Skip to main content

Creating a single static or shared library (dylib) that supports multiple arches

OSX has a nice tool that takes static, dylibs, or shared libraries for different system architectures and can pack them into a single library that can be loaded on different hardware called `lipo`.

Not sure where the name comes from (I see people call the libraries it creates `fat` libraries but lipo is supposed to remove fat? Idk). Anyways it's simple to use:

lipo -output <file> -create <lib/arch1.dylib> <lib/arch2.dylib> # etc...

Use man lipo for more info

LIPO(1)                                                                LIPO(1)

NAME
       lipo - create or operate on universal files

SYNOPSIS
       lipo  [-info]  [-detailed_info]  [-arch  arch_type  input_file]  ...  [
       input_file] ...  [-arch_blank arch_type]  [-create]  [-thin  arch_type]
       [-replace  arch_type  filename] ...  [-remove arch_type] ...  [-extract
       arch_type]  ...    [-extract_family   arch_type]   ...    [-verify_arch
       arch_type ...]  [-output output_file] [-segalign arch_type value] ...

DESCRIPTION
       The  lipo command creates or operates on ``universal'' (multi-architec-
       ture) files.  It only ever produces one output file, and  never  alters
       the  input  file.   The  operations that lipo performs are: listing the
       architecture types in a universal file;  creating  a  single  universal
       file from one or more input files; thinning out a single universal file
       to one specified architecture type; and extracting,  replacing,  and/or
       removing architectures types from the input file to create a single new
       universal output file.



So for Python for iOS, the toolchain builds libraries for x86_64, i386, armv7, and arm64. To make this run on any device (iPhone or simulator) just run lipo and use that as the library. The os will load either one.

You can test which arches are packed in a file using the `file` command. Without it:


mbp:armv7 jrm$ file libffi.dylib
libffi.dylib: Mach-O dynamically linked shared library arm_v7


After running lipo:

mbp:Libraries jrm$ file libffi.dylib
libffi.dylib: Mach-O universal binary with 4 architectures: [i386: Mach-O dynamically linked shared library i386] [x86_64: Mach-O 64-bit dynamically linked shared library x86_64] [arm_v7: Mach-O dynamically linked shared library arm_v7] [arm64: Mach-O 64-bit dynamically linked shared library 
arm64]
libffi.dylib (for architecture i386): Mach-O dynamically linked shared library i386
libffi.dylib (for architecture x86_64): Mach-O 64-bit dynamically linked shared library x86_64
libffi.dylib (for architecture armv7): Mach-O dynamically linked shared library arm_v7
libffi.dylib (for architecture arm64): Mach-O 64-bit dynamically linked shared library arm64



You can also add and remove arches with the tool (for release you probably don't need the IAs). Cool, one step closer to a complete Python for iOS build system!

Happy coding!











Comments

Popular posts from this blog

Kivy vs React-Native for building cross platform mobile apps

I've built three apps now using Kivy and one with React-Native, just wanted to share my thoughts on both. Just a warning, I am strongly biased towards python and this is all based on opinion and experience and is thus worth what you pay for it. I don't claim to be an expert in either of these, just have worked with each for several months.  If something is incorrect I'd love to hear advice. Kivy Demo of one of the apps Pros: Nice to be able to run natively on the desktop WITHOUT a simulator Python is easy to work with Use (almost) any python library Very easy to create custom widgets Kivy properties and data binding just work. Way nicer than React's "state" / flux / redux whatever you want to call it (stupid?).  Native interfaces (pyjnius) and (pyobjc) Runs and feels pretty smooth Cons: Default widget toolkit looks like Android 4.4. Requiring you use your own widgets or a theming kit like KivyMD  if styling bothers you Creating dy

Control Systems in Python - Part 1 - Bode and Step Response

I hate matlab with passion, yet sadly, nearly everyone uses it.  I'm a fan of Python and open source stuff so here's a simple article on how to do some common control systems stuff in Python. First we need to make sure the environment is setup. Install IPython (or you can use any other python shell, but a unicode supported shell is preferred) Install python-control (numpy, scipy) Install sympy These should do if your on Ubuntu/debian: sudo apt - get install python - sympy python-numpy python-scipy python-matplotlib ipython Then you need to install python control, see How to download and install python-control Intro to using Sympy Open ipython and run the following: import sympy from sympy import * sympy.init_printing() s = Symbol('s') Now we can do things like define transfer functions using the symbolic variable s. We can expand the bottom using the .simplify() method and we can do something more complex like... which is really nice because it

Control Systems in Python - Part 2 - Routh Hurwitz

In my last post Control Systems in Python Part 1 , i described how to setup and use Python for doing some basic plotting of transfer functions. One of the biggest benefits of using sympy vs numeric packages like matlab/numpy/scipy is the fact that you can use symbolic variables. This post includes a function for computing the Routh Hurwitz table (Note: It does not work for row's of zeros). Lets do my control systems design homework problem together :) (Warning: I have not verified if this answer is right so please correct me if it’s not!) The Problem The problem is DP 9.11 from Dorf & Bishop’s Modern Control Systems. ISBN 0136024580. Basically we have to design a controller to compensate for a system with a time delay. The controller is: And the system is: First we approximate the exponential term with a 2nd order polynomial using pade(0.4,2) such that: Thus the approximated system is: Using frequency response methods, design the controller so that th