forked from mirrors/gecko-dev
6d154c1ed3
Vendoring wheels has three benefits: * There's far less files, so Firefox checkouts will be smaller. * It works around `zipp` not allowing `pip install` from extracted source `tar.gz` files. Now, we should be able to use the pip resolver against vendored packages, which will be needed for future mach virtualenv work. * `./mach vendor python` takes far less time to execute. Since we need the raw Python to be available to add to the `sys.path`, we extract the wheels before putting them in tree. Due to the structure of some wheels being less nested than of a source `tar.gz`, `common_virtualenv_packages` needed to be adjusted accordingly. `install_pip_package()` had to be tweaked as well since you can't `pip install` an extracted wheel. So, we "re-bundle" the wheel before installing from a vendored package. Replace python packages with wheels where possible This contains the vendoring changes caused by the last patch. For reviewing, there's a couple things to note: * A bunch of files are deleted, since there's generally less files in a wheel than in a source archive. * There's a new `.dist-info` directory for each extracted wheel, so expect roughly 5 or 6 new files for each wheel'd package. * There should be no source code changes other than moves from package names changing from having `-` to having `_`. Differential Revision: https://phabricator.services.mozilla.com/D116512
41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
# -*- coding: utf-8 -*-
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"""The optimizer tries to constant fold expressions and modify the AST
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in place so that it should be faster to evaluate.
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Because the AST does not contain all the scoping information and the
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compiler has to find that out, we cannot do all the optimizations we
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want. For example, loop unrolling doesn't work because unrolled loops
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would have a different scope. The solution would be a second syntax tree
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that stored the scoping rules.
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"""
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from . import nodes
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from .visitor import NodeTransformer
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def optimize(node, environment):
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"""The context hint can be used to perform an static optimization
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based on the context given."""
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optimizer = Optimizer(environment)
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return optimizer.visit(node)
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class Optimizer(NodeTransformer):
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def __init__(self, environment):
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self.environment = environment
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def generic_visit(self, node, *args, **kwargs):
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node = super(Optimizer, self).generic_visit(node, *args, **kwargs)
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# Do constant folding. Some other nodes besides Expr have
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# as_const, but folding them causes errors later on.
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if isinstance(node, nodes.Expr):
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try:
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return nodes.Const.from_untrusted(
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node.as_const(args[0] if args else None),
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lineno=node.lineno,
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environment=self.environment,
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)
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except nodes.Impossible:
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pass
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return node
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