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 ...