made the checks in CheckExact

zip() takes varargs. django passes 3 containers to it.

Fix speculations at module scope

Conflicts:
	src/runtime/objmodel.cpp

Closes #466

Add im_class field to BoxedInstanceMethod, implement instancemethodRepr

Add support for string interning

Handle map(None,...), exec with module.__dict__ as globals

Singleton hcls storage strategy

The storage strategy per-object is the same as NORMAL, but instead of having
immutable chains of hidden classes so that we can share them between instances,
a SINGLETON hcls is unique to the single object that it is for.  This means
that it can be mutable.

This has the advantage that we don't have to track all the parents
of the hidden class.  This is especially helpful since the cases that
it's used for (Python classes and modules) tend to have a large number
of attributes (>100 not uncommon).

We could also use the DICT_BACKED strategy for those cases, but compared to
DICT_BACKED, SINGLETON should have much better lookup performance since
it is patchpoint-compatible.  Adding new attributes is probably slower,
and deleting attributes is probably much slower, but I think those are
hopefully rare.

This cuts non-jit 'import pip' memory by 15%, from 113MB to 98MB.

Not only does this improve perfomance, but it somehow improves performance
consistency as well.

we could use this in much more places if performance and memory benchmarking shows it's an improvement.

import with globals

It's a little bit complicated due to the fact that
gdb has to be the parent so that it can have the permissions
to ptrace the process that segfaults.

imports apparently have to look at the globals scope in order
to determine how to handle relative imports and package references.

Sqlalchemy for some reason does this, and once we have this sqlalchemy
imports.

delete capi/float.cpp

I don't remember the original reasoning for having the separate capi/float.cpp,
and all the other runtime/ files have their CAPI methods inline.

workaround for __rdtscp for now

put back in the Timer-based stats I removed in the stats-timer branch…

put back in the Timer-based stats I removed in the stats-timer branch, and allow stat timers to be disabled separately from the rest of the stats (disable them by default.)

Stat timers

Each thread has a stack of timers (which should have automatic scope.)  pushing a timer
onto the stack pauses the currently running one to avoid double counting, and popping a
timer resumes the previous one.

also make sure we pause the current timer, and swap out the current stack of timers when
swapping to/from generator stacks, since otherwise pushes/pops won't line up and we hit
asserts in StatTimer.

Timers and StatTimers accumulate their durations in terms of CPU ticks, which are converted
to microseconds only at Stats::dump() time, calculated with our estimate of CPU frequency.
Needless to say, this only works when there is no CPU stepping/scaling.

There are some additions to the Timer class that allow us to get the start/end time so that
we can sync up StatTimers with them, if both are used in a given piece of code.

getCPUTicks() is only implemented using __rdtscp() at the moment, so won't work on anything
not recent relatively recent x86.

we accumulate total ticks during dumping and output both 'ticks_in_main' and 'ticks_all_timers',
which should be equal.

These happen if you never have run the makefile build,
which should become increasingly common.

I didn't bother testing that this doesn't break the makefile build.

fix the remaining subclass checks for list comparisons <, <=, >, >=

Reduce memory by not caching analysis passes

On the simple test of `pyston -c "import pip"`, it reduces memory
usage from 194MB to 153MB (20% of the memory previously was cached
analysis data).  It also increases our benchmark geomean by ~1%,
which isn't great, but I think we can get that back eventually and
I don't think it's worth blocking this memory improvement for that.