One of the most talked-about features in Python 3.5 is **type hints**.

An example of **type hints** is mentioned in [this article][1] and [this one][2] while also mentioning to use type hints responsibly. Can someone explain more about them and when they should be used and when not?

  [1]: http://lwn.net/Articles/650904/
  [2]: http://lwn.net/Articles/640359/


What are type hints in Python 3.5?

How do I use type hints to annotate a function that returns an `Iterable` that always yields two values: a `bool` and a `str`?  The hint `Tuple[bool, str]` is close, except that it limits the return value type to a tuple, not a generator or other type of iterable.

I&#39;m mostly curious because I would like to annotate a function `foo()` that is used to return multiple values like this:

    always_a_bool, always_a_str = foo()

Usually functions like `foo()` do something like `return a, b` (which returns a tuple), but I would like the type hint to be flexible enough to replace the returned tuple with a generator or list or something else.

How to annotate types of multiple return values?

I&#39;m trying to split my huge class into two; well, basically into the &quot;main&quot; class and a mixin with additional functions, like so:

`main.py` file:

    import mymixin.py

    class Main(object, MyMixin):
        def func1(self, xxx):
            ...


`mymixin.py` file:

    class MyMixin(object):
        def func2(self: Main, xxx):  # &lt;--- note the type hint
            ...

Now, while this works just fine, the type hint in `MyMixin.func2` of course can&#39;t work. I can&#39;t import `main.py`, because I&#39;d get a cyclic import and without the hint, my editor (PyCharm) can&#39;t tell what `self` is.

I&#39;m using Python 3.4, but I&#39;m willing to move to 3.5 if a solution is available there.

Is there any way I can split my class into two files and keep all the &quot;connections&quot; so that my IDE still offers me auto-completion and all the other goodies that come from it knowing the types?

Python type hinting without cyclic imports

I am working on Django project where I need to create a form for inputs. I tried to import `reverse` from `django.core.urlresolvers`. I got an error:

    line 2, in from django.core.urlresolvers import reverse ImportError: No module named &#39;django.core.urlresolvers&#39;

I am using Python 3.5.2, Django 2.0 and MySQL.

ImportError: No module named &#39;django.core.urlresolvers&#39;

I know `@` is for decorators, but what is `@=` for in Python? Is it just reservation for some future idea?

This is just one of my many questions while reading `tokenizer.py`.

What is the &#39;@=&#39; symbol for in Python?

Sometimes there is some non-critical asynchronous operation that needs to happen but I don&#39;t want to wait for it to complete.  In Tornado&#39;s coroutine implementation you can &quot;fire &amp; forget&quot; an asynchronous function by simply ommitting the `yield` key-word.

I&#39;ve been trying to figure out how to &quot;fire &amp; forget&quot; with the new `async`/`await` syntax released in Python 3.5.  E.g., a simplified code snippet:

&lt;!-- language: lang-python --&gt;

    async def async_foo():
        print(&quot;Do some stuff asynchronously here...&quot;)
    
    def bar():
        async_foo()  # fire and forget &quot;async_foo()&quot;
    
    bar()


What happens though is that `bar()` never executes and instead we get a runtime warning:

&lt;!-- language: lang-python --&gt;

    RuntimeWarning: coroutine &#39;async_foo&#39; was never awaited
      async_foo()  # fire and forget &quot;async_foo()&quot;



&quot;Fire and forget&quot; python async/await

Why is `x**4.0` faster than `x**4`? I am using CPython 3.5.2.

    $ python -m timeit &quot;for x in range(100):&quot; &quot; x**4.0&quot;
      10000 loops, best of 3: 24.2 usec per loop

    $ python -m timeit &quot;for x in range(100):&quot; &quot; x**4&quot;
      10000 loops, best of 3: 30.6 usec per loop

I tried changing the power I raised by to see how it acts, and for example if I raise x to the power of 10 or 16 it&#39;s jumping from 30 to 35, but if I&#39;m raising by **10.0** as a float, it&#39;s just moving around 24.1~4.

I guess it has something to do with float conversion and powers of 2 maybe, but I don&#39;t really know.

I noticed that in both cases powers of 2 are faster, I guess since those calculations are more native/easy for the interpreter/computer. But still, with floats it&#39;s almost not moving. `2.0 =&gt; 24.1~4 &amp; 128.0 =&gt; 24.1~4` **but** `2 =&gt; 29 &amp; 128 =&gt; 62`

&lt;hr&gt; [TigerhawkT3](https://stackoverflow.com/users/2617068/tigerhawkt3) pointed out that it doesn&#39;t happen outside of the loop. I checked and the situation only occurs (from what I&#39;ve seen) when the **base** is getting raised. Any idea about that?

Why is x**4.0 faster than x**4 in Python 3?

I recently moved to Python 3.5 and noticed the [new matrix multiplication operator (@)][1] sometimes behaves differently from the [numpy dot][2] operator. In example, for 3d arrays:

    import numpy as np
    
    a = np.random.rand(8,13,13)
    b = np.random.rand(8,13,13)
    c = a @ b  # Python 3.5+
    d = np.dot(a, b)

The `@` operator returns an array of shape:

    c.shape
    (8, 13, 13)

while the `np.dot()` function returns:

    d.shape
    (8, 13, 8, 13)

How can I reproduce the same result with numpy dot? Are there any other significant differences?


  [1]: https://docs.python.org/3/whatsnew/3.5.html#whatsnew-pep-465
  [2]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html

Difference between numpy dot() and Python 3.5+ matrix multiplication @

I&#39;ve seen several basic Python 3.5 tutorials on asyncio doing the same operation in various flavours.
In this code:

    import asyncio  

    async def doit(i):
        print(&quot;Start %d&quot; % i)
        await asyncio.sleep(3)
        print(&quot;End %d&quot; % i)
        return i
    
    if __name__ == &#39;__main__&#39;:
        loop = asyncio.get_event_loop()
        #futures = [asyncio.ensure_future(doit(i), loop=loop) for i in range(10)]
        #futures = [loop.create_task(doit(i)) for i in range(10)]
        futures = [doit(i) for i in range(10)]
        result = loop.run_until_complete(asyncio.gather(*futures))
        print(result)

All the three variants above that define the ``futures`` variable achieve the same result; the only difference I can see is  that with the third variant the execution is out of order (which should not matter in most cases). Is there any other difference? Are there cases where I can&#39;t just use the simplest variant (plain list of coroutines)?

asyncio.ensure_future vs. BaseEventLoop.create_task vs. simple coroutine?

I was trying to remove unwanted characters from a given string using `text.translate()` in Python 3.4.

The minimal code is:

	import sys 
	s = &#39;abcde12345@#@$#%$&#39;
	mapper = dict.fromkeys(i for i in range(sys.maxunicode) if chr(i) in &#39;@#$&#39;)
	print(s.translate(mapper))

It works as expected. However the same program when executed in Python 3.4 and Python 3.5 gives a large difference.

The code to calculate timings is

	python3 -m timeit -s &quot;import sys;s = &#39;abcde12345@#@$#%$&#39;*1000 ; mapper = dict.fromkeys(i for i in range(sys.maxunicode) if chr(i) in &#39;@#$&#39;); &quot;   &quot;s.translate(mapper)&quot;

The Python 3.4 program takes ***1.3ms*** whereas the same program in Python 3.5 takes only ***26.4μs***. 

What has improved in Python 3.5 that makes it faster compared to Python 3.4?

Why is str.translate much faster in Python 3.5 compared to Python 3.4?

I am using Python 3.5.2 version on Windows 7 and tried using `python3 app.py`. I am getting this error message: 

    &#39;python3&#39; is not recognized as an internal or external command,
    operable program or batch file. 

Is there any specific cause about why the `python3` command is not working?

I also verified that the PATH is added to environment variables.


&#39;python3&#39; is not recognized as an internal or external command, operable program or batch file

I&#39;m migrating from `tornado` to `asyncio`, and I can&#39;t find the `asyncio` equivalent of `tornado`&#39;s `PeriodicCallback`. (A `PeriodicCallback` takes two arguments: the function to run and the number of milliseconds between calls.)
 
- Is there such an equivalent in `asyncio`?
- If not, what would be the cleanest way to implement this without running the risk of getting a `RecursionError` after a while?

How can I periodically execute a function with asyncio?

I have been launching Jupyter Notebook for years using the following command:

    jupyter-notebook --port=7000 --no-browser --no-mathjax
When I try to open the jupyter on the browser it ask me for a password, even though I have never set any before.
It is important to note that If I do set the port to a value different than `7000 (eg., the default 8888)` the interface will open with no problem

**I am running jupyter locally, and on the following setup:**

    Python 3.5.2

**With the following modules installed:**

    jupyter (1.0.0), jupyter-client (4.4.0), jupyter-console (5.0.0), jupyter-core (4.2.1), ipykernel (4.5.2), ipython (5.1.0), ipython-genutils (0.1.0), nbconvert (4.3.0), nbformat (4.2.0), notebook (4.3.0)

**NOTE: I have no jupyter configurations file**

Following are some of the output lines from the server:

    [I 19:16:24.358 NotebookApp] Serving notebooks from local directory: /Users/my_user_name
    [I 19:16:24.358 NotebookApp] 0 active kernels
    [I 19:16:24.358 NotebookApp] The Jupyter Notebook is running at: http://localhost:7000/?token=aa0dab6e2d85766f3e2e4f0f6633e4473db56a56c94cac76
    [I 19:16:24.358 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

And follwing are messages after I try to open it on the browser (using port 7000)

    [I 19:21:56.848 NotebookApp] 302 GET /tree (::1) 8.46ms
    [D 19:21:56.857 NotebookApp] Using contents: services/contents
    [D 19:21:56.919 NotebookApp] Path base/images/favicon.ico served from /usr/local/lib/python3.5/site-packages/notebook/static/base/images/favicon.ico
    [D 19:21:56.920 NotebookApp] Path components/jquery-ui/themes/smoothness/jquery-ui.min.css served from /usr/local/lib/python3.5/site-packages/notebook/static/components/jquery-ui/themes/smoothness/jquery-ui.min.css
    [D 19:21:56.922 NotebookApp] Path components/jquery-typeahead/dist/jquery.typeahead.min.css served from /usr/local/lib/python3.5/site-packages/notebook/static/components/jquery-typeahead/dist/jquery.typeahead.min.css
    [D 19:21:56.923 NotebookApp] Path style/style.min.css served from /usr/local/lib/python3.5/site-packages/notebook/static/style/style.min.css
    [D 19:21:56.925 NotebookApp] Path auth/css/override.css served from /usr/local/lib/python3.5/site-packages/notebook/static/auth/css/override.css
    [D 19:21:56.926 NotebookApp] Path components/es6-promise/promise.min.js served from /usr/local/lib/python3.5/site-packages/notebook/static/components/es6-promise/promise.min.js
    [D 19:21:56.926 NotebookApp] Path components/requirejs/require.js served from /usr/local/lib/python3.5/site-packages/notebook/static/components/requirejs/require.js
    [D 19:21:56.933 NotebookApp] Path base/images/logo.png served from /usr/local/lib/python3.5/site-packages/notebook/static/base/images/logo.png
    [D 19:21:56.934 NotebookApp] 200 GET /login?next=%2Ftree (::1) 80.86ms
    [D 19:21:57.001 NotebookApp] Path custom.css served from /usr/local/lib/python3.5/site-packages/notebook/static/custom/custom.css
    [D 19:21:57.003 NotebookApp] 304 GET /custom/custom.css (::1) 3.11ms
    [D 19:21:57.341 NotebookApp] Path auth/js/main.min.js served from /usr/local/lib/python3.5/site-packages/notebook/static/auth/js/main.min.js
    [D 19:21:57.344 NotebookApp] 200 GET /static/auth/js/main.min.js?v=20161219191623 (::1) 3.57ms

At this point there is a page from jupyter asking me to insert a password I have never set before.

## SOLVED! ##

With latest update of notebook module (4.3.1) the problem has been solved.

Once the jupyter notebook is launched the user is prompted to paste a URL into the browser at the first connection:

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:7000/?token=32be0f5ee74cfe521187bc479855ce8b9fbab9e8021701c9

This solved the problem!

How to disable password request for a Jupyter notebook session?

This might be silly but I am unable to install `cPickle` with python 3.5 docker image

**Dockerfile**

    FROM python:3.5-onbuild

**requirements.txt**

    cpickle

When I try to build the image

    $ docker build -t sample .
    Sending build context to Docker daemon 3.072 kB
    Step 1 : FROM python:3.5-onbuild
    # Executing 3 build triggers...
    Step 1 : COPY requirements.txt /usr/src/app/
    Step 1 : RUN pip install --no-cache-dir -r requirements.txt
     ---&gt; Running in 016c35a032ee
    Collecting cpickle (from -r requirements.txt (line 1))
      Could not find a version that satisfies the requirement cpickle (from -r requirements.txt (line 1)) (from versions: )
    No matching distribution found for cpickle (from -r requirements.txt (line 1))
    You are using pip version 7.1.2, however version 8.1.1 is available.
    You should consider upgrading via the &#39;pip install --upgrade pip&#39; command.
    The command &#39;/bin/sh -c pip install --no-cache-dir -r requirements.txt&#39; returned a non-zero code: 1



installing cPickle with python 3.5

When trying to run the asyncio hello world code example given in the docs:

    import asyncio

    async def hello_world():
        print(&quot;Hello World!&quot;)

    loop = asyncio.get_event_loop()
    # Blocking call which returns when the hello_world() coroutine is done
    loop.run_until_complete(hello_world())
    loop.close()
I get the error: 

    RuntimeError: Event loop is closed

I am using python 3.5.3.

&quot;Asyncio Event Loop is Closed&quot; when getting loop

So I am trying to use:

    sift = cv2.xfeatures2d.SIFT_create()

and it is coming up with this error:

 

    cv2.error: OpenCV(3.4.3) C:\projects\opencv-python\opencv_contrib\modules\xfeatures2d\src\sift.cpp:1207: error: (-213:The function/feature is not implemented) 
    This algorithm is patented and is excluded in this configuration; Set OPENCV_ENABLE_NONFREE CMake 
    option and rebuild the library in function &#39;cv::xfeatures2d::SIFT::create&#39;

I am using `Python 3.5.0` and `opencv(3.4.3)` and I am just using idle. This occured after I tried to install TensorFlow and I have tried looking around and have installed opencv-contrib-python but I am still getting the same error. Thank you in advance and I apologise if I have not included enough info




sift = cv2.xfeatures2d.SIFT_create() not working even though have contrib installed

Is there any difference between using `typing.Any` as opposed to `object` in typing? For example:

    def get_item(L: list, i: int) -&gt; typing.Any:
        return L[i]

Compared to:

    def get_item(L: list, i: int) -&gt; object:
        return L[i]

typing.Any vs object?

I want to use generator yield and async functions. I read [this topic][1], and wrote next code:

    import asyncio
    
    async def createGenerator():
    	mylist = range(3)
    	for i in mylist:
    		await asyncio.sleep(1)
    		yield i*i

    async def start():
    	mygenerator = await createGenerator()
    	for i in mygenerator:
    		print(i)
	
    loop = asyncio.get_event_loop()
    
    try:
    	loop.run_until_complete(start())
    	
    except KeyboardInterrupt:
    	loop.stop()
    	pass

But i got the error: 

SyntaxError: &#39;yield&#39; inside async function

How to use yield generator in async function?


  [1]: https://stackoverflow.com/questions/231767/what-does-the-yield-keyword-do-in-python

How to use &#39;yield&#39; inside async function?

How can I find out if a function or method is a normal function or an async function? I would like my code to automatically support normal or async callbacks and need a way to test what type of function is passed.

    async def exampleAsyncCb():
        pass

    def exampleNomralCb():
        pass

    def isAsync(someFunc):
        #do cool dynamic python stuff on the function
        return True/False

	async def callCallback(cb, arg):
		if isAsync(cb):
			await cb(arg)
		else:
			cb(arg)

And depending on what type of function gets passed it should either run it normally or with await. I tried various things but have no idea how to implement `isAsync()`.

Test if function or method is normal or asynchronous

python 3.5.2

**code 1**

    import urllib
    s = urllib.parse.quote(&#39;&quot;&#39;)
    print(s) 

it gave this error: 

&gt; AttributeError: module &#39;urllib&#39; has no attribute &#39;parse&#39;

**code 2**

    from urllib.parse import quote  
    # import urllib
    # s = urllib.parse.quote(&#39;&quot;&#39;)
    s = quote(&#39;&quot;&#39;)
    print(s) 

it works...

**code3**

    from flask import Flask
    # from urllib.parse import quote  
    # s = quote(&#39;&quot;&#39;)
    import urllib
    s = urllib.parse.quote(&#39;&quot;&#39;)
    print(s) 
 it works,too. because of flask? 

Why I don&#39;t have the error anymore? is it a bug ?





AttributeError: module &#39;urllib&#39; has no attribute &#39;parse&#39;

I&#39;d like to create a class which has `abc.ABCMeta` as a metaclass and is compatible both with Python 2.7 and Python 3.5. Until now, I only succeeded doing this either on 2.7 or on 3.5 - but never on both versions simultaneously. Could someone give me a hand?

Python 2.7:

    import abc
    class SomeAbstractClass(object):
        __metaclass__ = abc.ABCMeta
        @abc.abstractmethod
        def do_something(self):
            pass

Python 3.5:

    import abc
    class SomeAbstractClass(metaclass=abc.ABCMeta):
        @abc.abstractmethod
        def do_something(self):
            pass

## Testing

If we run the following test using the suitable version of the Python interpreter (Python 2.7 -&gt; Example 1, Python 3.5 -&gt; Example 2), it succeeds in both scenarios:

    import unittest
    class SomeAbstractClassTestCase(unittest.TestCase):
        def test_do_something_raises_exception(self):
            with self.assertRaises(TypeError) as error:
                processor = SomeAbstractClass()
            msg = str(error.exception)
            expected_msg = &quot;Can&#39;t instantiate abstract class SomeAbstractClass with abstract methods do_something&quot;
            self.assertEqual(msg, expected_msg)

## Problem

While running the test using Python 3.5, the expected behavior doesn&#39;t happen (`TypeError` is not raised while instantiating `SomeAbstractClass`):

    ======================================================================
    FAIL: test_do_something_raises_exception (__main__.SomeAbstractClassTestCase)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File &quot;/home/tati/sample_abc.py&quot;, line 22, in test_do_something_raises_exception
        processor = SomeAbstractClass()
    AssertionError: TypeError not raised
    
    ----------------------------------------------------------------------

Whereas running the test using Python 2.7 raises a `SyntaxError`:

     Python 2.7 incompatible
     Raises exception:
      File &quot;/home/tati/sample_abc.py&quot;, line 24
        class SomeAbstractClass(metaclass=abc.ABCMeta):
                                         ^
     SyntaxError: invalid syntax

Using abc.ABCMeta in a way it is compatible both with Python 2.7 and Python 3.5

I am debugging a Python (`3.5`) program with PyCharm (`PyCharm Community Edition 2016.2.2 ; Build #PC-162.1812.1, built on August 16, 2016 ; JRE: 1.8.0_76-release-b216 x86 ; JVM: OpenJDK Server VM by JetBrains s.r.o`) on Windows 10.

**The problem: when stopped at some breakpoints, the Debugger window is stuck at &quot;Collecting data&quot;, which eventually timeout.** (with *Unable to display frame variables*)

The data to be displayed is neither special, nor particularly large. It is somehow available to PyCharm since a conditional break point on some values of the said data works fine (the program breaks) -- it looks like the process to gather it for display only (as opposed to operational purposes) fails.

When I step into a function around the place I have my breakpoint, its data is displayed correctly. When I go up the stack (to the calling function, the one I stepped down from and where I wanted initially to have the breakpoint) - I am stuck with the &quot;Collecting data&quot; timeout again.

There have been numerous issues raised with the same point since at least 2005. Some were fixed, some not. The fixes were usually updates to the latest version (which I have).

**Is there a general direction I can go to in order to fix or work around this family of problems?**

---

EDIT: a year later the problem is still there and there is still no reaction from the devs/support after the bug was raised.

---

**EDIT April 2018: It looks like the problem is solved in the 2018.1 version**, the following code which was hanging when setting a breakpoint on the `print` line now works (I can see the variables):

    import threading
    
    def worker():
        a = 3
        print(&#39;hello&#39;)
    
    threading.Thread(target=worker).start()

Debugger times out at &quot;Collecting data...&quot;

I&#39;m trying to execute a [Python script](https://pastebin.com/jSjn1aaD), but I am getting the following error:

    Process finished with exit code 139 (interrupted by signal 11: SIGSEGV)

I&#39;m using python 3.5.2 on a Linux Mint 18.1 Serena OS

Can someone tell me why this happens, and how can I solve?


Process finished with exit code 139 (interrupted by signal 11: SIGSEGV)

Does asyncio supports asynchronous I/O for file operations? If yes, how I can use this in Python 3.5 with async/await syntax code?

Does asyncio supports asynchronous I/O for file operations?

    #!/usr/bin/env python3
    # -*- coding: utf-8 -*-
    import time
    
    async def foo():
      await time.sleep(1)
    
    foo()

I couldn&#39;t make this dead simple example to run:

    RuntimeWarning: coroutine &#39;foo&#39; was never awaited foo()

How to use async/await in Python 3.5?

I tried to install a package through pip3, and I got this error. Every pip/pip3 command that I run gives me this error- 

    alexg@hitbox:~$ pip3 -V
    Traceback (most recent call last):
      File &quot;/usr/local/bin/pip3&quot;, line 7, in &lt;module&gt;
        from pip import main
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/__init__.py&quot;, line 26, in &lt;module&gt;
        from pip.utils import get_installed_distributions, get_prog
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/utils/__init__.py&quot;, line 27, in &lt;module&gt;
        from pip._vendor import pkg_resources
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 3018, in &lt;module&gt;
        @_call_aside
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 3004, in _call_aside
        f(*args, **kwargs)
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 3046, in _initialize_master_working_set
        dist.activate(replace=False)
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 2578, in activate
        declare_namespace(pkg)
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 2152, in declare_namespace
        _handle_ns(packageName, path_item)
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 2092, in _handle_ns
        _rebuild_mod_path(path, packageName, module)
      File &quot;/home/alexg/.local/lib/python3.5/site-packages/pip/_vendor/pkg_resources/__init__.py&quot;, line 2121, in _rebuild_mod_path
        orig_path.sort(key=position_in_sys_path)
    AttributeError: &#39;_NamespacePath&#39; object has no attribute &#39;sort&#39;


I have tried running `pip3 install --upgrade pip setuptools` according to some answers, but every pip command gives me the error. I&#39;m stuck and can&#39;t do anything.

What could have caused it, and how can this be fixed?

I&#39;m on Ubuntu `16.04` with Python `3.5.2`

pip3 error - &#39;_NamespacePath&#39; object has no attribute &#39;sort&#39;

In modern versions of Python one can have static type analysis using function annotations, according to [PEP 484][1]. This is made easy through the typing module.

Now I&#39;m wondering how I would give a &quot;type hint&quot; towards a &quot;filestream&quot;.

    def myfunction(file: FILETYPE):
        pass

    with open(fname) as file:
        myfunction(file)

What would I insert as `FILETYPE`?

Using `print(type(file))` returns `&lt;class &#39;_io.TextIOWrapper&#39;&gt;` which isn&#39;t clear at all.

Isn&#39;t there a generic &quot;file&quot; type?

  [1]: https://www.python.org/dev/peps/pep-0484/


The correct way to annotate a &quot;file type&quot; in Python

I have few blocking functions `foo`, `bar` and I can&#39;t change those (Some internal library I don&#39;t control. Talks to one or more network services). How do I use it as async?. E.g. I wan&#39;t to do the following.

    results = []
    for inp in inps:
        val = foo(inp)
        result = bar(val)
        results.append(result)

This will be inefficient as I can call `foo` for the second input while I am waiting for the first and same for `bar`. How do I wrap them such that they are usable with asyncio (i.e new `async`, `await` syntax)?

Lets assume the functions are re-entrant. i.e it is fine to call `foo` again when already a previous `foo` is processing.


----------

**Update**

Extending answer with reusable decorator. Click [here](https://stackoverflow.com/a/53719009/) for example.

    def run_in_executor(f):
        @functools.wraps(f)
        def inner(*args, **kwargs):
            loop = asyncio.get_running_loop()
            return loop.run_in_executor(None, functools.partial(f, *args, **kwargs))
    
        return inner

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