3.4.1_OSX`  

At this point it will appear to work. However if you know try building it on a fresh OSX installation, it will fail. This is because:

    $ otool -D ./libpython3.4.1_OSX.dylib 
    ./libpython3.4.1_OSX.dylib:
    /usr/local/Frameworks/Python.framework/Versions/3.4/Python

The .dylib is still holding onto it&#39;s old location.  It&#39;s really weird to me that the .dylib contains a link to its location, as anything that uses it must know where it is in order to invoke it in the first place!

We can correct this with:

    $ install_name_tool -id @rpath/libpython3.4.1_OSX.dylib libpython3.4.1_OSX.dylib

But then also in our Xcode project we must:

* Go into `build phases`. Add a `copy files` step that copies `libpython3.4.1_OSX.dylib` to `Frameworks` (that&#39;s the right place to put it).  
* Go into `build settings -&gt; linking` and set `runpath search paths` to `@executable_path/../Frameworks/libpython3.4.1_OSX.dylib`  

Finally I need to go into `edit scheme -&gt; run -&gt; arguments -&gt; environment variables` and add `PYTHONHOME` with value `../Frameworks`

I suspect that to get this working I will also need to add a `PYTHONPATH`

Links:  
https://mikeash.com/pyblog/friday-qa-2009-11-06-linking-and-install-names.html  
http://qin.laya.com/tech_coding_help/dylib_linking.html  
https://github.com/conda/conda-build/issues/279#issuecomment-67241554  
https://stackoverflow.com/questions/9263256/can-you-please-help-me-understand-how-mach-o-libraries-work-in-mac-os-x  
http://nshipster.com/launch-arguments-and-environment-variables/  

Embed Python3 without standard library

I have just started writing some unit tests for a python project I have using `unittest` and `coverage`. I&#39;m only currently testing a small proportion, but I am trying to work out the code coverage

I run my tests and get the coverage using the following

    python -m unittest discover -s tests/
    coverage run -m unittest discover -s tests/
    coverage report -m

The problem I&#39;m having is that `coverage` is telling I have 44% code coverage and is only counting the files that:

1. were tested in the unit tests (i.e., all the files that were not tested are missing and not in the overall coverage)
 
2. were in the libraries in the virtual environment and code coverage of the actual tests too. Surely it should not be including the actual tests in the results?

Furthermore, it says the files that are actually tested in these unit tests only have the first few lines tested (which are in most cases the import statements)

How do I get a more realistic code coverage or is this how it is meant to be?

How do I make coverage include not tested files?

I have just started writing some unit tests for a python project I have using <code>unittest</code> and <code>coverage</code>. I'm only currently testing a small proportion, but I am trying to work out the code coverage
I run my tests and get the coverage using the following
<pre><code class="hljs language-arduino">python -m unittest discover -s tests/
coverage run -m unittest discover -s tests/
coverage report -m
</code></pre>
The problem I'm having is that <code>coverage</code> is telling I have 44% code coverage and is only counting the files that:
<ol>
<li>
were tested in the unit tests (i.e., all the files that were not tested are missing and not in the overall coverage)
</li>
<li>
were in the libraries in the virtual environment and code coverage of the actual tests too. Surely it should not be including the actual tests in the results?
</li>
</ol>
Furthermore, it says the files that are actually tested in these unit tests only have the first few lines tested (which are in most cases the import statements)
How do I get a more realistic code coverage or is this how it is meant to be?

I am trying to create a view where I save an object but I&#39;d like to _undo_ that save if some exception is raised. This is what I tried:

    class MyView(View):
    
        @transaction.atomic
        def post(self, request, *args, **kwargs):
            try:
                some_object = SomeModel(...)
                some_object.save()
    
                if something:
                    raise exception.NotAcceptable()
                    # When the workflow comes into this condition, I think the previous save should be undone
                    # What am I missing?
    
            except exception.NotAcceptable, e:
                # do something

What am I doing wrong? even when the exception is raised `some_object` is still in Database.

Django - Rollback save with transaction atomic

I&#39;ve got a &#39;DataFrame` which has occasional missing values, and looks something like this:

              Monday         Tuesday         Wednesday 
          ================================================
    Mike        42             NaN               12
    Jenna       NaN            NaN               15
    Jon         21              4                 1
   

I&#39;d like to add a new `column` to my data frame where I&#39;d calculate the average across all `columns` for every `row`.

Meaning, for `Mike`, I&#39;d need 
`(df[&#39;Monday&#39;] + df[&#39;Wednesday&#39;])/2`, but for `Jenna`, I&#39;d simply use `df[&#39;Wednesday amt.&#39;]/1`

Does anyone know the best way to account for this variation that results from missing values and calculate the average?

Row-wise average for a subset of columns with missing values

I am new to Python programming. Can anybody provide an explanation on what a *.pyw file is and how it works. 

.pyw files in python program

I&#39;d like to generate video using `AWS Lambda` feature.

I&#39;ve followed instructions found [here][1] and [here][2].

And I now have the following process to build my `Lambda` function:

## Step 1 ##

Fire a `Amazon Linux EC2` instance and run this as root on it:

&lt;!-- language: lang-sh --&gt;

    #! /usr/bin/env bash
    
    # Install the SciPy stack on Amazon Linux and prepare it for AWS Lambda
    
    yum -y update
    yum -y groupinstall &quot;Development Tools&quot;
    yum -y install blas --enablerepo=epel
    yum -y install lapack --enablerepo=epel
    yum -y install atlas-sse3-devel --enablerepo=epel
    yum -y install Cython --enablerepo=epel
    yum -y install python27
    yum -y install python27-numpy.x86_64
    yum -y install python27-numpy-f2py.x86_64
    yum -y install python27-scipy.x86_64
    
    /usr/local/bin/pip install --upgrade pip
    mkdir -p /home/ec2-user/stack
    /usr/local/bin/pip install moviepy -t /home/ec2-user/stack
    
    cp -R /usr/lib64/python2.7/dist-packages/numpy /home/ec2-user/stack/numpy
    cp -R /usr/lib64/python2.7/dist-packages/scipy /home/ec2-user/stack/scipy
    
    tar -czvf stack.tgz /home/ec2-user/stack/*

## Step 2 ##

I scp the resulting tarball to my laptop. And then run this script to build a zip archive.

&lt;!-- language: lang-sh --&gt;

    #! /usr/bin/env bash
    
    mkdir tmp
    rm lambda.zip
    tar -xzf stack.tgz -C tmp
    
    zip -9 lambda.zip process_movie.py
    zip -r9 lambda.zip *.ttf
    cd tmp/home/ec2-user/stack/
    zip -r9 ../../../../lambda.zip *

`process_movie.py` script is at the moment only a test to see if the stack is ok:

&lt;!-- language: lang-py --&gt;

    def make_movie(event, context):
        import os
        print(os.listdir(&#39;.&#39;))
        print(os.listdir(&#39;numpy&#39;))
        try:
            import scipy
        except ImportError:
            print(&#39;can not import scipy&#39;)
    
        try:
            import numpy
        except ImportError:
            print(&#39;can not import numpy&#39;)
    
        try:
            import moviepy
        except ImportError:
            print(&#39;can not import moviepy&#39;)

## Step 3 ##

Then I upload the resulting archive to S3 to be the source of my `lambda` function.
When I test the function I get the following `callstack`:

    START RequestId: 36c62b93-b94f-11e5-9da7-83f24fc4b7ca Version: $LATEST
    [&#39;tqdm&#39;, &#39;imageio-1.4.egg-info&#39;, &#39;decorator.pyc&#39;, &#39;process_movie.py&#39;, &#39;decorator-4.0.6.dist-info&#39;, &#39;imageio&#39;, &#39;moviepy&#39;, &#39;tqdm-3.4.0.dist-info&#39;, &#39;scipy&#39;, &#39;numpy&#39;, &#39;OpenSans-Regular.ttf&#39;, &#39;decorator.py&#39;, &#39;moviepy-0.2.2.11.egg-info&#39;]
    [&#39;add_newdocs.pyo&#39;, &#39;numarray&#39;, &#39;__init__.py&#39;, &#39;__config__.pyc&#39;, &#39;_import_tools.py&#39;, &#39;setup.pyo&#39;, &#39;_import_tools.pyc&#39;, &#39;doc&#39;, &#39;setupscons.py&#39;, &#39;__init__.pyc&#39;, &#39;setup.py&#39;, &#39;version.py&#39;, &#39;add_newdocs.py&#39;, &#39;random&#39;, &#39;dual.pyo&#39;, &#39;version.pyo&#39;, &#39;ctypeslib.pyc&#39;, &#39;version.pyc&#39;, &#39;testing&#39;, &#39;dual.pyc&#39;, &#39;polynomial&#39;, &#39;__config__.pyo&#39;, &#39;f2py&#39;, &#39;core&#39;, &#39;linalg&#39;, &#39;distutils&#39;, &#39;matlib.pyo&#39;, &#39;tests&#39;, &#39;matlib.pyc&#39;, &#39;setupscons.pyc&#39;, &#39;setup.pyc&#39;, &#39;ctypeslib.py&#39;, &#39;numpy&#39;, &#39;__config__.py&#39;, &#39;matrixlib&#39;, &#39;dual.py&#39;, &#39;lib&#39;, &#39;ma&#39;, &#39;_import_tools.pyo&#39;, &#39;ctypeslib.pyo&#39;, &#39;add_newdocs.pyc&#39;, &#39;fft&#39;, &#39;matlib.py&#39;, &#39;setupscons.pyo&#39;, &#39;__init__.pyo&#39;, &#39;oldnumeric&#39;, &#39;compat&#39;]
    can not import scipy
    &#39;module&#39; object has no attribute &#39;core&#39;: AttributeError
    Traceback (most recent call last):
      File &quot;/var/task/process_movie.py&quot;, line 91, in make_movie
        import numpy
      File &quot;/var/task/numpy/__init__.py&quot;, line 122, in &lt;module&gt;
        from numpy.__config__ import show as show_config
      File &quot;/var/task/numpy/numpy/__init__.py&quot;, line 137, in &lt;module&gt;
        import add_newdocs
      File &quot;/var/task/numpy/numpy/add_newdocs.py&quot;, line 9, in &lt;module&gt;
        from numpy.lib import add_newdoc
      File &quot;/var/task/numpy/lib/__init__.py&quot;, line 13, in &lt;module&gt;
        from polynomial import *
      File &quot;/var/task/numpy/lib/polynomial.py&quot;, line 11, in &lt;module&gt;
        import numpy.core.numeric as NX
    AttributeError: &#39;module&#39; object has no attribute &#39;core&#39;
    
    END RequestId: 36c62b93-b94f-11e5-9da7-83f24fc4b7ca
    REPORT RequestId: 36c62b93-b94f-11e5-9da7-83f24fc4b7ca	Duration: 112.49 ms	Billed Duration: 200 ms 	Memory Size: 1536 MB	Max Memory Used: 14 MB

	
I cant understand why python does not found the core directory that is present in the folder structure.


EDIT:

Following @jarmod advice I&#39;ve reduced the `lambda`function to:

&lt;!-- language: lang-py --&gt;

    def make_movie(event, context):
        print(&#39;running make movie&#39;)
        import numpy

I now have the following error:

    START RequestId: 6abd7ef6-b9de-11e5-8aee-918ac0a06113 Version: $LATEST
    running make movie
    Error importing numpy: you should not try to import numpy from
            its source directory; please exit the numpy source tree, and relaunch
            your python intepreter from there.: ImportError
    Traceback (most recent call last):
      File &quot;/var/task/process_movie.py&quot;, line 3, in make_movie
        import numpy
      File &quot;/var/task/numpy/__init__.py&quot;, line 127, in &lt;module&gt;
        raise ImportError(msg)
    ImportError: Error importing numpy: you should not try to import numpy from
            its source directory; please exit the numpy source tree, and relaunch
            your python intepreter from there.
    
    END RequestId: 6abd7ef6-b9de-11e5-8aee-918ac0a06113
    REPORT RequestId: 6abd7ef6-b9de-11e5-8aee-918ac0a06113	Duration: 105.95 ms	Billed Duration: 200 ms 	Memory Size: 1536 MB	Max Memory Used: 14 MB

	

  [1]: http://docs.aws.amazon.com/lambda/latest/dg/with-s3-example-deployment-pkg.html#with-s3-example-deployment-pkg-python
  [2]: http://www.perrygeo.com/running-python-with-compiled-code-on-aws-lambda.html

Using moviepy, scipy and numpy in amazon lambda

Let&#39;s say we have a dummy function:

    async def foo(arg):
        result = await some_remote_call(arg)
        return result.upper()

What&#39;s the difference between:

    import asyncio    

    coros = []
    for i in range(5):
        coros.append(foo(i))

    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(coros))

And:

    import asyncio

    futures = []
    for i in range(5):
        futures.append(asyncio.ensure_future(foo(i)))

    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(futures))

*Note*: The example returns a result, but this isn&#39;t the focus of the question. When return value matters, use `gather()` instead of `wait()`.

Regardless of return value, I&#39;m looking for clarity on `ensure_future()`. `wait(coros)` and `wait(futures)` both run the coroutines, so when and why should a coroutine be wrapped in `ensure_future`?

Basically, what&#39;s the Right Way (tm) to run a bunch of non-blocking operations using Python 3.5&#39;s `async`?

For extra credit, what if I want to batch the calls? For example, I need to call `some_remote_call(...)` 1000 times, but I don&#39;t want to crush the web server/database/etc with 1000 simultaneous connections. This is doable with a thread or process pool, but is there a way to do this with `asyncio`?

**2020 update (Python 3.7+)**: Don&#39;t use these snippets. Instead use:

    import asyncio

    async def do_something_async():
        tasks = []
        for i in range(5):
            tasks.append(asyncio.create_task(foo(i)))
        await asyncio.gather(*tasks)

    def do_something():
        asyncio.run(do_something_async)

Also consider using [Trio][1], a robust 3rd party alternative to asyncio.


  [1]: https://trio.readthedocs.io/

Difference between coroutine and future/task in Python 3.5?

I am in the process of upgrading our existing solution to .Net 4.6.1 and have been unable to get our unit tests to run during a server build. Locally they run as expected and flipping the framework version back to .Net 4.5.1 makes them run again on the server.

I am getting the following error:

&gt; No test found. Make sure that installed test discoverers &amp; executors, platform &amp; framework version settings are appropriate and try again.

I have reproduced the problem in a simpler setup:

 - Solution with a single C# Unit Test project with two tests (one failing, one passing).
 -  XAML build definition
   using the Default Template (TfvcTemplate.12.xaml)
 - TFS 2015 Update 1
   XAML build server with Visual Studio Enterprise 2015 Update 1
   installed (have six similar servers and all produce the same result)

No test found. Make sure that installed test discoverers &amp; executors, platform &amp; framework version settings are appropriate and try again

I&#39;m running unit tests in Android Studio. I have a Java class that loads a native library with the following code

     static
        {
           System.loadLibrary(&quot;mylibrary&quot;);
        }
But when I test this class inside my `src/test` directory I get 

    java.lang.UnsatisfiedLinkError: no mylibrary in java.library.path
    	at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1864)
    	at java.lang.Runtime.loadLibrary0(Runtime.java:870)
    	at java.lang.System.loadLibrary(System.java:1122)

How can I make it find the path of native .so libraries which is located at `src/main/libs` in order to unit test without errors?

Note: inside `src/main/libs` directory I have 3 more subdirectories: `armeabi`, `mips` and `x86`. Each one of those contains the proper .so file. I&#39;m using the **Non experimental version** for building NDK libs.

I don&#39;t wanna use other 3rd party testing libraries as all my other &quot;pure&quot; java classes can be unit tested fine. But if that&#39;s not possible then I&#39;m open to alternatives.

Here is my test code which throws the error

       @Test
        public void testNativeClass() throws Exception
        {
            MyNativeJavaClass test = new MyNativeJavaClass(&quot;lalalal&quot;)
            List&lt;String&gt; results = test.getResultsFromNativeMethodAndPutThemInArrayList();
            assertEquals(&quot;There should be only three result&quot;, 3, results.size());
        }

Unit test Java class that loads native library

I have started working with `OCMock` to write test cases for the existing project that I have integrated in my project workspace. After following all the steps mentioned in this [link][1].

When I first executed my test case it&#39;s giving the error above. I searched it and tried following some of the solutions like *creating new target*, *restarting Xcode* but it didn&#39;t help me out. Any idea?

[1]: http://ocmock.org/ios/


Test target X encountered an error (Early unexpected exit, operation never finished bootstrapping - no restart will be attempted

I&#39;m trying to write a unit test for a greater than overridden operator using Fluent Assertions in C#. The greater than operator in this class is supposed to throw an exception if either of the objects are null.

Usually when using Fluent Assertions, I would use a lambda expression to put the method into an action. I would then run the action and use `action.ShouldThrow&lt;Exception&gt;`. However, I can&#39;t figure out how to put an operator into a lambda expression.

I would rather not use NUnit&#39;s `Assert.Throws()`, the `Throws` Constraint, or the `[ExpectedException]` attribute for consistencies sake.

How to use Fluent Assertions to test for exception in inequality tests?

I use [Istanbul][1] for code coverage of unit tests in an AngularJS project. There are 4 types of coverage and they are

 - statement
 - branch
 - function
 - line

Statement, function and line are alright but i don&#39;t understand what &quot;branch&quot; is. What is branch?


  [1]: https://gotwarlost.github.io/istanbul/

What is a branch in code coverage for JavaScript unit testing

I have a python file `a.py` which contains two classes `A` and `B`.

    class A(object):
        def method_a(self):
            return &quot;Class A method a&quot;

    class B(object):
        def method_b(self):
            a = A()
            print a.method_a()

 
I would like to unittest `method_b` in class `B` by mocking `A`. Here is the content of the file `testa.py` for this purpose:

    import unittest
    import mock
    import a


    class TestB(unittest.TestCase):

        @mock.patch(&#39;a.A&#39;)
        def test_method_b(self, mock_a):
            mock_a.method_a.return_value = &#39;Mocked A&#39;
            b = a.B()
            b.method_b()


    if __name__ == &#39;__main__&#39;:
        unittest.main()

I expect to get `Mocked A` in the output. But what I get is:

    &lt;MagicMock name=&#39;A().method_a()&#39; id=&#39;4326621392&#39;&gt;

Where am I doing wrong?

Python returns MagicMock object instead of return_value

I&#39;m having some trouble dealing with the nested tuple which `Mock.call_args_list` returns.

    def test_foo(self):
        def foo(fn):
            fn(&#39;PASS and some other stuff&#39;)

        f = Mock()
        foo(f)
        foo(f)
        foo(f)

        for call in f.call_args_list:
            for args in call:
                for arg in args:
                    self.assertTrue(arg.startswith(&#39;PASS&#39;))

I would like to know if there is a better way to unpack that call_args_list on the mock object in order to make my assertion. This loop works, but it feels like there must be a more straight forward way.

Python mock call_args_list unpacking tuples for assertion on arguments

I&#39;m modifying some code to be compatible between `Python 2` and `Python 3`, but have observed a warning in unit test output.

    /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/unittest/case.py:601:
        ResourceWarning: unclosed socket.socket fd=4,
        family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=6,
        laddr=(&#39;1.1.2.3&#39;, 65087), raddr=(&#39;5.8.13.21&#39;, 8080)

A little research determined this was also happening from popular libraries like [requests][1] and [boto3][2].

I could ignore the warning or [filter it][3] completely.  If was my service, I could set the `connection: close` header in my response ([link][3]).

Here&#39;s an example that exhibits the warning in `Python 3.6.1`:

**app.py**

    import requests
    
    class Service(object):
        def __init__(self):
            self.session = requests.Session()
    
        def get_info(self):
            uri = &#39;http://api.stackexchange.com/2.2/info?site=stackoverflow&#39;
            response = self.session.get(uri)
            if response.status_code == 200:
                return response.json()
            else:
                response.raise_for_status()

        def __del__(self):
            self.session.close()
    
    if __name__ == &#39;__main__&#39;:
        service = Service()
        print(service.get_info())

**test.py**

    import unittest
    
    class TestService(unittest.TestCase):
        def test_growing(self):
            import app
            service = app.Service()
            res = service.get_info()
            self.assertTrue(res[&#39;items&#39;][0][&#39;new_active_users&#39;] &gt; 1)
    
    
    if __name__ == &#39;__main__&#39;:
        unittest.main()


Is there a better / correct way to manage the session so that it gets explicitly closed and not rely on `__del__()` to result in this sort of warning.

Thanks for any help.

  [1]: https://github.com/requests/requests/issues/3912
  [2]: https://github.com/boto/boto3/issues/454
  [3]: https://stackoverflow.com/questions/14938716/socket-resourcewarning-using-urllib-in-python-3

ResourceWarning unclosed socket in Python 3 Unit Test

I&#39;ve just started using [Coverage.py](http://coverage.readthedocs.org/en/latest/index.html) module and so decided to make a simple test to check how it works.

**Sample.py**

    def sum(num1, num2):
        return num1 + num2


    def sum_only_positive(num1, num2):
        if num1 &gt; 0 and num2 &gt; 0:
            return num1 + num2
        else:
            return None

**test.py**  

    from sample import sum, sum_only_positive

    def test_sum():
        assert sum(5, 5) == 10

    def test_sum_positive_ok():
        assert sum_only_positive(2, 2) == 4

    def test_sum_positive_fail():
        assert sum_only_positive(-1, 2) is None

As you see, all my code is covered with tests and py.test says all of them pass. I expect Coverage.py to show 100% coverage. Well, no.

[![Coverage.py results][1]][1]

Well, Coverage.py may not see test.py file, so I copied test functions to `sample.py` file and ran Coverage again:  
[![enter image description here][2]][2]

Then I added this block of code:

    if __name__ == &quot;__main__&quot;:
        print(sum(2, 4))
        print(sum_only_positive(2, 4))
        print(sum_only_positive(-1, 3))

and removed all test functions. After that, Coverage.py shows 100%:

[![enter image description here][3]][3]

Why is it so? Shouldn&#39;t Coverage.py show code test coverage, not just execution coverage? I&#39;ve read an official [F.A.Q.](http://coverage.readthedocs.org/en/latest/faq.html) for Coverage.py, but can&#39;t find the solution.  
Since many SO users are familiar with code testing and code coverage, I hope you can tell me, where am I mistaken.

*I have just one thought here: Coverage.py may simply watch which lines of code aren&#39;t executed so I should write tests for those lines. But there&#39;re lines which are executed already but aren&#39;t covered with tests so Coverage.py will fail here.*


  [1]: http://i.stack.imgur.com/bA2fO.png
  [2]: http://i.stack.imgur.com/ZM4dG.png
  [3]: http://i.stack.imgur.com/MmMqf.png

How to properly use coverage.py in Python?

I am trying to find the coverage using coverage module for a django project but gets 
```
Coverage.py warning: No data was collected. (no-data-collected)
```
My project folder has src and tests folders.

When I run 
```
coverage run -m pytest &amp;&amp; coverage report
```
It produces a report with 100% coverage with the list of files inside the tests folder.
Whereas when I run
```
coverage run --source=src -m pytest &amp;&amp; coverage report
```
it says 
```
Coverage.py warning: No data was collected. (no-data-collected)
No data to report.
```
When I try to give the `source=src` or `include=src` in the `.coveragerc` also the same warning occurs. The tests passes for all the above cases.

I want the coverage of the src folder.
Is it because I am missing some path setting?

Content Type	Original Author	Original Content on Stackoverflow
Question	user4591756	View Question on Stackoverflow
Solution 1 - Python	Ned Batchelder	View Answer on Stackoverflow
Solution 2 - Python	Daenyth	View Answer on Stackoverflow

How do I make coverage include not tested files?

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