So you've installed Python from an official binary installer on python.org's Releases page, you've installed Xcode from the App Store and the Command Line Tools from Xcode, you've installed pip from its setup script. And now, you try to "pip-X.Y install pyobjc" and it fails with a whole slew of obscure error messages. 

An easy workaround: Don't

The official binary installer seems like the easy way to do things, but it's not. It's built to work with every version of OS X from 10.6 to 10.9. This means whenever you build a package, it will try to build that package to work with every version of OS X from 10.6 to 10.9. This is very hard to do—especially on a 10.8 or 10.9 machine with Xcode 5.

If you're planning to build applications for binary distribution with, e.g., py2app, and you want them to work on an older version of OS X than you have, then you need to get this working. (Although even then, you might be better off building Python exactly the way you want, instead of using the binary installation.) So far, I haven't been able to get this working with Xcode 5; I've been using an old machine that I don't update.

For almost everyone else, it's unnecessary wasted effort.

Python 2

If you're using Python 2, just stick with Apple's pre-installed 2.7.2. Having multiple 2.7 installations at the same time is already a huge headache, and the added problems with building packages… is it really worth it?

Python 3

While it may seem counter-intuitive, building it yourself makes everything easier, because you end up with a Python installation tailored to your build toolchain, not to the Python Mac build machine's toolchain.

And if you use Homebrew, building it yourself is just "brew install python3". Plus, you get setuptools and pip (that work with your system), and a newer sqlite3, real readline, gdbm, and a few other things you wouldn't have thought of.

When are they going to fix it?

I know that the pythonmac SIG are aware of the problem. In fact, the problem has been around for a long time; it's just that the workarounds they've used since 10.6 no longer work. I have no idea what they're planning to do about it. You might want to watch the pythonmac-sig mailing list for progress, or join in to help.

The problem

There are actually two problems.

gcc is gone

The official Python.org binaries are built with Apple's custom gcc-4.2, as supplied by Xcode 3.2.

Xcode 4 stopped supplying gcc-4.2, but offered a transitional compiler called llvm-gcc-4.2 (because it used a custom gcc-4.2 frontend hooked up to the llvm backend), and the toolchain came with wrappers named things like "gcc-4.2" and "g++-4.2" and so on. This actually had some problems building Python itself, but for building extension modules—even complex ones like numpy and pyobjc—you usually got away with it.

Xcode 5 dropped llvm-gcc-4.2 as well. Now, all you've got is clang. And, while "gcc" is a wrapper around clang, "gcc-4.2" does not exist at all. So, many extensions will just fail to build, because they're looking for a compiler named "gcc-4.2" (or a C++ compiler named "g++-4.2", or a linker frontend named "gcc-4.2", or…). The new compiler—which Apple calls "Apple LLVM 5.0 (clang-500.2.76) (based on LLVM 3.3svn)", just to make it impossible for anyone to refer to—does a much better job than llvm-gcc-4.2; if you can just get distutils to use it everywhere, everything pretty much just works.

In some cases, just passing "CC=clang CXX=clang++" environment variables to the build will work. You can get further by also adding "MAINCC=clang LINKCC=clang". Anything that needs to run a configure script will _still_ end up picking up gcc-4.2, however, and there may be similar issues with projects that first build a local distutils.cfg or similar.

One workaround is to edit  /Library/Frameworks/Python.framework/Versions/X.Y/lib/pythonX.Y/config-X.Ym/Makefile to fix all references to gcc and g++ to instead reference clang and clang++, then cross your fingers. This seems to work.

Alternatively, you could create a symlink, or a hardlink, from /usr/bin/gcc to /usr/local/bin/gcc-4.2, and likewise for g++, and cross your fingers even tighter. I haven't tried this.

10.8 is the oldest SDK

We've always been at war with Eastasia, and we've always been compiling for 10.8. There has never been an older SDK. References in your configure scripts to MacOS10.6.sdk are errors.

Many extensions will build just fine without the 10.6 SDK—but they'll quietly build for your native system, which defeats the purpose of building a redistributable application.

You can still find the 10.6 and 10.7 SDKs in older Xcode packages from Apple (and, for 10.7, you can download the latest Command Line Tools for Lion, which is just the SDK slightly repackaged). Then you can copy them into /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/ and… whether they'll actually work, I don't know. They won't have an SDKSettings.plist file. They won't be registered in the list of known SDKs; the GUI and xcodebuild certainly won't find them, but maybe specifying them on the command line will work. Or maybe only if you use absolute paths.

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It's been more than a decade since Typical Programmer Greg Jorgensen taught the word about Abject-Oriented Programming.

Much of what he said still applies, but other things have changed. Languages in the Abject-Oriented space have been borrowing ideas from another paradigm entirely—and then everyone realized that languages like Python, Ruby, and JavaScript had been doing it for years and just hadn't noticed (because these languages do not require you to declare what you're doing, or even to know what you're doing). Meanwhile, new hybrid languages borrow freely from both paradigms.

This other paradigm—which is actually older, but was largely constrained to university basements until recent years—is called Functional Addiction.

A Functional Addict is someone who regularly gets higher-order—sometimes they may even exhibit dependent types—but still manages to retain a job.

Retaining a job is of course the goal of all programming. This is why some of these new hybrid languages, like Rust, check all borrowing, from both paradigms, so extensively that you can make regular progress for months without ever successfully compiling your code, and your managers will appreciate that progress. After all, once it does compile, it will definitely work.

Closures

It's long been known that Closures are dual to Encapsulation.

As Abject-Oriented Programming explained, Encapsulation involves making all of your variables public, and ideally global, to let the rest of the code decide what should and shouldn't be private.

Closures, by contrast, are a way of referring to variables from outer scopes. And there is no scope more outer than global.

Immutability

One of the reasons Functional Addiction has become popular in recent years is that to truly take advantage of multi-core systems, you need immutable data, sometimes also called persistent data.

Instead of mutating a function to fix a bug, you should always make a new copy of that function. For example:

function getCustName(custID)
{
    custRec = readFromDB("customer", custID);
    fullname = custRec[1] + ' ' + custRec[2];
    return fullname;
}

When you discover that you actually wanted fields 2 and 3 rather than 1 and 2, it might be tempting to mutate the state of this function. But doing so is dangerous. The right answer is to make a copy, and then try to remember to use the copy instead of the original:

function getCustName(custID)
{
    custRec = readFromDB("customer", custID);
    fullname = custRec[1] + ' ' + custRec[2];
    return fullname;
}

function getCustName2(custID)
{
    custRec = readFromDB("customer", custID);
    fullname = custRec[2] + ' ' + custRec[3];
    return fullname;
}

This means anyone still using the original function can continue to reference the old code, but as soon as it's no longer needed, it will be automatically garbage collected. (Automatic garbage collection isn't free, but it can be outsourced cheaply.)

Higher-Order Functions

In traditional Abject-Oriented Programming, you are required to give each function a name. But over time, the name of the function may drift away from what it actually does, making it as misleading as comments. Experience has shown that people will only keep once copy of their information up to date, and the CHANGES.TXT file is the right place for that.

Higher-Order Functions can solve this problem:

function []Functions = [
    lambda(custID) {
        custRec = readFromDB("customer", custID);
        fullname = custRec[1] + ' ' + custRec[2];
        return fullname;
    },
    lambda(custID) {
        custRec = readFromDB("customer", custID);
        fullname = custRec[2] + ' ' + custRec[3];
        return fullname;
    },
]

Now you can refer to this functions by order, so there's no need for names.

Parametric Polymorphism

Traditional languages offer Abject-Oriented Polymorphism and Ad-Hoc Polymorphism (also known as Overloading), but better languages also offer Parametric Polymorphism.

The key to Parametric Polymorphism is that the type of the output can be determined from the type of the inputs via Algebra. For example:

function getCustData(custId, x)
{
    if (x == int(x)) {
        custRec = readFromDB("customer", custId);
        fullname = custRec[1] + ' ' + custRec[2];
        return int(fullname);
    } else if (x.real == 0) {
        custRec = readFromDB("customer", custId);
        fullname = custRec[1] + ' ' + custRec[2];
        return double(fullname);
    } else {
        custRec = readFromDB("customer", custId);
        fullname = custRec[1] + ' ' + custRec[2];
        return complex(fullname);
    }
}

Notice that we've called the variable x. This is how you know you're using Algebraic Data Types. The names y, z, and sometimes w are also Algebraic.

Type Inference

Languages that enable Functional Addiction often feature Type Inference. This means that the compiler can infer your typing without you having to be explicit:


function getCustName(custID)
{
    // WARNING: Make sure the DB is locked here or
    custRec = readFromDB("customer", custID);
    fullname = custRec[1] + ' ' + custRec[2];
    return fullname;
}

We didn't specify what will happen if the DB is not locked. And that's fine, because the compiler will figure it out and insert code that corrupts the data, without us needing to tell it to!

By contrast, most Abject-Oriented languages are either nominally typed—meaning that you give names to all of your types instead of meanings—or dynamically typed—meaning that your variables are all unique individuals that can accomplish anything if they try.

Memoization

Memoization means caching the results of a function call:

function getCustName(custID)
{
    if (custID == 3) { return "John Smith"; }
    custRec = readFromDB("customer", custID);
    fullname = custRec[1] + ' ' + custRec[2];
    return fullname;
}

Non-Strictness

Non-Strictness is often confused with Laziness, but in fact Laziness is just one kind of Non-Strictness. Here's an example that compares two different forms of Non-Strictness:

/****************************************
*
* TO DO:
*
* get tax rate for the customer state
* eventually from some table
*
****************************************/
// function lazyTaxRate(custId) {}

function callByNameTextRate(custId)
{
    /****************************************
    *
    * TO DO:
    *
    * get tax rate for the customer state
    * eventually from some table
    *
    ****************************************/
}

Both are Non-Strict, but the second one forces the compiler to actually compile the function just so we can Call it By Name. This causes code bloat. The Lazy version will be smaller and faster. Plus, Lazy programming allows us to create infinite recursion without making the program hang:

/****************************************
*
* TO DO:
*
* get tax rate for the customer state
* eventually from some table
*
****************************************/
// function lazyTaxRateRecursive(custId) { lazyTaxRateRecursive(custId); }

Laziness is often combined with Memoization:

function getCustName(custID)
{
    // if (custID == 3) { return "John Smith"; }
    custRec = readFromDB("customer", custID);
    fullname = custRec[1] + ' ' + custRec[2];
    return fullname;
}

Outside the world of Functional Addicts, this same technique is often called Test-Driven Development. If enough tests can be embedded in the code to achieve 100% coverage, or at least a decent amount, your code is guaranteed to be safe. But because the tests are not compiled and executed in the normal run, or indeed ever, they don't affect performance or correctness.

Conclusion

Many people claim that the days of Abject-Oriented Programming are over. But this is pure hype. Functional Addiction and Abject Orientation are not actually at odds with each other, but instead complement each other.
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