Is Type Tracing for Python useful? Some experiments.

Type Tracing - as a program runs you trace it and record the types of variables coming in and out of functions, and being assigned to variables.
Is Type Tracing useful for providing quality benefits, documentation benefits, porting benefits, and also speed benefits to real python programs?

Python is now a gradually typed language, meaning that you can gradually apply types and along with type inference statically check your code is correct. Once you have added types to everything, you can catch quite a lot of errors. For several years I've been using the new type checking tools that have been popping up in the python ecosystem. I've given talks to user groups about them, and also trained people to use them. I think a lot of people are using these tools without even realizing it. They see in their IDE warnings about type issues, and methods are automatically completed for them.

But I've always had some thoughts in the back of my head about recording types at runtime of a program in order to help the type inference out (and to avoid having to annotate them manually yourself).

Note, that this technique is a different, but related thing to what is done in a tracing jit compiler.
Some days ago I decided to try Type Tracing out... and I was quite surprised by the results.

I asked myself these questions.

  • Can I store the types coming in and out of python functions, and the types assigned to variables in order to be useful for other things based on tracing the running of a program? (Yes)
  • Can I "Type Trace" a complex program? (Yes, a flask+sqlalchemy app test suite runs)
  • Is porting python 2 code quicker by Type Tracing combined with static type checking, documentation generation, and test generation? (Yes, refactoring is safer with a type checker and no manually written tests)
  • Can I generate better documentation automatically with Type Tracing? (Yes, return and parameter types and example values helps understanding greatly)
  • Can I use the types for automatic property testing? (Yes, hypothesis does useful testing just knowing some types and a few examples... which we recorded with the tracer)
  • Can I use example capture for tests and docs, as well as the types? (Yes)
  • Can I generate faster compiled code automatically just using the recorded types and Cython (Yes).

Benefits from Type Tracing.

Below I try to show that the following benefits can be obtained by combining Type Tracing with other existing python tools.
  • Automate documentation generation, by providing types to the documentation tool, and by collecting some example inputs and outputs.
  • Automate some type annotation.
  • Automatically find bugs static type checking can not. Without full type inference, existing python static type checkers can not find many issues until the types are fully annotated. Type Tracing can provide those types.
  • Speed up Python2 porting process, by finding issues other tools can't. It can also speed things up by showing people types and example inputs. This can greatly help people understand large programs when documentation is limited.
  • Use for Ahead Of Time (AOT) compilation with Cython.
  • Help property testing tools to find simple bugs without manually setting properties.

Tools used to hack something together.

  • coverage (extended the coverage checker to record types as it goes) 
  • mypy (static type checker for python)
  • Hypothesis (property testing... automated test generator)
  • Cython (a compiler for python code, and code with type annotations)
  • jedi (another python static type checker)
  • Sphinx (automatic documentation generator).
  • Cpython (the original C implementation of python)
More details below on the experiments.

Type Tracing using 'coverage'.

Originally I hacked up a set_trace script... and started going. But there really are so many corner cases. Also, I already run the "coverage" tool over the code base I'm working on.

I started with coverage.pytracer.PyTracer, since it's python. Coverage also comes with a faster tracer written in C. So far I'm just using the python one.

The plan later would be to perhaps use CoverageData. Which uses JSON, which means storing the type will be hard sometimes (eg, when they are dynamically generated). However, I think I'm happy to start with easy types. To start simple, I'll just record object types as strings with something like `repr(type(o)) if type(o) is not type else repr(o)`. Well, I'm not sure. So far, I'm happy with hacking everything into my fork of coverage, but to move it into production there is more work to be done. Things like multiprocess, multithreading all need to be handled.

Porting python 2 code with type tracing.

I first started porting code to python 3 in the betas... around 2007. Including some C API modules. I think I worked on one of the first single code base packages. Since then the tooling has gotten a lot better. Compatibility libraries exist (six), lots of people have figured out the dangerous points and documented them. Forward compatibility features were added into the python2.6 and 2.7, and 3.5 releases to make porting easier. However, it can still be hard.

Especially when Python 2 code bases often don't have many tests. Often zero tests. Also, there may be very little documentation, and the original developers have moved on.

But the code works, and it's been in production for a long time, and gets updates occasionally. Maybe it's not updated as often as it's needed because people are afraid of breaking things.

Steps to port to python 3 are usually these:

  1. Understand the code.
  2. Run the code in production (or on a copy of production data).
  3. With a debugger, look at what is coming in and out of functions.
  4. Write tests for everything.
  5. Write documentation.
  6. Run 2to3.
  7. Do lots of manual QA.
  8. Start refactoring.
  9. Repeat. Repeat manually writing tests, docs, and testing manually. Many times.
Remember that writing tests is usually harder than writing the code in the first place.

With type tracing helping to generate docs, types for the type checker, examples for human reading plus for the hypothesis property checker we get a lot more tools to help ensure quality.

A new way to port python2 code could be something like...
  1. Run program under Type Tracing, line/branch coverage, and example capture.
  2. Look at generated types, example inputs and outputs.
  3. Look at generated documentation.
  4. Gradually add type checking info with help of Type Tracing recorded types.
  5. Generate tests automatically with Type Tracing types, examples, and hypothesis automated property testing. Generate empty test stubs for things you still need to test.
  6. Once each module is fully typed, you can statically type check it.
  7. You can cross validate your type checked python code against your original code. Under the Type Tracer.
  8. Refactoring is easier with better docs, static type checks, tests, types for arguments and return values, and example inputs and outputs.
  9. Everything should be ported to work with the new forwards compatibility functionality in python2.7.
  10. Now with your various quality checks in place, you can start porting to python3. Note, you might not have needed to change any of the original code - only add types.
I would suggest the effort is about 1/5th of the normal time it takes to port things. Especially if you want to make sure the chance of introducing errors is very low.

Below are a couple of issues where Type Tracing can help over existing tools.

Integer divide issue.

Here I will show that the 2to3 conversion tool makes a bug with. Also, mypy does not detect a problem with the code.

# int_issue.py
def int_problem(x):
    return x / 4
print(int_problem(3))

$ python2 int_issue.py
0 
$ python3 int_issue.py
0.75

$ mypy --py2 int_issue.py
$ mypy int_issue.py
$ 2to3 int_issue.py
RefactoringTool: Skipping optional fixer: buffer
RefactoringTool: Skipping optional fixer: idioms
RefactoringTool: Skipping optional fixer: set_literal
RefactoringTool: Skipping optional fixer: ws_comma
RefactoringTool: Refactored int_issue.py
--- int_issue.py    (original)
+++ int_issue.py    (refactored)
@@ -3,4 +3,4 @@
 def int_problem(x):
     return x / 4

-print(int_problem(3))
+print((int_problem(3)))
RefactoringTool: Files that need to be modified:
RefactoringTool: int_issue.py

See how when run under python3 it gives a different result?

Can we fix it when Type Tracing adds types?  (Yes)

So, how about if we run the program under type tracing, and record the input types coming in and out? See how it adds a python3 compatible comment about taking an int, and returning an int. This is so that mypy (and other type checkers) can see what it is supposed to take in.
def int_problem(x):
    # type: (int) -> int
    return x / 4
print(int_problem(3))
$ mypy int_issue.py
int_issue.py:5: error: Incompatible return value type (got "float", expected "int")
I'm happy that Yes, Type Tracing combined with mypy can detect this issue whereas mypy can not by itself.


Binary or Text file issue?

Another porting issue not caught by existing tools is trying to do the right thing when a python file is in binary mode or in text mode. If in binary, read() will return bytes, otherwise it might return text.

In theory this could be made to work, however at the time of writing, there is an open issue with "dependent types" or "Factory Pattern" functions in mypy. More information on this, and also a work around I wrote see this issue: https://github.com/python/mypy/issues/2337#issuecomment-280850128

In there I show that you can create your own io.open replacement that always returns one type. eg, open_rw(fname) instead of open(fname, 'rw').

Once you know that .read() will return bytes, then you also know that it can't call .format() in python 3. The solution is to use % string formatting on bytes, which is supported from python3.5 upwards.

x = f.read() # type: bytes

So the answer here is that mypy could likely solve this issue by itself in the future (once things are fully type annotated). But for now, it's good to see combining type tracing with mypy could help detect binary and text encoding issues much faster.

Generating Cython code with recorded types.

I wanted to see if this was possible. So I took the simple example from the cython documentation.

I used my type tracer to transform this python:
def f(x):
    return x**2-x

def integrate_f(a, b, N):
    s = 0
    dx = (b-a)/N
    for i in range(N):
        s += f(a+i*dx)
    return s * dx

Before you look below... take a guess what parameters a, b, and N are? Note, how there are no comments. Note how the variable names are single letter. Note, how there are no tests. There are no examples.

In [2]: %timeit integrate_f(10.4, 2.3, 17)
100000 loops, best of 3: 5.12 µs per loop



Into this Cython code with annotated types after running it through Type Tracing:
In [1]: %load_ext Cython

In [2]: %%cython
   ...: cdef double f(double x):
   ...:     return x**2-x
   ...:
   ...: def integrate_f_c(double a, double b, int N):
   ...:     """
   ...:     :Example:
   ...:     >>> integrate_f_c(10.4, 2.3, 17)
   ...:     -342.34804152249137
   ...:     """
   ...:     cdef int i
   ...:     cdef double s, dx
   ...:     s = 0
   ...:     dx = (b-a)/N
   ...:     for i in range(N):
   ...:         s += f(a+i*dx)
   ...:     return s * dx 
   ...:

In [3]: %timeit integrate_f_c(10.4, 2.3, 17)

10000000 loops, best of 3: 117 ns per loop
Normal python was 5200 nanoseconds. The cython compiled version is 117 nanoseconds.  The result is 44x faster code, and we have all the types annotated, with an example. This helps you understand it a little better than before too.

This was a great result for me. It shows that yes combining Type Tracing with Cython can give improvements over Cython just by itself. Note, that Cython is not only for speeding up simple numeric code. It's also been used to speed up string based code, database access, network access, and game code.

So far I've made a simple mapping of python types to cython types. To make the code more useful would require quite a bit more effort. However, if you use it as a tool to help you write cython code yourself, then it's very useful to speed up that process.

The best cases so far are when it knows all of the types, all of the types have direct cython mappings, and it avoids calling python functions inside the function. In other words, 'pure' functions.

Cross validation for Cython and python versions?

In a video processing project I worked on there were implementations in C, and other assembly implementations of the same functions. A very simple way of testing is to run all the implementations and compare the results. If the C implementation gives the same results as the assembly implementations, then there's a pretty good chance they are correct.

In [1]:  assert integrate_f_c(10.4, 2.3, 17) == integrate_f(10.4, 2.3, 17)

If we have a test runner, we can check if the inputs and outputs are the same between the compiled code and the non compiled code. That is, cross validate implementations against each other for correctness.

Property testing.

The most popular property testing framework Quickcheck from the Haskell world. However, python also has an implementation - Hypothesis. Rather than supply examples, as is usual with unit testing you tell it about properties which hold true.

Can we generate a hypothesis test automatically using just types collected with Type Tracing?

Below we can see some unit tests (example based testing), as well as some Hypothesis tests (property testing). They are for a function "always_add_something(x)", which always adds something to the number given in. As a property, we would say that "always_add_something(x) > x".  That property will hold to be true for every value of x given x is an int.

Note, that the program is fully typed, and passes type checking with mypy. Also note that there is 100% test coverage if I remove the divide by zero error I inserted.

from hypothesis import given
import hypothesis.strategies

from bad_logic_issue import always_add_something, always_add_something_good

def test_always_add_something():# type: () -> None
    #type: () -> None
    assert always_add_something(5) >= 5
    assert always_add_something(200) >= 200

def test_always_add_something_good():
    #type: () -> None
    assert always_add_something_good(5) >= 5
    assert always_add_something_good(200) >= 200

@given(hypothesis.strategies.integers())
def test_always_add_something(x):
    assert always_add_something(x) > x


# Here we test the good one.
@given(hypothesis.strategies.integers())
def test_always_add_something(x):
    assert always_add_something_good(x) > x
Here are two implementations of the function. The first one is a contrived example in order to show two types of logic errors that are quite common. Even 30 year old code used by billions of people has been shown to have these errors. They're sort of hard to find with normal testing methods.

def always_add_something(x):
    # type: (int) -> int
    '''Silly function that is supposed to always add something to x.

    But it doesn't always... even though we have
     - 'complete' test coverage.
     - fully typed
    '''
    r = x #type: int
    if x > 0 and x < 10:
        r += 20
    elif x > 15 and x < 30:
        r //= 0
    elif x > 100:
        r += 30

    return r


def always_add_something_good(x):
    # type: (int) -> int
    '''This one always does add something.
    '''
    return x + 1

Now, hypothesis can find the errors when you write the property that the return value needs to be greater than the input. What about if we just use the types we record with Type Tracing to give hypothesis a chance to test? Hypothesis comes with a number of test strategies which generate many variations of a type. Eg, there is an "integers" strategy.

# Will it find an error just telling hypothesis that it takes an int as input?
@given(hypothesis.strategies.integers())
def test_always_add_something(x):
    always_add_something(x)

It finds the divide by zero issue (when x is 16). However it does not find the other issue, because it still does not know that there is a problem. We haven't told it anything about the result always needing to be greater than the input.
bad_logic_issue.py:13: ZeroDivisionError
-------------------------------------------------------- Hypothesis --------------------------------------------------------
Falsifying example: test_always_add_something(x=16)
The result is that yes, it could find one issue automatically, without having to write any extra test code, just from Trace Typing.

For pure functions, it would be also useful to record some examples for unit test generation.

In conclusion.

I'm happy with the experiment overall. I think it shows it can be a fairly useful technique for making python programs more understandable, faster, and more correct. It can also help speed up porting old python2 code dramatically (especially when that code has limited documentation and tests).

I think the experiment also shows that combining existing python tools (coverage, mypy, Cython, and hypothesis) can give some interesting extra abilities without not too much extra effort. eg. I didn't need to write a robust tracing module, I didn't need to write a static type checker, or a python compiler. However, it would take some effort to turn these into robust general purpose tools. Currently what I have is a collection of fragile hacks, without support for many corner cases :)

For now I don't plan to work on this any more in the short term. (Unless of course someone wants to hire me to port some python2 code. Then I'll work on these tools again since it speeds things up quite a lot).

Any corrections or suggestions? Please leave a comment, or see you on twitter @renedudfield

Comments

NotSqrt said…
Looks awesome !
Please tell us that you have some code visible somewhere, I'm so interested by this type tracing approach !
Pankaj said…
I am also very interested in such an approach. If you have something working please post it. IIRC Pycharm (the Python IDE from IntelliJ) can optionally do type tracing when debugging within the IDE to improve its static checking and suggestions. It also writes out stub files with the type information comments
Unknown said…
I agree, please post your code somewhere! This would be a huge help to the community
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All you have to do is to activate your Amazon Prime Video on amazon.com mytv using the activation code you retrieve. amazon.com/mytv Microsoft Office is an application software. amazon.com/mytv It is used in most of the businesses and organizations Install office setup on your Pc's to get best advantage of it. amazon.com/mytv mostly used tasks are ms-word, Ms-excel and Ms-powerpoint.Amazon Web Services Scalable Cloud Computing Services: Audible Download Audio Books: DPReview Digital Photography: IMDb Movies, TV & Celebrities.Now enter the activation or verification code that appears on your tv display. amazon.com/mytv Amazon Prime Video is one of the most amazing and interesting platforms to watch. Amazon Prime on your Roku,Amazon Fire TV, Chromecast, and similar streaming devices.amazon.com/mytv Amazon Prime is a subscription-based platform that gives access to the users of amazon.com/mytv large range of services such as unlimited video streaming, amazon.com/mytv Amazon.com Store Card; Amazon Business Card; Amazon Business Line of Credit; Shop with Points; Credit Card Marketplace;
Surbhi Sharma said…


Amazon Prime on your Roku,Amazon Fire TV, Chromecast, and similar streaming devices. amazon.com/mytv Amazon Prime is a subscription-based platform that gives access to the users of a large range of services such as unlimited video streaming, amazon.com/mytv Amazon.com Store Card; amazon.com/mytv Amazon Business Card; Amazon Business Line of Credit; Shop with Points; Credit Card Marketplace;Amazon Web Services Scalable amazon.com/mytv Cloud Computing Services: Audible Download Audio Books: DPReview Digital Photography: IMDb Movies, TV & Celebrities : Follow the below-stated steps to activate Amazon Prime Video on your Smart TV now: amazon.com/mytv GO to the home page of the Smart TV and search for Amazon Prime Video. Amazon App will open in front of you.amazon.com/mytv Here you will find “Register on the Amazon Website” and “Sign in and Start”. Amazon Video was previously called Amazon Video and before that it was called Amazon Instant Video. Through Amazon Prime you can enjoy new and old movies and TV service. primevideo.com/mytv Amazon Prime is very well known for its name as well as its services. Amazon Prime is the best American Internet video on demand service.

Surbhi Sharma said…

Xfinity is a platform which will keep you entertained and offers HD content at a very exciting price. Xfinity.com/authorize Here you can stream any content online.Xfinity. Let's activate your device. Xfinity.com/authorize Enter your activation code: Access on Roku and smart TV's will be available once your Xfinity.com/authorize Xfinity products have been set up in your home.


Webroot cyber security is a ultimate internet security suite for complete protection against today's diverse range of threat on windows. webroot.com/safe key features are 100% secure secure shopping, 1 click virus scanning, malicious website filtering, unblock antivirus. webroot.com/safe if you want to install it then visit our site: webroot.com/safe Get instant help for downloading webroot antivirus to protect your device appoint webroot.com/safe where you can find all your problems solved. Antivirus programming, for example, Webroot SecureAnywhere Antivirus baffles malware in two or three different ways. webroot.com/safe install webroot with key code It filters information and squares infections that it recognizes. What's more, it evacuates malware that is as of now held up in a PC. webroot.com/safe Much obliged to you for picking Webroot web security. You're nearly secured! Essentially complete the accompanying strides beneath to finish your introduce.
Surbhi Sharma said…
A progressing Microsoft statement gives some comprehension of how the association designs the landing of new Office 365 ProPlus features. Office.com/setup Microsoft uses the equivalent "channels" language for MS Office 365 ProPlus incorporates revives as it does with Windows 10 feature invigorates. Office.com/setup To activate office setup you need to visit Office.com/setup where you can find what all you can do on office setup.office Remote turns your phone into a smart remote that interacts with Microsoft Office on your PC. Office.com/setup The app lets you control Word, Excel, and PowerPoint from across the room, Office.com/setup so you can walk around freely during presentations.

Surbhi Sharma said…

Introduce mcafee antivirus in your PC with high class experts and best tech group. Simply ring us and we are prepared to help you till the last moment of establishment - visit here.To activate mcafee.com/activate with Mcafee enter product key code. Mcafee provides the best security protection all over the world. Everyday online fraud payment using phishing websites and free third-party tools mcafee.com/activate created by attackers to get user sensitive information.McAfee antivirus offers a variety of ways to scan for threats. Real-time scanning, when turned on, mcafee.com/activate scans files whenever they are accessed, which helps to protect your computer while you are using it, while keeping resource consumption to a minimum. Enter your McAfee activation key to the appropriate field. mcafee.com/activate Go to the Activate icon to get your key. Later, your subscription will be activated and you will be eligible to save and download McAfee. mcafee.com/activate For account and technical support directly from McAfee's award winning Service and Support Website. mcafee.com/activate Get help via MVT, FAQs, and live support via chat and phones. mcafee.com/activate Protect all your devices with McAfee. We offer leading Antivirus, VPN, Cloud, Endpoint, & Enterprise Security Solutions. mcafee.com/activate Get the most innovative antivirus & cyber security solutions available today! McAfee Premium Protection has all you need to protect against malware and possible cyber threats. mcafee.com/activate You can get it from now.

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Love said…
How to Start a Blog: Easy Guide to Make $302k One Year
In this article, we will talk about how to start a blog. Seven easy steps will help you in creating your Blog. People have earned massive amounts with their blogs. They have made $1 million in a brief period.
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Love said…
How to Make Money on YouTube: A platform that can give you high profits
Thinking about how to make money on YouTube? YouTube is no longer restricted to huge influencers or musicians. It has a good number of opportunities for everyday people.
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Love said…
How to Make Money Blogging
Are you fascinated about how to make money blogging? The first step will be to unlearn what you have learned to date from the ‘Experts.’
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Love said…
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Primevideomytv said…
Primevideo.com my/tv - The Best Way to Register Your Device for the Prime Video Program in Canada. To access the Prime Video TM service and sign in your personal tool, observe those commands. Depending to your version, pick Video, Application, My Apps, or Apps. If you have any troubles registering your tool with Amazon Prime, you could contact the Amazon Prime support team at www.Primevideo.com/mytv.
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