Taus 8517eff0f7 Python: Fix bad performance
A few changes, all bundled together:

- We were getting a lot of magic applied to the predicates in the
  `ImportStar` module, and this was causing needless re-evaluation.
  To address this, the easiest solution was to simply cache the entire
  module.
- In order to separate this from the dataflow analysis and make it
  dependent only on control flow, `potentialImportStarBase` was changed
  to return a `ControlFlowNode`.
- `isDefinedLocally` was defined on control flow nodes, which meant we
  were duplicating a lot of tuples due to control flow splitting, to no
  actual benefit.

Finally, there was a really bad join in `isDefinedLocally` that was
fixed by separating out a helper predicate. This is a case where we
could use a three-way join, since the join between the `Scope`, the
`name` string and the `Name` is big no matter what.

If we join `scope_defines_name` with `n.getId()`, we'll get `Name`s
belonging to irrelevant scopes.

If we join `scope_defines_name` with the enclosing scope of the `Name`
`n`, then we'll get this also for `Name`s that don't share their `getId`
with the local variable defined in the scope.

If we join `n.getId()` with `n.getScope()...` then we'll get all
enclosing scopes for each `Name`.

The last of these is what we currently have. It's not terrible, but not
great either. (Though thankfully it's rare to have lots of enclosing
scopes.)
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CodeQL

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CodeQL: the libraries and queries that power security researchers around the world, as well as code scanning in GitHub Advanced Security
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