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- """Rope object analysis and inference package
- Rope makes some simplifying assumptions about a python program. It
- assumes that a program only performs assignments and function calls.
- Tracking assignments is simple and `PyName` objects handle that. The
- main problem is function calls. Rope uses these two approaches for
- obtaining call information:
- * Static object analysis: `rope.base.pycore.PyCore.analyze_module()`
- It can analyze modules to obtain information about functions. This
- is done by analyzing function calls in a module or scope. Currently
- SOA analyzes the scopes that are changed while saving or when the
- user asks to analyze a module. That is mainly because static
- analysis is time-consuming.
- * Dynamic object analysis: `rope.base.pycore.PyCore.run_module()`
- When you run a module or your testsuite, when DOA is enabled, it
- collects information about parameters passed to and objects returned
- from functions. The main problem with this approach is that it is
- quite slow; Not when looking up the information but when collecting
- them.
- An instance of `rope.base.oi.objectinfo.ObjectInfoManager` can be used
- for accessing these information. It saves the data in a
- `rope.base.oi.objectdb.ObjectDB` internally.
- Now if our objectdb does not know anything about a function and we
- need the value returned by it, static object inference, SOI, comes
- into play. It analyzes function body and tries to infer the object
- that is returned from it (we usually need the returned value for the
- given parameter objects).
- Rope might collect and store information for other `PyName`\s, too.
- For instance rope stores the object builtin containers hold.
- """
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