19 Jan 2021

feedPlanet Python

Stack Abuse: Python: Catch Multiple Exceptions in One Line

Introduction

In this article we're going to be taking a look at the try/except clause, and specifically how you can catch multiple exceptions in a single line, as well as how to use the suppress() method.

Both of these techniques will help you in writing more accessible and versatile code that adheres to DRY (don't repeat yourself) principles.

Let's start by looking at the problem:

try:
    do_the_thing()
except TypeError as e:
    do_the_other_thing()
except KeyError as e:
    do_the_other_thing()
except IndexError as e:
    do_the_other_thing()

Brutal.

As we can see, this is very WET code, we repeat the same invocation multiple times. Practices like this can make our code's reading and refactoring a living nightmare.

Rather than writing exceptions one after another, wouldn't it be better to group all of these exception handlers into a single line?

Multiple Exceptions

If you're just here for a quick answer, it's simple: use a tuple.

All the errors contained in the exception line tuple will be evaluated together:

try:
    do_the_thing()
except (TypeError, KeyError, IndexError) as e:
    do_the_other_thing()

Easy, right?

Avoiding Bad Practices

"Errors should never pass silently." - The Zen of Python.

try/except clauses are probably the most misused pattern in Python.

Used improperly, they end up being the cliché of drunks and lampposts, being used only when the Python interpreter start caroling the "12 Errors of Christmas".

It's very tempting to just put a try and a bare exception on a problem to "make it go away". By doing that, we're effectively sweeping the exceptions under the rug, which is a shame, especially since they can be wonderfully helpful in recovering from potentially fatal errors, or shining a light on hidden bugs.

That's why when using except clauses you should always be sure to specify the errors you know you could encounter, and exclude the ones you don't.

Letting your program fail is okay, even preferred, to just pretending the problem doesn't exist.

"Errors should never pass silently... unless explicitly silenced."

However, once in a blue moon when you do get the opportunity to ignore exception handling, you can use suppress():

from contextlib import suppress

with suppress(TypeError, KeyError, IndexError):
    do_the_thing()

The suppress() method takes a number of exceptions as its argument, and performs a try/except/pass with those errors. As you can see it also let's you write multiple exceptions in a single line.

This let's you avoid writing a try/except/pass manually:

try:
    do_the_thing()
except (TypeError, KeyError, IndexError) as e:
    pass

Better yet, it's also standard in any version of Python 3.4 and above!

Conclusion

In this article, we've covered how to handle multiple exceptions in a single line. We've also briefly gone over some bad practices of ignoring exceptions, and used the supress() function to supress exceptions explicitly.

19 Jan 2021 1:30pm GMT

Django Weblog: Django 3.2 alpha 1 released

Django 3.2 alpha 1 is now available. It represents the first stage in the 3.2 release cycle and is an opportunity for you to try out the changes coming in Django 3.2.

Django 3.2 has a mezcla of new features which you can read about in the in-development 3.2 release notes.

This alpha milestone marks the feature freeze. The current release schedule calls for a beta release in about a month and a release candidate about a month from then. We'll only be able to keep this schedule if we get early and often testing from the community. Updates on the release schedule are available on the django-developers mailing list.

As with all alpha and beta packages, this is not for production use. But if you'd like to take some of the new features for a spin, or to help find and fix bugs (which should be reported to the issue tracker), you can grab a copy of the alpha package from our downloads page or on PyPI.

The PGP key ID used for this release is Carlton Gibson: E17DF5C82B4F9D00

19 Jan 2021 1:15pm GMT

Podcast.__init__: Driving Toward A Faster Python Interpreter With Pyston

One of the common complaints about Python is that it is slow. There are languages and runtimes that can execute code faster, but they are not as easy to be productive with, so many people are willing to make that tradeoff. There are some use cases, however, that truly need the benefit of faster execution. To address this problem Kevin Modzelewski helped to create the Pyston intepreter that is focused on speeding up unmodified Python code. In this episode he shares the history of the project, discusses his current efforts to optimize a fork of the CPython interpreter, and his goals for building a business to support the ongoing work to make Python faster for everyone. This is an interesting look at the opportunities that exist in the Python ecosystem and the work being done to address some of them.

Summary

One of the common complaints about Python is that it is slow. There are languages and runtimes that can execute code faster, but they are not as easy to be productive with, so many people are willing to make that tradeoff. There are some use cases, however, that truly need the benefit of faster execution. To address this problem Kevin Modzelewski helped to create the Pyston intepreter that is focused on speeding up unmodified Python code. In this episode he shares the history of the project, discusses his current efforts to optimize a fork of the CPython interpreter, and his goals for building a business to support the ongoing work to make Python faster for everyone. This is an interesting look at the opportunities that exist in the Python ecosystem and the work being done to address some of them.

Announcements

  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you're ready to launch your next app or want to try a project you hear about on the show, you'll need somewhere to deploy it, so take a look at our friends over at Linode. With the launch of their managed Kubernetes platform it's easy to get started with the next generation of deployment and scaling, powered by the battle tested Linode platform, including simple pricing, node balancers, 40Gbit networking, dedicated CPU and GPU instances, and worldwide data centers. Go to pythonpodcast.com/linode and get a $100 credit to try out a Kubernetes cluster of your own. And don't forget to thank them for their continued support of this show!
  • Your host as usual is Tobias Macey and today I'm interviewing Kevin Modzelewski about his work on Pyston, an interpreter for Python focused on compatibility and speed.

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by describing what Pyston is and how it got started?
  • Can you share some of the history of the project and the recent changes?
    • What is your motivation for focusing on Pyston and Python optimization?
  • What are the use cases that you are primarily focused on with Pyston?
  • Why do you think Python needs another performance project?
  • Can you describe the technical implementation of Pyston?
    • How has the project evolved since you first began working on it?
  • What are the biggest challenges that you face in maintaining compatibility with CPython?
  • How does the approach to Pyston compare to projects like PyPy and Pyjion?
  • How are you approaching sustainability and governance of the project?
  • What are some of the most interesting, innovative, or unexpected uses for Pyston that you have seen?
  • What have you found to be the most interesting, unexpected, or challenging lessons that you have learned while working on Pyston?
  • When is Pyston the wrong choice?
  • What do you have planned for the future of the project?

Keep In Touch

Picks

Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

19 Jan 2021 2:03am GMT

10 Nov 2011

feedPlanetJava

OSDir.com - Java: Oracle Introduces New Java Specification Requests to Evolve Java Community Process

From the Yet Another dept.:

To further its commitment to the Java Community Process (JCP), Oracle has submitted the first of two Java Specification Requests (JSRs) to update and revitalize the JCP.

10 Nov 2011 6:01am GMT

OSDir.com - Java: No copied Java code or weapons of mass destruction found in Android

From the Fact Checking dept.:

ZDNET: Sometimes the sheer wrongness of what is posted on the web leaves us speechless. Especially when it's picked up and repeated as gospel by otherwise reputable sites like Engadget. "Google copied Oracle's Java code, pasted in a new license, and shipped it," they reported this morning.



Sorry, but that just isn't true.

10 Nov 2011 6:01am GMT

OSDir.com - Java: Java SE 7 Released

From the Grande dept.:

Oracle today announced the availability of Java Platform, Standard Edition 7 (Java SE 7), the first release of the Java platform under Oracle stewardship.

10 Nov 2011 6:01am GMT

28 Oct 2011

feedPlanet Ruby

O'Reilly Ruby: MacRuby: The Definitive Guide

Ruby and Cocoa on OS X, the iPhone, and the Device That Shall Not Be Named

28 Oct 2011 8:00pm GMT

14 Oct 2011

feedPlanet Ruby

Charles Oliver Nutter: Why Clojure Doesn't Need Invokedynamic (Unless You Want It to be More Awesome)

This was originally posted as a comment on @fogus's blog post "Why Clojure doesn't need invokedynamic, but it might be nice". I figured it's worth a top-level post here.

Ok, there's some good points here and a few misguided/misinformed positions. I'll try to cover everything.

First, I need to point out a key detail of invokedynamic that may have escaped notice: any case where you must bounce through a generic piece of code to do dispatch -- regardless of how fast that bounce may be -- prevents a whole slew of optimizations from happening. This might affect Java dispatch, if there's any argument-twiddling logic shared between call sites. It would definitely affect multimethods, which are using a hand-implemented PIC. Any case where there's intervening code between the call site and the target would benefit from invokedynamic, since invokedynamic could be used to plumb that logic and let it inline straight through. This is, indeed, the primary benefit of using invokedynamic: arbitrarily complex dispatch logic folds away allowing the dispatch to optimize as if it were direct.

Your point about inference in Java dispatch is a fair one...if Clojure is able to infer all cases, then there's no need to use invokedynamic at all. But unless Clojure is able to infer all cases, then you've got this little performance time bomb just waiting to happen. Tweak some code path and obscure the inference, and kablam, you're back on a slow reflective impl. Invokedynamic would provide a measure of consistency; the only unforeseen perf impact would be when the dispatch turns out to *actually* be polymorphic, in which case even a direct call wouldn't do much better.

For multimethods, the benefit should be clear: the MM selection logic would be mostly implemented using method handles and "leaf" logic, allowing hotspot to inline it everywhere it is used. That means for small-morphic MM call sites, all targets could potentially inline too. That's impossible without invokedynamic unless you generate every MM path immediately around the eventual call.

Now, on to defs and Var lookup. Depending on the cost of Var lookup, using a SwitchPoint-based invalidation plus invokedynamic could be a big win. In Java 7u2, SwitchPoint-based invalidation is essentially free until invalidated, and as you point out that's a rare case. There would essentially be *no* cost in indirecting through a var until that var changes...and then it would settle back into no cost until it changes again. Frequently-changing vars could gracefully degrade to a PIC.

It's also dangerous to understate the impact code size has on JVM optimization. The usual recommendation on the JVM is to move code into many small methods, possibly using call-through logic as in multimethods to reuse the same logic in many places. As I've mentioned, that defeats many optimizations, so the next approach is often to hand-inline logic everywhere it's used, to let the JVM have a more optimizable view of the system. But now we're stepping on our own feet...by adding more bytecode, we're almost certainly impacting the JVM's optimization and inlining budgets.

OpenJDK (and probably the other VMs too) has various limits on how far it will go to optimize code. A large number of these limits are based on the bytecoded size of the target methods. Methods that get too big won't inline, and sometimes won't compile. Methods that inline a lot of code might not get inlined into other methods. Methods that inline one path and eat up too much budget might push out more important calls later on. The only way around this is to reduce bytecode size, which is where invokedynamic comes in.

As of OpenJDK 7u2, MethodHandle logic is not included when calculating inlining budgets. In other words, if you push all the Java dispatch logic or multimethod dispatch logic or var lookup into mostly MethodHandles, you're getting that logic *for free*. That has had a tremendous impact on JRuby performance; I had previous versions of our compiler that did indeed infer static target methods from the interpreter, but they were often *slower* than call site caching solely because the code was considerably larger. With invokedynamic, a call is a call is a call, and the intervening plumbing is not counted against you.

Now, what about negative impacts to Clojure itself...

#0 is a red herring. JRuby supports Java 5, 6, and 7 with only a few hundred lines of changes in the compiler. Basically, the compiler has abstract interfaces for doing things like constant lookup, literal loading, and dispatch that we simply reimplement to use invokedynamic (extending the old non-indy logic for non-indified paths). In order to compile our uses of invokedynamic, we use Rémi Forax's JSR-292 backport, which includes a "mock" jar with all the invokedynamic APIs stubbed out. In our release, we just leave that library out, reflectively load the invokedynamic-based compiler impls, and we're off to the races.

#1 would be fair if the Oracle Java 7u2 early-access drops did not already include the optimizations that gave JRuby those awesome numbers. The biggest of those optimizations was making SwitchPoint free, but also important are the inlining discounting and MutableCallSite improvements. The perf you see for JRuby there can apply to any indirected behavior in Clojure, with the same perf benefits as of 7u2.

For #2, to address the apparent vagueness in my blog post...the big perf gain was largely from using SwitchPoint to invalidate constants rather than pinging a global serial number. Again, indirection folds away if you can shove it into MethodHandles. And it's pretty easy to do it.

#3 is just plain FUD. Oracle has committed to making invokedynamic work well for Java too. The current thinking is that "lambda", the support for closures in Java 7, will use invokedynamic under the covers to implement "function-like" constructs. Oracle has also committed to Nashorn, a fully invokedynamic-based JavaScript implementation, which has many of the same challenges as languages like Ruby or Python. I talked with Adam Messinger at Oracle, who explained to me that Oracle chose JavaScript in part because it's so far away from Java...as I put it (and he agreed) it's going to "keep Oracle honest" about optimizing for non-Java languages. Invokedynamic is driving the future of the JVM, and Oracle knows it all too well.

As for #4...well, all good things take a little effort :) I think the effort required is far lower than you suspect, though.

14 Oct 2011 2:40pm GMT

07 Oct 2011

feedPlanet Ruby

Ruby on Rails: Rails 3.1.1 has been released!

Hi everyone,

Rails 3.1.1 has been released. This release requires at least sass-rails 3.1.4

CHANGES

ActionMailer

ActionPack

ActiveModel

ActiveRecord

ActiveResource

ActiveSupport

Railties

SHA-1

You can find an exhaustive list of changes on github. Along with the closed issues marked for v3.1.1.

Thanks to everyone!

07 Oct 2011 5:26pm GMT

21 Mar 2011

feedPlanet Perl

Planet Perl is going dormant

Planet Perl is going dormant. This will be the last post there for a while.

image from planet.perl.org

Why? There are better ways to get your Perl blog fix these days.

You might enjoy some of the following:

Will Planet Perl awaken again in the future? It might! The universe is a big place, filled with interesting places, people and things. You never know what might happen, so keep your towel handy.

21 Mar 2011 2:04am GMT

improving on my little wooden "miniatures"

A few years ago, I wrote about cheap wooden discs as D&D minis, and I've been using them ever since. They do a great job, and cost nearly nothing. For the most part, we've used a few for the PCs, marked with the characters' initials, and the rest for NPCs and enemies, usually marked with numbers.

With D&D 4E, we've tended to have combats with more and more varied enemies. (Minions are wonderful things.) Numbering has become insufficient. It's too hard to remember what numbers are what monster, and to keep initiative order separate from token numbers. In the past, I've colored a few tokens in with the red or green whiteboard markers, and that has been useful. So, this afternoon I found my old paints and painted six sets of five colors. (The black ones I'd already made with sharpies.)

D&D tokens: now in color

I'm not sure what I'll want next: either I'll want five more of each color or I'll want five more colors. More colors will require that I pick up some white paint, while more of those colors will only require that I re-match the secondary colors when mixing. I think I'll wait to see which I end up wanting during real combats.

These colored tokens should work together well with my previous post about using a whiteboard for combat overview. Like-type monsters will get one color, and will all get grouped to one slot on initiative. Last night, for example, the two halfling warriors were red and acted in the same initiative slot. The three halfling minions were unpainted, and acted in another, later slot. Only PCs get their own initiative.

I think that it did a good amount to speed up combat, and that's even when I totally forgot to bring the combat whiteboard (and the character sheets!) with me. Next time, we'll see how it works when it's all brought together.

21 Mar 2011 12:47am GMT

20 Mar 2011

feedPlanet Perl

Perl Vogue T-Shirts

Is Plack the new Black?In Pisa I gave a lightning talk about Perl Vogue. People enjoyed it and for a while I thought that it might actually turn into a project.

I won't though. It would just take far too much effort. And, besides, a couple of people have pointed out to be that the real Vogue are rather protective of their brand.

So it's not going to happen, I'm afraid. But as a subtle reminder of the ideas behind Perl Vogue I've created some t-shirts containing the article titles from the talk. You can get them from my Spreadshirt shop.

20 Mar 2011 12:02pm GMT