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20.2 C Embedding API Overview
The first thing you should know about Python's embedded-call API is that it is less structured than the extension interfaces. Embedding Python in C may require a bit more creativity on your part than extending; you must pick tools from a general collection of calls to implement the Python integration, rather than coding to a boilerplate structure. The upside of this loose structure is that programs can combine embedding calls and strategies to build up arbitrary integration architectures.
The lack of a more rigid model for embedding is largely the result of a less clear-cut goal. When extending Python, there is a distinct separation for Python and C responsibilities and a clear structure for the integration. C modules and types are required to fit the Python module/type model by conforming to standard extension structures. This makes the integration seamless for Python clients: C extensions look like Python objects and handle most of the work.
But when Python is embedded, the structure isn't as obvious; because C is the enclosing level, there is no clear way to know what model the embedded Python code should fit. C may want to run objects fetched from modules, strings fetched from files or parsed out of documents, and so on. Instead of deciding what C can and cannot do, Python provides a collection of general embedding interface tools, which you use and structure according to your embedding goals.
Most of these tools correspond to tools available to Python programs. Table 20-1 lists some of the more common API calls used for embedding, and their Python equivalents. In general, if you can figure out how to accomplish your embedding goals in pure Python code, you can probably find C API tools that achieve the same results.
Because embedding relies on API call selection, though, becoming familiar with the Python C API is fundamental to the embedding task. This chapter presents a handful of representative embedding examples and discusses common API calls, but does not provide a comprehensive list of all tools in the API. Once you've mastered the examples here, you'll probably need to consult Python's integration manuals for more details on available calls in this domain. The most recent Python release comes with two standard manuals for C/C++ integration programmers: Extending and Embedding, an integration tutorial; and Python/C API, the Python runtime library reference.
You can find these manuals on the book's CD (view CD-ROM content online at http://examples.oreilly.com/python2), or fetch their most recent releases at http://www.python.org. Beyond this chapter, these manuals are likely to be your best resource for up-to-date and complete Python API tool information.
20.2.1 What Is Embedded Code?
Before we jump into details, let's get a handle on some of the core ideas in the embedding domain. When this book speaks of "embedded" Python code, it simply means any Python program structure that can be executed from C. Generally speaking, embedded Python code can take a variety of forms:
The Python binary library is usually what is physically embedded in the C program; the actual Python code run from C can come from a wide variety of sources:
Registration is a technique commonly used in callback scenarios that we will explore in more detail later in this chapter. But especially for strings of code, there are as many possible sources as there are for C character strings. For example, C programs can construct arbitrary Python code dynamically by building and running strings.
Finally, once you have some Python code to run, you need a way to communicate with it: the Python code may need to use inputs passed in from the C layer, and may want to generate outputs to communicate results back to C. In fact, embedding generally becomes interesting only when the embedded code has access to the enclosing C layer. Usually, the form of the embedded code suggests its communication mediums:
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