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Trivial cleanups following bpo-31370 (#3649)

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* Trivial cleanups following bpo-31370

* Also cleanup the "importlib._bootstrap_external" module
This commit is contained in:
Antoine Pitrou 2017-09-18 23:50:44 +02:00 • committed by GitHub
parent b43c4caf81
commit 88c60c9668
16 changed files with 171 additions and 209 deletions
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5
Lib/_pydecimal.py
View file

@ -431,10 +431,7 @@ _rounding_modes = (ROUND_DOWN, ROUND_HALF_UP, ROUND_HALF_EVEN, ROUND_CEILING,
##### Context Functions ################################################## ##### Context Functions ##################################################
# The getcontext() and setcontext() function manage access to a thread-local # The getcontext() and setcontext() function manage access to a thread-local
# current context. Py2.4 offers direct support for thread locals. If that # current context.
# is not available, use threading.current_thread() which is slower but will
# work for older Pythons. If threads are not part of the build, create a
# mock threading object with threading.local() returning the module namespace.
import threading import threading

14
Lib/importlib/_bootstrap.py
View file

@ -1121,25 +1121,13 @@ def _setup(sys_module, _imp_module):
# Directly load built-in modules needed during bootstrap. # Directly load built-in modules needed during bootstrap.
self_module = sys.modules[__name__] self_module = sys.modules[__name__]
for builtin_name in ('_warnings',): for builtin_name in ('_thread', '_warnings', '_weakref'):
if builtin_name not in sys.modules: if builtin_name not in sys.modules:
builtin_module = _builtin_from_name(builtin_name) builtin_module = _builtin_from_name(builtin_name)
else: else:
builtin_module = sys.modules[builtin_name] builtin_module = sys.modules[builtin_name]
setattr(self_module, builtin_name, builtin_module) setattr(self_module, builtin_name, builtin_module)
# Directly load the _thread module (needed during bootstrap).
try:
thread_module = _builtin_from_name('_thread')
except ImportError:
# Python was built without threads
thread_module = None
setattr(self_module, '_thread', thread_module)
# Directly load the _weakref module (needed during bootstrap).
weakref_module = _builtin_from_name('_weakref')
setattr(self_module, '_weakref', weakref_module)
def _install(sys_module, _imp_module): def _install(sys_module, _imp_module):
"""Install importers for builtin and frozen modules""" """Install importers for builtin and frozen modules"""

6
Lib/importlib/_bootstrap_external.py
View file

@ -1411,11 +1411,7 @@ def _setup(_bootstrap_module):
setattr(self_module, 'path_separators', ''.join(path_separators)) setattr(self_module, 'path_separators', ''.join(path_separators))
# Directly load the _thread module (needed during bootstrap). # Directly load the _thread module (needed during bootstrap).
try: thread_module = _bootstrap._builtin_from_name('_thread')
thread_module = _bootstrap._builtin_from_name('_thread')
except ImportError:
# Python was built without threads
thread_module = None
setattr(self_module, '_thread', thread_module) setattr(self_module, '_thread', thread_module)
# Directly load the _weakref module (needed during bootstrap). # Directly load the _weakref module (needed during bootstrap).

2
Lib/test/ssl_servers.py
View file

@ -2,13 +2,13 @@ import os
import sys import sys
import ssl import ssl
import pprint import pprint
import threading
import urllib.parse import urllib.parse
# Rename HTTPServer to _HTTPServer so as to avoid confusion with HTTPSServer. # Rename HTTPServer to _HTTPServer so as to avoid confusion with HTTPSServer.
from http.server import (HTTPServer as _HTTPServer, from http.server import (HTTPServer as _HTTPServer,
SimpleHTTPRequestHandler, BaseHTTPRequestHandler) SimpleHTTPRequestHandler, BaseHTTPRequestHandler)
from test import support from test import support
threading = support.import_module("threading")
here = os.path.dirname(__file__) here = os.path.dirname(__file__)

1
Lib/test/support/__init__.py
View file

@ -2060,7 +2060,6 @@ def threading_cleanup(*original_values):
def reap_threads(func): def reap_threads(func):
"""Use this function when threads are being used. This will """Use this function when threads are being used. This will
ensure that the threads are cleaned up even when the test fails. ensure that the threads are cleaned up even when the test fails.
If threading is unavailable this function does nothing.
""" """
@functools.wraps(func) @functools.wraps(func)
def decorator(*args): def decorator(*args):

3
Lib/test/test_httplib.py
View file

@ -5,6 +5,7 @@ import itertools
import os import os
import array import array
import socket import socket
import threading
import unittest import unittest
TestCase = unittest.TestCase TestCase = unittest.TestCase
@ -1077,8 +1078,6 @@ class BasicTest(TestCase):
def test_response_fileno(self): def test_response_fileno(self):
# Make sure fd returned by fileno is valid. # Make sure fd returned by fileno is valid.
threading = support.import_module("threading")
serv = socket.socket( serv = socket.socket(
socket.AF_INET, socket.SOCK_STREAM, socket.IPPROTO_TCP) socket.AF_INET, socket.SOCK_STREAM, socket.IPPROTO_TCP)
self.addCleanup(serv.close) self.addCleanup(serv.close)

2
Lib/test/test_idle.py
View file

@ -1,7 +1,7 @@
import unittest import unittest
from test.support import import_module from test.support import import_module
# Skip test if _thread or _tkinter wasn't built, if idlelib is missing, # Skip test if _tkinter wasn't built, if idlelib is missing,
# or if tcl/tk is not the 8.5+ needed for ttk widgets. # or if tcl/tk is not the 8.5+ needed for ttk widgets.
tk = import_module('tkinter') # imports _tkinter tk = import_module('tkinter') # imports _tkinter
if tk.TkVersion < 8.5: if tk.TkVersion < 8.5:

3
Lib/test/test_multiprocessing_main_handling.py
View file

@ -1,7 +1,6 @@
# tests __main__ module handling in multiprocessing # tests __main__ module handling in multiprocessing
from test import support from test import support
# Skip tests if _thread or _multiprocessing wasn't built. # Skip tests if _multiprocessing wasn't built.
support.import_module('_thread')
support.import_module('_multiprocessing') support.import_module('_multiprocessing')
import importlib import importlib

2
Lib/test/test_thread.py
View file

@ -2,7 +2,7 @@ import os
import unittest import unittest
import random import random
from test import support from test import support
thread = support.import_module('_thread') import _thread as thread
import time import time
import sys import sys
import weakref import weakref

2
Lib/test/test_threadsignals.py
View file

@ -5,7 +5,7 @@ import signal
import os import os
import sys import sys
from test import support from test import support
thread = support.import_module('_thread') import _thread as thread
import time import time
if (sys.platform[:3] == 'win'): if (sys.platform[:3] == 'win'):

1
Lib/test/test_tools/test_sundry.py
View file

@ -40,7 +40,6 @@ class TestSundryScripts(unittest.TestCase):
for name in self.windows_only: for name in self.windows_only:
import_tool(name) import_tool(name)
@unittest.skipIf(not support.threading, "test requires _thread module")
def test_analyze_dxp_import(self): def test_analyze_dxp_import(self):
if hasattr(sys, 'getdxp'): if hasattr(sys, 'getdxp'):
import_tool('analyze_dxp') import_tool('analyze_dxp')

2
Lib/test/test_winreg.py
View file

@ -4,7 +4,7 @@
import os, sys, errno import os, sys, errno
import unittest import unittest
from test import support from test import support
threading = support.import_module("threading") import threading
from platform import machine from platform import machine
# Do this first so test will be skipped if module doesn't exist # Do this first so test will be skipped if module doesn't exist

2
Lib/test/test_wsgiref.py
View file

@ -18,6 +18,7 @@ import os
import re import re
import signal import signal
import sys import sys
import threading
import unittest import unittest
@ -253,7 +254,6 @@ class IntegrationTests(TestCase):
# BaseHandler._write() and _flush() have to write all data, even if # BaseHandler._write() and _flush() have to write all data, even if
# it takes multiple send() calls. Test this by interrupting a send() # it takes multiple send() calls. Test this by interrupting a send()
# call with a Unix signal. # call with a Unix signal.
threading = support.import_module("threading")
pthread_kill = support.get_attribute(signal, "pthread_kill") pthread_kill = support.get_attribute(signal, "pthread_kill")
def app(environ, start_response): def app(environ, start_response):

8
Lib/test/test_xmlrpc.py
View file

@ -1175,13 +1175,7 @@ class GzipUtilTestCase(unittest.TestCase):
class ServerProxyTestCase(unittest.TestCase): class ServerProxyTestCase(unittest.TestCase):
def setUp(self): def setUp(self):
unittest.TestCase.setUp(self) unittest.TestCase.setUp(self)
if threading: self.url = URL
self.url = URL
else:
# Without threading, http_server() and http_multi_server() will not
# be executed and URL is still equal to None. 'http://' is a just
# enough to choose the scheme (HTTP)
self.url = 'http://'
def test_close(self): def test_close(self):
p = xmlrpclib.ServerProxy(self.url) p = xmlrpclib.ServerProxy(self.url)

185
Python/importlib.h
View file

@ -1707,8 +1707,8 @@ const unsigned char _Py_M__importlib[] = {
0,0,0,114,11,0,0,0,218,18,95,98,117,105,108,116, 0,0,0,114,11,0,0,0,218,18,95,98,117,105,108,116,
105,110,95,102,114,111,109,95,110,97,109,101,66,4,0,0, 105,110,95,102,114,111,109,95,110,97,109,101,66,4,0,0,
115,8,0,0,0,0,1,10,1,8,1,12,1,114,197,0, 115,8,0,0,0,0,1,10,1,8,1,12,1,114,197,0,
0,0,99,2,0,0,0,0,0,0,0,12,0,0,0,12, 0,0,99,2,0,0,0,0,0,0,0,10,0,0,0,5,
0,0,0,67,0,0,0,115,244,0,0,0,124,1,97,0, 0,0,0,67,0,0,0,115,174,0,0,0,124,1,97,0,
124,0,97,1,116,2,116,1,131,1,125,2,120,86,116,1, 124,0,97,1,116,2,116,1,131,1,125,2,120,86,116,1,
106,3,160,4,161,0,68,0,93,72,92,2,125,3,125,4, 106,3,160,4,161,0,68,0,93,72,92,2,125,3,125,4,
116,5,124,4,124,2,131,2,114,28,124,3,116,1,106,6, 116,5,124,4,124,2,131,2,114,28,124,3,116,1,106,6,
@ -1719,101 +1719,94 @@ const unsigned char _Py_M__importlib[] = {
100,5,68,0,93,46,125,8,124,8,116,1,106,3,107,7, 100,5,68,0,93,46,125,8,124,8,116,1,106,3,107,7,
114,144,116,13,124,8,131,1,125,9,110,10,116,1,106,3, 114,144,116,13,124,8,131,1,125,9,110,10,116,1,106,3,
124,8,25,0,125,9,116,14,124,7,124,8,124,9,131,3, 124,8,25,0,125,9,116,14,124,7,124,8,124,9,131,3,
1,0,113,120,87,0,121,12,116,13,100,2,131,1,125,10, 1,0,113,120,87,0,100,4,83,0,41,6,122,250,83,101,
87,0,110,24,4,0,116,15,107,10,114,206,1,0,1,0, 116,117,112,32,105,109,112,111,114,116,108,105,98,32,98,121,
1,0,100,3,125,10,89,0,110,2,88,0,116,14,124,7, 32,105,109,112,111,114,116,105,110,103,32,110,101,101,100,101,
100,2,124,10,131,3,1,0,116,13,100,4,131,1,125,11, 100,32,98,117,105,108,116,45,105,110,32,109,111,100,117,108,
116,14,124,7,100,4,124,11,131,3,1,0,100,3,83,0, 101,115,32,97,110,100,32,105,110,106,101,99,116,105,110,103,
41,6,122,250,83,101,116,117,112,32,105,109,112,111,114,116, 32,116,104,101,109,10,32,32,32,32,105,110,116,111,32,116,
108,105,98,32,98,121,32,105,109,112,111,114,116,105,110,103, 104,101,32,103,108,111,98,97,108,32,110,97,109,101,115,112,
32,110,101,101,100,101,100,32,98,117,105,108,116,45,105,110, 97,99,101,46,10,10,32,32,32,32,65,115,32,115,121,115,
32,109,111,100,117,108,101,115,32,97,110,100,32,105,110,106, 32,105,115,32,110,101,101,100,101,100,32,102,111,114,32,115,
101,99,116,105,110,103,32,116,104,101,109,10,32,32,32,32, 121,115,46,109,111,100,117,108,101,115,32,97,99,99,101,115,
105,110,116,111,32,116,104,101,32,103,108,111,98,97,108,32, 115,32,97,110,100,32,95,105,109,112,32,105,115,32,110,101,
110,97,109,101,115,112,97,99,101,46,10,10,32,32,32,32, 101,100,101,100,32,116,111,32,108,111,97,100,32,98,117,105,
65,115,32,115,121,115,32,105,115,32,110,101,101,100,101,100, 108,116,45,105,110,10,32,32,32,32,109,111,100,117,108,101,
32,102,111,114,32,115,121,115,46,109,111,100,117,108,101,115, 115,44,32,116,104,111,115,101,32,116,119,111,32,109,111,100,
32,97,99,99,101,115,115,32,97,110,100,32,95,105,109,112, 117,108,101,115,32,109,117,115,116,32,98,101,32,101,120,112,
32,105,115,32,110,101,101,100,101,100,32,116,111,32,108,111, 108,105,99,105,116,108,121,32,112,97,115,115,101,100,32,105,
97,100,32,98,117,105,108,116,45,105,110,10,32,32,32,32, 110,46,10,10,32,32,32,32,114,20,0,0,0,114,167,0,
109,111,100,117,108,101,115,44,32,116,104,111,115,101,32,116, 0,0,114,56,0,0,0,78,41,3,114,20,0,0,0,114,
119,111,32,109,111,100,117,108,101,115,32,109,117,115,116,32, 167,0,0,0,114,56,0,0,0,41,15,114,49,0,0,0,
98,101,32,101,120,112,108,105,99,105,116,108,121,32,112,97, 114,14,0,0,0,114,13,0,0,0,114,80,0,0,0,218,
115,115,101,100,32,105,110,46,10,10,32,32,32,32,114,167, 5,105,116,101,109,115,114,171,0,0,0,114,70,0,0,0,
0,0,0,114,20,0,0,0,78,114,56,0,0,0,41,1, 114,142,0,0,0,114,76,0,0,0,114,152,0,0,0,114,
114,167,0,0,0,41,16,114,49,0,0,0,114,14,0,0, 129,0,0,0,114,134,0,0,0,114,1,0,0,0,114,197,
0,114,13,0,0,0,114,80,0,0,0,218,5,105,116,101, 0,0,0,114,5,0,0,0,41,10,218,10,115,121,115,95,
109,115,114,171,0,0,0,114,70,0,0,0,114,142,0,0, 109,111,100,117,108,101,218,11,95,105,109,112,95,109,111,100,
0,114,76,0,0,0,114,152,0,0,0,114,129,0,0,0, 117,108,101,90,11,109,111,100,117,108,101,95,116,121,112,101,
114,134,0,0,0,114,1,0,0,0,114,197,0,0,0,114, 114,15,0,0,0,114,84,0,0,0,114,94,0,0,0,114,
5,0,0,0,114,71,0,0,0,41,12,218,10,115,121,115, 83,0,0,0,90,11,115,101,108,102,95,109,111,100,117,108,
95,109,111,100,117,108,101,218,11,95,105,109,112,95,109,111, 101,90,12,98,117,105,108,116,105,110,95,110,97,109,101,90,
100,117,108,101,90,11,109,111,100,117,108,101,95,116,121,112, 14,98,117,105,108,116,105,110,95,109,111,100,117,108,101,114,
101,114,15,0,0,0,114,84,0,0,0,114,94,0,0,0,
114,83,0,0,0,90,11,115,101,108,102,95,109,111,100,117,
108,101,90,12,98,117,105,108,116,105,110,95,110,97,109,101,
90,14,98,117,105,108,116,105,110,95,109,111,100,117,108,101,
90,13,116,104,114,101,97,100,95,109,111,100,117,108,101,90,
14,119,101,97,107,114,101,102,95,109,111,100,117,108,101,114,
10,0,0,0,114,10,0,0,0,114,11,0,0,0,218,6, 10,0,0,0,114,10,0,0,0,114,11,0,0,0,218,6,
95,115,101,116,117,112,73,4,0,0,115,50,0,0,0,0, 95,115,101,116,117,112,73,4,0,0,115,36,0,0,0,0,
9,4,1,4,3,8,1,20,1,10,1,10,1,6,1,10, 9,4,1,4,3,8,1,20,1,10,1,10,1,6,1,10,
1,6,2,2,1,10,1,14,3,10,1,10,1,10,1,10, 1,6,2,2,1,10,1,14,3,10,1,10,1,10,1,10,
2,10,1,16,3,2,1,12,1,14,2,10,1,12,3,8, 2,10,1,114,201,0,0,0,99,2,0,0,0,0,0,0,
1,114,201,0,0,0,99,2,0,0,0,0,0,0,0,2, 0,2,0,0,0,3,0,0,0,67,0,0,0,115,38,0,
0,0,0,3,0,0,0,67,0,0,0,115,38,0,0,0, 0,0,116,0,124,0,124,1,131,2,1,0,116,1,106,2,
116,0,124,0,124,1,131,2,1,0,116,1,106,2,160,3, 160,3,116,4,161,1,1,0,116,1,106,2,160,3,116,5,
116,4,161,1,1,0,116,1,106,2,160,3,116,5,161,1, 161,1,1,0,100,1,83,0,41,2,122,48,73,110,115,116,
1,0,100,1,83,0,41,2,122,48,73,110,115,116,97,108, 97,108,108,32,105,109,112,111,114,116,101,114,115,32,102,111,
108,32,105,109,112,111,114,116,101,114,115,32,102,111,114,32, 114,32,98,117,105,108,116,105,110,32,97,110,100,32,102,114,
98,117,105,108,116,105,110,32,97,110,100,32,102,114,111,122, 111,122,101,110,32,109,111,100,117,108,101,115,78,41,6,114,
101,110,32,109,111,100,117,108,101,115,78,41,6,114,201,0, 201,0,0,0,114,14,0,0,0,114,166,0,0,0,114,110,
0,0,114,14,0,0,0,114,166,0,0,0,114,110,0,0, 0,0,0,114,142,0,0,0,114,152,0,0,0,41,2,114,
0,114,142,0,0,0,114,152,0,0,0,41,2,114,199,0, 199,0,0,0,114,200,0,0,0,114,10,0,0,0,114,10,
0,0,114,200,0,0,0,114,10,0,0,0,114,10,0,0, 0,0,0,114,11,0,0,0,218,8,95,105,110,115,116,97,
0,114,11,0,0,0,218,8,95,105,110,115,116,97,108,108, 108,108,108,4,0,0,115,6,0,0,0,0,2,10,2,12,
120,4,0,0,115,6,0,0,0,0,2,10,2,12,1,114, 1,114,202,0,0,0,99,0,0,0,0,0,0,0,0,1,
202,0,0,0,99,0,0,0,0,0,0,0,0,1,0,0, 0,0,0,4,0,0,0,67,0,0,0,115,32,0,0,0,
0,4,0,0,0,67,0,0,0,115,32,0,0,0,100,1, 100,1,100,2,108,0,125,0,124,0,97,1,124,0,160,2,
100,2,108,0,125,0,124,0,97,1,124,0,160,2,116,3, 116,3,106,4,116,5,25,0,161,1,1,0,100,2,83,0,
106,4,116,5,25,0,161,1,1,0,100,2,83,0,41,3, 41,3,122,57,73,110,115,116,97,108,108,32,105,109,112,111,
122,57,73,110,115,116,97,108,108,32,105,109,112,111,114,116, 114,116,101,114,115,32,116,104,97,116,32,114,101,113,117,105,
101,114,115,32,116,104,97,116,32,114,101,113,117,105,114,101, 114,101,32,101,120,116,101,114,110,97,108,32,102,105,108,101,
32,101,120,116,101,114,110,97,108,32,102,105,108,101,115,121, 115,121,115,116,101,109,32,97,99,99,101,115,115,114,19,0,
115,116,101,109,32,97,99,99,101,115,115,114,19,0,0,0, 0,0,78,41,6,218,26,95,102,114,111,122,101,110,95,105,
78,41,6,218,26,95,102,114,111,122,101,110,95,105,109,112, 109,112,111,114,116,108,105,98,95,101,120,116,101,114,110,97,
111,114,116,108,105,98,95,101,120,116,101,114,110,97,108,114, 108,114,116,0,0,0,114,202,0,0,0,114,14,0,0,0,
116,0,0,0,114,202,0,0,0,114,14,0,0,0,114,80, 114,80,0,0,0,114,1,0,0,0,41,1,114,203,0,0,
0,0,0,114,1,0,0,0,41,1,114,203,0,0,0,114, 0,114,10,0,0,0,114,10,0,0,0,114,11,0,0,0,
10,0,0,0,114,10,0,0,0,114,11,0,0,0,218,27, 218,27,95,105,110,115,116,97,108,108,95,101,120,116,101,114,
95,105,110,115,116,97,108,108,95,101,120,116,101,114,110,97, 110,97,108,95,105,109,112,111,114,116,101,114,115,116,4,0,
108,95,105,109,112,111,114,116,101,114,115,128,4,0,0,115, 0,115,6,0,0,0,0,3,8,1,4,1,114,204,0,0,
6,0,0,0,0,3,8,1,4,1,114,204,0,0,0,41, 0,41,2,78,78,41,1,78,41,2,78,114,19,0,0,0,
2,78,78,41,1,78,41,2,78,114,19,0,0,0,41,51, 41,51,114,3,0,0,0,114,116,0,0,0,114,12,0,0,
114,3,0,0,0,114,116,0,0,0,114,12,0,0,0,114, 0,114,16,0,0,0,114,51,0,0,0,114,29,0,0,0,
16,0,0,0,114,51,0,0,0,114,29,0,0,0,114,36, 114,36,0,0,0,114,17,0,0,0,114,18,0,0,0,114,
0,0,0,114,17,0,0,0,114,18,0,0,0,114,41,0, 41,0,0,0,114,42,0,0,0,114,45,0,0,0,114,57,
0,0,114,42,0,0,0,114,45,0,0,0,114,57,0,0, 0,0,0,114,59,0,0,0,114,69,0,0,0,114,75,0,
0,114,59,0,0,0,114,69,0,0,0,114,75,0,0,0, 0,0,114,78,0,0,0,114,85,0,0,0,114,96,0,0,
114,78,0,0,0,114,85,0,0,0,114,96,0,0,0,114, 0,114,97,0,0,0,114,103,0,0,0,114,79,0,0,0,
97,0,0,0,114,103,0,0,0,114,79,0,0,0,114,129, 114,129,0,0,0,114,134,0,0,0,114,137,0,0,0,114,
0,0,0,114,134,0,0,0,114,137,0,0,0,114,92,0, 92,0,0,0,114,81,0,0,0,114,140,0,0,0,114,141,
0,0,114,81,0,0,0,114,140,0,0,0,114,141,0,0, 0,0,0,114,82,0,0,0,114,142,0,0,0,114,152,0,
0,114,82,0,0,0,114,142,0,0,0,114,152,0,0,0, 0,0,114,157,0,0,0,114,163,0,0,0,114,165,0,0,
114,157,0,0,0,114,163,0,0,0,114,165,0,0,0,114, 0,114,170,0,0,0,114,174,0,0,0,90,15,95,69,82,
170,0,0,0,114,174,0,0,0,90,15,95,69,82,82,95, 82,95,77,83,71,95,80,82,69,70,73,88,114,176,0,0,
77,83,71,95,80,82,69,70,73,88,114,176,0,0,0,114, 0,114,179,0,0,0,218,6,111,98,106,101,99,116,114,180,
179,0,0,0,218,6,111,98,106,101,99,116,114,180,0,0, 0,0,0,114,181,0,0,0,114,182,0,0,0,114,189,0,
0,114,181,0,0,0,114,182,0,0,0,114,189,0,0,0, 0,0,114,193,0,0,0,114,196,0,0,0,114,197,0,0,
114,193,0,0,0,114,196,0,0,0,114,197,0,0,0,114, 0,114,201,0,0,0,114,202,0,0,0,114,204,0,0,0,
201,0,0,0,114,202,0,0,0,114,204,0,0,0,114,10, 114,10,0,0,0,114,10,0,0,0,114,10,0,0,0,114,
0,0,0,114,10,0,0,0,114,10,0,0,0,114,11,0, 11,0,0,0,218,8,60,109,111,100,117,108,101,62,25,0,
0,0,218,8,60,109,111,100,117,108,101,62,25,0,0,0, 0,0,115,96,0,0,0,4,0,4,2,8,8,8,8,4,
115,96,0,0,0,4,0,4,2,8,8,8,8,4,2,4, 2,4,3,16,4,14,68,14,21,14,16,8,37,8,17,8,
3,16,4,14,68,14,21,14,16,8,37,8,17,8,11,14, 11,14,8,8,11,8,12,8,16,8,36,14,27,14,101,16,
8,8,11,8,12,8,16,8,36,14,27,14,101,16,26,10, 26,10,45,14,60,8,17,8,17,8,24,8,29,8,23,8,
45,14,60,8,17,8,17,8,24,8,29,8,23,8,15,14, 15,14,73,14,77,14,13,8,9,8,9,10,47,8,16,4,
73,14,77,14,13,8,9,8,9,10,47,8,16,4,1,8, 1,8,2,8,27,6,3,8,16,10,15,8,31,8,27,18,
2,8,27,6,3,8,16,10,15,8,31,8,27,18,35,8, 35,8,7,8,35,8,8,
7,8,47,8,8,
}; };

142
Python/importlib_external.h
View file

@ -2289,7 +2289,7 @@ const unsigned char _Py_M__importlib_external[] = {
0,114,159,0,0,0,80,5,0,0,115,8,0,0,0,0, 0,114,159,0,0,0,80,5,0,0,115,8,0,0,0,0,
5,12,1,8,1,8,1,114,159,0,0,0,99,1,0,0, 5,12,1,8,1,8,1,114,159,0,0,0,99,1,0,0,
0,0,0,0,0,12,0,0,0,12,0,0,0,67,0,0, 0,0,0,0,0,12,0,0,0,12,0,0,0,67,0,0,
0,115,188,1,0,0,124,0,97,0,116,0,106,1,97,1, 0,115,156,1,0,0,124,0,97,0,116,0,106,1,97,1,
116,0,106,2,97,2,116,1,106,3,116,4,25,0,125,1, 116,0,106,2,97,2,116,1,106,3,116,4,25,0,125,1,
120,56,100,26,68,0,93,48,125,2,124,2,116,1,106,3, 120,56,100,26,68,0,93,48,125,2,124,2,116,1,106,3,
107,7,114,58,116,0,160,5,124,2,161,1,125,3,110,10, 107,7,114,58,116,0,160,5,124,2,161,1,125,3,110,10,
@ -2306,17 +2306,15 @@ const unsigned char _Py_M__importlib_external[] = {
116,9,100,12,131,1,130,1,116,6,124,1,100,13,124,8, 116,9,100,12,131,1,130,1,116,6,124,1,100,13,124,8,
131,3,1,0,116,6,124,1,100,14,124,7,131,3,1,0, 131,3,1,0,116,6,124,1,100,14,124,7,131,3,1,0,
116,6,124,1,100,15,100,16,160,10,124,6,161,1,131,3, 116,6,124,1,100,15,100,16,160,10,124,6,161,1,131,3,
1,0,121,14,116,0,160,5,100,17,161,1,125,9,87,0, 1,0,116,0,160,5,100,17,161,1,125,9,116,6,124,1,
110,26,4,0,116,9,107,10,144,1,114,52,1,0,1,0, 100,17,124,9,131,3,1,0,116,0,160,5,100,18,161,1,
1,0,100,18,125,9,89,0,110,2,88,0,116,6,124,1, 125,10,116,6,124,1,100,18,124,10,131,3,1,0,124,5,
100,17,124,9,131,3,1,0,116,0,160,5,100,19,161,1, 100,7,107,2,144,1,114,88,116,0,160,5,100,19,161,1,
125,10,116,6,124,1,100,19,124,10,131,3,1,0,124,5, 125,11,116,6,124,1,100,20,124,11,131,3,1,0,116,6,
100,7,107,2,144,1,114,120,116,0,160,5,100,20,161,1, 124,1,100,21,116,11,131,0,131,3,1,0,116,12,160,13,
125,11,116,6,124,1,100,21,124,11,131,3,1,0,116,6,
124,1,100,22,116,11,131,0,131,3,1,0,116,12,160,13,
116,2,160,14,161,0,161,1,1,0,124,5,100,7,107,2, 116,2,160,14,161,0,161,1,1,0,124,5,100,7,107,2,
144,1,114,184,116,15,160,16,100,23,161,1,1,0,100,24, 144,1,114,152,116,15,160,16,100,22,161,1,1,0,100,23,
116,12,107,6,144,1,114,184,100,25,116,17,95,18,100,18, 116,12,107,6,144,1,114,152,100,24,116,17,95,18,100,25,
83,0,41,27,122,205,83,101,116,117,112,32,116,104,101,32, 83,0,41,27,122,205,83,101,116,117,112,32,116,104,101,32,
112,97,116,104,45,98,97,115,101,100,32,105,109,112,111,114, 112,97,116,104,45,98,97,115,101,100,32,105,109,112,111,114,
116,101,114,115,32,102,111,114,32,105,109,112,111,114,116,108, 116,101,114,115,32,102,111,114,32,105,109,112,111,114,116,108,
@ -2345,10 +2343,10 @@ const unsigned char _Py_M__importlib_external[] = {
111,114,116,108,105,98,32,114,101,113,117,105,114,101,115,32, 111,114,116,108,105,98,32,114,101,113,117,105,114,101,115,32,
112,111,115,105,120,32,111,114,32,110,116,114,3,0,0,0, 112,111,115,105,120,32,111,114,32,110,116,114,3,0,0,0,
114,27,0,0,0,114,23,0,0,0,114,32,0,0,0,90, 114,27,0,0,0,114,23,0,0,0,114,32,0,0,0,90,
7,95,116,104,114,101,97,100,78,90,8,95,119,101,97,107, 7,95,116,104,114,101,97,100,90,8,95,119,101,97,107,114,
114,101,102,90,6,119,105,110,114,101,103,114,167,0,0,0, 101,102,90,6,119,105,110,114,101,103,114,167,0,0,0,114,
114,7,0,0,0,122,4,46,112,121,119,122,6,95,100,46, 7,0,0,0,122,4,46,112,121,119,122,6,95,100,46,112,
112,121,100,84,41,4,114,52,0,0,0,114,63,0,0,0, 121,100,84,78,41,4,114,52,0,0,0,114,63,0,0,0,
114,24,1,0,0,114,140,0,0,0,41,19,114,118,0,0, 114,24,1,0,0,114,140,0,0,0,41,19,114,118,0,0,
0,114,8,0,0,0,114,143,0,0,0,114,235,0,0,0, 0,114,8,0,0,0,114,143,0,0,0,114,235,0,0,0,
114,109,0,0,0,90,18,95,98,117,105,108,116,105,110,95, 114,109,0,0,0,90,18,95,98,117,105,108,116,105,110,95,
@ -2368,64 +2366,64 @@ const unsigned char _Py_M__importlib_external[] = {
101,90,14,119,101,97,107,114,101,102,95,109,111,100,117,108, 101,90,14,119,101,97,107,114,101,102,95,109,111,100,117,108,
101,90,13,119,105,110,114,101,103,95,109,111,100,117,108,101, 101,90,13,119,105,110,114,101,103,95,109,111,100,117,108,101,
114,4,0,0,0,114,4,0,0,0,114,6,0,0,0,218, 114,4,0,0,0,114,4,0,0,0,114,6,0,0,0,218,
6,95,115,101,116,117,112,91,5,0,0,115,82,0,0,0, 6,95,115,101,116,117,112,91,5,0,0,115,76,0,0,0,
0,8,4,1,6,1,6,3,10,1,10,1,10,1,12,2, 0,8,4,1,6,1,6,3,10,1,10,1,10,1,12,2,
10,1,16,3,22,1,14,2,22,1,8,1,10,1,10,1, 10,1,16,3,22,1,14,2,22,1,8,1,10,1,10,1,
4,2,2,1,10,1,6,1,14,1,12,2,8,1,12,1, 4,2,2,1,10,1,6,1,14,1,12,2,8,1,12,1,
12,1,18,3,2,1,14,1,16,2,10,1,12,3,10,1, 12,1,18,3,10,1,12,3,10,1,12,3,10,1,10,1,
12,3,10,1,10,1,12,3,14,1,14,1,10,1,10,1, 12,3,14,1,14,1,10,1,10,1,10,1,114,30,1,0,
10,1,114,30,1,0,0,99,1,0,0,0,0,0,0,0, 0,99,1,0,0,0,0,0,0,0,2,0,0,0,4,0,
2,0,0,0,4,0,0,0,67,0,0,0,115,50,0,0, 0,0,67,0,0,0,115,50,0,0,0,116,0,124,0,131,
0,116,0,124,0,131,1,1,0,116,1,131,0,125,1,116, 1,1,0,116,1,131,0,125,1,116,2,106,3,160,4,116,
2,106,3,160,4,116,5,106,6,124,1,142,0,103,1,161, 5,106,6,124,1,142,0,103,1,161,1,1,0,116,2,106,
1,1,0,116,2,106,7,160,8,116,9,161,1,1,0,100, 7,160,8,116,9,161,1,1,0,100,1,83,0,41,2,122,
1,83,0,41,2,122,41,73,110,115,116,97,108,108,32,116, 41,73,110,115,116,97,108,108,32,116,104,101,32,112,97,116,
104,101,32,112,97,116,104,45,98,97,115,101,100,32,105,109, 104,45,98,97,115,101,100,32,105,109,112,111,114,116,32,99,
112,111,114,116,32,99,111,109,112,111,110,101,110,116,115,46, 111,109,112,111,110,101,110,116,115,46,78,41,10,114,30,1,
78,41,10,114,30,1,0,0,114,159,0,0,0,114,8,0, 0,0,114,159,0,0,0,114,8,0,0,0,114,252,0,0,
0,0,114,252,0,0,0,114,147,0,0,0,114,4,1,0, 0,114,147,0,0,0,114,4,1,0,0,114,17,1,0,0,
0,114,17,1,0,0,218,9,109,101,116,97,95,112,97,116, 218,9,109,101,116,97,95,112,97,116,104,114,161,0,0,0,
104,114,161,0,0,0,114,247,0,0,0,41,2,114,29,1, 114,247,0,0,0,41,2,114,29,1,0,0,90,17,115,117,
0,0,90,17,115,117,112,112,111,114,116,101,100,95,108,111, 112,112,111,114,116,101,100,95,108,111,97,100,101,114,115,114,
97,100,101,114,115,114,4,0,0,0,114,4,0,0,0,114, 4,0,0,0,114,4,0,0,0,114,6,0,0,0,218,8,
6,0,0,0,218,8,95,105,110,115,116,97,108,108,159,5, 95,105,110,115,116,97,108,108,155,5,0,0,115,8,0,0,
0,0,115,8,0,0,0,0,2,8,1,6,1,20,1,114, 0,0,2,8,1,6,1,20,1,114,32,1,0,0,41,1,
32,1,0,0,41,1,114,0,0,0,0,41,2,114,1,0, 114,0,0,0,0,41,2,114,1,0,0,0,114,2,0,0,
0,0,114,2,0,0,0,41,1,114,49,0,0,0,41,1, 0,41,1,114,49,0,0,0,41,1,78,41,3,78,78,78,
78,41,3,78,78,78,41,3,78,78,78,41,2,114,62,0, 41,3,78,78,78,41,2,114,62,0,0,0,114,62,0,0,
0,0,114,62,0,0,0,41,1,78,41,1,78,41,58,114, 0,41,1,78,41,1,78,41,58,114,111,0,0,0,114,12,
111,0,0,0,114,12,0,0,0,90,37,95,67,65,83,69, 0,0,0,90,37,95,67,65,83,69,95,73,78,83,69,78,
95,73,78,83,69,78,83,73,84,73,86,69,95,80,76,65, 83,73,84,73,86,69,95,80,76,65,84,70,79,82,77,83,
84,70,79,82,77,83,95,66,89,84,69,83,95,75,69,89, 95,66,89,84,69,83,95,75,69,89,114,11,0,0,0,114,
114,11,0,0,0,114,13,0,0,0,114,19,0,0,0,114, 13,0,0,0,114,19,0,0,0,114,21,0,0,0,114,30,
21,0,0,0,114,30,0,0,0,114,40,0,0,0,114,41, 0,0,0,114,40,0,0,0,114,41,0,0,0,114,45,0,
0,0,0,114,45,0,0,0,114,46,0,0,0,114,48,0, 0,0,114,46,0,0,0,114,48,0,0,0,114,58,0,0,
0,0,114,58,0,0,0,218,4,116,121,112,101,218,8,95, 0,218,4,116,121,112,101,218,8,95,95,99,111,100,101,95,
95,99,111,100,101,95,95,114,142,0,0,0,114,17,0,0, 95,114,142,0,0,0,114,17,0,0,0,114,132,0,0,0,
0,114,132,0,0,0,114,16,0,0,0,114,20,0,0,0, 114,16,0,0,0,114,20,0,0,0,90,17,95,82,65,87,
90,17,95,82,65,87,95,77,65,71,73,67,95,78,85,77, 95,77,65,71,73,67,95,78,85,77,66,69,82,114,77,0,
66,69,82,114,77,0,0,0,114,76,0,0,0,114,88,0, 0,0,114,76,0,0,0,114,88,0,0,0,114,78,0,0,
0,0,114,78,0,0,0,90,23,68,69,66,85,71,95,66, 0,90,23,68,69,66,85,71,95,66,89,84,69,67,79,68,
89,84,69,67,79,68,69,95,83,85,70,70,73,88,69,83, 69,95,83,85,70,70,73,88,69,83,90,27,79,80,84,73,
90,27,79,80,84,73,77,73,90,69,68,95,66,89,84,69, 77,73,90,69,68,95,66,89,84,69,67,79,68,69,95,83,
67,79,68,69,95,83,85,70,70,73,88,69,83,114,83,0, 85,70,70,73,88,69,83,114,83,0,0,0,114,89,0,0,
0,0,114,89,0,0,0,114,95,0,0,0,114,99,0,0, 0,114,95,0,0,0,114,99,0,0,0,114,101,0,0,0,
0,114,101,0,0,0,114,120,0,0,0,114,127,0,0,0, 114,120,0,0,0,114,127,0,0,0,114,139,0,0,0,114,
114,139,0,0,0,114,145,0,0,0,114,148,0,0,0,114, 145,0,0,0,114,148,0,0,0,114,153,0,0,0,218,6,
153,0,0,0,218,6,111,98,106,101,99,116,114,160,0,0, 111,98,106,101,99,116,114,160,0,0,0,114,165,0,0,0,
0,114,165,0,0,0,114,166,0,0,0,114,181,0,0,0, 114,166,0,0,0,114,181,0,0,0,114,191,0,0,0,114,
114,191,0,0,0,114,206,0,0,0,114,214,0,0,0,114, 206,0,0,0,114,214,0,0,0,114,219,0,0,0,114,225,
219,0,0,0,114,225,0,0,0,114,220,0,0,0,114,226, 0,0,0,114,220,0,0,0,114,226,0,0,0,114,245,0,
0,0,0,114,245,0,0,0,114,247,0,0,0,114,4,1, 0,0,114,247,0,0,0,114,4,1,0,0,114,22,1,0,
0,0,114,22,1,0,0,114,159,0,0,0,114,30,1,0, 0,114,159,0,0,0,114,30,1,0,0,114,32,1,0,0,
0,114,32,1,0,0,114,4,0,0,0,114,4,0,0,0, 114,4,0,0,0,114,4,0,0,0,114,4,0,0,0,114,
114,4,0,0,0,114,6,0,0,0,218,8,60,109,111,100, 6,0,0,0,218,8,60,109,111,100,117,108,101,62,24,0,
117,108,101,62,24,0,0,0,115,108,0,0,0,4,0,4, 0,0,115,108,0,0,0,4,0,4,1,4,1,2,1,6,
1,4,1,2,1,6,3,8,17,8,5,8,5,8,6,8, 3,8,17,8,5,8,5,8,6,8,12,8,10,8,9,8,
12,8,10,8,9,8,5,8,7,10,22,10,124,16,1,12, 5,8,7,10,22,10,124,16,1,12,2,4,1,4,2,6,
2,4,1,4,2,6,2,6,2,8,2,16,45,8,34,8, 2,6,2,8,2,16,45,8,34,8,19,8,12,8,12,8,
19,8,12,8,12,8,28,8,17,10,55,10,12,10,10,8, 28,8,17,10,55,10,12,10,10,8,14,6,3,4,1,14,
14,6,3,4,1,14,67,14,64,14,29,16,110,14,41,18, 67,14,64,14,29,16,110,14,41,18,45,18,16,4,3,18,
45,18,16,4,3,18,53,14,60,14,42,14,127,0,5,14, 53,14,60,14,42,14,127,0,5,14,127,0,22,10,23,8,
127,0,22,10,23,8,11,8,68, 11,8,64,
}; };