Resourceful Code Reuse

Reusing well-written, well-debugged, and well-tested code
improves productivity, code quality, and software configurability and
relieves pressure on software developers. When you organize your code
into self-contained modular units, you can use them as building blocks
for your future projects and share them with other programmers, if
needed. Understand the benefits and downsides of seven code reuse models
so you can confidently reuse code at any development stage. Create
static and dynamic libraries in C and Python, two of the most popular
modern programming languages. Adapt your code for the real world: deploy
shared functions remotely and build software that accesses them using
remote procedure calls.

Avoid the drawbacks and harness the
benefits associated with seven code reuse models. Create static and
dynamic libraries in C and Python, deploy shared functions remotely, and
build software that makes intelligent use of remote procedure calls. In
no time at all, you'll develop the confidence to reuse code at any
stage of real-world development.

This one-stop solution covers the
complete build cycle: editing, compiling, linking, and running a ready
program. Apply Linux/macOS power software development tools, such as ld,
ldd, ranlib, and nm, to construct and explore state-of-the-art function
libraries in C that could be linked with application-specific code
either permanently or for the duration of execution. Learn why Python
has modules for reuse and how they differ from C object files and
libraries. Understand the risks and other negative implications of
sharing and reuse. As a bonus, distill the dependencies between your
project's components and automate and optimize your build process with
the "make" utility.

Whether
you are an amateur coder or an experienced developer, become a more
productive and resourceful programmer by reusing previously written
code.

What You Need:

To compile and run the C
examples mentioned in the book, you need a decent C compiler (GCC is the
best, but Intel and Microsoft would probably work, too) and a set of C
development tools: maker (make), linker (ld), file, strip, ldd, and
ranlib. Again, the GNU development toolset works marvels; other toolsets
may or may not work. All examples in the book have been tested on a
Linux computer but will most likely work on macOS. For the Python
examples, a Python-3.x interpreter is all you want. No third-party
modules are required.