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1,535
py
Python
lte/gateway/python/magma/pipelined/qos/tc_ops.py
rdefosse/magma
d12ac827d0cdb39f499ce202e9e1196cc50b68d7
[ "BSD-3-Clause" ]
1
2021-11-03T21:37:26.000Z
2021-11-03T21:37:26.000Z
lte/gateway/python/magma/pipelined/qos/tc_ops.py
rdefosse/magma
d12ac827d0cdb39f499ce202e9e1196cc50b68d7
[ "BSD-3-Clause" ]
143
2020-09-08T06:24:23.000Z
2022-03-29T05:56:53.000Z
lte/gateway/python/magma/pipelined/qos/tc_ops.py
hixio-mh/magma
2602de5cecd590c1f30a1c798feb2e78b58f5de7
[ "BSD-3-Clause" ]
2
2021-05-27T18:15:16.000Z
2021-05-27T18:41:39.000Z
""" Copyright 2021 The Magma Authors. This source code is licensed under the BSD-style license found in the LICENSE file in the root directory of this source tree. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import ( absolute_import, division, print_function, unicode_literals, ) from abc import ABC, abstractmethod class TcOpsBase(ABC): """ Implements TC lower level operations to create scheduler and filters. Each function has all argments required to create TC object. There is minimal state maintained in object. """ @abstractmethod def create_htb(self, iface: str, qid: str, max_bw: str, rate:str, parent_qid: str = None) -> int: """ Create HTB scheduler """ ... @abstractmethod def del_htb(self, iface: str, qid: str) -> int: """ Delete HTB scheduler """ ... @abstractmethod def create_filter(self, iface: str, mark: str, qid: str, proto: int = 3) -> int: """ Create FW filter """ ... @abstractmethod def del_filter(self, iface: str, mark: str, qid: str, proto: int = 3) -> int: """ Delete FW filter """ ...
26.016949
84
0.63127
1f14a844461fbfff4f907ba4992117b196bea35c
3,771
py
Python
tests/test_threading.py
lotapp/loguru
19ec234db32a05c46bfe837d71eabaa28bac5577
[ "MIT" ]
null
null
null
tests/test_threading.py
lotapp/loguru
19ec234db32a05c46bfe837d71eabaa28bac5577
[ "MIT" ]
null
null
null
tests/test_threading.py
lotapp/loguru
19ec234db32a05c46bfe837d71eabaa28bac5577
[ "MIT" ]
1
2019-04-03T03:06:29.000Z
2019-04-03T03:06:29.000Z
from threading import Thread, Barrier import itertools from loguru import logger import time class NonSafeSink: def __init__(self, sleep_time): self.sleep_time = sleep_time self.written = "" self.stopped = False def write(self, message): if self.stopped: raise RuntimeError("Can't write on stopped sink") length = len(message) self.written += message[:length] time.sleep(self.sleep_time) self.written += message[length:] def stop(self): self.stopped = True def test_safe_logging(): barrier = Barrier(2) counter = itertools.count() sink = NonSafeSink(1) logger.add(sink, format="{message}", catch=False) def threaded(): barrier.wait() logger.info("___{}___", next(counter)) threads = [Thread(target=threaded) for _ in range(2)] for thread in threads: thread.start() for thread in threads: thread.join() logger.stop() assert sink.written in ("___0___\n___1___\n", "___1___\n___0___\n") def test_safe_adding_while_logging(writer): barrier = Barrier(2) counter = itertools.count() sink_1 = NonSafeSink(1) sink_2 = NonSafeSink(1) logger.add(sink_1, format="{message}", catch=False) def thread_1(): barrier.wait() logger.info("aaa{}bbb", next(counter)) def thread_2(): barrier.wait() time.sleep(0.5) logger.add(sink_2, format="{message}", catch=False) logger.info("ccc{}ddd", next(counter)) threads = [Thread(target=thread_1), Thread(target=thread_2)] for thread in threads: thread.start() for thread in threads: thread.join() logger.stop() assert sink_1.written == "aaa0bbb\nccc1ddd\n" assert sink_2.written == "ccc1ddd\n" def test_safe_removing_while_logging(): barrier = Barrier(2) counter = itertools.count() sink_1 = NonSafeSink(1) sink_2 = NonSafeSink(1) a = logger.add(sink_1, format="{message}", catch=False) b = logger.add(sink_2, format="{message}", catch=False) def thread_1(): barrier.wait() logger.info("aaa{}bbb", next(counter)) def thread_2(): barrier.wait() time.sleep(0.5) logger.remove(a) logger.info("ccc{}ddd", next(counter)) threads = [Thread(target=thread_1), Thread(target=thread_2)] for thread in threads: thread.start() for thread in threads: thread.join() logger.stop() assert sink_1.written == "aaa0bbb\n" assert sink_2.written == "aaa0bbb\nccc1ddd\n" def test_safe_writing_after_removing(capsys): barrier = Barrier(2) i = logger.add(NonSafeSink(1), format="{message}", catch=False) j = logger.add(NonSafeSink(1), format="{message}", catch=False) def write(): barrier.wait() logger.info("Writing") def remove(): barrier.wait() time.sleep(0.5) logger.remove(j) threads = [Thread(target=write), Thread(target=remove)] for thread in threads: thread.start() for thread in threads: thread.join() logger.stop() out, err = capsys.readouterr() assert out == "" assert err == "" def test_heavily_threaded_logging(capsys): logger.remove() def function(): i = logger.add(NonSafeSink(0.1), format="{message}", catch=False) logger.debug("AAA") logger.info("BBB") logger.success("CCC") logger.remove(i) threads = [Thread(target=function) for _ in range(10)] for thread in threads: thread.start() for thread in threads: thread.join() logger.stop() out, err = capsys.readouterr() assert out == "" assert err == ""
22.446429
73
0.612304
d6e53f5295e615030a860afc4b2e9b24fa416d4a
8,073
py
Python
SC101_Projects/SC101_Assignment2/breakoutgraphics.py
TobyCCC/MystanCodeProJects
fac747e681875777b5d40bac3bcfebe204ca44f8
[ "MIT" ]
null
null
null
SC101_Projects/SC101_Assignment2/breakoutgraphics.py
TobyCCC/MystanCodeProJects
fac747e681875777b5d40bac3bcfebe204ca44f8
[ "MIT" ]
null
null
null
SC101_Projects/SC101_Assignment2/breakoutgraphics.py
TobyCCC/MystanCodeProJects
fac747e681875777b5d40bac3bcfebe204ca44f8
[ "MIT" ]
null
null
null
""" stanCode Breakout Project Adapted from Eric Roberts's Breakout by Sonja Johnson-Yu, Kylie Jue, Nick Bowman, and Jerry Liao YOUR DESCRIPTION HERE """ from campy.graphics.gwindow import GWindow from campy.graphics.gobjects import GOval, GRect, GLabel from campy.gui.events.mouse import onmouseclicked, onmousemoved import random BRICK_SPACING = 5 # Space between bricks (in pixels). This space is used for horizontal and vertical spacing. BRICK_WIDTH = 40 # Height of a brick (in pixels). BRICK_HEIGHT = 15 # Height of a brick (in pixels). BRICK_ROWS = 10 # Number of rows of bricks. BRICK_COLS = 10 # Number of columns of bricks. BRICK_OFFSET = 50 # Vertical offset of the topmost brick from the window top (in pixels). BALL_RADIUS = 10 # Radius of the ball (in pixels). PADDLE_WIDTH = 75 # Width of the paddle (in pixels). PADDLE_HEIGHT = 15 # Height of the paddle (in pixels). PADDLE_OFFSET = 50 # Vertical offset of the paddle from the window bottom (in pixels). INITIAL_Y_SPEED = 7 # Initial vertical speed for the ball. MAX_X_SPEED = 5 # Maximum initial horizontal speed for the ball. class BreakoutGraphics: def __init__(self, ball_radius = BALL_RADIUS, paddle_width = PADDLE_WIDTH, paddle_height = PADDLE_HEIGHT, paddle_offset = PADDLE_OFFSET, brick_rows = BRICK_ROWS, brick_cols = BRICK_COLS, brick_width = BRICK_WIDTH, brick_height = BRICK_HEIGHT, brick_offset = BRICK_OFFSET, brick_spacing = BRICK_SPACING, title='Breakout'): # Create a graphical window, with some extra space window_width = brick_rows * (brick_width + brick_spacing) - brick_spacing window_height = brick_offset + 3 * (brick_cols * (brick_height + brick_spacing) - brick_spacing) self.window = GWindow(width=window_width, height=window_height, title=title) # Create a paddle self.paddle = GRect(paddle_width, paddle_height) self.paddle.filled = True self.window.add(self.paddle, (window_width-paddle_width)/2, window_height-paddle_offset-paddle_height) # Center a filled ball in the graphical window self.ball = GOval(ball_radius*2, ball_radius*2) self.ball.filled = True self.window.add(self.ball, window_width/2-ball_radius, window_height/2-ball_radius) # Default initial velocity for the ball self.__dx, self.__dy = self.v_set() # Initialize our mouse listeners self.__game_start = False # 判斷遊戲是否開始 onmousemoved(self.mouse_move) onmouseclicked(self.on_set) # Draw bricks self._brick_offset = brick_offset self._brick_width = brick_width self._brick_height = brick_height self._brick_spacing = brick_spacing self.brick_rows = brick_rows self.brick_cols = brick_cols self.__build_brick_col() # Create score board self.score = 0 self.score_board = GLabel(f"Score : {self.score}") self.score_board.font = "Comic Sans MS-15" self.window.add(self.score_board, 3, self.score_board.height+15) @staticmethod def v_set(): """ 設定速度 :return:(dx, dy), int """ vx = random.randint(1, MAX_X_SPEED) if random.random() > 0.5: vx *= -1 vy = INITIAL_Y_SPEED return vx, vy def get_speed(self): """ 回傳給user端dx和dy :return: (dx, dy), int """ return self.__dx, self.__dy def game_start(self): """ 回報遊戲是否開始 """ return self.__game_start def mouse_move(self, mouse): position = mouse.x - self.paddle.width / 2 # 由滑鼠位置反推paddle的位置 if position <= 0: self.paddle.x = 0 elif position >= self.window.width-self.paddle.width: self.paddle.x = self.window.width-self.paddle.width else: self.paddle.x = position def on_set(self, mouse): self.__game_start = True # 回傳遊戲開始 def __build_brick_col(self): """ 由上至下建造所有的brick """ for i in range(0, self.brick_cols): color = i * 255 // (self.brick_cols + 1) # 設定灰階顏色 self.__build_brick_row(self._brick_offset + i * (self._brick_spacing + self._brick_height), color) def __build_brick_row(self, build_height, gray_scale): """ build_height: int, 建造的高度 gray_scale: int, RGB值 """ for i in range(0, self.brick_rows): a_brick = self.__build_a_brick(gray_scale) self.window.add(a_brick, i*(self._brick_width+self._brick_spacing), build_height) def __build_a_brick(self, gray_scale): """ gray_scale: int, RGB值 :return: obj, 建造好的brick """ brick = GRect(self._brick_width, self._brick_height) brick.filled = True brick.color = (gray_scale, gray_scale, gray_scale) brick.fill_color = (gray_scale, gray_scale, gray_scale) return brick def reset_ball_position(self): """ 把球重置到畫面中央,速度重設 """ self.ball.x = (self.window.width-self.ball.width)/2 self.ball.y = (self.window.height-self.ball.height)/2 self.__dx, self.__dy = self.v_set() def hit_paddle(self): """ 判斷是否打到paddle :return: boolean """ maybe_paddle = self.window.get_object_at(self.ball.x, self.ball.y+self.ball.height) if maybe_paddle is not None and maybe_paddle == self.paddle: return True else: maybe_paddle = self.window.get_object_at(self.ball.x + self.ball.width, self.ball.y + self.ball.height) if maybe_paddle is not None and maybe_paddle == self.paddle: return True else: return False def rebound_x(self): """ 將dx變號 """ self.__dx *= -1 def rebound_y(self): """ 將dy變號 """ self.__dy *= -1 def hit_block(self): """ 判斷是否打到block,並且設定打到磚塊後的反彈速度 :return: boolean """ # 判斷是否打到磚塊 maybe_block = self.window.get_object_at(self.ball.x, self.ball.y) if maybe_block is None or maybe_block == self.paddle or maybe_block == self.score_board: maybe_block = self.window.get_object_at(self.ball.x+self.ball.width, self.ball.y) if maybe_block is None or maybe_block == self.paddle or maybe_block == self.score_board: maybe_block = self.window.get_object_at(self.ball.x, self.ball.y+self.ball.height) if maybe_block is None or maybe_block == self.paddle or maybe_block == self.score_board: maybe_block = self.window.get_object_at(self.ball.x+self.ball.width, self.ball.y + self.ball.height) if maybe_block is None or maybe_block == self.paddle or maybe_block == self.score_board: return False # 判斷打到磚塊的何處,計算反彈 ball_on_top = maybe_block.y - self.ball.y > self.ball.height-INITIAL_Y_SPEED and maybe_block.y - self.ball.y <= self.ball.height ball_under_buttom = self.ball.y-maybe_block.y > self._brick_height-INITIAL_Y_SPEED and self.ball.y-maybe_block.y <= self._brick_height ball_is_left = maybe_block.x - self.ball.x > self.ball.width-abs(self.__dx) and maybe_block.x - self.ball.x <= self.ball.width ball_is_right = self.ball.x-maybe_block.x > self._brick_width-abs(self.__dx) and self.ball.x-maybe_block.x <= self._brick_width if ball_on_top or ball_under_buttom: self.rebound_y() if ball_is_left or ball_is_right: # 也可用elif會比較正常,因為大部分是打到磚塊上下 self.rebound_x() self.window.remove(maybe_block) self.score += 10 # 打到磚塊後的得分 return True
39.18932
142
0.616871
ccd0b7dc72bf45066e97e2a5d6a06d5ba7a0e501
1,204
py
Python
20201005/homework.py
ObukhovVladislav/python-basics
268af015fdd3392fd77783b38ef74be2ca6db7da
[ "Apache-2.0" ]
null
null
null
20201005/homework.py
ObukhovVladislav/python-basics
268af015fdd3392fd77783b38ef74be2ca6db7da
[ "Apache-2.0" ]
null
null
null
20201005/homework.py
ObukhovVladislav/python-basics
268af015fdd3392fd77783b38ef74be2ca6db7da
[ "Apache-2.0" ]
null
null
null
class Student: def __init__(self): self.name = None self.surname = None self.patronymic = None self.group_number = None self.student_card = None self.gradebook = None class Teacher: def __init__(self): self.name = None self.surname = None self.patronymic = None self.discipline = None class StudyGroup: def __init__(self): self.number = None self.number_of_students = None self.specialty = None self.curator = None class College: def __init__(self): self.college_name = None self.administration = None self.number_of_students = None self.specialties = None class Exam: def __init__(self): self.mark = None self.teacher = None self.discipline = None self.student = None class StudentOnTheExam: def __init__(self): self.mark = None self.teacher = None self.discipline = None self.gradebook = None class Car: def __init__(self): self.engine = None self.color = None self.brand = None self.mark = None self.type = None
20.40678
38
0.584718
8ee4ba7a3f42df59cf603e31442f01323788919a
847
py
Python
imsearch/repository/__init__.py
x0rzkov/imsearch
d39d08ef77c48435c9f333134cafe41a9ca95da9
[ "Apache-2.0" ]
64
2019-01-16T10:06:37.000Z
2022-03-24T03:17:48.000Z
imsearch/repository/__init__.py
x0rzkov/imsearch
d39d08ef77c48435c9f333134cafe41a9ca95da9
[ "Apache-2.0" ]
8
2020-03-08T18:18:56.000Z
2020-09-09T03:20:21.000Z
imsearch/repository/__init__.py
x0rzkov/imsearch
d39d08ef77c48435c9f333134cafe41a9ca95da9
[ "Apache-2.0" ]
13
2020-01-30T09:37:57.000Z
2022-03-09T08:20:45.000Z
from ..exception import InvalidAttributeError from .mongo import MongoRepository def get_repository(index_name, repo_type): repo = MongoRepository(index_name) return RepositoryWrapper(repo) class RepositoryWrapper: def __init__(self, repo): self.db = repo def clean(self): self.db.clean() def insert(self, data): if isinstance(data, dict): return self.db.insert_one(data) if isinstance(data, list): return self.db.insert_many(data) raise InvalidAttributeError( data, 'data of type dict or list expected, got {}'.format(type(data))) def find(self, query, many=False): if many: return self.db.find(query) else: return self.db.find_one(query) def dump(self): return self.db.find({})
23.527778
82
0.624557
cc0f22d969e0e63a7f63d237edc68a7fbcd15000
32,453
gyp
Python
chrome/test/data/nacl/nacl_test_data.gyp
iplo/Chain
8bc8943d66285d5258fffc41bed7c840516c4422
[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
231
2015-01-08T09:04:44.000Z
2021-12-30T03:03:10.000Z
chrome/test/data/nacl/nacl_test_data.gyp
JasonEric/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
1
2017-02-14T21:55:58.000Z
2017-02-14T21:55:58.000Z
chrome/test/data/nacl/nacl_test_data.gyp
JasonEric/chromium
c7361d39be8abd1574e6ce8957c8dbddd4c6ccf7
[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
268
2015-01-21T05:53:28.000Z
2022-03-25T22:09:01.000Z
# Copyright (c) 2012 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. { 'includes': [ '../../../../ppapi/ppapi_nacl_test_common.gypi', ], 'targets': [ { 'target_name': 'shared_test_files', 'type': 'none', 'variables': { 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'test_files': [ # TODO(ncbray) move into chrome/test/data/nacl when all tests are # converted. '<(DEPTH)/ppapi/native_client/tests/ppapi_browser/progress_event_listener.js', '<(DEPTH)/ppapi/native_client/tools/browser_tester/browserdata/nacltest.js', # Files that aren't assosiated with any particular executable. 'bad/ppapi_bad.html', 'bad/ppapi_bad.js', 'bad/ppapi_bad_native.html', 'bad/ppapi_bad_doesnotexist.nmf', 'bad/ppapi_bad_magic.nmf', 'bad/ppapi_bad_manifest_uses_nexes.nmf', 'bad/ppapi_bad_manifest_bad_files.nmf', 'bad/ppapi_bad_manifest_nexe_arch.nmf', 'crash/ppapi_crash.html', 'manifest_file/test_file.txt', ], }, }, { 'target_name': 'simple_test', 'type': 'none', 'variables': { 'nexe_target': 'simple', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ 'simple.cc', ], 'test_files': [ 'nacl_load_test.html', ], }, }, { 'target_name': 'exit_status_test', 'type': 'none', 'variables': { 'nexe_target': 'pm_exit_status_test', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ 'exit_status/pm_exit_status_test.cc', ], 'test_files': [ 'exit_status/pm_exit_status_test.html', ], }, }, { 'target_name': 'sysconf_nprocessors_onln_test', 'type': 'none', 'variables': { 'nexe_target': 'sysconf_nprocessors_onln_test', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ 'sysconf_nprocessors_onln/sysconf_nprocessors_onln_test.cc', ], 'test_files': [ 'sysconf_nprocessors_onln/sysconf_nprocessors_onln_test.html', ], }, }, { 'target_name': 'ppapi_test_lib', 'type': 'none', 'variables': { 'nlib_target': 'libppapi_test_lib.a', 'nso_target': 'libppapi_test_lib.so', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ # TODO(ncbray) move these files once SCons no longer depends on them. '../../../../ppapi/native_client/tests/ppapi_test_lib/get_browser_interface.cc', '../../../../ppapi/native_client/tests/ppapi_test_lib/internal_utils.cc', '../../../../ppapi/native_client/tests/ppapi_test_lib/module_instance.cc', '../../../../ppapi/native_client/tests/ppapi_test_lib/testable_callback.cc', '../../../../ppapi/native_client/tests/ppapi_test_lib/test_interface.cc', ] }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', ], }, { 'target_name': 'nacl_ppapi_util', 'type': 'none', 'variables': { 'nlib_target': 'libnacl_ppapi_util.a', 'nso_target': 'libnacl_ppapi_util.so', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ # TODO(ncbray) move these files once SCons no longer depends on them. '../../../../ppapi/native_client/src/untrusted/nacl_ppapi_util/string_buffer.cc', '../../../../ppapi/native_client/src/untrusted/nacl_ppapi_util/nacl_ppapi_util.cc', '../../../../ppapi/native_client/src/untrusted/nacl_ppapi_util/ppapi_srpc_main.c', ] }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', ], }, { 'target_name': 'ppapi_progress_events', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_progress_events', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'progress_events/ppapi_progress_events.cc', ], 'test_files': [ 'progress_events/ppapi_progress_events.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_bad_ppp_initialize', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_ppp_initialize', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_ppp_initialize.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_bad_ppp_initialize_crash', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_ppp_initialize_crash', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_ppp_initialize_crash.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_bad_no_ppp_instance', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_no_ppp_instance', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_no_ppp_instance.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_bad_get_ppp_instance_crash', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_get_ppp_instance_crash', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_get_ppp_instance_crash.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_bad_ppp_instance_didcreate', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_ppp_instance_didcreate', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_ppp_instance_didcreate.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_bad_ppp_instance_didcreate_crash', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_bad_ppp_instance_didcreate_crash', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'bad/ppapi_bad_ppp_instance_didcreate_crash.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', ], }, { 'target_name': 'ppapi_crash_via_check_failure', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_crash_via_check_failure', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'crash/ppapi_crash_via_check_failure.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_crash_via_exit_call', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_crash_via_exit_call', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'crash/ppapi_crash_via_exit_call.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_crash_in_callback', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_crash_in_callback', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'crash/ppapi_crash_in_callback.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_crash_off_main_thread', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_crash_off_main_thread', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'crash/ppapi_crash_off_main_thread.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_crash_ppapi_off_main_thread', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_crash_ppapi_off_main_thread', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'crash/ppapi_crash_ppapi_off_main_thread.cc', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'pm_redir_test', 'type': 'none', 'variables': { 'nexe_target': 'pm_redir_test', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lplatform', '-lgio', ], 'sources': [ 'postmessage_redir/pm_redir_test.cc', ], 'test_files': [ 'postmessage_redir/pm_redir_test.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', ], }, { 'target_name': 'pm_manifest_file', 'type': 'none', 'variables': { 'nexe_target': 'pm_manifest_file', 'build_newlib': 1, 'build_glibc': 1, # TODO(ncbray) support file injection into PNaCl manifest. 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lnacl_ppapi_util', '-lppapi_cpp', '-lppapi', '-lsrpc', '-lplatform', '-lgio', '-limc', '-limc_syscalls', '-lweak_ref', ], 'sources': [ 'manifest_file/pm_manifest_file_test.cc', ], 'create_nmf_args_portable': [ '-xtest_file:test_file.txt', '-xnmf says hello world:test_file.txt', ], 'test_files': [ 'manifest_file/pm_manifest_file_test.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:srpc_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/imc/imc.gyp:imc_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:imc_syscalls_lib', '<(DEPTH)/native_client/src/trusted/weak_ref/weak_ref.gyp:weak_ref_lib', 'nacl_ppapi_util', ], }, { 'target_name': 'pm_pre_init_manifest_file', 'type': 'none', 'variables': { 'nexe_target': 'pm_pre_init_manifest_file', 'build_newlib': 1, 'build_glibc': 1, # TODO(ncbray) support file injection into PNaCl manifest. 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lnacl_ppapi_util', '-lppapi_cpp', '-lppapi', '-lsrpc', '-lplatform', '-lgio', '-limc', '-limc_syscalls', '-lweak_ref', ], 'sources': [ 'manifest_file/pm_pre_init_manifest_file_test.cc', ], 'create_nmf_args_portable': [ '-xtest_file:test_file.txt', '-xnmf says hello world:test_file.txt', ], 'test_files': [ 'manifest_file/pm_pre_init_manifest_file_test.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:srpc_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/imc/imc.gyp:imc_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:imc_syscalls_lib', '<(DEPTH)/native_client/src/trusted/weak_ref/weak_ref.gyp:weak_ref_lib', 'nacl_ppapi_util', ], }, { 'target_name': 'irt_manifest_file', 'type': 'none', 'variables': { 'nexe_target': 'irt_manifest_file', 'build_newlib': 1, # Linking problems - can't find __nacl_irt_query. 'build_glibc': 0, # TODO(ncbray) support file injection into PNaCl manifest. 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lnacl_ppapi_util', '-lppapi_cpp', '-lppapi', '-lsrpc', '-lplatform', '-lgio', '-limc', '-limc_syscalls', '-lweak_ref', '-lnacl', ], 'sources': [ 'manifest_file/irt_manifest_file_test.cc', ], 'create_nmf_args_portable': [ '-xtest_file:test_file.txt', '-xnmf says hello world:test_file.txt', ], 'test_files': [ 'manifest_file/irt_manifest_file_test.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:srpc_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/imc/imc.gyp:imc_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:imc_syscalls_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:nacl_lib', '<(DEPTH)/native_client/src/trusted/weak_ref/weak_ref.gyp:weak_ref_lib', 'nacl_ppapi_util', ], }, { 'target_name': 'pm_nameservice_test', 'type': 'none', 'variables': { 'nexe_target': 'pm_nameservice_test', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lnacl_ppapi_util', '-lppapi_cpp', '-lppapi', '-lsrpc', '-lplatform', '-lgio', '-limc', '-limc_syscalls', '-lweak_ref', ], 'sources': [ 'nameservice/pm_nameservice_test.cc', ], 'test_files': [ 'nameservice/pm_nameservice_test.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:srpc_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/imc/imc.gyp:imc_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:imc_syscalls_lib', '<(DEPTH)/native_client/src/trusted/weak_ref/weak_ref.gyp:weak_ref_lib', 'nacl_ppapi_util', ], }, { 'target_name': 'ppapi_extension_mime_handler', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_extension_mime_handler', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'extension_mime_handler/ppapi_extension_mime_handler.cc', ], 'test_files': [ 'extension_mime_handler/ppapi_extension_mime_handler.html', 'extension_mime_handler/mime_test_data.dat', # For faking the file's MIME type. 'extension_mime_handler/mime_test_data.dat.mock-http-headers', # Turns the test data directory into an extension. Hackish. # Note that the .nexe names are embedded in this file. 'extension_mime_handler/manifest.json', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', 'ppapi_test_lib', ], }, { 'target_name': 'pnacl_error_handling_test', 'type': 'none', 'variables': { 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', # No need to translate AOT. 'enable_x86_32': 0, 'enable_x86_64': 0, 'enable_arm': 0, # Use prebuilt NMF files. 'generate_nmf': 0, 'test_files': [ 'pnacl_error_handling/pnacl_error_handling.html', 'pnacl_error_handling/bad.pexe', 'pnacl_error_handling/pnacl_bad_pexe.nmf', 'pnacl_error_handling/pnacl_bad_doesnotexist.nmf', 'pnacl_error_handling/pnacl_illformed_manifest.nmf', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', ] }, { 'target_name': 'pnacl_mime_type_test', 'type': 'none', 'variables': { 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', # No need to translate AOT. 'enable_x86_32': 0, 'enable_x86_64': 0, 'enable_arm': 0, 'test_files': [ 'pnacl_mime_type/pnacl_mime_type.html', ], }, }, { 'target_name': 'pnacl_options_test', 'type': 'none', 'variables': { 'nexe_target': 'pnacl_options', 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', # No need to translate these AOT, when we just need the pexe. 'enable_x86_32': 0, 'enable_x86_64': 0, 'enable_arm': 0, 'sources': [ 'simple.cc', ], 'test_files': [ 'pnacl_nmf_options/pnacl_options.html', 'pnacl_nmf_options/pnacl_o_0.nmf', 'pnacl_nmf_options/pnacl_o_2.nmf', 'pnacl_nmf_options/pnacl_o_large.nmf', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', ] }, { 'target_name': 'pnacl_dyncode_syscall_disabled_test', 'type': 'none', 'variables': { # This tests that nexes produced by translation in the browser are not # able to use the dyncode syscalls. Pre-translated nexes are not # subject to this constraint, so we do not test them. 'enable_x86_32': 0, 'enable_x86_64': 0, 'enable_arm': 0, 'nexe_target': 'pnacl_dyncode_syscall_disabled', 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', # The "_private" variant of the library calls the syscalls # directly, which allows us to test the syscalls directly, # even when the dyncode IRT interface is also disabled under # PNaCl. '-lnacl_dyncode_private', ], 'sources': [ 'pnacl_dyncode_syscall_disabled/pnacl_dyncode_syscall_disabled.cc', ], 'test_files': [ 'pnacl_dyncode_syscall_disabled/pnacl_dyncode_syscall_disabled.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:nacl_dyncode_private_lib', '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'pnacl_exception_handling_disabled_test', 'type': 'none', 'variables': { # This tests that nexes produced by translation in the browser are not # able to use hardware exception handling. Pre-translated nexes are # not subject to this constraint, so we do not test them. 'enable_x86_32': 0, 'enable_x86_64': 0, 'enable_arm': 0, 'nexe_target': 'pnacl_exception_handling_disabled', 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', # The "_private" variant of the library calls the syscalls # directly, which allows us to test the syscalls directly, # even when the exception-handling IRT interface is also # disabled under PNaCl. '-lnacl_exception_private', ], 'sources': [ 'pnacl_exception_handling_disabled/pnacl_exception_handling_disabled.cc', ], 'test_files': [ 'pnacl_exception_handling_disabled/pnacl_exception_handling_disabled.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/untrusted/nacl/nacl.gyp:nacl_exception_private_lib', '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, # Legacy NaCl PPAPI interface tests being here. { 'target_name': 'ppapi_ppb_core', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_ppb_core', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'ppapi/ppb_core/ppapi_ppb_core.cc', ], 'test_files': [ 'ppapi/ppb_core/ppapi_ppb_core.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_ppb_instance', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_ppb_instance', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'ppapi/ppb_instance/ppapi_ppb_instance.cc', ], 'test_files': [ 'ppapi/ppb_instance/ppapi_ppb_instance.html', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, { 'target_name': 'ppapi_ppp_instance', 'type': 'none', 'variables': { 'nexe_target': 'ppapi_ppp_instance', 'build_newlib': 1, 'build_glibc': 1, 'build_pnacl_newlib': 1, 'nexe_destination_dir': 'nacl_test_data', 'link_flags': [ '-lppapi', '-lppapi_test_lib', '-lplatform', '-lgio', ], 'sources': [ 'ppapi/ppp_instance/ppapi_ppp_instance.cc', ], 'test_files': [ 'ppapi/ppp_instance/ppapi_ppp_instance.html', 'ppapi/ppp_instance/ppapi_ppp_instance.js', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform_lib', '<(DEPTH)/native_client/src/shared/gio/gio.gyp:gio_lib', '<(DEPTH)/ppapi/native_client/native_client.gyp:ppapi_lib', '<(DEPTH)/ppapi/ppapi_untrusted.gyp:ppapi_cpp_lib', 'ppapi_test_lib', ], }, ], 'conditions': [ ['target_arch!="arm"', { # Source file does not have asm for ARM. 'targets': [ { 'target_name': 'partly_invalid', 'type': 'none', 'variables': { 'nexe_target': 'partly_invalid', 'build_newlib': 1, 'build_glibc': 0, 'build_pnacl_newlib': 0, 'nexe_destination_dir': 'nacl_test_data', 'sources': [ '<(DEPTH)/native_client/tests/stubout_mode/partly_invalid.c', ], }, 'dependencies': [ '<(DEPTH)/native_client/tools.gyp:prep_toolchain', ], }, ], }], ], }
33.630052
93
0.569901
b9aa8ae90cf761411e286acb5db9370e4e2d9254
2,419
py
Python
src/selfdroid/api/v1/APIv1Authenticator.py
vitlabuda/selfdroid-web-app
9eac9ee2c34038de13e179b6afb3d530a086e7b2
[ "Apache-2.0", "BSD-3-Clause" ]
1
2022-03-13T14:57:04.000Z
2022-03-13T14:57:04.000Z
src/selfdroid/api/v1/APIv1Authenticator.py
vitlabuda/selfdroid-web-app
9eac9ee2c34038de13e179b6afb3d530a086e7b2
[ "Apache-2.0", "BSD-3-Clause" ]
null
null
null
src/selfdroid/api/v1/APIv1Authenticator.py
vitlabuda/selfdroid-web-app
9eac9ee2c34038de13e179b6afb3d530a086e7b2
[ "Apache-2.0", "BSD-3-Clause" ]
null
null
null
# SPDX-License-Identifier: BSD-3-Clause # # Copyright (c) 2021 Vít Labuda. All rights reserved. # # Redistribution and use in source and binary forms, with or without modification, are permitted provided that the # following conditions are met: # 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following # disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the # following disclaimer in the documentation and/or other materials provided with the distribution. # 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote # products derived from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, # INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import base64 import flask from selfdroid.AuthenticatorBase import AuthenticatorBase from selfdroid.SelfdroidRuntimeError import SelfdroidRuntimeError class APIv1Authenticator(AuthenticatorBase): _HEADER_KEY_PASSWORD: str = "X-SelfdroidAPI-Password" def check_user_password_from_headers(self) -> bool: password_base64 = flask.request.headers.get(APIv1Authenticator._HEADER_KEY_PASSWORD, default="", type=str) try: password = base64.b64decode(password_base64, validate=True).decode("utf-8") except ValueError: return False return self.check_user_password(password) def check_admin_password(self, password: str) -> bool: """ API endpoints mustn't require admin access! """ raise SelfdroidRuntimeError("Admin access is forbidden via the API!")
50.395833
118
0.767259
8f6706bb381910caf81378ac6ec0346eec78d7e3
857
py
Python
xlsxwriter/test/comparison/test_hyperlink38.py
dthadi3/XlsxWriter
f1801e82240aa9c746ce14948ef95990b83162cf
[ "BSD-2-Clause-FreeBSD" ]
1
2020-07-01T07:24:37.000Z
2020-07-01T07:24:37.000Z
xlsxwriter/test/comparison/test_hyperlink38.py
dthadi3/XlsxWriter
f1801e82240aa9c746ce14948ef95990b83162cf
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
xlsxwriter/test/comparison/test_hyperlink38.py
dthadi3/XlsxWriter
f1801e82240aa9c746ce14948ef95990b83162cf
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2020, John McNamara, jmcnamara@cpan.org # from ..excel_comparison_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.set_filename('hyperlink38.xlsx') def test_create_file(self): """Test the creation of a simple XlsxWriter file with image(s).""" workbook = Workbook(self.got_filename) worksheet = workbook.add_worksheet() worksheet.insert_image('E9', self.image_dir + 'red.png', {'url': 'internal:Sheet1!A1'}) workbook.close() self.assertExcelEqual()
24.485714
79
0.591599
0cecab4059e239235cb28f12c2441abd617659bd
656,316
py
Python
template_container_mouse/labels/slice_137.py
lkondratova/Brainplot
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
[ "MIT" ]
null
null
null
template_container_mouse/labels/slice_137.py
lkondratova/Brainplot
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
[ "MIT" ]
null
null
null
template_container_mouse/labels/slice_137.py
lkondratova/Brainplot
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
[ "MIT" ]
null
null
null
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855.692308
865
0.497151
fa6d116271efa6250b06087c7f3e912de4ac7b0b
1,473
py
Python
tests/test_firewall.py
haginara/pan-os-python
f6f8a04ddd5a1299d8aea08c38ad2ba1059b69e3
[ "0BSD" ]
162
2016-04-03T12:00:20.000Z
2020-07-24T18:46:16.000Z
tests/test_firewall.py
haginara/pan-os-python
f6f8a04ddd5a1299d8aea08c38ad2ba1059b69e3
[ "0BSD" ]
242
2016-03-18T23:53:00.000Z
2020-07-24T22:02:05.000Z
tests/test_firewall.py
haginara/pan-os-python
f6f8a04ddd5a1299d8aea08c38ad2ba1059b69e3
[ "0BSD" ]
95
2016-03-16T13:10:28.000Z
2020-07-17T01:47:15.000Z
# Copyright (c) 2014, Palo Alto Networks # # Permission to use, copy, modify, and/or distribute this software for any # purpose with or without fee is hereby granted, provided that the above # copyright notice and this permission notice appear in all copies. # # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES # WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR # ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES # WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN # ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF # OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. import unittest import panos import panos.firewall class TestFirewall(unittest.TestCase): def test_id_returns_serial(self): expected = "serial#" fw = panos.firewall.Firewall(serial=expected,) ret_val = fw.id self.assertEqual(expected, ret_val) def test_id_returns_hostname(self): expected = "hostName" fw = panos.firewall.Firewall(hostname=expected,) ret_val = fw.id self.assertEqual(expected, ret_val) def test_id_returns_no_id(self): expected = "<no-id>" fw = panos.firewall.Firewall() ret_val = fw.id self.assertEqual(expected, ret_val) if __name__ == "__main__": unittest.main()
28.326923
74
0.717583
35f84fc32c1a714ef60b7eadf77f3f1e1bdff609
1,623
pyde
Python
mode/examples/Topics/Fractals and L-Systems/Tree/Tree.pyde
timgates42/processing.py
78a237922c2a928b83f4ad579dbf8d32c0099890
[ "Apache-2.0" ]
1,224
2015-01-01T22:09:23.000Z
2022-03-29T19:43:56.000Z
mode/examples/Topics/Fractals and L-Systems/Tree/Tree.pyde
timgates42/processing.py
78a237922c2a928b83f4ad579dbf8d32c0099890
[ "Apache-2.0" ]
253
2015-01-14T03:45:51.000Z
2022-02-08T01:18:19.000Z
mode/examples/Topics/Fractals and L-Systems/Tree/Tree.pyde
timgates42/processing.py
78a237922c2a928b83f4ad579dbf8d32c0099890
[ "Apache-2.0" ]
225
2015-01-13T18:38:33.000Z
2022-03-30T20:27:39.000Z
""" Recursive Tree by Daniel Shiffman. Renders a simple tree-like structure via recursion. The branching angle is calculated as a function of the horizontal mouse location. Move the mouse left and right to change the angle. """ def setup(): size(640, 360) def draw(): background(0) frameRate(30) stroke(255) # Let's pick an angle 0 to 90 degrees based on the mouse position a = (mouseX / float(width)) * 90 # Convert it to radians # Start the tree from the bottom of the screen translate(width / 2, height) # Draw a line 120 pixels line(0, 0, 0, -120) # Move to the end of that line translate(0, -120) # Start the recursive branching! branch(120, radians(a)) def branch(h, theta): # Each branch will be 2/3rds the size of the previous one h *= 0.66 # All recursive functions must have an exit condition!!!! # Here, ours is when the length of the branch is 2 pixels or less if h > 2: # Save the current state of transformation (i.e. where are we now) pushMatrix() rotate(theta) # Rotate by theta line(0, 0, 0, -h) # Draw the branch translate(0, -h) # Move to the end of the branch branch(h, theta) # Ok, now call myself to draw two branches!! # Whenever we get back here, we "pop" in order to restore the previous # matrix state popMatrix() # Repeat the same thing, only branch off to the "left" this time! with pushMatrix(): rotate(-theta) line(0, 0, 0, -h) translate(0, -h) branch(h, theta)
31.211538
78
0.61984
9ba0c4a5d260c4a81b2f42f5f4de1f25d02311e4
42
py
Python
Squest/version.py
slarimore02/squest
369cf7d6a15855d41da36e4689ddfe84c4c5acae
[ "Apache-2.0" ]
null
null
null
Squest/version.py
slarimore02/squest
369cf7d6a15855d41da36e4689ddfe84c4c5acae
[ "Apache-2.0" ]
null
null
null
Squest/version.py
slarimore02/squest
369cf7d6a15855d41da36e4689ddfe84c4c5acae
[ "Apache-2.0" ]
null
null
null
__version__ = "1.4" VERSION = __version__
14
21
0.738095
04a7e62cb17767369621cab8167890caca05cf65
12,902
py
Python
libretto/models/individu.py
dezede/dezede
985ed1b42a2a6bab996e26c1b92444ae04afcc2c
[ "BSD-3-Clause" ]
15
2015-02-10T21:16:31.000Z
2021-03-25T16:46:20.000Z
libretto/models/individu.py
dezede/dezede
985ed1b42a2a6bab996e26c1b92444ae04afcc2c
[ "BSD-3-Clause" ]
4
2021-02-10T15:42:08.000Z
2022-03-11T23:20:38.000Z
libretto/models/individu.py
dezede/dezede
985ed1b42a2a6bab996e26c1b92444ae04afcc2c
[ "BSD-3-Clause" ]
6
2016-07-10T14:20:48.000Z
2022-01-19T18:34:02.000Z
from django.core.exceptions import ValidationError from django.db import connection from django.db.models import ( CharField, ForeignKey, ManyToManyField, PROTECT, BooleanField) from django.urls import reverse from django.utils.html import strip_tags from django.utils.safestring import mark_safe from django.utils.translation import ( pgettext_lazy, ugettext, ugettext_lazy as _) from tinymce.models import HTMLField from common.utils.abbreviate import abbreviate from common.utils.html import href, sc, hlp from common.utils.text import str_list, str_list_w_last, ex from .base import ( CommonModel, AutoriteModel, UniqueSlugModel, TypeDeParente, PublishedManager, PublishedQuerySet, AncrageSpatioTemporel, slugify_unicode, ISNI_VALIDATORS) from .evenement import Evenement __all__ = ('TypeDeParenteDIndividus', 'ParenteDIndividus', 'Individu') class TypeDeParenteDIndividus(TypeDeParente): class Meta(object): unique_together = ('nom', 'nom_relatif') verbose_name = _('type de parenté d’individus') verbose_name_plural = _('types de parenté d’individus') ordering = ('classement',) @staticmethod def invalidated_relations_when_saved(all_relations=False): if all_relations: return ('parentes',) return () class ParenteDIndividus(CommonModel): type = ForeignKey('TypeDeParenteDIndividus', related_name='parentes', verbose_name=_('type'), on_delete=PROTECT) parent = ForeignKey('Individu', related_name='enfances', verbose_name=_('individu parent'), on_delete=PROTECT) enfant = ForeignKey('Individu', related_name='parentes', verbose_name=_('individu enfant'), on_delete=PROTECT) class Meta(object): verbose_name = _('parenté d’individus') verbose_name_plural = _('parentés d’individus') ordering = ('type', 'parent', 'enfant') @staticmethod def invalidated_relations_when_saved(all_relations=False): if all_relations: return ('parent', 'enfant') return () def clean(self): try: parent, enfant = self.parent, self.enfant except Individu.DoesNotExist: return if parent and enfant and parent == enfant: raise ValidationError(_('Un individu ne peut avoir une ' 'parenté avec lui-même.')) def __str__(self): return ugettext('%(parent)s, %(type)s de %(enfant)s') % { 'parent': self.parent, 'type': self.type.nom, 'enfant': self.enfant} class IndividuQuerySet(PublishedQuerySet): def are_feminins(self): return all(i.is_feminin() for i in self) class IndividuManager(PublishedManager): def get_queryset(self): return IndividuQuerySet(self.model, using=self._db) def are_feminins(self): return self.get_queryset().are_feminins() class Individu(AutoriteModel, UniqueSlugModel): particule_nom = CharField( _('particule du nom d’usage'), max_length=10, blank=True, db_index=True) # TODO: rendre le champ nom 'blank' nom = CharField(_('nom d’usage'), max_length=200, db_index=True) particule_nom_naissance = CharField( _('particule du nom de naissance'), max_length=10, blank=True, db_index=True) nom_naissance = CharField( _('nom de naissance'), max_length=200, blank=True, db_index=True, help_text=_('Ne remplir que s’il est différent du nom d’usage.')) prenoms = CharField(_('prénoms'), max_length=50, blank=True, db_index=True, help_text=ex('Antonio')) prenoms_complets = CharField( _('prénoms complets'), max_length=100, blank=True, db_index=True, help_text= ex('Antonio Lucio', post=' Ne remplir que s’il existe un ou des prénoms ' 'peu usités pour cet individu.')) pseudonyme = CharField(_('pseudonyme'), max_length=200, blank=True, db_index=True) DESIGNATIONS = ( ('S', _('Standard (nom, prénoms et pseudonyme)')), ('P', _('Pseudonyme (uniquement)')), ('L', _('Nom d’usage (uniquement)')), # L pour Last name ('B', _('Nom de naissance (standard)')), # B pour Birth name ('F', _('Prénom(s) (uniquement)')), # F pour First name ) designation = CharField(_('affichage'), max_length=1, choices=DESIGNATIONS, default='S') TITRES = ( ('M', _('M.')), ('J', _('Mlle')), # J pour Jouvencelle ('F', _('Mme')), ) titre = CharField(pgettext_lazy('individu', 'titre'), max_length=1, choices=TITRES, blank=True, db_index=True) naissance = AncrageSpatioTemporel(has_heure=False, verbose_name=_('naissance')) deces = AncrageSpatioTemporel(has_heure=False, verbose_name=_('décès')) professions = ManyToManyField( 'Profession', related_name='individus', blank=True, verbose_name=_('professions')) enfants = ManyToManyField( 'self', through='ParenteDIndividus', related_name='parents', symmetrical=False, verbose_name=_('enfants')) biographie = HTMLField(_('biographie'), blank=True) isni = CharField( _('Identifiant ISNI'), max_length=16, blank=True, validators=ISNI_VALIDATORS, help_text=_('Exemple : « 0000000121269154 » pour Mozart.')) sans_isni = BooleanField(_('sans ISNI'), default=False) objects = IndividuManager() class Meta(object): verbose_name = _('individu') verbose_name_plural = _('individus') ordering = ('nom',) permissions = (('can_change_status', _('Peut changer l’état')),) @staticmethod def invalidated_relations_when_saved(all_relations=False): relations = ('auteurs', 'elements_de_distribution',) if all_relations: relations += ('enfants', 'dossiers',) return relations def get_slug(self): parent = super(Individu, self).get_slug() return slugify_unicode(self.nom) or parent def get_absolute_url(self): return reverse('individu_detail', args=(self.slug,)) def permalien(self): return reverse('individu_permanent_detail', args=(self.pk,)) def link(self): return self.html() link.short_description = _('lien') def oeuvres(self): oeuvres = self.auteurs.oeuvres() return oeuvres.exclude(extrait_de__in=oeuvres) def oeuvres_with_descendants(self): return self.auteurs.oeuvres() def publications(self): return self.auteurs.sources() def apparitions(self): # FIXME: Gérer la période d’activité des membres d’un groupe. sql = """ SELECT DISTINCT COALESCE(distribution.evenement_id, programme.evenement_id) FROM libretto_elementdedistribution AS distribution LEFT JOIN libretto_elementdeprogramme AS programme ON (programme.id = distribution.element_de_programme_id) WHERE distribution.individu_id = %s """ with connection.cursor() as cursor: cursor.execute(sql, (self.pk,)) evenement_ids = [t[0] for t in cursor.fetchall()] return Evenement.objects.filter(id__in=evenement_ids) def evenements_referents(self): return Evenement.objects.filter( programme__oeuvre__auteurs__individu=self).distinct() def membre_de(self): return self.membres.order_by('-debut', 'instrument', 'classement') def calc_titre(self, tags=False): titre = self.titre if not titre: return '' if tags: if titre == 'M': return hlp(ugettext('M.'), 'Monsieur') elif titre == 'J': return hlp(ugettext('M<sup>lle</sup>'), 'Mademoiselle') elif titre == 'F': return hlp(ugettext('M<sup>me</sup>'), 'Madame') if titre == 'M': return ugettext('Monsieur') elif titre == 'J': return ugettext('Mademoiselle') elif titre == 'F': return ugettext('Madame') raise ValueError('Type de titre inconnu, il devrait être M, J, ou F.') def is_feminin(self): return self.titre in ('J', 'F',) def get_particule(self, naissance=False, lon=True): particule = (self.particule_nom_naissance if naissance else self.particule_nom) if lon and particule and particule[-1] not in "'’": return f'{particule} ' return particule def calc_professions(self, tags=True): if not self.pk: return '' return mark_safe( str_list_w_last( p.html(feminin=self.is_feminin(), tags=tags, caps=i == 0) for i, p in enumerate(self.professions.all()) ) ) calc_professions.short_description = _('professions') calc_professions.admin_order_field = 'professions__nom' def html(self, tags=True, lon=False, show_prenoms=True, designation=None, abbr=True, links=True): if designation is None: designation = self.designation titre = self.calc_titre(tags) prenoms = (self.prenoms_complets if lon and self.prenoms_complets else self.prenoms) nom = self.nom if lon: nom = f'{self.get_particule()}{nom}' pseudonyme = self.pseudonyme def standard(main, prenoms): particule = self.get_particule(naissance=(designation == 'B'), lon=lon) l = [] if nom and not prenoms: l.append(titre) l.append(main) if show_prenoms and (prenoms or particule and not lon): if lon: l.insert(max(len(l) - 1, 0), prenoms) else: if prenoms: prenoms = abbreviate(prenoms, tags=tags, enabled=abbr) if particule: particule = sc(particule, tags) prenom_and_particule = (f'{prenoms} {particule}' if prenoms and particule else (prenoms or particule)) l.append(f'({prenom_and_particule})') out = str_list(l, ' ') if pseudonyme: alias = (ugettext('dite') if self.is_feminin() else ugettext('dit')) out += f' {alias}\u00A0{pseudonyme}' return out if designation in 'SL': main = nom elif designation == 'F': main = prenoms elif designation == 'P': main = pseudonyme elif designation == 'B': nom_naissance = self.nom_naissance if lon: nom_naissance = f'{self.get_particule(True)}{nom_naissance}' main = nom_naissance main = sc(main, tags) out = standard(main, prenoms) if designation in 'SB' else main if tags: return href(self.get_absolute_url(), out, links) return out html.short_description = _('rendu HTML') def nom_seul(self, tags=False, abbr=False, links=False): return self.html(tags=tags, lon=False, show_prenoms=False, abbr=abbr, links=links) def nom_complet(self, tags=True, designation='S', abbr=False, links=True): return self.html(tags=tags, lon=True, designation=designation, abbr=abbr, links=links) def related_label(self, tags=False): return self.html(tags=tags, abbr=False) related_label.short_description = _('individu') def related_label_html(self): return self.related_label(tags=True) def clean(self): naissance = self.naissance.date deces = self.deces.date if naissance and deces and deces < naissance: message = _('Le décès ne peut précéder la naissance.') raise ValidationError({'naissance_date': message, 'deces_date': message}) if self.isni and self.sans_isni: message = _('« ISNI » ne peut être rempli ' 'lorsque « Sans ISNI » est coché.') raise ValidationError({'isni': message, 'sans_isni': message}) def __str__(self): return strip_tags(self.html(tags=False)) @staticmethod def autocomplete_search_fields(): return ( 'nom__unaccent__icontains', 'nom_naissance__unaccent__icontains', 'pseudonyme__unaccent__icontains', 'prenoms__unaccent__icontains', )
37.725146
83
0.600605
d021caacc345b859b3820976f94fc1111a1c87e4
1,507
py
Python
lecture09/zipcode.py
nd-cse-20289-sp22/cse-20289-sp22-examples
7ef32af96a7ed7679a01980bc0db83ef22058c31
[ "MIT" ]
1
2022-02-17T21:31:07.000Z
2022-02-17T21:31:07.000Z
lecture09/zipcode.py
nd-cse-20289-sp21/cse-20289-sp21-examples
490b49ea2d49de0daace44fa661c8878b6bdf6a4
[ "MIT" ]
null
null
null
lecture09/zipcode.py
nd-cse-20289-sp21/cse-20289-sp21-examples
490b49ea2d49de0daace44fa661c8878b6bdf6a4
[ "MIT" ]
8
2021-03-05T18:48:21.000Z
2021-05-23T15:11:56.000Z
#!/usr/bin/env python3 import os import re import sys import requests # Functions def usage(status=0): print(f'''Usage: {os.path.basename(sys.argv[0])} [flags] -c CITY Which city to search -s STATE Which state to search (Indiana)''') sys.exit(status) def zipcodes(city, state): url = f'https://www.zipcodestogo.com/{state}/' regex = r'/([^/]+)/[A-Z]{2}/([0-9]{5})/">' # Review: regex # Discuss: popen #response = os.popen('curl -sL {}'.format(url)).read() #for current, zipcode in re.findall(regex, response): headers = {'User-Agent': __name__} # Discuss: requests response = requests.get(url, headers=headers) # Discuss: re.findall for current, zipcode in re.findall(regex, response.text): if city is None or city == current: print(zipcode) def main(): state = 'Indiana' city = None # Review: None arguments = sys.argv[1:] # Review: parsing arguments while arguments and arguments[0].startswith('-'): argument = arguments.pop(0) if argument == '-c': city = arguments.pop(0) elif argument == '-s': state = arguments.pop(0) elif argument == '-h': usage(0) else: usage(1) zipcodes(city, state) # Main execution if __name__ == '__main__': main()
27.4
75
0.525547
78de1eae4a7e25191ccd8f485396746227b52fae
3,267
py
Python
email_queue.py
aroraumang/email-queue-1
1770bda5110b12a24cedeef03e083269e9d9ad46
[ "BSD-3-Clause" ]
null
null
null
email_queue.py
aroraumang/email-queue-1
1770bda5110b12a24cedeef03e083269e9d9ad46
[ "BSD-3-Clause" ]
null
null
null
email_queue.py
aroraumang/email-queue-1
1770bda5110b12a24cedeef03e083269e9d9ad46
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- """ email_queue.py """ from email.message import Message from trytond.model import ModelSQL, ModelView, fields from trytond.sendmail import get_smtp_server from trytond.transaction import Transaction __all__ = ['EmailQueue'] class EmailQueue(ModelSQL, ModelView): """ Email Queue """ __name__ = "email.queue" from_addr = fields.Char("From Address", required=True, readonly=True) to_addrs = fields.Char("To Addresses", required=True, readonly=True) msg = fields.Text("Message", required=True, readonly=True) attempts = fields.Integer("Attempts", required=True, readonly=True) state = fields.Selection([ ("outbox", "Outbox"), ("sending", "Sending"), ("sent", "Sent"), ("failed", "Failed"), ], "State", required=True, readonly=True) @staticmethod def default_state(): return "outbox" @staticmethod def default_attempts(): return 0 @classmethod def queue_mail(cls, from_addr, to_addrs, msg): """ Add the message to the email queue :param from_addr: Address from which the email is sent :type from_addr: String :param to_addres: A string or a list of string addresses. (a bare string will be treated as a list with 1 address) :param msg: RFC822 Message as a string or an instance of Message or its subclasses from email.mime module """ if isinstance(to_addrs, (list, tuple)): to_addrs = ','.join(to_addrs) if isinstance(msg, Message): msg = msg.as_string() return cls.create([{ 'from_addr': from_addr, 'to_addrs': to_addrs, 'msg': msg, }]) def send(self, smtp_server): """ Send this email with transaction safety using the given server """ assert self.state == 'outbox', 'Only mails in outbox can be sent' values = {'attempts': self.attempts + 1} with Transaction().new_transaction() as txn: try: self.write([self], {'state': 'sending'}) smtp_server.sendmail( self.from_addr, self.to_addrs.replace(';', ',').split(','), self.msg ) except Exception: txn.rollback() # Record the attempts and check if the mail has to be # marked for permanent failure with Transaction().new_transaction() as txn: if values['attempts'] >= 3: values['state'] = 'failed' self.write([self], values) txn.commit() # Finally raise the exception again raise else: values['state'] = 'sent' self.write([self], values) txn.commit() @classmethod def send_all(cls): """ Sends emails with the default SMTP server and marks them as sent. """ server = get_smtp_server() for mail in cls.search([('state', '=', 'outbox')]): mail.send(server) server.quit()
29.7
79
0.544536
bfa0b329f95975f21ee545458c656daea12ee0f1
4,139
py
Python
project/settings.py
cspt2-build-week-abr/Backend
2e349f3ff73db1cbe9bb4f13fceae4847fe47f2f
[ "MIT" ]
null
null
null
project/settings.py
cspt2-build-week-abr/Backend
2e349f3ff73db1cbe9bb4f13fceae4847fe47f2f
[ "MIT" ]
8
2019-12-04T23:44:37.000Z
2022-02-10T11:45:47.000Z
project/settings.py
cspt2-build-week-abr/Backend
2e349f3ff73db1cbe9bb4f13fceae4847fe47f2f
[ "MIT" ]
null
null
null
""" Django settings for project project. Generated by 'django-admin startproject' using Django 2.2.3. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'yl3k7@b7@-a6i(%nq^-970&*(0%=%)g%$+_j@xmzpzq=g6_wzy' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['mud-pokemon.herokuapp.com', '127.0.0.1', 'localhost'] # Application definition INSTALLED_APPS = [ 'corsheaders', 'mud', 'graphene_django', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] MIDDLEWARE = [ 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'project.urls' CORS_ORIGIN_ALLOW_ALL = True CORS_ORIGIN_WHITELIST = ( 'http://localhost:3000', ) CSRF_COOKIE_SECURE = False TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'project.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' GRAPHENE = { 'SCHEMA': 'mud.schema.schema', } # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.11/howto/static-files/ PROJECT_ROOT = os.path.join(os.path.abspath(__file__)) STATIC_ROOT = os.path.join(PROJECT_ROOT, 'staticfiles') STATIC_URL = '/static/' # Extra lookup directories for collectstatic to find static files STATICFILES_DIRS = ( os.path.join(PROJECT_ROOT, 'static'), ) # Add configuration for static files storage using whitenoise STATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage' import dj_database_url prod_db = dj_database_url.config(conn_max_age=500) DATABASES['default'].update(prod_db)
27.052288
91
0.708867
3172f7c8257ac226b61908e6a7ad8809bda81362
501
py
Python
VernamCipher ~ Encoder and Decoder.py
MichaelWiciak/Ciphers
15cb979448ccc74b148877ae06142666f55187df
[ "MIT" ]
null
null
null
VernamCipher ~ Encoder and Decoder.py
MichaelWiciak/Ciphers
15cb979448ccc74b148877ae06142666f55187df
[ "MIT" ]
null
null
null
VernamCipher ~ Encoder and Decoder.py
MichaelWiciak/Ciphers
15cb979448ccc74b148877ae06142666f55187df
[ "MIT" ]
null
null
null
class VernamCipher(object): def __init__(self): self.__key = "abcdefghijklmnbodujdjhdabcdefghijklmnbodujdjhd" def useVernamCipher(self,stringToBeEncrypted): text = stringToBeEncrypted encryptedText = "" pointer = 0 for char in text: encryptedText += chr(ord(char) ^ ord(self.__key[pointer])) pointer += 1 if pointer ==len(self.__key): pointer = 0 return encryptedText
31.3125
71
0.576846
8abcccffdbd0a766917c2fc6d5e0462a58fceeb3
8,464
py
Python
platform/android/scripts/release.py
kravtsun/mapbox-gl-native
ea8ec38df156c6683c886253dbb1f6bc828686ff
[ "BSL-1.0", "Apache-2.0" ]
null
null
null
platform/android/scripts/release.py
kravtsun/mapbox-gl-native
ea8ec38df156c6683c886253dbb1f6bc828686ff
[ "BSL-1.0", "Apache-2.0" ]
null
null
null
platform/android/scripts/release.py
kravtsun/mapbox-gl-native
ea8ec38df156c6683c886253dbb1f6bc828686ff
[ "BSL-1.0", "Apache-2.0" ]
null
null
null
''' Utility to schedule SDK builds in Bitrise. Examples: - Publish a snapshot from master (release.py uses the current branch) $ git branch * master 1234-fix-crash $ python release.py --stage snapshot - Publish a snapshot from a feature branch (same as before, just switch branchs with git): $ git branch master * 1234-fix-crash $ python release.py --stage snapshot - Publish a beta from a pre-release branch: $ git branch master * release-android-420-beta1 $ python release.py --stage beta --version 4.2.0-beta.1 - Publish a beta from a release branch: $ git branch master * release-android-420 $ python release.py --stage final --version 4.2.0 TODO: - Add a flag to wait until the release has been built (Bitrise) and published (Maven). ''' import click import json import os import requests import subprocess # Three stages, from less stable to more stable ALLOWED_STAGES = ['snapshot', 'beta', 'final'] # Get the version from GRADLE_PROPERTIES_PATH below CURRENT_VERSION_TAG = 'current' # You can find the API token in https://www.bitrise.io/app/79cdcbdc42de4303#/code -> API token BITRISE_API_TOKEN_ENV_VAR = 'BITRISE_API_TOKEN' # In the future we might want to consider alpha, or rc. ALLOWED_PRE_RELEASE = ['beta'] # We get the default version from here MAPBOX_GL_ANDROID_SDK_PATH = '../MapboxGLAndroidSDK' GRADLE_PROPERTIES_PATH = '%s/gradle.properties' % MAPBOX_GL_ANDROID_SDK_PATH GRADLE_TOKEN = 'VERSION_NAME=' FABRIC_PROPERTIES_PATH = '%s/src/main/resources/fabric/com.mapbox.mapboxsdk.mapbox-android-sdk.properties' % MAPBOX_GL_ANDROID_SDK_PATH FABRIC_TOKEN = 'fabric-version=' # Bitrise URL_BITRISE = 'https://www.bitrise.io/app/79cdcbdc42de4303/build/start.json' # We support three parameters: stage, branch, and version @click.command() @click.option('--stage', default=ALLOWED_STAGES[0], type=click.Choice(ALLOWED_STAGES), prompt='Set stage', help='The release stage.') @click.option('--version', default=CURRENT_VERSION_TAG, prompt='Set version', help='The version you want to publish. E.g: 4.2.0-SNAPSHOT, 4.2.0-beta.1, or 4.2.0. If you set the version to "%s", the script will default to the current SNAPSHOT version.' % CURRENT_VERSION_TAG) def release(stage, version): # Validate params final_stage = validate_stage(stage=stage) final_branch = validate_branch(stage=final_stage) final_version = validate_version(stage=final_stage, branch=final_branch, version=version) # Get user confirmation click.echo('\n===== Build information =====') click.echo('- Stage: %s' % final_stage) click.echo('- Branch: %s' % final_branch) click.echo('- Version: %s' % final_version) click.confirm('\nDoes it look right?', abort=True) # Proceed if (final_stage == 'snapshot'): publish_snapshot(branch=final_branch, version=final_version) elif (final_stage == 'beta'): publish_beta(branch=final_branch, version=final_version) elif (final_stage == 'final'): publish_final(branch=final_branch, version=final_version) def validate_stage(stage): if stage not in ALLOWED_STAGES: abort_with_message('Invalid stage: %s' % stage) return stage def validate_branch(stage): branch = git_get_current_branch() if not branch: abort_with_message('The current folder is not a git repository.') if branch == 'master' and stage != 'snapshot': abort_with_message('You need to swtich to a release branch for a beta or a final release.') return branch def validate_version(stage, branch, version): if stage == 'snapshot' and branch == 'master' and version != CURRENT_VERSION_TAG: abort_with_message('You cannot specify a custom version if you are building a snapshot from master.') if not version or version == CURRENT_VERSION_TAG: version = get_current_version(file_path=GRADLE_PROPERTIES_PATH, file_var=GRADLE_TOKEN) if stage == 'snapshot': if not 'SNAPSHOT' in version: abort_with_message('Version should contain the word SNAPSHOT: %s' % version) elif stage == 'beta': if not ALLOWED_PRE_RELEASE[0] in version: abort_with_message('Version should contain the word %s: %s' % (ALLOWED_PRE_RELEASE[0], version)) elif stage == 'final': if not version or 'SNAPSHOT' in version or ALLOWED_PRE_RELEASE[0] in version: abort_with_message('Version cannot be empty, or contain the words SNAPSHOT or %s: %s' % (ALLOWED_PRE_RELEASE[0], version)) return version def publish_snapshot(branch, version): click.echo('Publishing snapshot for branch: %s (version: %s).' % (branch, version)) if branch != 'master': dirty_gradle = update_current_version(file_path=GRADLE_PROPERTIES_PATH, file_var=GRADLE_TOKEN, version=version) if dirty_gradle: git_add(path=GRADLE_PROPERTIES_PATH) git_commit_and_push(branch=branch, version=version) do_bitrise_request(build_params={'branch': branch, 'workflow_id': 'scheduled'}) def publish_beta(branch, version): click.echo('Publishing beta from branch: %s (version: %s).' % (branch, version)) dirty_gradle = update_current_version(file_path=GRADLE_PROPERTIES_PATH, file_var=GRADLE_TOKEN, version=version) if dirty_gradle: git_add(path=GRADLE_PROPERTIES_PATH) git_commit_and_push(branch=branch, version=version) do_bitrise_request(build_params={'branch': branch, 'workflow_id': 'scheduled'}) def publish_final(branch, version): click.echo('Publishing final release from branch: %s (version: %s).' % (branch, version)) dirty_gradle = update_current_version(file_path=GRADLE_PROPERTIES_PATH, file_var=GRADLE_TOKEN, version=version) if dirty_gradle: git_add(path=GRADLE_PROPERTIES_PATH) dirty_fabric = update_current_version(file_path=FABRIC_PROPERTIES_PATH, file_var=FABRIC_TOKEN, version=version) if dirty_fabric: git_add(path=FABRIC_PROPERTIES_PATH) if dirty_gradle or dirty_fabric: git_commit_and_push(branch=branch, version=version) do_bitrise_request(build_params={'branch': branch, 'workflow_id': 'scheduled'}) # # Utils # def abort_with_message(message): click.echo(message) click.get_current_context().abort() def execute_call(command): click.echo('Executing: %s' % command) result = subprocess.call(command, shell=True) if result != 0: abort_with_message('Command failed: %s' % command) # # Bitrise # def get_bitrise_api_token(): bitrise_api_token = os.environ.get(BITRISE_API_TOKEN_ENV_VAR) if not bitrise_api_token: abort_with_message('You need to set the BITRISE_API_TOKEN environment variable.') click.echo('Found Bitrise API token.') return bitrise_api_token def do_bitrise_request(build_params): data = { 'hook_info': {'type': 'bitrise', 'api_token': get_bitrise_api_token()}, 'build_params' : build_params} click.echo('Bitrise request data: %s' % json.dumps(data)) click.confirm('\nDo you want to start a build?', abort=True) r = requests.post(URL_BITRISE, data=json.dumps(data)) click.echo('- Bitrise response code: %s' % r.status_code) click.echo('- Bitrise response content: %s' % r.text) # # Git # def git_get_current_branch(): return subprocess.check_output('git symbolic-ref --short HEAD'.split(' ')).strip() def git_add(path): execute_call(command='git add %s' % path) def git_commit_and_push(branch, version): message = '[android] [auto] Update properties to version %s in preparation for build.' % version commands = [ 'git commit -m "%s"' % message, 'git push -u origin %s' % branch] for command in commands: execute_call(command=command) # # Read and update properties files # def get_current_version(file_path, file_var): click.echo('Getting current version from %s.' % file_path) with open(file_path, 'r') as f: for line in f: if line.startswith(file_var): version_name = line[len(file_var):].strip() click.echo('Current version is %s.' % version_name) return version_name return None def update_current_version(file_path, file_var, version): dirty = False click.echo('Updating file to version %s: %s.' % (version, file_path)) with open(file_path, 'r') as f: file_lines = f.readlines() for line_number in range(len(file_lines)): if file_lines[line_number].startswith(file_var): content_old = file_lines[line_number] content_new = '%s%s\n' % (file_var, version) if (content_old != content_new): click.echo('%s -> %s' % (content_old.strip(), content_new.strip())) file_lines[line_number] = content_new dirty = True if dirty: with open(file_path, 'w') as f: f.writelines(file_lines) else: click.echo('File already has the right version.') return dirty if __name__ == '__main__': release()
34.688525
274
0.749055
b03962a578373ef3ac798cbf8f27f25faac7340a
18,157
py
Python
remindmebot_reply.py
jjmerri/xrpRemindMe-Reddit
37d833e742e1614dc6454384810a6f69e41cf941
[ "MIT" ]
null
null
null
remindmebot_reply.py
jjmerri/xrpRemindMe-Reddit
37d833e742e1614dc6454384810a6f69e41cf941
[ "MIT" ]
null
null
null
remindmebot_reply.py
jjmerri/xrpRemindMe-Reddit
37d833e742e1614dc6454384810a6f69e41cf941
[ "MIT" ]
null
null
null
#!/usr/bin/env python3.6 # ============================================================================= # IMPORTS # ============================================================================= import praw import MySQLdb import traceback from threading import Thread, Lock import os import sys import configparser import time import requests import logging from datetime import datetime from requests.exceptions import HTTPError, ConnectionError, Timeout from praw.exceptions import APIException, ClientException, PRAWException from socket import timeout # ============================================================================= # GLOBALS # ============================================================================= # Reads the config file config = configparser.ConfigParser() config.read("remindmebot.cfg") bot_username = config.get("Reddit", "username") bot_password = config.get("Reddit", "password") client_id = config.get("Reddit", "client_id") client_secret = config.get("Reddit", "client_secret") #Reddit info reddit = praw.Reddit(client_id=client_id, client_secret=client_secret, password=bot_password, user_agent='cryptoRemindMe by /u/BoyAndHisBlob', username=bot_username) # DB Info DB_USER = config.get("SQL", "user") DB_PASS = config.get("SQL", "passwd") ENVIRONMENT = config.get("REMINDME", "environment") DEV_USER_NAME = "BoyAndHisBlob" FORMAT = '%(asctime)-15s %(message)s' logging.basicConfig(format=FORMAT) logger = logging.getLogger('cryptoRemindMeBot') logger.setLevel(logging.INFO) supported_tickers = ["ADA","BCH","BCN","BTC","BTG","DASH","DOGE","ETC","ETH","LSK","LTC","NEO","QASH","QTUM","REQ", "STEEM","XEM","XLM","XMR","XRB","XRP","ZEC"] MAX_API_TIME_LIMIT = 2000 cc_max_api_per_sec = 15 cc_total_api_calls = 0 cc_api_lock = Lock() # ============================================================================= # CLASSES # ============================================================================= class DbConnectiton(object): """ DB connection class """ connection = None cursor = None def __init__(self): self.connection = MySQLdb.connect( host="localhost", user=DB_USER, passwd=DB_PASS, db="crypto_remind_me" ) self.cursor = self.connection.cursor() class Reply(object): def __init__(self): self._db_connection = DbConnectiton() self._replyMessage =( "cryptoRemindMeBot private message here!" "\n\n**The message:** \n\n>{message}" "\n\n**The original comment:** \n\n>{original}" "\n\n**The parent comment from the original comment or its submission:** \n\n>{parent}" "{origin_date_text}" "\n\nYou requested a reminder when the price of {ticker} reached {new_price} from {origin_price}." "\n\nThe price hit {price} at {price_time} using CryptoCompare's Current Aggregate." "\n\n_____\n\n" "^| [^(README)](https://github.com/jjmerri/cryptoRemindMe-Reddit/blob/master/README.md)" " ^| [^(Your Reminders)](http://np.reddit.com/message/compose/?to=cryptoRemindMeBot&subject=List Of Reminders&message=MyReminders!)" " ^| [^(Feedback)](http://np.reddit.com/message/compose/?to=BoyAndHisBlob&subject=cryptoRemindMe Feedback)" " ^| [^(Code)](https://github.com/jjmerri/cryptoRemindMe-Reddit)" " ^| [^(Tip BoyAndHisBlob)](https://blobware-tips.firebaseapp.com)" ) self.last_price_time = {} self._price_history = {} self.lock = Lock() def set_price_extremes(self): """ Sets the high and low since the last run """ global cc_total_api_calls #reset number of calls for new iteration cc_total_api_calls = 0 lastrun_file = open("lastrun.txt", "r") lastrun_sec = {} for lastrun in lastrun_file.read().splitlines(): values = lastrun.split(" ") if len(values) == 2: lastrun_sec[values[0]] = int(values[1]) lastrun_file.close() price_threads = []; for supported_ticker in supported_tickers: current_time_sec = int(time.time()) if supported_ticker in lastrun_sec: mins_since_lastrun = (current_time_sec - lastrun_sec[supported_ticker]) // 60 else: #max allowed by API mins_since_lastrun = MAX_API_TIME_LIMIT if mins_since_lastrun > MAX_API_TIME_LIMIT: mins_since_lastrun = MAX_API_TIME_LIMIT #Get data from at least 10 min back mins_since_lastrun = mins_since_lastrun if mins_since_lastrun >= 10 else 10 #Thread api calls because they take a while in succession t = Thread(target=self._update_price_data, args=[supported_ticker, mins_since_lastrun]) price_threads.append(t) t.start() #Wait for all price data to be set for price_thread in price_threads: price_thread.join() for supported_ticker in supported_tickers: if supported_ticker in self._price_history: #false if we couldnt retriev price data from the API for minute_data in self._price_history[supported_ticker]: high = minute_data['high'] low = minute_data['low'] #sometimes the API incorrectly returns 0 so this is an attempt to avoid incorrectly notifying on 0 price if high > 0 and low > 0: if (supported_ticker + "_high") not in self._price_history or high > self._price_history[supported_ticker + "_high"]: self._price_history[supported_ticker + "_high"] = high self._price_history[supported_ticker + "_high_time"] = minute_data['time'] if (supported_ticker + "_low") not in self._price_history or low < self._price_history[supported_ticker + "_low"]: self._price_history[supported_ticker + "_low"] = low self._price_history[supported_ticker + "_low_time"] = minute_data['time'] if supported_ticker not in self.last_price_time or minute_data['time'] > self.last_price_time[supported_ticker]: self.last_price_time[supported_ticker] = minute_data['time'] def _update_price_data(self, ticker, limit): """ :param ticker: the ticker for the crypto that the price info is being updated for :param limit: number of minutes back to get the price data """ global cc_total_api_calls api_url = 'https://min-api.cryptocompare.com/data/histominute?fsym={ticker}&tsym=USD&e=CCCAGG&limit={limit}'.format( ticker = ticker, limit = str(limit)) api_error_count = 0 #Loop to retry getting API data. Will break on success or 10 consecutive errors while True: #if we exceed the allowed number of api calls wait and reset counters #wait is set to 2 seconds because 1 isnt enough for some reason #even though the API says 15 calls per second with cc_api_lock: if cc_total_api_calls >= cc_max_api_per_sec: time.sleep(2) cc_total_api_calls = 0 cc_total_api_calls += 1 r = requests.get(api_url) response = r.json() #If not success then retry up to 10 times after 1 sec wait if response.get("Response", "Error") != "Success": api_error_count += 1 print("Retry number {error_count} Retrieving {ticker} Info".format(ticker = ticker, error_count = api_error_count)) time.sleep(1) if api_error_count >= 10: send_dev_pm("Error Retrieving {ticker} Info".format(ticker = ticker), "Max error count hit. Could not retrieve histo info from {url}".format(url = api_url)) break #dont infinite loop. Maybe the API is down. else: break #Not sure if this lock is necessary but it makes me feel better and adds little overhead with self.lock: self._price_history[ticker] = response['Data'] def _parent_comment(self, commentId): """ Returns the parent comment or if it's a top comment return the original submission """ try: comment = reddit.comment(id=commentId) if comment.is_root: return comment.submission.permalink else: return comment.parent().permalink except IndexError as err: logger.exception("parrent_comment error") return "It seems your original comment was deleted, unable to return parent comment." # Catch any URLs that are not reddit comments except Exception as err: logger.exception("HTTPError/PRAW parent comment") return "Parent comment not required for this URL." def populate_reply_list(self): """ Checks to see through SQL if net_date is < current time """ select_statement = "SELECT * FROM reminder WHERE " single_where_clause = "(new_price <= %s AND new_price >= origin_price AND ticker = %s) OR (new_price >= %s AND new_price <= origin_price AND ticker = %s)" where_clause = ((single_where_clause + " OR ") * len(supported_tickers))[0:-4] cmd = select_statement + where_clause cmd_args = [] for supported_ticker in supported_tickers: if (supported_ticker + "_high") in self._price_history and (supported_ticker + "_low") in self._price_history: cmd_args.append(self._price_history[supported_ticker + "_high"]) cmd_args.append(supported_ticker) cmd_args.append(self._price_history[supported_ticker + "_low"]) cmd_args.append(supported_ticker) else: #remove a where clause + " AND " cmd_minus_where_length = len(single_where_clause) + 4 cmd = cmd[:(cmd_minus_where_length * -1)] self._db_connection.cursor.execute(cmd, cmd_args) def send_replies(self): """ Loop through data looking for which comments are old """ data = self._db_connection.cursor.fetchall() already_commented = [] for row in data: # checks to make sure ID hasn't been commented already # For situtations where errors happened if row[0] not in already_commented: ticker = row[9] object_name = row[1] new_price = row[3] origin_price = row[4] comment_create_datetime = row[10] send_reply = False message_price = 0.0 message_price_time = 0 try: for minute_data in self._price_history[ticker]: price_high = minute_data['high'] price_low = minute_data['low'] price_time = minute_data['time'] if price_time >= comment_create_datetime.timestamp(): if new_price <= price_high and new_price >= origin_price: message_price = price_high elif new_price >= price_low and new_price <= origin_price: message_price = price_low else: # This is not the minute_data that triggered the reply continue message_price_time = price_time send_reply = True break except IndexError as err: logger.exception("IndexError in send_replies") send_reply = False # Catch any URLs that are not reddit comments except Exception as err: logger.exception("Unknown Exception send_replies") send_reply = False if send_reply: # MySQl- object_name, message, comment_create_datetime, reddit user, new_price, origin_price, permalink, ticker, message_price_time, message_price delete_message = self._send_reply(object_name, row[2], comment_create_datetime, row[5], new_price, origin_price, row[8], ticker, message_price_time, message_price) if delete_message: cmd = "DELETE FROM reminder WHERE id = %s" self._db_connection.cursor.execute(cmd, [row[0]]) self._db_connection.connection.commit() already_commented.append(row[0]) self._db_connection.connection.commit() self._db_connection.connection.close() def _send_reply(self, object_name, message, comment_create_datetime, author, new_price, origin_price, permalink, ticker, message_price_time, message_price): """ Replies a second time to the user after a set amount of time """ logger.info("---------------") logger.info(author) logger.info(object_name) utc_create_date_str = str(datetime.utcfromtimestamp(comment_create_datetime.timestamp())) origin_date_text = ("\n\nYou requested this reminder on: " "[" + utc_create_date_str + " UTC](http://www.wolframalpha.com/input/?i=" + utc_create_date_str + " UTC To Local Time)") message_price_datetime = datetime.utcfromtimestamp(message_price_time) message_price_datetime_formatted = ("[" + format(message_price_datetime, '%Y-%m-%d %H:%M:%S') + " UTC](http://www.wolframalpha.com/input/?i=" + format(message_price_datetime, '%Y-%m-%d %H:%M:%S') + " UTC To Local Time)") try: reddit.redditor(str(author)).message('cryptoRemindMeBot Reminder!', self._replyMessage.format( message=message, original=permalink, parent= self._parent_comment(object_name), origin_date_text = origin_date_text, new_price = '${:,.4f}'.format(new_price), origin_price = '${:,.4f}'.format(origin_price), price = '${:,.4f}'.format(message_price), price_time = message_price_datetime_formatted, ticker = ticker )) logger.info("Sent Reply") return True except APIException as err: logger.exception("APIException in _send_reply") return False except IndexError as err: logger.exception("IndexError in _send_reply") return False except (HTTPError, ConnectionError, Timeout, timeout) as err: logger.exception("HTTPError in _send_reply") time.sleep(10) return False except ClientException as err: logger.exception("ClientException in _send_reply") time.sleep(10) return False except PRAWException as err: logger.exception("PRAWException in _send_reply") time.sleep(10) return False except Exception as err: logger.exception("Unknown Exception in _send_reply") return False def update_last_run(checkReply): lastrun_tickers = "" for supported_ticker in supported_tickers: # dont let 0 get into the lastrun.txt. It breaks the api call to get the prices if supported_ticker not in checkReply.last_price_time: checkReply.last_price_time[supported_ticker] = 10000 lastrun_tickers += supported_ticker + " " + str( checkReply.last_price_time.get(supported_ticker, "10000")) + "\n" lastrun_file = open("lastrun.txt", "w") lastrun_file.write(lastrun_tickers) lastrun_file.close() def create_running(): running_file = open("reply_bot.running", "w") running_file.write(str(os.getpid())) running_file.close() def send_dev_pm(subject, body): reddit.redditor(DEV_USER_NAME).message(subject, body) # ============================================================================= # MAIN # ============================================================================= def main(): logger.info("start") start_process = False if ENVIRONMENT == "DEV": os.remove("reply_bot.running") logger.info("running file removed") if not os.path.isfile("reply_bot.running"): create_running() start_process = True else: start_process = False logger.error("Reply already running! Will not start.") while start_process and os.path.isfile("reply_bot.running"): try: logger.info("Start Main Loop") checkReply = Reply() checkReply.set_price_extremes() checkReply.populate_reply_list() checkReply.send_replies() update_last_run(checkReply) logger.info("End Main Loop") time.sleep(600) except Exception as err: logger.exception("Unknown Exception in main loop") try: send_dev_pm("Unknown Exception in main loop", "Error: {exception}\n\n{trace}".format(exception = str(err), trace = traceback.format_exc())) except Exception as err: logger.exception("Unknown senidng dev pm") time.sleep(600) sys.exit() # ============================================================================= # RUNNER # ============================================================================= if __name__ == '__main__': main()
41.933025
183
0.572506
9b6b15d81bc8dd6e2805778ad9b2932ae0d7f3d2
5,359
py
Python
init2winit/dataset_lib/datasets.py
google/init2winit
62ec9fd31bd7b38bb7c220f15d4187bf0706506d
[ "Apache-2.0" ]
32
2021-05-15T01:03:44.000Z
2022-03-31T10:54:48.000Z
init2winit/dataset_lib/datasets.py
google/init2winit
62ec9fd31bd7b38bb7c220f15d4187bf0706506d
[ "Apache-2.0" ]
31
2021-05-20T08:03:40.000Z
2022-03-31T10:27:42.000Z
init2winit/dataset_lib/datasets.py
google/init2winit
62ec9fd31bd7b38bb7c220f15d4187bf0706506d
[ "Apache-2.0" ]
6
2021-05-20T06:10:04.000Z
2022-03-31T18:55:04.000Z
# coding=utf-8 # Copyright 2021 The init2winit Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Data generators for init2winit.""" import collections from init2winit.dataset_lib import fake_dataset from init2winit.dataset_lib import imagenet_dataset from init2winit.dataset_lib import mlperf_imagenet_dataset from init2winit.dataset_lib import nqm_noise from init2winit.dataset_lib import ogbg_molpcba from init2winit.dataset_lib import proteins from init2winit.dataset_lib import small_image_datasets from init2winit.dataset_lib import translate_wmt _Dataset = collections.namedtuple('Dataset', ('getter', 'hparams', 'meta_data')) _ALL_DATASETS = { 'mnist': _Dataset(small_image_datasets.get_mnist, small_image_datasets.MNIST_HPARAMS, small_image_datasets.MNIST_METADATA), 'mnist_autoencoder': _Dataset(small_image_datasets.get_mnist_autoencoder, small_image_datasets.MNIST_AUTOENCODER_HPARAMS, small_image_datasets.MNIST_AUTOENCODER_METADATA), 'fashion_mnist': _Dataset(small_image_datasets.get_fashion_mnist, small_image_datasets.FASHION_MNIST_HPARAMS, small_image_datasets.FASHION_MNIST_METADATA), 'cifar10': _Dataset(small_image_datasets.get_cifar10, small_image_datasets.CIFAR10_DEFAULT_HPARAMS, small_image_datasets.CIFAR10_METADATA), 'cifar100': _Dataset(small_image_datasets.get_cifar100, small_image_datasets.CIFAR100_DEFAULT_HPARAMS, small_image_datasets.CIFAR100_METADATA), 'fake': _Dataset(fake_dataset.get_fake, fake_dataset.DEFAULT_HPARAMS, fake_dataset.METADATA), 'imagenet': _Dataset(imagenet_dataset.get_imagenet, imagenet_dataset.DEFAULT_HPARAMS, imagenet_dataset.METADATA), 'translate_wmt': _Dataset(translate_wmt.get_translate_wmt, translate_wmt.DEFAULT_HPARAMS, translate_wmt.METADATA), 'mlperf_imagenet': _Dataset(mlperf_imagenet_dataset.get_mlperf_imagenet, mlperf_imagenet_dataset.DEFAULT_HPARAMS, mlperf_imagenet_dataset.METADATA), 'svhn_no_extra': _Dataset(small_image_datasets.get_svhn_no_extra, small_image_datasets.SVHN_NO_EXTRA_DEFAULT_HPARAMS, small_image_datasets.SVHN_NO_EXTRA_METADATA), 'nqm_noise': _Dataset(nqm_noise.get_nqm_noise, nqm_noise.NQM_HPARAMS, nqm_noise.NQM_METADATA), 'ogbg_molpcba': _Dataset(ogbg_molpcba.get_ogbg_molpcba, ogbg_molpcba.DEFAULT_HPARAMS, ogbg_molpcba.METADATA), 'uniref50': _Dataset(proteins.get_uniref, proteins.DEFAULT_HPARAMS, proteins.METADATA), } def get_dataset(dataset_name): """Maps dataset name to a dataset_builder.""" try: return _ALL_DATASETS[dataset_name].getter except KeyError: raise ValueError('Unrecognized dataset: {}'.format(dataset_name)) def get_dataset_hparams(dataset_name): """Maps dataset name to default_hps.""" try: hparams = _ALL_DATASETS[dataset_name].hparams # TODO(mbadura): Refactor to explicitly support different input specs if 'input_shape' not in hparams or hparams.input_shape is None: if 'input_edge_shape' in hparams and 'input_node_shape' in hparams: hparams.input_shape = (hparams.input_node_shape, hparams.input_edge_shape) elif dataset_name == 'lm1b': max_len = max(hparams.max_target_length, hparams.max_eval_target_length) hparams.input_shape = (max_len,) elif dataset_name == 'translate_wmt': max_len = max(hparams.max_target_length, hparams.max_eval_target_length, hparams.max_predict_length) hparams.input_shape = [(max_len,), (max_len,)] else: raise ValueError( 'Undefined input shape for dataset: {}'.format(dataset_name)) return hparams except KeyError: raise ValueError('Unrecognized dataset: {}'.format(dataset_name)) def get_dataset_meta_data(dataset_name): """Maps dataset name to a dict of dataset meta_data. meta_data is a dictionary where the keys will depend on the dataset. Required keys - All models: num_classes, is_one_hot This dictionary will be referenced by the model constructor. New datasets may have new keys, this will work as long as the model references the key properly. Args: dataset_name: (str) the name of the dataset. Returns: A dict of dataset metadata as described above. Raises: ValueError, if the dataset_name is not in _ALL_DATASETS. """ try: return _ALL_DATASETS[dataset_name].meta_data except KeyError: raise ValueError('Unrecognized dataset: {}'.format(dataset_name))
39.696296
80
0.718418
92945ac983ee2d3471ddca6d814360139a20e1f0
9,462
py
Python
src/cray/boa/s3client.py
Cray-HPE/boa
0718b5a1f40134f16b7279a93f545d9f5ca2b664
[ "MIT" ]
null
null
null
src/cray/boa/s3client.py
Cray-HPE/boa
0718b5a1f40134f16b7279a93f545d9f5ca2b664
[ "MIT" ]
2
2022-03-09T18:00:45.000Z
2022-03-29T18:54:52.000Z
src/cray/boa/s3client.py
Cray-HPE/boa
0718b5a1f40134f16b7279a93f545d9f5ca2b664
[ "MIT" ]
null
null
null
# # MIT License # # (C) Copyright 2020-2022 Hewlett Packard Enterprise Development LP # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included # in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, # ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS IN THE SOFTWARE. # ''' Created on February 5th, 2020 @author: jasons ''' import json import logging import os import boto3 from botocore.exceptions import ClientError from botocore.config import Config as BotoConfig from urllib.parse import urlparse from . import TooManyArtifacts, ArtifactMissing, NontransientException LOGGER = logging.getLogger(__name__) class S3MissingConfiguration(NontransientException): """ We were missing configuration information need to contact S3. """ class S3Url(object): """ https://stackoverflow.com/questions/42641315/s3-urls-get-bucket-name-and-path/42641363 """ def __init__(self, url): self._parsed = urlparse(url, allow_fragments=False) @property def bucket(self): return self._parsed.netloc @property def key(self): if self._parsed.query: return self._parsed.path.lstrip('/') + '?' + self._parsed.query else: return self._parsed.path.lstrip('/') @property def url(self): return self._parsed.geturl() def s3_client(connection_timeout=60, read_timeout=60): """ Return an s3 client Args: connection_timeout -- Number of seconds to wait to time out the connection Default: 60 seconds read_timeout -- Number of seconds to wait to time out a read Default: 60 seconds Returns: Returns an s3 client object Raises: S3MissingConfiguration -- it cannot contact S3 because it did not have the proper credentials or configuration """ try: s3_access_key = os.environ['S3_ACCESS_KEY'] s3_secret_key = os.environ['S3_SECRET_KEY'] s3_protocol = os.environ['S3_PROTOCOL'] s3_gateway = os.environ['S3_GATEWAY'] except KeyError as error: LOGGER.error("Missing needed S3 configuration: %s", error) raise S3MissingConfiguration(error) from error s3 = boto3.client('s3', endpoint_url=s3_protocol + "://" + s3_gateway, aws_access_key_id=s3_access_key, aws_secret_access_key=s3_secret_key, use_ssl=False, verify=False, config=BotoConfig( connect_timeout=connection_timeout, read_timeout=read_timeout)) return s3 class S3Object: """ A generic S3 object. It provides a way to download the object. """ def __init__(self, path, etag=None): """ Args: path (string): S3 path to the S3 object etag (string): S3 entity tag """ self.path = path self.etag = etag self.s3url = S3Url(self.path) @property def object_header(self): """ Get the S3 object's header metadata. Return: The S3 object headers Raises: ClientError """ try: s3 = s3_client() s3_obj = s3.head_object( Bucket=self.s3url.bucket, Key=self.s3url.key ) except ClientError as error: LOGGER.error("s3 object %s was not found.", self.path) LOGGER.debug(error) raise if self.etag and self.etag != s3_obj["ETag"].strip('\"'): LOGGER.warning("s3 object %s was found, but has an etag '%s' that does " "not match what BOS has '%s'.", self.path, s3_obj["ETag"], self.etag) return s3_obj @property def object(self): """ The S3 object itself. If the object was not found, log it and return an error. Args: path -- path to the S3 key etag -- Entity tag Return: S3 Object Raises: boto3.execptions.ClientError -- when it cannot read from S3 """ s3 = s3_client() LOGGER.info("++ _get_s3_download_url %s with etag %s.", self.path, self.etag) try: return s3.get_object(Bucket=self.s3url.bucket, Key=self.s3url.key) except ClientError as error: LOGGER.error("Unable to download object {}.".format(self.path)) LOGGER.debug(error) raise class S3BootArtifacts(S3Object): def __init__(self, path, etag=None): """ Args: path (string): S3 path to the S3 object etag (string): S3 entity tag """ S3Object.__init__(self, path, etag) self._manifest_json = None @property def manifest_json(self): """ Read a manifest.json file from S3. If the object was not found, log it and return an error. Args: path -- path to the S3 key etag -- Entity tag Return: Manifest file in JSON format Raises: boto3.execptions.ClientError -- when it cannot read from S3 """ if self._manifest_json: return self._manifest_json try: s3_manifest_obj = self.object s3_manifest_data = s3_manifest_obj['Body'].read().decode('utf-8') except (ClientError, NoSuchKey) as error: LOGGER.error("Unable to read manifest file {}.".format(self.path)) LOGGER.debug(error) raise # Cache the manifest.json file self._manifest_json = json.loads(s3_manifest_data) return self._manifest_json def _get_artifact(self, artifact_type): """ Get the artifact_type artifact object out of the manifest. The artifact object looks like this { "link": { "path": "s3://boot-artifacts/F6C1CC79-9A5B-42B6-AD3F-E7EFCF22CAE8/rootfs", "etag": "foo", "type": "s3" }, "type": "application/vnd.cray.image.rootfs.squashfs", "md5": "cccccckvnfdikecvecdngnljnnhvdlvbkueckgbkelee" } Return: Artifact object Raises: ValueError -- Manifest file is corrupt or invalid ArtifactMissing -- The requested artifact is missing TooManyArtifacts -- There is more than one artifact when only one was expected """ try: artifacts = [artifact for artifact in self.manifest_json['artifacts'] if artifact['type'] == artifact_type] except ValueError as value_error: LOGGER.info("Received ValueError while processing manifest file.") LOGGER.debug(value_error) raise if not artifacts: msg = "No %s artifact could be found in the image manifest." % artifact_type LOGGER.info(msg) raise ArtifactMissing(msg) if len(artifacts) > 1: msg = "Multiple %s artifacts found in the manifest." % artifact_type LOGGER.info(msg) raise TooManyArtifacts(msg) return artifacts[0] @property def initrd(self): """ Get the initrd artifact object out of the manifest. Return: initrd object """ return self._get_artifact('application/vnd.cray.image.initrd') @property def kernel(self): """ Get the kernel artifact object out of the manifest. Return: Kernel object """ return self._get_artifact('application/vnd.cray.image.kernel') @property def boot_parameters(self): """ Get the kernel artifact object out of the manifest, if one exists. Return: boot parameters object if one exists, else None """ try: bp = self._get_artifact('application/vnd.cray.image.parameters.boot') except ArtifactMissing: bp = None return bp @property def rootfs(self): """ Get the rootfs artifact object out of the manifest. Return: rootfs object """ return self._get_artifact('application/vnd.cray.image.rootfs.squashfs')
30.720779
99
0.589833
8ce3e6c23686524aab069d616d1b93fd501493f1
13,106
py
Python
Source/mainwindow_v3p1.py
DouglasYuen/ProjectBobo
c663e30ee9020b30acfcb142289d9692411d09e5
[ "MIT" ]
null
null
null
Source/mainwindow_v3p1.py
DouglasYuen/ProjectBobo
c663e30ee9020b30acfcb142289d9692411d09e5
[ "MIT" ]
null
null
null
Source/mainwindow_v3p1.py
DouglasYuen/ProjectBobo
c663e30ee9020b30acfcb142289d9692411d09e5
[ "MIT" ]
null
null
null
''' ** RUN THIS FILE ** version 3.1: click print prompts user agreement. Added ui_user_agreement.ui and .py The window expects Disclaimers.html in the same directory Version 3: Main window connecting stuff on the GUI (in ui_mainwindow_3SQ.py) with the program functionality Uses ColumnView instead of ListViews Note: runs with Python 3, PyQt5 Reqs: FileParser, StringAssembler (comment out the test lines) Author: Rose and Samuel Resources: http://nikolak.com/pyqt-qt-designer-getting-started/ **this is in PyQt4 http://zetcode.com/gui/pyqt5/firstprograms/ http://doc.qt.io/qt-5/modelview.html http://www.binpress.com/tutorial/building-a-text-editor-with-pyqt-part-one/143 https://stackoverflow.com/questions/33924369/how-to-open-a-window-with-a-click-of-a-button-from-another-window-using-pyqt Sam's Excel-file to-do list: -Find a way to categorize conditions / subconditions -Create blank spaces for extra conditions not included in the CSV Program to-do: -Set up something to extend __ for typing vs. writing on paper -Maybe consider moving Print Button function to a different "File Writer" file. to do: -implement checkboxes or way of quickly removing added item -file output options -restructure to only get subconditions when condition is selected -format form text -fix QAccessibleTable::child invalid index errors when...? too many are added? (this has to do with accessibility options) potential problem spots: -addSelectionsToForm -there must be a more efficient way to populate the model from the dictionary -populateModel: there must be a more general way to make the model and make this work -is it more efficient to just grab the subtypeID or to subclass QStandardItem somehow to make populateModel() work with Condition class objects? ''' import sys # for passing argv into QApplication from PyQt5.Qt import * # still unsure what best to import from ui_mainwindow_v3 import Ui_MainWindow from ui_user_agreement import Ui_userAgreement # the code that generates the lists from StringAssembler import * #This is the list that will contain the selected subconditions FinalList=[] class DisplayWindow(QMainWindow, Ui_MainWindow): def __init__(self): super().__init__() #lots of diff ways to set this up? self.setupUi(self) self.newWindow = None #default values customText = "" #populate model and view dictOfConditions = self.assembleConditionDictionary() self.theDataStructure = self.makeConditionModel() # TESTING------------------- # testData = {'adc':['cait','kayle'], 'supp':['zyra','janna','nami'], 'you':[]} # self.populateModel(self.theDataStructure, testData) # for testing customText=" your face" #----------------------------- self.populateModel(self.theDataStructure, dictOfConditions) self.conditionsViewer.setModel(self.theDataStructure) #this needs to be before setting selection model self.selectedConditions = self.conditionsViewer.selectionModel() # separate model #connect buttons self.selectedConditions.selectionChanged.connect(lambda: self.addSelectionsToForm(self.selectedConditions)) self.printButton.clicked.connect(self.showAgreement) self.clearAllButton.clicked.connect(self.MainConditionList.clear) self.clearAllButton.clicked.connect(self.SubConditionList.clear) self.addButtonCondition.clicked.connect(self.addToMainList) self.addButtonSubCondition.clicked.connect(self.addToSubList) self.removeButton.clicked.connect(self.removeFromList) def showAgreement(self): # when the print button is clicked, opens a new window displaying user agreement # agree button makes the forms and closes the dialog # decline button closes the dialog self.newWindow = QMainWindow() userAgreement = Ui_userAgreement() userAgreement.setupUi(self.newWindow) self.uaText = "Disclaimers.html" if self.uaText: with open(self.uaText) as file: userAgreement.textBrowser.setHtml(file.read()) self.newWindow.show() #connect buttons userAgreement.agreeButton.clicked.connect(self.genFinalList) userAgreement.agreeButton.clicked.connect(self.newWindow.close) userAgreement.declineButton.clicked.connect(self.newWindow.close) # ------------------------------------------------------------------------------------------- # Tree Library # ------------------------------------------------------------------------------------------- def assembleConditionDictionary(self): #initializes the condition dictionary using methods from StringAssembler.py conditionKeys = returnAllConditionKeys() #list dictionary = {} for key in conditionKeys: subconditions = returnAllConditionsForKey(key) #list sublist = [] for subcondition in subconditions: sublist.append(subcondition.subtypeID) #get the str name of the subcondition dictionary[key] = sublist return dictionary def makeConditionModel(self): # makes the "model" that hosts the lists of conditions and subconditions model = QStandardItemModel() return model def populateModel(self, model, inputDictionary): # This method assumes the input is the form {a:[b,c,...],...} where b, c... are # Condition type. A more general way would be to restructure the model so this # method can be recursive? for condition, subconditions in inputDictionary.items(): #to loop over dict item = QStandardItem(condition) model.appendRow(item) if subconditions: for subcondition in subconditions: subitem = QStandardItem(subcondition) """ # make and append the strings stringForSubcondition = makeStringSetForSubcondition(condition, subcondition) for subsubitem in stringForSubcondition: stringItem = QStandardItem(subsubitem) subitem.appendRow(stringItem) """ item.appendRow(subitem) # ------------------------------------------------------------------------------------------- #BUTTONS # ------------------------------------------------------------------------------------------- def addSelectionsToForm(self, selectionModel): # when items are selected, add, parse and display in selectionPreview #get selected items from conditionsViewer self.AlphaBox.clear() selectedIndices = selectionModel.selectedIndexes() for index in selectedIndices: selectedItem = self.theDataStructure.itemFromIndex(index) theString = selectedItem.text() #display in the QtextEdit box self.AlphaBox.setText(theString) #Remove button function def removeFromList(self): for item in self.MainConditionList.selectedItems(): self.MainConditionList.takeItem(self.MainConditionList.row(item)) for item in self.SubConditionList.selectedItems(): self.SubConditionList.takeItem(self.SubConditionList.row(item)) #Add button function def addToMainList(self): self.MainConditionList.addItem(self.AlphaBox.text()) def addToSubList(self): self.SubConditionList.addItem(self.AlphaBox.text()) # ------------------------------------------------------------------------------------------- # the File Writer # ------------------------------------------------------------------------------------------- def genFinalList(self): FinalListMain=([item.text() for item in self.MainConditionList.selectedItems()]) FinalListSub=([item.text() for item in self.SubConditionList.selectedItems()]) DictOutput = dict(zip(FinalListMain, FinalListSub)) #Creating .txt files ProgressFile = open("z.Progress Note.txt","w") HandoverFile = open("z.Handover File.txt","w") count=1 #Format for the Progress Note ProgressFile.write("PROGRESS NOTE" + '\n') ProgressFile.write("Date:" + '\n' +'\n') ProgressFile.write("Summary:_" + '\n' +'\n') #This loop generates the conditions for handover and progress notes files #Progress Note for alpha in DictOutput: ProgressFile.write(str(count) + ". " + DictOutput[alpha].upper() + '\n') Z = makeStringSetForSubcondition(alpha,DictOutput[alpha],"P") for beta in Z: if (beta == "%%%"): ProgressFile.write("") else: ProgressFile.write(str(beta) + '\n') #ProgressFile.write(" ".join(str(x) for x in Z)) ProgressFile.write('\n') ProgressFile.write('\n') count=count+1 count=1 #Append P/E to Progress Note #I am sure there is a better way to shorten to unique entries only in an order that makes sense. But until then...we're stuck with this I guess. ProgressFile.write("PHYSICAL EXAM:" + '\n') CombinedExamUniqueOnly=[] for gamma in CombinedExam: if gamma not in CombinedExamUniqueOnly: CombinedExamUniqueOnly.append(gamma) CombinedExam.clear() CombinedExamUniqueOnly.sort() for delta in CombinedExamUniqueOnly: if int(delta[0:2]) < 50: delta=delta[4:] if delta[0] == "^": ProgressFile.write('\n' + str(delta[1:]) + '\n') else: ProgressFile.write(str(delta) + '\n') ProgressFile.write('\n' + "INVESTIGATIONS:" + '\n') for delta in CombinedExamUniqueOnly: if int(delta[0:2]) > 50: delta=delta[4:] if delta[0] == "^": ProgressFile.write('\n' + str(delta[1:]) + '\n') else: ProgressFile.write(str(delta) + '\n') #Format for Handover file HandoverFile.write("THE CHECKLIST" + '\n') HandoverFile.write("Date created:" + '\n' +'\n') HandoverFile.write("Summary:_" + '\n' +'\n') HandoverFile.write("Advanced Care Plan:___" + '\n') HandoverFile.write("Patient is from: Home, Senior's Apartment, Assisted Living, SL3, SL4, or LTC" + '\n') HandoverFile.write('\n'+"TASKS TO BE DONE DAILY:"+'\n') HandoverFile.write("Dates:") for i in range(18): HandoverFile.write(" ") i = i + 1 HandoverFile.write(" || ") for i in range(15): HandoverFile.write(" ") i = i + 1 HandoverFile.write(" |___|___|___|___|___|___|___|" +'\n') DailyTasks=[] HospitalizationTasks=[] DischargeTasks=[] for alpha in DictOutput: Y = makeStringSetForSubcondition(alpha,DictOutput[alpha],"H") Z = str(DictOutput[alpha]) Spaces=" " if len(Z) > 25: Z=Z[0:24] for beta in Y: X=str(beta) if X[0] != "@": if X[0] != "#": while len(Z) < 25: Z += "_" while len(X) < 15: X += " " if len(X) == 15: HandoverFile.write(Z + "|| " + X) HandoverFile.write(" |___|___|___|___|___|___|___|" +'\n') elif len(X) > 15: while len(X) < 57: X += " " HandoverFile.write(Z + "|| " + X[0:44] + '\n') HandoverFile.write(Spaces + "|| " + " " + X[45:56] +" |___|___|___|___|___|___|___|" +'\n') count=count+1 #Additional Blank Options at the end for j in range(3): for i in range(25): HandoverFile.write("_") i = i + 1 HandoverFile.write("||_") for i in range(16): HandoverFile.write("_") i = i + 1 HandoverFile.write("|___|___|___|___|___|___|___|" +'\n') j=j+1 HandoverFile.write('\n') count=1 HandoverFile.write('\n'+"TASKS FOR THIS HOSPITAL STAY:"+'\n') for alpha in DictOutput: Y = makeStringSetForSubcondition(alpha,DictOutput[alpha],"H") Z = str(DictOutput[alpha]) if len(Z) > 25: Z=Z[0:24] for beta in Y: X=str(beta) if X[0] == "@": HandoverFile.write(Z + " || " + X[1:] + '\n') HandoverFile.write('\n'+"MEDICAL TASKS FOR DISCHARGE:"+'\n') for alpha in DictOutput: Y = makeStringSetForSubcondition(alpha,DictOutput[alpha],"H") Z = str(DictOutput[alpha]) if len(Z) > 25: Z=Z[0-24] for beta in Y: X=str(beta) if X[0] == "#": HandoverFile.write(Z + " || " + X[1:] + '\n') HandoverFile.write('\n') HandoverFile.write('\n'+"ADDITIONAL TASKS REQUIRED ON DISCHARGE:"+'\n') HandoverFile.write("Patient's Disposition is: Home, Senior's Apartment, Assisted Living, SL3, SL4, or LTC" + '\n') HandoverFile.write("Patient is to be followed up by::"+'\n') for i in range(3): HandoverFile.write('\t'+"___________________"+'\n') HandoverFile.write("Mobility & Function Agreed by PT + OT:___"+'\n') HandoverFile.write('\n'+"Problem List:" +'\n') for beta in FinalListSub: HandoverFile.write(str(count) + ". " + beta + '\n') count=count+1 ProgressFile.close() HandoverFile.close() # ------------------------------------------------------------------------------------------- #Some old code attempting to send to a Text Editor Widget # ------------------------------------------------------------------------------------------- """ def saveForm(self): # grabs text in text editor and saves to a text file in HTML to preserve style with open('finalForm.txt', 'wt') as theFileOutput: theFileOutput.write(self.selectionPreview.toHtml()) def previewForm(self): # shows print preview and option to print to printer printPreview = QPrintPreviewDialog() printPreview.paintRequested.connect(lambda p: self.selectionPreview.print_(p)) printPreview.exec_() def printForm(self): confirm = QPrintDialog() if confirm.exec_()== QDialog.Accepted: self.selectionPreview.print_(confirm.printer()) """ def main(): app = QApplication(sys.argv) form = DisplayWindow() form.show() sys.exit(app.exec_()) if __name__ == '__main__': main()
32.60199
146
0.661834
af1bac40c33df1e3c87d21679843b49c59018017
518
py
Python
lib/galaxy/managers/lddas.py
blankenberg/galaxy-data-resource
ca32a1aafd64948f489a4e5cf88096f32391b1d9
[ "CC-BY-3.0" ]
null
null
null
lib/galaxy/managers/lddas.py
blankenberg/galaxy-data-resource
ca32a1aafd64948f489a4e5cf88096f32391b1d9
[ "CC-BY-3.0" ]
null
null
null
lib/galaxy/managers/lddas.py
blankenberg/galaxy-data-resource
ca32a1aafd64948f489a4e5cf88096f32391b1d9
[ "CC-BY-3.0" ]
null
null
null
from galaxy.managers import base as manager_base class LDDAManager( manager_base.ModelManager ): """ A fairly sparse manager for LDDAs. """ def __init__( self ): """ Set up and initialize other managers needed by lddas. """ pass def get( self, trans, id, check_accessible=True ): return manager_base.get_object( trans, id, 'LibraryDatasetDatasetAssociation', check_ownership=False, check_accessible=check_accessible )
30.470588
98
0.635135
8ab7f6170399c45432627d17800e2678fc1cc5b2
511
py
Python
linear_regression_readline/code/code_length_1/lr_ds34.py
rodonguyen/vres_code_2021
cb49d941db4dfc5137e887b195f403fb4262cfd8
[ "MIT" ]
null
null
null
linear_regression_readline/code/code_length_1/lr_ds34.py
rodonguyen/vres_code_2021
cb49d941db4dfc5137e887b195f403fb4262cfd8
[ "MIT" ]
null
null
null
linear_regression_readline/code/code_length_1/lr_ds34.py
rodonguyen/vres_code_2021
cb49d941db4dfc5137e887b195f403fb4262cfd8
[ "MIT" ]
null
null
null
from sklearn import linear_model x_values = [] y_values = [] n = 1 with open('./dataset/dataset_34.csv') as f: for i in range(0, n): x,y = f.readline().replace('\n','').split(',') x, y = float(x), float(y) x_values.append([x,y]) y_values.append(y) # Create linear regression object regression = linear_model.LinearRegression() # Train the model using the training sets regression.fit(x_values, y_values) print("Coefficients: \n", regression.coef_)
23.227273
55
0.62818
00e435e0276cc1cb6db7a313e1505aac0f28f281
2,080
py
Python
routes/api_card.py
Officeyutong/HelloJudge2
e88c0a1198f8531ee0c1121dccfedb51f3f0aa0e
[ "MIT" ]
21
2020-02-24T07:56:55.000Z
2022-01-22T11:32:28.000Z
routes/api_card.py
Officeyutong/HelloJudge2
e88c0a1198f8531ee0c1121dccfedb51f3f0aa0e
[ "MIT" ]
1
2021-02-07T13:08:47.000Z
2021-02-09T04:50:49.000Z
routes/api_card.py
Officeyutong/HelloJudge2
e88c0a1198f8531ee0c1121dccfedb51f3f0aa0e
[ "MIT" ]
3
2020-06-04T07:56:20.000Z
2021-06-21T04:04:15.000Z
from models.problem import Problem from models.submission import Submission import typing from main import background_task_queue, db, config, permission_manager from main import web_app as app from common.permission import require_permission from common.utils import unpack_argument from flask_sqlalchemy import BaseQuery from flask import session from utils import make_response from models.user import User import sqlalchemy.sql.expression as expr from sqlalchemy.sql import func import flask @app.route("/api/card/problem", methods=["POST"]) @unpack_argument def api_card_problem(problemID: int): """ 获取题目卡片数据 { "id":"题目ID", "title":"题目名", "acceptedCount":"AC数", "submitCount":"总提交数", "myStatus":{ //如果不存在则为空 "score":"我的分数", "fullScore":"题目满分", "status":"提交状态", "submissionID":"提交ID" } } """ problem: Problem = db.session.query( Problem.id, Problem.title, Problem.cached_accepted_count, Problem.cached_submit_count, Problem.subtasks).filter(Problem.id == problemID).one_or_none() if not problem: flask.abort(404) result = { "id": problem.id, "title": problem.title, "acceptedCount": problem.cached_accepted_count, "submitCount": problem.cached_submit_count, "myStatus": {} } my_submission: Submission = db.session.query( Submission.id, Submission.score, Submission.status ).filter(expr.and_( Submission.uid == session.get("uid", -1), Submission.problem_id == problemID )).order_by(Submission.score.desc()).limit(1).one_or_none() if my_submission: result["myStatus"] = { "score": my_submission.score, "fullScore": sum(item["score"] for item in problem.subtasks), "status": my_submission.status, "submissionID": my_submission.id } return make_response(0, data=result)
31.515152
74
0.622115
8643bd3ac7910e48726b42598153a8af71ed2992
18,135
py
Python
aiida/backends/sqlalchemy/utils.py
joepvd/aiida_core
6e9711046753332933f982971db1d7ac7e7ade58
[ "BSD-2-Clause" ]
null
null
null
aiida/backends/sqlalchemy/utils.py
joepvd/aiida_core
6e9711046753332933f982971db1d7ac7e7ade58
[ "BSD-2-Clause" ]
null
null
null
aiida/backends/sqlalchemy/utils.py
joepvd/aiida_core
6e9711046753332933f982971db1d7ac7e7ade58
[ "BSD-2-Clause" ]
null
null
null
# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida_core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### from __future__ import division from __future__ import absolute_import from __future__ import print_function try: import ultrajson as json from functools import partial # double_precision = 15, to replicate what PostgreSQL numerical type is # using json_dumps = partial(json.dumps, double_precision=15) json_loads = partial(json.loads, precise_float=True) except ImportError: import aiida.utils.json as json json_dumps = json.dumps json_loads = json.loads import datetime import re import six from alembic import command from alembic.config import Config from alembic.runtime.environment import EnvironmentContext from alembic.script import ScriptDirectory from dateutil import parser from sqlalchemy import create_engine from sqlalchemy.orm import scoped_session from sqlalchemy.orm import sessionmaker from aiida.backends import sqlalchemy as sa, settings from aiida.common.setup import (get_profile_config) ALEMBIC_FILENAME = "alembic.ini" ALEMBIC_REL_PATH = "migrations" def flag_modified(instance, key): """Wrapper around `sqlalchemy.orm.attributes.flag_modified` to correctly dereference utils.ModelWrapper Since SqlAlchemy 1.2.12 (and maybe earlier but not in 1.0.19) the flag_modified function will check that the key is actually present in the instance or it will except. If we pass a model instance, wrapped in the ModelWrapper the call will raise an InvalidRequestError. In this function that wraps the flag_modified of SqlAlchemy, we derefence the model instance if the passed instance is actually wrapped in the ModelWrapper. """ from sqlalchemy.orm.attributes import flag_modified as flag_modified_sqla from aiida.orm.implementation.sqlalchemy.utils import ModelWrapper if isinstance(instance, ModelWrapper): instance = instance._model flag_modified_sqla(instance, key) def recreate_after_fork(engine): """ :param engine: the engine that will be used by the sessionmaker Callback called after a fork. Not only disposes the engine, but also recreates a new scoped session to use independent sessions in the forked process. """ sa.engine.dispose() sa.scopedsessionclass = scoped_session(sessionmaker(bind=sa.engine, expire_on_commit=True)) def reset_session(config): """ :param config: the configuration of the profile from the configuration file Resets (global) engine and sessionmaker classes, to create a new one (or creates a new one from scratch if not already available) """ from multiprocessing.util import register_after_fork engine_url = ( "postgresql://{AIIDADB_USER}:{AIIDADB_PASS}@" "{AIIDADB_HOST}{sep}{AIIDADB_PORT}/{AIIDADB_NAME}" ).format(sep=':' if config['AIIDADB_PORT'] else '', **config) sa.engine = create_engine(engine_url, json_serializer=dumps_json, json_deserializer=loads_json, encoding='utf-8') sa.scopedsessionclass = scoped_session(sessionmaker(bind=sa.engine, expire_on_commit=True)) register_after_fork(sa.engine, recreate_after_fork) def load_dbenv(profile=None, connection=None): """ Load the database environment (SQLAlchemy) and perform some checks. :param profile: the string with the profile to use. If not specified, use the default one specified in the AiiDA configuration file. """ _load_dbenv_noschemacheck(profile=profile) # Check schema version and the existence of the needed tables check_schema_version() def _load_dbenv_noschemacheck(profile=None, connection=None): """ Load the SQLAlchemy database. """ config = get_profile_config(settings.AIIDADB_PROFILE) reset_session(config) _aiida_autouser_cache = None def dumps_json(d): """ Transforms all datetime object into isoformat and then returns the JSON """ def f(v): if isinstance(v, list): return [f(_) for _ in v] elif isinstance(v, dict): return dict((key, f(val)) for key, val in v.items()) elif isinstance(v, datetime.datetime): return v.isoformat() return v return json_dumps(f(d)) date_reg = re.compile(r'^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d+(\+\d{2}:\d{2})?$') def loads_json(s): """ Loads the json and try to parse each basestring as a datetime object """ ret = json_loads(s) def f(d): if isinstance(d, list): for i, val in enumerate(d): d[i] = f(val) return d elif isinstance(d, dict): for k, v in d.items(): d[k] = f(v) return d elif isinstance(d, six.string_types): if date_reg.match(d): try: return parser.parse(d) except (ValueError, TypeError): return d return d return d return f(ret) # XXX the code here isn't different from the one use in Django. We may be able # to refactor it in some way def install_tc(session): """ Install the transitive closure table with SqlAlchemy. """ links_table_name = "db_dblink" links_table_input_field = "input_id" links_table_output_field = "output_id" closure_table_name = "db_dbpath" closure_table_parent_field = "parent_id" closure_table_child_field = "child_id" session.execute(get_pg_tc(links_table_name, links_table_input_field, links_table_output_field, closure_table_name, closure_table_parent_field, closure_table_child_field)) def get_pg_tc(links_table_name, links_table_input_field, links_table_output_field, closure_table_name, closure_table_parent_field, closure_table_child_field): """ Return the transitive closure table template """ from string import Template pg_tc = Template(""" DROP TRIGGER IF EXISTS autoupdate_tc ON $links_table_name; DROP FUNCTION IF EXISTS update_tc(); CREATE OR REPLACE FUNCTION update_tc() RETURNS trigger AS $$BODY$$ DECLARE new_id INTEGER; old_id INTEGER; num_rows INTEGER; BEGIN IF tg_op = 'INSERT' THEN IF EXISTS ( SELECT Id FROM $closure_table_name WHERE $closure_table_parent_field = new.$links_table_input_field AND $closure_table_child_field = new.$links_table_output_field AND depth = 0 ) THEN RETURN null; END IF; IF new.$links_table_input_field = new.$links_table_output_field OR EXISTS ( SELECT id FROM $closure_table_name WHERE $closure_table_parent_field = new.$links_table_output_field AND $closure_table_child_field = new.$links_table_input_field ) THEN RETURN null; END IF; INSERT INTO $closure_table_name ( $closure_table_parent_field, $closure_table_child_field, depth) VALUES ( new.$links_table_input_field, new.$links_table_output_field, 0); new_id := lastval(); UPDATE $closure_table_name SET entry_edge_id = new_id , exit_edge_id = new_id , direct_edge_id = new_id WHERE id = new_id; INSERT INTO $closure_table_name ( entry_edge_id, direct_edge_id, exit_edge_id, $closure_table_parent_field, $closure_table_child_field, depth) SELECT id , new_id , new_id , $closure_table_parent_field , new.$links_table_output_field , depth + 1 FROM $closure_table_name WHERE $closure_table_child_field = new.$links_table_input_field; INSERT INTO $closure_table_name ( entry_edge_id, direct_edge_id, exit_edge_id, $closure_table_parent_field, $closure_table_child_field, depth) SELECT new_id , new_id , id , new.$links_table_input_field , $closure_table_child_field , depth + 1 FROM $closure_table_name WHERE $closure_table_parent_field = new.$links_table_output_field; INSERT INTO $closure_table_name ( entry_edge_id, direct_edge_id, exit_edge_id, $closure_table_parent_field, $closure_table_child_field, depth) SELECT A.id , new_id , B.id , A.$closure_table_parent_field , B.$closure_table_child_field , A.depth + B.depth + 2 FROM $closure_table_name A CROSS JOIN $closure_table_name B WHERE A.$closure_table_child_field = new.$links_table_input_field AND B.$closure_table_parent_field = new.$links_table_output_field; END IF; IF tg_op = 'DELETE' THEN IF NOT EXISTS( SELECT id FROM $closure_table_name WHERE $closure_table_parent_field = old.$links_table_input_field AND $closure_table_child_field = old.$links_table_output_field AND depth = 0 ) THEN RETURN NULL; END IF; CREATE TABLE PurgeList (Id int); INSERT INTO PurgeList SELECT id FROM $closure_table_name WHERE $closure_table_parent_field = old.$links_table_input_field AND $closure_table_child_field = old.$links_table_output_field AND depth = 0; WHILE (1 = 1) loop INSERT INTO PurgeList SELECT id FROM $closure_table_name WHERE depth > 0 AND ( entry_edge_id IN ( SELECT Id FROM PurgeList ) OR direct_edge_id IN ( SELECT Id FROM PurgeList ) OR exit_edge_id IN ( SELECT Id FROM PurgeList ) ) AND Id NOT IN (SELECT Id FROM PurgeList ); GET DIAGNOSTICS num_rows = ROW_COUNT; if (num_rows = 0) THEN EXIT; END IF; end loop; DELETE FROM $closure_table_name WHERE Id IN ( SELECT Id FROM PurgeList); DROP TABLE PurgeList; END IF; RETURN NULL; END $$BODY$$ LANGUAGE plpgsql VOLATILE COST 100; CREATE TRIGGER autoupdate_tc AFTER INSERT OR DELETE OR UPDATE ON $links_table_name FOR each ROW EXECUTE PROCEDURE update_tc(); """) return pg_tc.substitute(links_table_name=links_table_name, links_table_input_field=links_table_input_field, links_table_output_field=links_table_output_field, closure_table_name=closure_table_name, closure_table_parent_field=closure_table_parent_field, closure_table_child_field=closure_table_child_field) def check_schema_version(force_migration=False, alembic_cfg=None): """ Check if the version stored in the database is the same of the version of the code. :note: if the DbSetting table does not exist, this function does not fail. The reason is to avoid to have problems before running the first migrate call. :note: if no version is found, the version is set to the version of the code. This is useful to have the code automatically set the DB version at the first code execution. :raise ConfigurationError: if the two schema versions do not match. Otherwise, just return. """ import sys from aiida.common.utils import query_yes_no from aiida.backends import sqlalchemy as sa from aiida.backends.settings import IN_DOC_MODE # Early exit if we compile the documentation since the schema # check is not needed and it creates problems with the sqlalchemy # migrations if IN_DOC_MODE: return # If an alembic configuration file is given then use that one. if alembic_cfg is None: alembic_cfg = get_alembic_conf() # Getting the version of the code and the database # Reusing the existing engine (initialized by AiiDA) with sa.engine.begin() as connection: alembic_cfg.attributes['connection'] = connection code_schema_version = get_migration_head(alembic_cfg) db_schema_version = get_db_schema_version(alembic_cfg) if code_schema_version != db_schema_version: if db_schema_version is None: print("It is time to perform your first SQLAlchemy migration.") else: print("The code schema version is {}, but the version stored in " "the database is {}." .format(code_schema_version, db_schema_version)) if force_migration or query_yes_no("Would you like to migrate to the " "latest version?", "yes"): print("Migrating to the last version") # Reusing the existing engine (initialized by AiiDA) with sa.engine.begin() as connection: alembic_cfg.attributes['connection'] = connection command.upgrade(alembic_cfg, "head") else: print("No migration is performed. Exiting since database is out " "of sync with the code.") sys.exit(1) def get_migration_head(config): """ This function returns the head of the migration scripts. :param config: The alembic configuration. :return: The version of the head. """ script = ScriptDirectory.from_config(config) return script.get_current_head() def get_db_schema_version(config): """ This function returns the current version of the database. :param config: The alembic configuration. :return: The version of the database. """ if config is None: return None script = ScriptDirectory.from_config(config) def get_db_version(rev, _): if isinstance(rev, tuple) and len(rev) > 0: config.attributes['rev'] = rev[0] else: config.attributes['rev'] = None return [] with EnvironmentContext( config, script, fn=get_db_version ): script.run_env() return config.attributes['rev'] def get_alembic_conf(): """ This function returns the alembic configuration file contents by doing the necessary updates in the 'script_location' name. :return: The alembic configuration. """ # Constructing the alembic full path & getting the configuration import os dir_path = os.path.dirname(os.path.realpath(__file__)) alembic_fpath = os.path.join(dir_path, ALEMBIC_FILENAME) alembic_cfg = Config(alembic_fpath) # Set the alembic script directory location alembic_dpath = os.path.join(dir_path, ALEMBIC_REL_PATH) alembic_cfg.set_main_option('script_location', alembic_dpath) return alembic_cfg def alembic_command(selected_command, *args, **kwargs): """ This function calls the necessary alembic command with the provided arguments. :param selected_command: The command that should be called from the alembic commands. :param args: The arguments. :param kwargs: The keyword arguments. :return: Nothing. """ if selected_command is None: return # Get the requested alembic command from the available commands al_command = getattr(command, selected_command) alembic_cfg = get_alembic_conf() with sa.engine.begin() as connection: alembic_cfg.attributes['connection'] = connection if selected_command in ['current', 'history']: if 'verbose' in args: al_command(alembic_cfg, verbose=True) else: al_command(alembic_cfg, *args, **kwargs) elif selected_command == 'revision': al_command(alembic_cfg, message=args[0][0]) else: al_command(alembic_cfg, *args, **kwargs) def delete_nodes_and_connections_sqla(pks_to_delete): """ Delete all nodes corresponding to pks in the input. :param pks_to_delete: A list, tuple or set of pks that should be deleted. """ from aiida.backends import sqlalchemy as sa from aiida.backends.sqlalchemy.models.node import DbNode, DbLink from aiida.backends.sqlalchemy.models.group import table_groups_nodes session = sa.get_scoped_session() try: # I am first making a statement to delete the membership of these nodes to groups. # Since table_groups_nodes is a sqlalchemy.schema.Table, I am using expression language to compile # a stmt to be executed by the session. It works, but it's not nice that two different ways are used! # Can this be changed? stmt = table_groups_nodes.delete().where(table_groups_nodes.c.dbnode_id.in_(list(pks_to_delete))) session.execute(stmt) # First delete links, then the Nodes, since we are not cascading deletions. # Here I delete the links coming out of the nodes marked for deletion. session.query(DbLink).filter(DbLink.input_id.in_(list(pks_to_delete))).delete(synchronize_session='fetch') # Here I delete the links pointing to the nodes marked for deletion. session.query(DbLink).filter(DbLink.output_id.in_(list(pks_to_delete))).delete(synchronize_session='fetch') # Now I am deleting the nodes session.query(DbNode).filter(DbNode.id.in_(list(pks_to_delete))).delete(synchronize_session='fetch') # Here I commit this scoped session! session.commit() except Exception as e: # If there was any exception, I roll back the session. session.rollback() raise e finally: session.close()
33.153565
119
0.659994
78da4ffb56fd155e227e684d88b8f58a84806283
196
py
Python
experiments/multip.py
huxia001/autokeras
f4503bb3a3be014b452f54d8e2d187bb6419f627
[ "MIT" ]
1
2018-08-03T05:59:54.000Z
2018-08-03T05:59:54.000Z
experiments/multip.py
HangJie720/autokeras
1619d8c398a955559fb6389797716c9a0989cb43
[ "MIT" ]
null
null
null
experiments/multip.py
HangJie720/autokeras
1619d8c398a955559fb6389797716c9a0989cb43
[ "MIT" ]
1
2018-08-31T12:49:57.000Z
2018-08-31T12:49:57.000Z
import multiprocessing from time import sleep def foo(a, b): return a + b d = {} p = multiprocessing.Pool(2) data = p.map_async(foo, [[3, 4], [5, 6]]) print(data.get()) p.close() p.join()
13.066667
41
0.622449
91ab1a8ff6fe61b1236f737d549b3de42fefef0f
771
py
Python
core/admin.py
Hassan-gholipoor/Todo_App_API
19f9c141868fa0b01a11ed2a20f665d97b877340
[ "MIT" ]
null
null
null
core/admin.py
Hassan-gholipoor/Todo_App_API
19f9c141868fa0b01a11ed2a20f665d97b877340
[ "MIT" ]
null
null
null
core/admin.py
Hassan-gholipoor/Todo_App_API
19f9c141868fa0b01a11ed2a20f665d97b877340
[ "MIT" ]
null
null
null
from django.contrib import admin from django.contrib.auth.admin import UserAdmin as BaseUserAdmin from django.utils.translation import gettext_lazy as _ from core import models class UserAdmin(BaseUserAdmin): ordering = ['id'] list_display = ['email', 'name'] fieldsets = ( (None, {"fields": ("email", "password")}), (_("Personal Info"), {"fields": ("name",)}), (_("Permissions"), {"fields": ("is_active", ("is_staff", "is_superuser"))}), (_("Important dates"), {"fields": ("last_login",)}) ) add_fieldsets = ( (None, { "classes": ('wide',), "fields": ('email', 'password1', 'password2') }), ) admin.site.register(models.User, UserAdmin) admin.site.register(models.Todo)
29.653846
84
0.599222
2a46d2b5ab30a87f7025507ff6c6dd84d8a165f5
940
py
Python
woof_nf/workflow/bin/shared.py
umccr/woof-nf
0d4ac533e67dc2b28252bf50379133184524d1bd
[ "OLDAP-2.2.1" ]
null
null
null
woof_nf/workflow/bin/shared.py
umccr/woof-nf
0d4ac533e67dc2b28252bf50379133184524d1bd
[ "OLDAP-2.2.1" ]
null
null
null
woof_nf/workflow/bin/shared.py
umccr/woof-nf
0d4ac533e67dc2b28252bf50379133184524d1bd
[ "OLDAP-2.2.1" ]
null
null
null
import pathlib import subprocess import sys def get_woofr_source_fp() -> pathlib.Path: return get_lib_path() / 'woofr_compare.R' def get_lib_path() -> pathlib.Path: # Currently the nf-amazon plugin only uploads the ./bin/ directory to AWS instances. Any ./lib/ # files accessed during task execution are required to be in ./bin/. The ./bin/ directory # appears as /nextflow-bin/ on AWS instances. return pathlib.Path(__file__).parent def execute_command(command: str) -> subprocess.CompletedProcess: result = subprocess.run( command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True, encoding='utf-8' ) if result.returncode != 0: print('Failed to run command:', result.args, file=sys.stderr) print('stdout:', result.stdout, file=sys.stderr) print('stderr:', result.stderr, file=sys.stderr) sys.exit(1) return result
30.322581
99
0.671277
45a6b44377355d64a68094ef9bbcc6d15f21c27f
948
py
Python
app/DBbase.py
ophioglossum/video
31b969bddc7f3509d5ebaab1aff9d7e2399365ff
[ "MIT" ]
null
null
null
app/DBbase.py
ophioglossum/video
31b969bddc7f3509d5ebaab1aff9d7e2399365ff
[ "MIT" ]
null
null
null
app/DBbase.py
ophioglossum/video
31b969bddc7f3509d5ebaab1aff9d7e2399365ff
[ "MIT" ]
null
null
null
from config import database from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker,scoped_session from sqlalchemy.pool import QueuePool #数据库基础类 class DBbase(): def __init__(self): self.engine = create_engine( database.DB_HOST, poolclass=QueuePool, max_overflow=0, # 超过连接池大小外最多创建的连接 pool_size=5, # 连接池大小 pool_timeout=30, # 池中没有线程最多等待的时间 pool_recycle=-1, # 多久之后对线程池中的线程进行一次连接的回收(重置) echo=database.DB_DEBUG, echo_pool=database.DB_DEBUG ) # engine是2.2中创建的连接 self.DBSession = sessionmaker(bind=self.engine) self.session = scoped_session(self.DBSession) def __del__(self): self.session.remove() self.engine.dispose() #获取一个新的连接池 def _get_new_session(self): # 创建Session类实例 new_session = scoped_session(self.DBSession) return new_session
31.6
57
0.650844
ac4a29c0047fff68943b8d600da4f2cd013aeb41
677
py
Python
tests/test_kademlia.py
vtemian/kademlia
0994f76f314481316bedcfa6b5c3e404e33df53c
[ "MIT" ]
null
null
null
tests/test_kademlia.py
vtemian/kademlia
0994f76f314481316bedcfa6b5c3e404e33df53c
[ "MIT" ]
null
null
null
tests/test_kademlia.py
vtemian/kademlia
0994f76f314481316bedcfa6b5c3e404e33df53c
[ "MIT" ]
null
null
null
import time import pytest from kademlia import Kademlia @pytest.fixture def nodes(): node1 = Kademlia("127.0.0.1", 5001) node2 = Kademlia("127.0.0.1", 5002, register_to=node1) return node1, node2 def test_ping(nodes): node1, node2 = nodes node1.ping(node2) assert node1.received_jobs[-1] == { "job_type": "pong", "sender": node2.id, } assert node2.received_jobs[-1] == { "job_type": "ping", "sender": node1.id, } assert False #def test_key_propagation(nodes): # node1, node2 = nodes # # node1["awesome-key"] = "cool-value" # assert node2["awesome-key"] == "cool-value"
18.297297
58
0.592319
498b617eecf768c6216cade6f230739f52bfa19a
1,857
py
Python
python/src/nnabla/backward_function/random_choice.py
chunxiaosz/nnabla
9f4249313129d0fd23d304453830157fee96a2e5
[ "Apache-2.0" ]
1
2019-09-10T06:51:37.000Z
2019-09-10T06:51:37.000Z
python/src/nnabla/backward_function/random_choice.py
langbin2014/nnabla
e94bac5bed65337010e2ac07a5937fb862ab2dd8
[ "Apache-2.0" ]
null
null
null
python/src/nnabla/backward_function/random_choice.py
langbin2014/nnabla
e94bac5bed65337010e2ac07a5937fb862ab2dd8
[ "Apache-2.0" ]
null
null
null
# Copyright (c) 2017 Sony Corporation. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np import nnabla as nn import nnabla.functions as F from .backward_function import BackwardFunction class RandomChoiceBackward(BackwardFunction): def name(self): return 'RandomChoiceBackward' def _create_forward_inputs_and_outputs(self, inputs, outputs): # Inputs on the forward graph inputs_fwd = [] for i in range(self._num_inputs_fwd): need_grad = self.forward_func.inputs[i].need_grad v = nn.Variable(inputs[i].shape, need_grad=need_grad) v.data = inputs[i].data v.grad = outputs[i].data inputs_fwd += [v] # Outputs on the forward graph outputs_fwd = [] for i in range(self._num_outputs_fwd): inp = inputs[self._num_inputs_fwd + i] v = nn.Variable(inp.shape) v.grad = inp.data outputs_fwd += [v] return inputs_fwd, outputs_fwd def backward_impl(self, inputs, outputs, prop_down, accum): # inputs: [inputs_fwd_graph] + [inputs_bwd_graph] or # [inputs_fwd_graph] + [outputs_fwd_graph] + [inputs_bwd_graph] raise NotImplementedError( "The backward method of RandomChoiceBackward class is not implemented.")
37.14
84
0.681745
89fb09ea458052372ec5c573208ade0132c9690b
4,500
py
Python
roles/lib_openshift/src/class/oc_group.py
shgriffi/openshift-ansible
6313f519307cf50055589c3876d8bec398bbc4d4
[ "Apache-2.0" ]
1
2017-12-13T01:11:57.000Z
2017-12-13T01:11:57.000Z
roles/lib_openshift/src/class/oc_group.py
shgriffi/openshift-ansible
6313f519307cf50055589c3876d8bec398bbc4d4
[ "Apache-2.0" ]
6
2018-02-01T11:13:38.000Z
2018-02-02T08:01:15.000Z
roles/lib_openshift/src/class/oc_group.py
shgriffi/openshift-ansible
6313f519307cf50055589c3876d8bec398bbc4d4
[ "Apache-2.0" ]
4
2018-10-27T00:29:24.000Z
2022-01-07T07:39:51.000Z
# pylint: skip-file # flake8: noqa class OCGroup(OpenShiftCLI): ''' Class to wrap the oc command line tools ''' kind = 'group' def __init__(self, config, verbose=False): ''' Constructor for OCGroup ''' super(OCGroup, self).__init__(config.namespace, config.kubeconfig) self.config = config self.namespace = config.namespace self._group = None @property def group(self): ''' property function service''' if not self._group: self.get() return self._group @group.setter def group(self, data): ''' setter function for yedit var ''' self._group = data def exists(self): ''' return whether a group exists ''' if self.group: return True return False def get(self): '''return group information ''' result = self._get(self.kind, self.config.name) if result['returncode'] == 0: self.group = Group(content=result['results'][0]) elif 'groups \"{}\" not found'.format(self.config.name) in result['stderr']: result['returncode'] = 0 result['results'] = [{}] return result def delete(self): '''delete the object''' return self._delete(self.kind, self.config.name) def create(self): '''create the object''' return self._create_from_content(self.config.name, self.config.data) def update(self): '''update the object''' return self._replace_content(self.kind, self.config.name, self.config.data) def needs_update(self): ''' verify an update is needed ''' return not Utils.check_def_equal(self.config.data, self.group.yaml_dict, skip_keys=[], debug=True) # pylint: disable=too-many-return-statements,too-many-branches @staticmethod def run_ansible(params, check_mode=False): '''run the idempotent ansible code''' gconfig = GroupConfig(params['name'], params['namespace'], params['kubeconfig'], ) oc_group = OCGroup(gconfig, verbose=params['debug']) state = params['state'] api_rval = oc_group.get() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} ##### # Get ##### if state == 'list': return {'changed': False, 'results': api_rval['results'], 'state': state} ######## # Delete ######## if state == 'absent': if oc_group.exists(): if check_mode: return {'changed': True, 'msg': 'CHECK_MODE: Would have performed a delete.'} api_rval = oc_group.delete() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} return {'changed': True, 'results': api_rval, 'state': state} return {'changed': False, 'state': state} if state == 'present': ######## # Create ######## if not oc_group.exists(): if check_mode: return {'changed': True, 'msg': 'CHECK_MODE: Would have performed a create.'} # Create it here api_rval = oc_group.create() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} # return the created object api_rval = oc_group.get() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} return {'changed': True, 'results': api_rval, 'state': state} ######## # Update ######## if oc_group.needs_update(): api_rval = oc_group.update() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} # return the created object api_rval = oc_group.get() if api_rval['returncode'] != 0: return {'failed': True, 'msg': api_rval} return {'changed': True, 'results': api_rval, 'state': state} return {'changed': False, 'results': api_rval, 'state': state} return {'failed': True, 'msg': 'Unknown state passed. {}'.format(state)}
30.201342
106
0.512
6ccdcb0248ddee32637260f06a1c3bf66c3d9755
545
py
Python
tests/schema/models_cyclic.py
Alirezaja1384/tortoise-orm
e7ecbc81d43860a3b0b6d5d9da27497ed6234049
[ "Apache-2.0" ]
33
2018-04-07T09:50:22.000Z
2018-08-24T10:25:29.000Z
tests/schema/models_cyclic.py
Alirezaja1384/tortoise-orm
e7ecbc81d43860a3b0b6d5d9da27497ed6234049
[ "Apache-2.0" ]
41
2018-03-29T17:09:18.000Z
2018-08-24T16:37:38.000Z
tests/schema/models_cyclic.py
Alirezaja1384/tortoise-orm
e7ecbc81d43860a3b0b6d5d9da27497ed6234049
[ "Apache-2.0" ]
4
2018-06-27T08:45:11.000Z
2018-07-30T18:16:55.000Z
""" This is the testing Models — Cyclic """ from tortoise import fields from tortoise.models import Model class One(Model): tournament: fields.ForeignKeyRelation["Two"] = fields.ForeignKeyField( "models.Two", related_name="events" ) class Two(Model): tournament: fields.ForeignKeyRelation["Three"] = fields.ForeignKeyField( "models.Three", related_name="events" ) class Three(Model): tournament: fields.ForeignKeyRelation[One] = fields.ForeignKeyField( "models.One", related_name="events" )
22.708333
76
0.699083
18e617dd29f9f7671dd608cb62fe149a18bc34e2
24,257
py
Python
mvpa2/base/verbosity.py
nno/PyMVPA
a125596bf81b8e9848768852f697bd3cff9674c4
[ "MIT" ]
227
2015-01-17T20:13:54.000Z
2022-01-26T21:14:30.000Z
mvpa2/base/verbosity.py
nno/PyMVPA
a125596bf81b8e9848768852f697bd3cff9674c4
[ "MIT" ]
364
2015-01-05T21:55:09.000Z
2021-09-09T20:37:55.000Z
mvpa2/base/verbosity.py
nno/PyMVPA
a125596bf81b8e9848768852f697bd3cff9674c4
[ "MIT" ]
111
2015-01-06T19:26:41.000Z
2022-01-26T21:14:31.000Z
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## # # See COPYING file distributed along with the PyMVPA package for the # copyright and license terms. # ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## """Verbose output and debugging facility Examples: from verbosity import verbose, debug; debug.active = [1,2,3]; debug(1, "blah") """ __docformat__ = 'restructuredtext' from sys import stdout, stderr # GOALS # any logger should be able # to log into a file or stdout/stderr # provide ability to log with/without a new line at the end # # debug logger should be able # to log sets of debug statements # add/remove debug setid items # give verbose description about registered debugset items class Logger(object): """Base class to provide logging """ def __init__(self, handlers=None): """Initialize the logger with a set of handlers to use for output Each hanlder must have write() method implemented """ if handlers is None: handlers = [stdout] self.__close_handlers = [] self.__handlers = [] # pylint friendliness self._set_handlers(handlers) self.__lfprev = True self.__crprev = 0 # number of symbols in previous cr-ed def __del__(self): self._close_opened_handlers() ##REF: Name was automagically refactored def _set_handlers(self, handlers): """Set list of handlers for the log. A handler can be opened files, stdout, stderr, or a string, which will be considered a filename to be opened for writing """ handlers_ = [] self._close_opened_handlers() for handler in handlers: if isinstance(handler, basestring): try: handler = {'stdout' : stdout, 'stderr' : stderr}[handler.lower()] except: try: handler = open(handler, 'w') self.__close_handlers.append(handler) except: raise RuntimeError, \ "Cannot open file %s for writing by the logger" \ % handler handlers_.append(handler) self.__handlers = handlers_ ##REF: Name was automagically refactored def _close_opened_handlers(self): """Close opened handlers (such as opened logfiles """ for handler in self.__close_handlers: handler.close() ##REF: Name was automagically refactored def _get_handlers(self): """Return active handlers """ return self.__handlers def __call__(self, msg, args=None, lf=True, cr=False, **kwargs): """Write msg to each of the handlers. It can append a newline (lf = Line Feed) or return to the beginning before output and to take care about cleaning previous message if present it appends a newline (lf = Line Feed) since most commonly each call is a separate message """ if args is not None: try: msg = msg % args except Exception as e: msg = "%s [%% FAILED due to %s]" % (msg, e) if 'msgargs' in kwargs: msg = msg % kwargs['msgargs'] if cr: msg_ = "" if self.__crprev > 0: # wipe out older line to make sure to see no ghosts msg_ = "\r%s" % (" "*self.__crprev) msg_ += "\r" + msg self.__crprev = len(msg) msg = msg_ # since it makes no sense this days for cr and lf, # override lf lf = False else: self.__crprev += len(msg) if lf: msg = msg + "\n" self.__crprev = 0 # nothing to clear for handler in self.__handlers: try: handler.write(msg) except: print "Failed writing on handler %s" % handler raise try: handler.flush() except: # it might be not implemented.. pass self.__lfprev = lf handlers = property(fget=_get_handlers, fset=_set_handlers) lfprev = property(fget=lambda self:self.__lfprev) class LevelLogger(Logger): """Logger not to log anything with a level smaller than specified. """ def __init__(self, level=0, indent=" ", *args, **kwargs): """ Parameters ---------- level : int, optional Level to consider be active. indent : str, optional String to use for indentation. """ Logger.__init__(self, *args, **kwargs) self.__level = level # damn pylint ;-) self.__indent = indent self._set_level(level) self._set_indent(indent) ##REF: Name was automagically refactored def _set_level(self, level): """Set logging level """ if __debug__: try: from mvpa2.base import debug debug('VERBOSE', 'Setting verbosity to %r from %r', (self.__level, level)) except: pass ilevel = int(level) if ilevel < 0: raise ValueError, \ "Negative verbosity levels (got %d) are not supported" \ % ilevel self.__level = ilevel ##REF: Name was automagically refactored def _set_indent(self, indent): """Either to indent the lines based on message log level""" self.__indent = "%s" % indent def __call__(self, level, msg, *args, **kwargs): """Write msg and indent using self.indent it if it was requested. It appends a newline since most commonly each call is a separate message """ if level <= self.level: if self.lfprev and self.indent: # indent if previous line ended with newline msg = self.indent * level + msg Logger.__call__(self, msg, *args, **kwargs) level = property(fget=lambda self: self.__level, fset=_set_level) indent = property(fget=lambda self: self.__indent, fset=_set_indent) class OnceLogger(Logger): """Logger which prints a message for a given ID just once. It could be used for one-time warning to don't overfill the output with useless repeatative messages. """ def __init__(self, *args, **kwargs): """Define once logger. """ Logger.__init__(self, *args, **kwargs) self._known = {} def __call__(self, ident, msg, count=1, *args, **kwargs): """Write `msg` if `ident` occured less than `count` times by now. """ if ident not in self._known: self._known[ident] = 0 if count < 0 or self._known[ident] < count: self._known[ident] += 1 Logger.__call__(self, msg, *args, **kwargs) class SetLogger(Logger): """Logger which prints based on defined sets identified by Id. """ def __init__(self, register=None, active=None, printsetid=True, *args, **kwargs): """ Parameters ---------- register : dict or None What Ids are to be known. Each item dictionary contains consists of concise key and a description as the value. active : iterable What Ids to consider active upon initialization. printsetid : bool, optional Either to prefix each line with the target Id of a set in which the line was printed to (default behavior). """ if register is None: register = {} if active is None: active = [] Logger.__init__(self, *args, **kwargs) self.__printsetid = printsetid self.__registered = register # all "registered" sets descriptions # which to output... pointless since __registered self._set_active(active) self._set_printsetid(printsetid) ##REF: Name was automagically refactored def _set_active(self, active): """Set active logging set """ # just unique entries... we could have simply stored Set I guess, # but then smth like debug.active += ["BLAH"] would not work from mvpa2.base import verbose self.__active = [] registered_keys = self.__registered.keys() for item in list(set(active)): if item == '': continue if isinstance(item, basestring): if item in ['?', 'list', 'help']: self.print_registered(detailed=(item != '?')) raise SystemExit(0) if item.upper() == "ALL": verbose(2, "Enabling all registered debug handlers") self.__active = registered_keys break # try to match item as it is regexp regexp_str = "^%s$" % item try: regexp = re.compile(regexp_str) except: raise ValueError, \ "Unable to create regular expression out of %s" % item matching_keys = filter(regexp.match, registered_keys) toactivate = matching_keys if len(toactivate) == 0: ids = self.registered.keys() ids.sort() raise ValueError, \ "Unknown debug ID '%s' was asked to become active," \ " or regular expression '%s' did not get any match" \ " among known ids: %s" \ % (item, regexp_str, ids) else: toactivate = [item] # Lets check if asked items are known for item_ in toactivate: if not (item_ in registered_keys): raise ValueError, \ "Unknown debug ID %s was asked to become active" \ % item_ self.__active += toactivate self.__active = list(set(self.__active)) # select just unique ones self.__maxstrlength = max([len(str(x)) for x in self.__active] + [0]) if len(self.__active): verbose(2, "Enabling debug handlers: %s" % `self.__active`) ##REF: Name was automagically refactored def _set_printsetid(self, printsetid): """Either to print set Id at each line""" self.__printsetid = printsetid def __call__(self, setid, msg, *args, **kwargs): """ Write msg It appends a newline since most commonly each call is a separate message """ if setid in self.__active: if len(msg) > 0 and self.__printsetid: msg = "[%%-%ds] " % self.__maxstrlength % (setid) + msg Logger.__call__(self, msg, *args, **kwargs) def register(self, setid, description): """ "Register" a new setid with a given description for easy finding """ if setid in self.__registered: raise ValueError, \ "Setid %s is already known with description '%s'" % \ (`setid`, self.__registered[setid]) self.__registered[setid] = description ##REF: Name was automagically refactored def set_active_from_string(self, value): """Given a string listing registered(?) setids, make then active """ # somewhat evil but works since verbose must be initiated # by now self.active = value.split(",") def print_registered(self, detailed=True): print "Registered debug entries: ", kd = self.registered rks = sorted(kd.keys()) maxl = max([len(k) for k in rks]) if not detailed: # short list print ', '.join(rks) else: print for k in rks: print '%%%ds %%s' % maxl % (k, kd[k]) printsetid = property(fget=lambda self: self.__printsetid, \ fset=_set_printsetid) active = property(fget=lambda self: self.__active, fset=_set_active) registered = property(fget=lambda self: self.__registered) if __debug__: import os, re import traceback import time from os import getpid from os.path import basename, dirname __pymvpa_pid__ = getpid() def parse_status(field='VmSize', value_only=False): """Return stat information on current process. Usually it is needed to know where the memory is gone, that is why VmSize is the default for the field to spit out TODO: Spit out multiple fields. Use some better way than parsing proc """ regex = re.compile('^%s:' % field) match = None try: for l in open('/proc/%d/status' % __pymvpa_pid__): if regex.match(l): match = l.strip() break if match: match = re.sub('[ \t]+', ' ', match) except IOError: pass if match and value_only: match = match.split(':', 1)[1].lstrip() return match def get_vmem_from_status(): """Return utilization of virtual memory Deprecated implementation which relied on parsing proc/PID/status """ rss, vms = [parse_status(field=x, value_only=True) for x in ['VmRSS', 'VmSize']] if rss is None or vms is None: # So not available on this system -- signal with negatives # but do not crash return (-1, -1) if rss[-3:] == vms[-3:] and rss[-3:] == ' kB': # the same units rss = int(rss[:-3]) # strip from rss vms = int(vms[:-3]) return (rss, vms) try: # we prefer to use psutil if available # and let's stay away from "externals" module for now # Note: importing as __Process so it does not get # 'queried' by autodoc leading to an exception # while being unable to get values for the properties from psutil import Process as __Process __pymvpa_process__ = __Process(__pymvpa_pid__) __pymvpa_memory_info = __pymvpa_process__.memory_info if hasattr(__pymvpa_process__, 'memory_info') \ else __pymvpa_process__.get_memory_info def get_vmem(): """Return utilization of virtual memory Generic implementation using psutil """ mi = __pymvpa_memory_info() # in later versions of psutil mi is a named tuple. # but that is not the case on Debian squeeze with psutil 0.1.3 rss = mi[0] / 1024 vms = mi[1] / 1024 return (rss, vms) except ImportError: get_vmem = get_vmem_from_status def get_vmem_str(): """Return a string summary about utilization of virtual_memory """ vmem = get_vmem() try: return "RSS/VMS: %d/%d kB" % vmem except: return "RSS/VMS: %s" % str(vmem) def _get_vmem_max_str_gen(): """Return peak vmem utilization so far. It is a generator, get_vmem_max_str later is bound to .next of it - to mimic static variables """ rss_max = 0 vms_max = 0 while True: rss, vms = get_vmem() rss_max = max(rss, rss_max) vms_max = max(vms, vms_max) yield "max RSS/VMS: %d/%d kB" % (rss_max, vms_max) get_vmem_max_str = _get_vmem_max_str_gen().next def mbasename(s): """Custom function to include directory name if filename is too common Also strip .py at the end """ base = basename(s) if base.endswith('.py'): base = base[:-3] if base in set(['base', '__init__']): base = basename(dirname(s)) + '.' + base return base class TraceBack(object): """Customized traceback to be included in debug messages """ def __init__(self, collide=False): """Initialize TrackBack metric Parameters ---------- collide : bool if True then prefix common with previous invocation gets replaced with ... """ self.__prev = "" self.__collide = collide def __call__(self): ftb = traceback.extract_stack(limit=100)[:-2] entries = [[mbasename(x[0]), str(x[1])] for x in ftb] entries = [ e for e in entries if e[0] != 'unittest' ] # lets make it more consize entries_out = [entries[0]] for entry in entries[1:]: if entry[0] == entries_out[-1][0]: entries_out[-1][1] += ',%s' % entry[1] else: entries_out.append(entry) sftb = '>'.join(['%s:%s' % (mbasename(x[0]), x[1]) for x in entries_out]) if self.__collide: # lets remove part which is common with previous invocation prev_next = sftb common_prefix = os.path.commonprefix((self.__prev, sftb)) common_prefix2 = re.sub('>[^>]*$', '', common_prefix) if common_prefix2 != "": sftb = '...' + sftb[len(common_prefix2):] self.__prev = prev_next return sftb class RelativeTime(object): """Simple helper class to provide relative time it took from previous invocation""" def __init__(self, format="%3.3f sec"): """ Parameters ---------- format : str String format to use for reporting time. """ self.__prev = None self.__format = format def __call__(self): dt = 0.0 ct = time.time() if self.__prev is not None: dt = ct - self.__prev self.__prev = ct return self.__format % dt class DebugLogger(SetLogger): """ Logger for debugging purposes. Expands SetLogger with ability to print some interesting information (named Metric... XXX) about current process at each debug printout """ _known_metrics = { # TODO: make up Windows-friendly version or pure Python platform # independent version (probably just make use of psutil) 'vmem' : get_vmem_str, 'vmem_max' : get_vmem_max_str, 'pid' : getpid, # lambda : parse_status(field='Pid'), 'asctime' : time.asctime, 'tb' : TraceBack(), 'tbc' : TraceBack(collide=True), } def __init__(self, metrics=None, offsetbydepth=True, *args, **kwargs): """ Parameters ---------- metrics : iterable of (func or str) or None What metrics (functions) to be reported. If item is a string, it is matched against `_known_metrics` keys. offsetbydepth : bool, optional Either to offset lines depending on backtrace depth (default behavior). *args, **kwargs Passed to SetLogger initialization XXX """ if metrics is None: metrics = [] SetLogger.__init__(self, *args, **kwargs) self.__metrics = [] self._offsetbydepth = offsetbydepth self._reltimer = RelativeTime() self._known_metrics = DebugLogger._known_metrics self._known_metrics['reltime'] = self._reltimer for metric in metrics: self._registerMetric(metric) ##REF: Name was automagically refactored def register_metric(self, func): """Register some metric to report func can be either a function call or a string which should correspond to known metrics """ if isinstance(func, basestring): if func in ['all', 'ALL']: func = self._known_metrics.keys() if isinstance(func, basestring): if func in DebugLogger._known_metrics: func = DebugLogger._known_metrics[func] else: if func in ['?', 'list', 'help']: print 'Known debug metrics: ', \ ', '.join(DebugLogger._known_metrics.keys()) raise SystemExit(0) else: raise ValueError, \ "Unknown name %s for metric in DebugLogger" % \ func + " Known metrics are " + \ `DebugLogger._known_metrics.keys()` elif isinstance(func, list): self.__metrics = [] # reset for item in func: self.register_metric(item) return if not func in self.__metrics: try: from mvpa2.base import debug debug("DBG", "Registering metric %s" % func) self.__metrics.append(func) except: pass def __call__(self, setid, msg, *args, **kwargs): if setid not in self.registered: raise ValueError, "Not registered debug ID %s" % setid if not setid in self.active: # don't even compute the metrics, since they might # be statefull as RelativeTime return msg_ = ' / '.join([str(x()) for x in self.__metrics]) if len(msg_) > 0: msg_ = "{%s}" % msg_ if len(msg) > 0: # determine blank offset using backstacktrace if self._offsetbydepth: level = len(traceback.extract_stack()) - 2 else: level = 1 if len(msg) > 250 and 'DBG' in self.active and not setid.endswith('_TB'): tb = traceback.extract_stack(limit=2) msg += " !!!2LONG!!!. From %s" % str(tb[0]) msg = "DBG%s:%s%s" % (msg_, " "*level, msg) SetLogger.__call__(self, setid, msg, *args, **kwargs) else: msg = msg_ Logger.__call__(self, msg, *args, **kwargs) ##REF: Name was automagically refactored def _set_offset_by_depth(self, b): self._offsetbydepth = b offsetbydepth = property(fget=lambda x:x._offsetbydepth, fset=_set_offset_by_depth) metrics = property(fget=lambda x:x.__metrics, fset=register_metric) if not __debug__: class BlackHoleLogger(SetLogger): '''A logger that does absolutely nothing - it is used as a fallback so that debug(...) can still be called even if not __debug__''' def __init__(self, metrics=None, offsetbydepth=True, *args, **kwargs): '''Initializes the logger - ignores all input arguments''' # do not be evil - initialize through the parent class SetLogger.__init__(self, *args, **kwargs) def __call__(self, setid, msg, *args, **kwargs): pass def register_metric(self, func): pass def register(self, setid, description): pass def set_active_from_string(self, value): pass def print_registered(self, detailed=True): print "BlackHoleLogger: nothing registered "
34.212976
109
0.531682
824b7f371a5990b30dddd5f4fc2643723d5b3406
10,562
py
Python
tasks/summarization/make_datafiles.py
omri123/rotational-unit-of-memory
e796c841e1e837df09497ba77c3bc285db47d02d
[ "MIT" ]
82
2019-04-18T19:32:03.000Z
2022-03-19T00:50:56.000Z
tasks/summarization/make_datafiles.py
omri123/rotational-unit-of-memory
e796c841e1e837df09497ba77c3bc285db47d02d
[ "MIT" ]
4
2019-04-22T11:58:43.000Z
2020-05-31T01:43:03.000Z
tasks/summarization/make_datafiles.py
omri123/rotational-unit-of-memory
e796c841e1e837df09497ba77c3bc285db47d02d
[ "MIT" ]
26
2019-04-22T11:21:42.000Z
2021-11-29T06:01:10.000Z
import sys import os import hashlib import struct import subprocess import collections import tensorflow as tf from tensorflow.core.example import example_pb2 sd_single_close_quote = u'\u2019' # unicode sd_double_close_quote = u'\u201d' END_TOKENS = ['.', '!', '?', '...', "'", "`", '"', sd_single_close_quote, sd_double_close_quote, ")"] # acceptable ways to end a sentence # We use these to separate the summary sentences in the .bin datafiles SENTENCE_START = '<s>' SENTENCE_END = '</s>' all_train_urls = "url_lists/all_train.txt" all_val_urls = "url_lists/all_val.txt" all_test_urls = "url_lists/all_test.txt" sd_tokenized_stories_dir = "sd_paper_tokenized" sd_tokenized_abstracts_dir = "sd_title_tokenized" finished_files_dir = "finished_files" chunks_dir = os.path.join(finished_files_dir, "chunked") # These are the number of .story files we expect there to be in sd_stories_dir and dm_stories_dir num_expected_sd_stories = 50308 VOCAB_SIZE = 50000 CHUNK_SIZE = 1000 # num examples per chunk, for the chunked data def chunk_file(set_name): in_file = 'finished_files/%s.bin' % set_name reader = open(in_file, "rb") chunk = 0 finished = False while not finished: chunk_fname = os.path.join(chunks_dir, '%s_%03d.bin' % (set_name, chunk)) # new chunk with open(chunk_fname, 'wb') as writer: for _ in range(CHUNK_SIZE): len_bytes = reader.read(8) if not len_bytes: finished = True break str_len = struct.unpack('q', len_bytes)[0] example_str = struct.unpack('%ds' % str_len, reader.read(str_len))[0] writer.write(struct.pack('q', str_len)) writer.write(struct.pack('%ds' % str_len, example_str)) chunk += 1 def chunk_all(): # Make a dir to hold the chunks if not os.path.isdir(chunks_dir): os.mkdir(chunks_dir) # Chunk the data for set_name in ['train', 'val', 'test']: print("Splitting %s data into chunks..." % set_name) chunk_file(set_name) print("Saved chunked data in %s" % chunks_dir) def tokenize_stories(stories_dir, tokenized_stories_dir): """Maps a whole directory of .story files to a tokenized version using Stanford CoreNLP Tokenizer""" print("Preparing to tokenize %s to %s..." % (stories_dir, tokenized_stories_dir)) stories = os.listdir(stories_dir) # make IO list file print("Making list of files to tokenize...") with open("mapping.txt", "w") as f: for s in stories: f.write("%s \t %s\n" % (os.path.join(stories_dir, s), os.path.join(tokenized_stories_dir, s))) command = ['java', 'edu.stanford.nlp.process.PTBTokenizer', '-ioFileList', '-preserveLines', 'mapping.txt'] print("Tokenizing %i files in %s and saving in %s..." % (len(stories), stories_dir, tokenized_stories_dir)) subprocess.call(command) print("Stanford CoreNLP Tokenizer has finished.") os.remove("mapping.txt") # Check that the tokenized stories directory contains the same number of files as the original directory num_orig = len(os.listdir(stories_dir)) num_tokenized = len(os.listdir(tokenized_stories_dir)) if num_orig != num_tokenized: raise Exception("The tokenized stories directory %s contains %i files, but it should contain the same number as %s (which has %i files). Was there an error during tokenization?" % (tokenized_stories_dir, num_tokenized, stories_dir, num_orig)) print("Successfully finished tokenizing %s to %s.\n" % (stories_dir, tokenized_stories_dir)) def read_text_file(text_file): lines = [] with open(text_file, "r") as f: for line in f: lines.append(line.strip()) return lines def hashhex(s): """Returns a heximal formated SHA1 hash of the input string.""" h = hashlib.sha1() h.update(s) return h.hexdigest() # def get_url_hashes(url_list): # return [hashhex(url) for url in url_list] def fix_missing_period(line): """Adds a period to a line that is missing a period""" if "@highlight" in line: return line if line=="": return line if line[-1] in END_TOKENS: return line # print line[-1] return line + " ." def get_lines(file): lines = read_text_file(file) # Lowercase everything lines = [line.lower() for line in lines] # Put periods on the ends of lines that are missing them (this is a problem in the dataset because many image captions don't end in periods; consequently they end up in the body of the article as run-on sentences) lines = [fix_missing_period(line) for line in lines] lines = ' '.join(lines) # Separate out article and abstract sentences # article_lines = [] # highlights = [] # next_is_highlight = False # for idx,line in enumerate(lines): # if line == "": # continue # empty line # elif line.startswith("@highlight"): # next_is_highlight = True # elif next_is_highlight: # highlights.append(line) # else: # article_lines.append(line) # Make article into a single string # article = ' '.join(article_lines) # # Make abstract into a signle string, putting <s> and </s> tags around the sentences # abstract = ' '.join(["%s %s %s" % (SENTENCE_START, sent, SENTENCE_END) for sent in highlights]) return lines def write_to_bin(url_file, out_file, makevocab=False): """Reads the tokenized .story files corresponding to the urls listed in the url_file and writes them to a out_file.""" print("Making bin file for URLs listed in %s..." % url_file) url_list = read_text_file(url_file) story_fnames = [s for s in url_list] num_stories = len(story_fnames) if makevocab: vocab_counter = collections.Counter() with open(out_file, 'wb') as writer: for idx,s in enumerate(story_fnames): if idx % 1000 == 0: print("Writing story %i of %i; %.2f percent done" % (idx, num_stories, float(idx)*100.0/float(num_stories))) # Look in the tokenized story dirs to find the .story file corresponding to this url if os.path.isfile(os.path.join(sd_tokenized_stories_dir, s)) and os.path.isfile(os.path.join(sd_tokenized_abstracts_dir, s)): story_file = os.path.join(sd_tokenized_stories_dir, s) abstract_file = os.path.join(sd_tokenized_abstracts_dir, s) else: print("Error: Couldn't find tokenized story file %s in either tokenized story directories %s. Was there an error during tokenization?" % (s, sd_tokenized_stories_dir)) # Check again if tokenized stories directories contain correct number of files print("Checking that the tokenized stories directories %s contain correct number of files..." % (sd_tokenized_stories_dir)) check_num_stories(sd_tokenized_stories_dir, num_expected_sd_stories) raise Exception("Tokenized stories directories %s contain correct number of files but story file %s found in neither." % (sd_tokenized_stories_dir, s)) # Get the strings to write to .bin file article = get_lines(story_file) abstract = get_lines(abstract_file) print(idx, abstract) # Write to tf.Example tf_example = example_pb2.Example() tf_example.features.feature['article'].bytes_list.value.extend([article]) tf_example.features.feature['abstract'].bytes_list.value.extend([abstract]) tf_example_str = tf_example.SerializeToString() str_len = len(tf_example_str) writer.write(struct.pack('q', str_len)) writer.write(struct.pack('%ds' % str_len, tf_example_str)) # Write the vocab to file, if applicable if makevocab: art_tokens = article.split(' ') abs_tokens = abstract.split(' ') abs_tokens = [t for t in abs_tokens if t not in [SENTENCE_START, SENTENCE_END]] # remove these tags from vocab tokens = art_tokens + abs_tokens tokens = [t.strip() for t in tokens] # strip tokens = [t for t in tokens if t!=""] # remove empty vocab_counter.update(tokens) print("Finished writing file %s\n" % out_file) # write vocab to file if makevocab: print("Writing vocab file...") with open(os.path.join(finished_files_dir, "vocab"), 'w') as writer: for word, count in vocab_counter.most_common(VOCAB_SIZE): writer.write(word + ' ' + str(count) + '\n') print("Finished writing vocab file") def check_num_stories(stories_dir, num_expected): num_stories = len(os.listdir(stories_dir)) if num_stories != num_expected: raise Exception("stories directory %s contains %i files but should contain %i" % (stories_dir, num_stories, num_expected)) if __name__ == '__main__': if len(sys.argv) != 3: print("USAGE: python make_datafiles.py <sd_stories_dir> <sd_abstracts_dir>") sys.exit() sd_stories_dir = sys.argv[1] sd_abstracts_dir = sys.argv[2] print("Check the stories/abstracts directories contain the correct number of .story files") check_num_stories(sd_stories_dir, num_expected_sd_stories) check_num_stories(sd_abstracts_dir, num_expected_sd_stories) print("Create some new directories") if not os.path.exists(sd_tokenized_stories_dir): os.makedirs(sd_tokenized_stories_dir) if not os.path.exists(sd_tokenized_abstracts_dir): os.makedirs(sd_tokenized_abstracts_dir) if not os.path.exists(finished_files_dir): os.makedirs(finished_files_dir) print("Run stanford tokenizer on both stories dirs and abstracts dirs, outputting to tokenized stories directories") tokenize_stories(sd_stories_dir, sd_tokenized_stories_dir) tokenize_stories(sd_abstracts_dir, sd_tokenized_abstracts_dir) print("Read the tokenized stories, do a little postprocessing then write to bin files") write_to_bin(all_test_urls, os.path.join(finished_files_dir, "test.bin")) write_to_bin(all_val_urls, os.path.join(finished_files_dir, "val.bin")) write_to_bin(all_train_urls, os.path.join(finished_files_dir, "train.bin"), makevocab=True) print("Chunk the data. This splits each of train.bin, val.bin and test.bin into smaller chunks, each containing e.g. 1000 examples, and saves them in finished_files/chunks") chunk_all()
43.286885
250
0.674778
07db2bc31830c6edfe71c4b56e2362cfbf9a7a7c
11,425
py
Python
script.module.nanscrapers/lib/nanscrapers/modules/js2py/translators/pyjsparserdata.py
TheWardoctor/wardoctors-repo
893f646d9e27251ffc00ca5f918e4eb859a5c8f0
[ "Apache-2.0" ]
1
2019-03-05T09:38:10.000Z
2019-03-05T09:38:10.000Z
script.module.universalscrapers/lib/universalscrapers/modules/js2py/translators/pyjsparserdata.py
Reapercrew666/crypt
e1e0994f5323c6b454ac0f65fb2e579f7bea8e5a
[ "Beerware" ]
null
null
null
script.module.universalscrapers/lib/universalscrapers/modules/js2py/translators/pyjsparserdata.py
Reapercrew666/crypt
e1e0994f5323c6b454ac0f65fb2e579f7bea8e5a
[ "Beerware" ]
1
2021-11-05T20:48:09.000Z
2021-11-05T20:48:09.000Z
# The MIT License # # Copyright 2014, 2015 Piotr Dabkowski # # Permission is hereby granted, free of charge, to any person obtaining # a copy of this software and associated documentation files (the 'Software'), # to deal in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of # the Software, and to permit persons to whom the Software is furnished to do so, subject # to the following conditions: # # The above copyright notice and this permission notice shall be included in all copies or # substantial portions of the Software. # # THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT # LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE # OR THE USE OR OTHER DEALINGS IN THE SOFTWARE from __future__ import unicode_literals import sys import unicodedata import six from collections import defaultdict if six.PY3: unichr = chr xrange = range unicode = str token = { 'BooleanLiteral': 1, 'EOF': 2, 'Identifier': 3, 'Keyword': 4, 'NullLiteral': 5, 'NumericLiteral': 6, 'Punctuator': 7, 'StringLiteral': 8, 'RegularExpression': 9, 'Template': 10 } #TokenName = {v:k for k,v in token.iteritems()} TokenName = {} for k, v in token.iteritems(): TokenName[v] = k FnExprTokens = ['(', '{', '[', 'in', 'typeof', 'instanceof', 'new', 'return', 'case', 'delete', 'throw', 'void', # assignment operators '=', '+=', '-=', '*=', '/=', '%=', '<<=', '>>=', '>>>=', '&=', '|=', '^=', ',', # binary/unary operators '+', '-', '*', '/', '%', '++', '--', '<<', '>>', '>>>', '&', '|', '^', '!', '~', '&&', '||', '?', ':', '===', '==', '>=', '<=', '<', '>', '!=', '!=='] syntax= ['AssignmentExpression', 'AssignmentPattern', 'ArrayExpression', 'ArrayPattern', 'ArrowFunctionExpression', 'BlockStatement', 'BinaryExpression', 'BreakStatement', 'CallExpression', 'CatchClause', 'ClassBody', 'ClassDeclaration', 'ClassExpression', 'ConditionalExpression', 'ContinueStatement', 'DoWhileStatement', 'DebuggerStatement', 'EmptyStatement', 'ExportAllDeclaration', 'ExportDefaultDeclaration', 'ExportNamedDeclaration', 'ExportSpecifier', 'ExpressionStatement', 'ForStatement', 'ForInStatement', 'FunctionDeclaration', 'FunctionExpression', 'Identifier', 'IfStatement', 'ImportDeclaration', 'ImportDefaultSpecifier', 'ImportNamespaceSpecifier', 'ImportSpecifier', 'Literal', 'LabeledStatement', 'LogicalExpression', 'MemberExpression', 'MethodDefinition', 'NewExpression', 'ObjectExpression', 'ObjectPattern', 'Program', 'Property', 'RestElement', 'ReturnStatement', 'SequenceExpression', 'SpreadElement', 'Super', 'SwitchCase', 'SwitchStatement', 'TaggedTemplateExpression', 'TemplateElement', 'TemplateLiteral', 'ThisExpression', 'ThrowStatement', 'TryStatement', 'UnaryExpression', 'UpdateExpression', 'VariableDeclaration', 'VariableDeclarator', 'WhileStatement', 'WithStatement'] # Error messages should be identical to V8. messages = { 'UnexpectedToken': 'Unexpected token %s', 'UnexpectedNumber': 'Unexpected number', 'UnexpectedString': 'Unexpected string', 'UnexpectedIdentifier': 'Unexpected identifier', 'UnexpectedReserved': 'Unexpected reserved word', 'UnexpectedTemplate': 'Unexpected quasi %s', 'UnexpectedEOS': 'Unexpected end of input', 'NewlineAfterThrow': 'Illegal newline after throw', 'InvalidRegExp': 'Invalid regular expression', 'UnterminatedRegExp': 'Invalid regular expression: missing /', 'InvalidLHSInAssignment': 'Invalid left-hand side in assignment', 'InvalidLHSInForIn': 'Invalid left-hand side in for-in', 'MultipleDefaultsInSwitch': 'More than one default clause in switch statement', 'NoCatchOrFinally': 'Missing catch or finally after try', 'UnknownLabel': 'Undefined label \'%s\'', 'Redeclaration': '%s \'%s\' has already been declared', 'IllegalContinue': 'Illegal continue statement', 'IllegalBreak': 'Illegal break statement', 'IllegalReturn': 'Illegal return statement', 'StrictModeWith': 'Strict mode code may not include a with statement', 'StrictCatchVariable': 'Catch variable may not be eval or arguments in strict mode', 'StrictVarName': 'Variable name may not be eval or arguments in strict mode', 'StrictParamName': 'Parameter name eval or arguments is not allowed in strict mode', 'StrictParamDupe': 'Strict mode function may not have duplicate parameter names', 'StrictFunctionName': 'Function name may not be eval or arguments in strict mode', 'StrictOctalLiteral': 'Octal literals are not allowed in strict mode.', 'StrictDelete': 'Delete of an unqualified identifier in strict mode.', 'StrictLHSAssignment': 'Assignment to eval or arguments is not allowed in strict mode', 'StrictLHSPostfix': 'Postfix increment/decrement may not have eval or arguments operand in strict mode', 'StrictLHSPrefix': 'Prefix increment/decrement may not have eval or arguments operand in strict mode', 'StrictReservedWord': 'Use of future reserved word in strict mode', 'TemplateOctalLiteral': 'Octal literals are not allowed in template strings.', 'ParameterAfterRestParameter': 'Rest parameter must be last formal parameter', 'DefaultRestParameter': 'Unexpected token =', 'ObjectPatternAsRestParameter': 'Unexpected token {', 'DuplicateProtoProperty': 'Duplicate __proto__ fields are not allowed in object literals', 'ConstructorSpecialMethod': 'Class constructor may not be an accessor', 'DuplicateConstructor': 'A class may only have one constructor', 'StaticPrototype': 'Classes may not have static property named prototype', 'MissingFromClause': 'Unexpected token', 'NoAsAfterImportNamespace': 'Unexpected token', 'InvalidModuleSpecifier': 'Unexpected token', 'IllegalImportDeclaration': 'Unexpected token', 'IllegalExportDeclaration': 'Unexpected token'} PRECEDENCE = {'||':1, '&&':2, '|':3, '^':4, '&':5, '==':6, '!=':6, '===':6, '!==':6, '<':7, '>':7, '<=':7, '>=':7, 'instanceof':7, 'in':7, '<<':8, '>>':8, '>>>':8, '+':9, '-':9, '*':11, '/':11, '%':11} class Token: pass class Syntax: pass class Messages: pass class PlaceHolders: ArrowParameterPlaceHolder = 'ArrowParameterPlaceHolder' for k,v in token.items(): setattr(Token, k, v) for e in syntax: setattr(Syntax, e, e) for k,v in messages.items(): setattr(Messages, k, v) #http://stackoverflow.com/questions/14245893/efficiently-list-all-characters-in-a-given-unicode-category BOM = u'\uFEFF' ZWJ = u'\u200D' ZWNJ = u'\u200C' TAB = u'\u0009' VT = u'\u000B' FF = u'\u000C' SP = u'\u0020' NBSP = u'\u00A0' LF = u'\u000A' CR = u'\u000D' LS = u'\u2028' PS = u'\u2029' U_CATEGORIES = defaultdict(list) for c in map(unichr, range(sys.maxunicode + 1)): U_CATEGORIES[unicodedata.category(c)].append(c) UNICODE_LETTER = set(U_CATEGORIES['Lu']+U_CATEGORIES['Ll']+ U_CATEGORIES['Lt']+U_CATEGORIES['Lm']+ U_CATEGORIES['Lo']+U_CATEGORIES['Nl']) UNICODE_COMBINING_MARK = set(U_CATEGORIES['Mn']+U_CATEGORIES['Mc']) UNICODE_DIGIT = set(U_CATEGORIES['Nd']) UNICODE_CONNECTOR_PUNCTUATION = set(U_CATEGORIES['Pc']) IDENTIFIER_START = UNICODE_LETTER.union(['$','_', '\\']) # and some fucking unicode escape sequence IDENTIFIER_PART = IDENTIFIER_START.union(UNICODE_COMBINING_MARK).union(UNICODE_DIGIT).union(UNICODE_CONNECTOR_PUNCTUATION).union([ZWJ, ZWNJ]) WHITE_SPACE = [0x20, 0x09, 0x0B, 0x0C, 0xA0, 0x1680, 0x180E, 0x2000, 0x2001, 0x2002, 0x2003, 0x2004, 0x2005, 0x2006, 0x2007, 0x2008, 0x2009, 0x200A, 0x202F, 0x205F, 0x3000, 0xFEFF] LINE_TERMINATORS = [0x0A, 0x0D, 0x2028, 0x2029] def isIdentifierStart(ch): return (ch if isinstance(ch, unicode) else unichr(ch)) in IDENTIFIER_START def isIdentifierPart(ch): return (ch if isinstance(ch, unicode) else unichr(ch)) in IDENTIFIER_PART def isWhiteSpace(ch): return (ord(ch) if isinstance(ch, unicode) else ch) in WHITE_SPACE def isLineTerminator(ch): return (ord(ch) if isinstance(ch, unicode) else ch) in LINE_TERMINATORS OCTAL = ['0', '1', '2', '3', '4', '5', '6', '7'] DEC = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] HEX = set('0123456789abcdefABCDEF') HEX_CONV = {'a': 10, 'c': 12, 'b': 11, 'e': 14, 'd': 13, 'f': 15, '1': 1, '0': 0, '3': 3, '2': 2, '5': 5, '4': 4, '7': 7, '6': 6, '9': 9, '8': 8} for i,e in enumerate('ABCDEF', 10): HEX_CONV[e] = i def isDecimalDigit(ch): return (ch if isinstance(ch, unicode) else unichr(ch)) in DEC def isHexDigit(ch): return (ch if isinstance(ch, unicode) else unichr(ch)) in HEX def isOctalDigit(ch): return (ch if isinstance(ch, unicode) else unichr(ch)) in OCTAL def isFutureReservedWord(w): return w in [ 'enum', 'export', 'import', 'super'] def isStrictModeReservedWord(w): return w in ['implements', 'interface', 'package', 'private', 'protected', 'public', 'static', 'yield', 'let'] def isRestrictedWord(w): return w in ['eval', 'arguments'] def isKeyword(w): # 'const' is specialized as Keyword in V8. # 'yield' and 'let' are for compatibility with SpiderMonkey and ES.next. # Some others are from future reserved words. return w in ['if', 'in', 'do', 'var', 'for', 'new', 'try', 'let', 'this', 'else', 'case', 'void', 'with', 'enum', 'while', 'break', 'catch', 'throw', 'const', 'yield', 'class', 'super', 'return', 'typeof', 'delete', 'switch', 'export', 'import', 'default', 'finally', 'extends', 'function', 'continue', 'debugger', 'instanceof', 'pyimport'] class JsSyntaxError(Exception): pass if __name__=='__main__': assert isLineTerminator('\n') assert isLineTerminator(0x0A) assert isIdentifierStart('$') assert isIdentifierStart(100) assert isWhiteSpace(' ')
37.956811
145
0.605777
0b3b56f7d3d7180ef4d21e4f9a48de524bd857e6
156
py
Python
olympics/string_test.py
ColeWeinstein/cs257
18453fd5d556169484c0fc3414f5e1fa07bbb04c
[ "MIT" ]
null
null
null
olympics/string_test.py
ColeWeinstein/cs257
18453fd5d556169484c0fc3414f5e1fa07bbb04c
[ "MIT" ]
null
null
null
olympics/string_test.py
ColeWeinstein/cs257
18453fd5d556169484c0fc3414f5e1fa07bbb04c
[ "MIT" ]
null
null
null
def main(): string_seq = 'Hello, {name}. How are you?'.format(name='Cole', medal=True) print(string_seq) if __name__ == '__main__': main()
26
79
0.608974
52ebe634af580c3414104c8f8c2d3ac7d77adf61
2,980
py
Python
MIoU.py
kanekoNK/MaskImg
142b09484be58737a4e9e1bef18cf6289f8c055b
[ "MIT" ]
null
null
null
MIoU.py
kanekoNK/MaskImg
142b09484be58737a4e9e1bef18cf6289f8c055b
[ "MIT" ]
null
null
null
MIoU.py
kanekoNK/MaskImg
142b09484be58737a4e9e1bef18cf6289f8c055b
[ "MIT" ]
null
null
null
import numpy as np import cv2 from time import sleep from PIL import Image import matplotlib.pyplot as plt import glob def main(): FClass = sorted(glob.glob("/home/kaneko/models/research/deeplab/IoUtestimg/Class/*")) Fimg = sorted(glob.glob("/home/kaneko/models/research/deeplab/IoUtestimg/1000/*")) Sum = 0 for i in range(0,15): print(FClass[i]) print(Fimg[i]) image = cv2.imread(Fimg[i]) # ファイル読み込み image1 = cv2.imread(FClass[i]) # ファイル読み込み image2 = cv2.resize(image1, dsize=(513, 384)) Sum = Sum + sub(image, image2) print(Sum) print(i+1) MIoU = Sum / 15 print(MIoU) def sub(image, image2): # BGRでの色抽出 #af 茎の色 bgrLower = np.array([0, 100, 0]) # 抽出する色の下限 bgrUpper = np.array([50, 150, 50]) # 抽出する色の上限 bgrResult1 = bgrExtraction(image, bgrLower, bgrUpper) sleep(1) #af 葉っぱの色 # bgrLower1 = np.array([0, 0, 120]) # 抽出する色の下限 # bgrUpper1 = np.array([50, 50, 140]) # 抽出する色の上限 # bgrResult = bgrExtraction(image, bgrLower1, bgrUpper1) # cv2.imshow('BGR_test2', bgrResult) # sleep(1) bgrLower = np.array([200, 0, 0]) # 抽出する色の下限 bgrUpper = np.array([255, 50, 50]) # 抽出する色の上限 bgrResult2 = bgrExtraction(image2, bgrLower, bgrUpper) sleep(1) blended = cv2.addWeighted(src1=bgrResult1,alpha=0.7,src2=bgrResult2,beta=0.3,gamma=0) # cv2.imshow('1 + 2', blended) hsv = cv2.cvtColor(blended, cv2.COLOR_BGR2HSV) bin_img = cv2.inRange(hsv, (0, 10, 0), (255, 255, 255)) # cv2.imshow('1mask OR 2mask', bin_img) hsv = cv2.cvtColor(bgrResult1, cv2.COLOR_BGR2HSV) bin_img2 = cv2.inRange(hsv, (0, 10, 0), (255, 255, 255)) # cv2.imshow('1mask', bin_img2) hsv = cv2.cvtColor(bgrResult2, cv2.COLOR_BGR2HSV) bin_img3 = cv2.inRange(hsv, (0, 10, 0), (255, 255, 255)) # cv2.imshow('2mask', bin_img3) img_msk1 = cv2.cvtColor(bgrResult1, cv2.COLOR_BGR2GRAY) img_msk2 = cv2.cvtColor(bgrResult2, cv2.COLOR_BGR2GRAY) img_AND = cv2.bitwise_and(img_msk1, img_msk2) # cv2.imshow('1mask AND 2mask', img_AND) th,img_up = cv2.threshold(img_AND, 1, 255, cv2.THRESH_BINARY) # cv2.imshow('1mask AND 2mask 2', img_up) pixel_number = np.size(img_up) pixel_sum = np.sum(img_up) white_pixel_number1 = pixel_sum/255 print("Area of Intersection(AND) ピクセル数",white_pixel_number1) pixel_number = np.size(bin_img) pixel_sum = np.sum(bin_img) white_pixel_number2 = pixel_sum/255 print("Area of Union(OR) ピクセル数",white_pixel_number2) IoU = white_pixel_number1 / white_pixel_number2 print("IoU", IoU) return IoU # cv2.waitKey(0) # cv2.destroyAllWindows() # BGRで特定の色を抽出する関数 def bgrExtraction(image, bgrLower, bgrUpper): img_mask = cv2.inRange(image, bgrLower, bgrUpper) # BGRからマスクを作成 result = cv2.bitwise_and(image, image, mask=img_mask) # 元画像とマスクを合成 return result if __name__ == '__main__': main()
30.10101
89
0.651678
e5081de3fcf654692c34e4d9255311a84f14e72e
77,634
py
Python
sympy/combinatorics/permutations.py
lemmalearning/sympy
62ad387ed3f7b243c889dd342296afc9a32ad1ea
[ "BSD-3-Clause" ]
1
2015-08-31T06:55:47.000Z
2015-08-31T06:55:47.000Z
sympy/combinatorics/permutations.py
lemmalearning/sympy
62ad387ed3f7b243c889dd342296afc9a32ad1ea
[ "BSD-3-Clause" ]
null
null
null
sympy/combinatorics/permutations.py
lemmalearning/sympy
62ad387ed3f7b243c889dd342296afc9a32ad1ea
[ "BSD-3-Clause" ]
3
2015-04-18T22:33:32.000Z
2015-09-23T06:45:07.000Z
from __future__ import print_function, division import random from collections import defaultdict from sympy.core import Basic from sympy.core.compatibility import is_sequence, reduce, xrange from sympy.utilities.iterables import (flatten, has_variety, minlex, has_dups, runs) from sympy.polys.polytools import lcm from sympy.matrices import zeros from sympy.mpmath.libmp.libintmath import ifac def _af_rmul(a, b): """ Return the product b*a; input and output are array forms. The ith value is a[b[i]]. Examples ======== >>> from sympy.combinatorics.permutations import _af_rmul, Permutation >>> Permutation.print_cyclic = False >>> a, b = [1, 0, 2], [0, 2, 1] >>> _af_rmul(a, b) [1, 2, 0] >>> [a[b[i]] for i in range(3)] [1, 2, 0] This handles the operands in reverse order compared to the ``*`` operator: >>> a = Permutation(a); b = Permutation(b) >>> list(a*b) [2, 0, 1] >>> [b(a(i)) for i in range(3)] [2, 0, 1] See Also ======== rmul, _af_rmuln """ return [a[i] for i in b] def _af_rmuln(*abc): """ Given [a, b, c, ...] return the product of ...*c*b*a using array forms. The ith value is a[b[c[i]]]. Examples ======== >>> from sympy.combinatorics.permutations import _af_rmul, Permutation >>> Permutation.print_cyclic = False >>> a, b = [1, 0, 2], [0, 2, 1] >>> _af_rmul(a, b) [1, 2, 0] >>> [a[b[i]] for i in range(3)] [1, 2, 0] This handles the operands in reverse order compared to the ``*`` operator: >>> a = Permutation(a); b = Permutation(b) >>> list(a*b) [2, 0, 1] >>> [b(a(i)) for i in range(3)] [2, 0, 1] See Also ======== rmul, _af_rmul """ a = abc m = len(a) if m == 3: p0, p1, p2 = a return [p0[p1[i]] for i in p2] if m == 4: p0, p1, p2, p3 = a return [p0[p1[p2[i]]] for i in p3] if m == 5: p0, p1, p2, p3, p4 = a return [p0[p1[p2[p3[i]]]] for i in p4] if m == 6: p0, p1, p2, p3, p4, p5 = a return [p0[p1[p2[p3[p4[i]]]]] for i in p5] if m == 7: p0, p1, p2, p3, p4, p5, p6 = a return [p0[p1[p2[p3[p4[p5[i]]]]]] for i in p6] if m == 8: p0, p1, p2, p3, p4, p5, p6, p7 = a return [p0[p1[p2[p3[p4[p5[p6[i]]]]]]] for i in p7] if m == 1: return a[0][:] if m == 2: a, b = a return [a[i] for i in b] if m == 0: raise ValueError("String must not be empty") p0 = _af_rmuln(*a[:m//2]) p1 = _af_rmuln(*a[m//2:]) return [p0[i] for i in p1] def _af_parity(pi): """ Computes the parity of a permutation in array form. The parity of a permutation reflects the parity of the number of inversions in the permutation, i.e., the number of pairs of x and y such that x > y but p[x] < p[y]. Examples ======== >>> from sympy.combinatorics.permutations import _af_parity >>> _af_parity([0,1,2,3]) 0 >>> _af_parity([3,2,0,1]) 1 See Also ======== Permutation """ n = len(pi) a = [0] * n c = 0 for j in range(n): if a[j] == 0: c += 1 a[j] = 1 i = j while pi[i] != j: i = pi[i] a[i] = 1 return (n - c) % 2 def _af_invert(a): """ Finds the inverse, ~A, of a permutation, A, given in array form. Examples ======== >>> from sympy.combinatorics.permutations import _af_invert, _af_rmul >>> A = [1, 2, 0, 3] >>> _af_invert(A) [2, 0, 1, 3] >>> _af_rmul(_, A) [0, 1, 2, 3] See Also ======== Permutation, __invert__ """ inv_form = [0] * len(a) for i, ai in enumerate(a): inv_form[ai] = i return inv_form def _af_pow(a, n): """ Routine for finding powers of a permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation, _af_pow >>> Permutation.print_cyclic = False >>> p = Permutation([2,0,3,1]) >>> p.order() 4 >>> _af_pow(p._array_form, 4) [0, 1, 2, 3] """ if n == 0: return list(range(len(a))) if n < 0: return _af_pow(_af_invert(a), -n) if n == 1: return a[:] elif n == 2: b = [a[i] for i in a] elif n == 3: b = [a[a[i]] for i in a] elif n == 4: b = [a[a[a[i]]] for i in a] else: # use binary multiplication b = list(range(len(a))) while 1: if n & 1: b = [b[i] for i in a] n -= 1 if not n: break if n % 4 == 0: a = [a[a[a[i]]] for i in a] n = n // 4 elif n % 2 == 0: a = [a[i] for i in a] n = n // 2 return b def _af_commutes_with(a, b): """ Checks if the two permutations with array forms given by ``a`` and ``b`` commute. Examples ======== >>> from sympy.combinatorics.permutations import _af_commutes_with >>> _af_commutes_with([1,2,0], [0,2,1]) False See Also ======== Permutation, commutes_with """ return not any(a[b[i]] != b[a[i]] for i in range(len(a) - 1)) class Cycle(dict): """ Wrapper around dict which provides the functionality of a disjoint cycle. A cycle shows the rule to use to move subsets of elements to obtain a permutation. The Cycle class is more flexible that Permutation in that 1) all elements need not be present in order to investigate how multiple cycles act in sequence and 2) it can contain singletons: >>> from sympy.combinatorics.permutations import Perm, Cycle A Cycle will automatically parse a cycle given as a tuple on the rhs: >>> Cycle(1, 2)(2, 3) Cycle(1, 3, 2) The identity cycle, Cycle(), can be used to start a product: >>> Cycle()(1, 2)(2,3) Cycle(1, 3, 2) The array form of a Cycle can be obtained by calling the list method (or passing it to the list function) and all elements from 0 will be shown: >>> a = Cycle(1, 2) >>> a.list() [0, 2, 1] >>> list(a) [0, 2, 1] If a larger (or smaller) range is desired use the list method and provide the desired size -- but the Cycle cannot be truncated to a size smaller than the largest element that is out of place: >>> b = Cycle(2,4)(1,2)(3,1,4)(1,3) >>> b.list() [0, 2, 1, 3, 4] >>> b.list(b.size + 1) [0, 2, 1, 3, 4, 5] >>> b.list(-1) [0, 2, 1] Singletons are not shown when printing with one exception: the largest element is always shown -- as a singleton if necessary: >>> Cycle(1, 4, 10)(4, 5) Cycle(1, 5, 4, 10) >>> Cycle(1, 2)(4)(5)(10) Cycle(1, 2)(10) The array form can be used to instantiate a Permutation so other properties of the permutation can be investigated: >>> Perm(Cycle(1,2)(3,4).list()).transpositions() [(1, 2), (3, 4)] Notes ===== The underlying structure of the Cycle is a dictionary and although the __iter__ method has been redefiend to give the array form of the cycle, the underlying dictionary items are still available with the such methods as items(): >>> list(Cycle(1, 2).items()) [(1, 2), (2, 1)] See Also ======== Permutation """ def __missing__(self, arg): """Enter arg into dictionary and return arg.""" self[arg] = arg return arg def __iter__(self): for i in self.list(): yield i def __call__(self, *other): """Return product of cycles processed from R to L. Examples ======== >>> from sympy.combinatorics.permutations import Cycle as C >>> from sympy.combinatorics.permutations import Permutation as Perm >>> C(1, 2)(2, 3) Cycle(1, 3, 2) An instance of a Cycle will automatically parse list-like objects and Permutations that are on the right. It is more flexible than the Permutation in that all elements need not be present: >>> a = C(1, 2) >>> a(2, 3) Cycle(1, 3, 2) >>> a(2, 3)(4, 5) Cycle(1, 3, 2)(4, 5) """ rv = Cycle(*other) for k, v in zip(list(self.keys()), [rv[self[k]] for k in self.keys()]): rv[k] = v return rv def list(self, size=None): """Return the cycles as an explicit list starting from 0 up to the greater of the largest value in the cycles and size. Truncation of trailing unmoved items will occur when size is less than the maximum element in the cycle; if this is desired, setting ``size=-1`` will guarantee such trimming. Examples ======== >>> from sympy.combinatorics.permutations import Cycle >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Cycle(2, 3)(4, 5) >>> p.list() [0, 1, 3, 2, 5, 4] >>> p.list(10) [0, 1, 3, 2, 5, 4, 6, 7, 8, 9] Passing a length too small will trim trailing, unchanged elements in the permutation: >>> Cycle(2, 4)(1, 2, 4).list(-1) [0, 2, 1] """ if not self and size is None: raise ValueError('must give size for empty Cycle') if size is not None: big = max([i for i in self.keys() if self[i] != i]) size = max(size, big + 1) else: size = self.size return [self[i] for i in range(size)] def __repr__(self): """We want it to print as a Cycle, not as a dict. Examples ======== >>> from sympy.combinatorics import Cycle >>> Cycle(1, 2) Cycle(1, 2) >>> print(_) Cycle(1, 2) >>> list(Cycle(1, 2).items()) [(1, 2), (2, 1)] """ if not self: return 'Cycle()' cycles = Permutation(self).cyclic_form s = ''.join(str(tuple(c)) for c in cycles) big = self.size - 1 if not any(i == big for c in cycles for i in c): s += '(%s)' % big return 'Cycle%s' % s def __init__(self, *args): """Load up a Cycle instance with the values for the cycle. Examples ======== >>> from sympy.combinatorics.permutations import Cycle >>> Cycle(1, 2, 6) Cycle(1, 2, 6) """ if not args: return if len(args) == 1: if isinstance(args[0], Permutation): for c in args[0].cyclic_form: self.update(self(*c)) return elif isinstance(args[0], Cycle): for k, v in args[0].items(): self[k] = v return args = [int(a) for a in args] if has_dups(args): raise ValueError('All elements must be unique in a cycle.') for i in range(-len(args), 0): self[args[i]] = args[i + 1] @property def size(self): return max(self.keys()) + 1 def copy(self): return Cycle(self) class Permutation(Basic): """ A permutation, alternatively known as an 'arrangement number' or 'ordering' is an arrangement of the elements of an ordered list into a one-to-one mapping with itself. The permutation of a given arrangement is given by indicating the positions of the elements after re-arrangment [2]_. For example, if one started with elements [x, y, a, b] (in that order) and they were reordered as [x, y, b, a] then the permutation would be [0, 1, 3, 2]. Notice that (in SymPy) the first element is always referred to as 0 and the permutation uses the indices of the elements in the original ordering, not the elements (a, b, etc...) themselves. >>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = False Permutations Notation ===================== Permutations are commonly represented in disjoint cycle or array forms. Array Notation and 2-line Form ------------------------------------ In the 2-line form, the elements and their final positions are shown as a matrix with 2 rows: [0 1 2 ... n-1] [p(0) p(1) p(2) ... p(n-1)] Since the first line is always range(n), where n is the size of p, it is sufficient to represent the permutation by the second line, referred to as the "array form" of the permutation. This is entered in brackets as the argument to the Permutation class: >>> p = Permutation([0, 2, 1]); p Permutation([0, 2, 1]) Given i in range(p.size), the permutation maps i to i^p >>> [i^p for i in range(p.size)] [0, 2, 1] The composite of two permutations p*q means first apply p, then q, so i^(p*q) = (i^p)^q which is i^p^q according to Python precedence rules: >>> q = Permutation([2, 1, 0]) >>> [i^p^q for i in range(3)] [2, 0, 1] >>> [i^(p*q) for i in range(3)] [2, 0, 1] One can use also the notation p(i) = i^p, but then the composition rule is (p*q)(i) = q(p(i)), not p(q(i)): >>> [(p*q)(i) for i in range(p.size)] [2, 0, 1] >>> [q(p(i)) for i in range(p.size)] [2, 0, 1] >>> [p(q(i)) for i in range(p.size)] [1, 2, 0] Disjoint Cycle Notation ----------------------- In disjoint cycle notation, only the elements that have shifted are indicated. In the above case, the 2 and 1 switched places. This can be entered in two ways: >>> Permutation(1, 2) == Permutation([[1, 2]]) == p True Only the relative ordering of elements in a cycle matter: >>> Permutation(1,2,3) == Permutation(2,3,1) == Permutation(3,1,2) True The disjoint cycle notation is convenient when representing permutations that have several cycles in them: >>> Permutation(1, 2)(3, 5) == Permutation([[1, 2], [3, 5]]) True It also provides some economy in entry when computing products of permutations that are written in disjoint cycle notation: >>> Permutation(1, 2)(1, 3)(2, 3) Permutation([0, 3, 2, 1]) >>> _ == Permutation([[1, 2]])*Permutation([[1, 3]])*Permutation([[2, 3]]) True Entering a singleton in a permutation is a way to indicate the size of the permutation. The ``size`` keyword can also be used. Array-form entry: >>> Permutation([[1, 2], [9]]) Permutation([0, 2, 1], size=10) >>> Permutation([[1, 2]], size=10) Permutation([0, 2, 1], size=10) Cyclic-form entry: >>> Permutation(1, 2, size=10) Permutation([0, 2, 1], size=10) >>> Permutation(9)(1, 2) Permutation([0, 2, 1], size=10) Caution: no singleton containing an element larger than the largest in any previous cycle can be entered. This is an important difference in how Permutation and Cycle handle the __call__ syntax. A singleton argument at the start of a Permutation performs instantiation of the Permutation and is permitted: >>> Permutation(5) Permutation([], size=6) A singleton entered after instantiation is a call to the permutation -- a function call -- and if the argument is out of range it will trigger an error. For this reason, it is better to start the cycle with the singleton: The following fails because there is is no element 3: >>> Permutation(1, 2)(3) Traceback (most recent call last): ... IndexError: list index out of range This is ok: only the call to an out of range singleton is prohibited; otherwise the permutation autosizes: >>> Permutation(3)(1, 2) Permutation([0, 2, 1, 3]) >>> Permutation(1, 2)(3, 4) == Permutation(3, 4)(1, 2) True Equality testing ---------------- The array forms must be the same in order for permutations to be equal: >>> Permutation([1, 0, 2, 3]) == Permutation([1, 0]) False Identity Permutation -------------------- The identity permutation is a permutation in which no element is out of place. It can be entered in a variety of ways. All the following create an identity permutation of size 4: >>> I = Permutation([0, 1, 2, 3]) >>> all(p == I for p in [ ... Permutation(3), ... Permutation(range(4)), ... Permutation([], size=4), ... Permutation(size=4)]) True Watch out for entering the range *inside* a set of brackets (which is cycle notation): >>> I == Permutation([range(4)]) False Permutation Printing ==================== There are a few things to note about how Permutations are printed. 1) If you prefer one form (array or cycle) over another, you can set that with the print_cyclic flag. >>> Permutation(1, 2)(4, 5)(3, 4) Permutation([0, 2, 1, 4, 5, 3]) >>> p = _ >>> Permutation.print_cyclic = True >>> p Permutation(1, 2)(3, 4, 5) >>> Permutation.print_cyclic = False 2) Regardless of the setting, a list of elements in the array for cyclic form can be obtained and either of those can be copied and supplied as the argument to Permutation: >>> p.array_form [0, 2, 1, 4, 5, 3] >>> p.cyclic_form [[1, 2], [3, 4, 5]] >>> Permutation(_) == p True 3) Printing is economical in that as little as possible is printed while retaining all information about the size of the permutation: >>> Permutation([1, 0, 2, 3]) Permutation([1, 0, 2, 3]) >>> Permutation([1, 0, 2, 3], size=20) Permutation([1, 0], size=20) >>> Permutation([1, 0, 2, 4, 3, 5, 6], size=20) Permutation([1, 0, 2, 4, 3], size=20) >>> p = Permutation([1, 0, 2, 3]) >>> Permutation.print_cyclic = True >>> p Permutation(3)(0, 1) >>> Permutation.print_cyclic = False The 2 was not printed but it is still there as can be seen with the array_form and size methods: >>> p.array_form [1, 0, 2, 3] >>> p.size 4 Short introduction to other methods =================================== The permutation can act as a bijective function, telling what element is located at a given position >>> q = Permutation([5, 2, 3, 4, 1, 0]) >>> q.array_form[1] # the hard way 2 >>> q(1) # the easy way 2 >>> dict([(i, q(i)) for i in range(q.size)]) # showing the bijection {0: 5, 1: 2, 2: 3, 3: 4, 4: 1, 5: 0} The full cyclic form (including singletons) can be obtained: >>> p.full_cyclic_form [[0, 1], [2], [3]] Any permutation can be factored into transpositions of pairs of elements: >>> Permutation([[1, 2], [3, 4, 5]]).transpositions() [(1, 2), (3, 5), (3, 4)] >>> Permutation.rmul(*[Permutation([ti], size=6) for ti in _]).cyclic_form [[1, 2], [3, 4, 5]] The number of permutations on a set of n elements is given by n! and is called the cardinality. >>> p.size 4 >>> p.cardinality 24 A given permutation has a rank among all the possible permutations of the same elements, but what that rank is depends on how the permutations are enumerated. (There are a number of different methods of doing so.) The lexicographic rank is given by the rank method and this rank is used to increment a partion with addition/subtraction: >>> p.rank() 6 >>> p + 1 Permutation([1, 0, 3, 2]) >>> p.next_lex() Permutation([1, 0, 3, 2]) >>> _.rank() 7 >>> p.unrank_lex(p.size, rank=7) Permutation([1, 0, 3, 2]) The product of two permutations p and q is defined as their composition as functions, (p*q)(i) = q(p(i)) [6]_. >>> p = Permutation([1, 0, 2, 3]) >>> q = Permutation([2, 3, 1, 0]) >>> list(q*p) [2, 3, 0, 1] >>> list(p*q) [3, 2, 1, 0] >>> [q(p(i)) for i in range(p.size)] [3, 2, 1, 0] The permutation can be 'applied' to any list-like object, not only Permutations: >>> p(['zero', 'one', 'four', 'two']) ['one', 'zero', 'four', 'two'] >>> p('zo42') ['o', 'z', '4', '2'] If you have a list of arbitrary elements, the corresponding permutation can be found with the from_sequence method: >>> Permutation.from_sequence('SymPy') Permutation([1, 3, 2, 0, 4]) See Also ======== Cycle References ========== .. [1] Skiena, S. 'Permutations.' 1.1 in Implementing Discrete Mathematics Combinatorics and Graph Theory with Mathematica. Reading, MA: Addison-Wesley, pp. 3-16, 1990. .. [2] Knuth, D. E. The Art of Computer Programming, Vol. 4: Combinatorial Algorithms, 1st ed. Reading, MA: Addison-Wesley, 2011. .. [3] Wendy Myrvold and Frank Ruskey. 2001. Ranking and unranking permutations in linear time. Inf. Process. Lett. 79, 6 (September 2001), 281-284. DOI=10.1016/S0020-0190(01)00141-7 .. [4] D. L. Kreher, D. R. Stinson 'Combinatorial Algorithms' CRC Press, 1999 .. [5] Graham, R. L.; Knuth, D. E.; and Patashnik, O. Concrete Mathematics: A Foundation for Computer Science, 2nd ed. Reading, MA: Addison-Wesley, 1994. .. [6] http://en.wikipedia.org/wiki/Permutation#Product_and_inverse .. [7] http://en.wikipedia.org/wiki/Lehmer_code """ is_Permutation = True _array_form = None _cyclic_form = None _cycle_structure = None _size = None _rank = None def __new__(cls, *args, **kwargs): """ Constructor for the Permutation object from a list or a list of lists in which all elements of the permutation may appear only once. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False Permutations entered in array-form are left unaltered: >>> Permutation([0, 2, 1]) Permutation([0, 2, 1]) Permutations entered in cyclic form are converted to array form; singletons need not be entered, but can be entered to indicate the largest element: >>> Permutation([[4, 5, 6], [0, 1]]) Permutation([1, 0, 2, 3, 5, 6, 4]) >>> Permutation([[4, 5, 6], [0, 1], [19]]) Permutation([1, 0, 2, 3, 5, 6, 4], size=20) All manipulation of permutations assumes that the smallest element is 0 (in keeping with 0-based indexing in Python) so if the 0 is missing when entering a permutation in array form, an error will be raised: >>> Permutation([2, 1]) Traceback (most recent call last): ... ValueError: Integers 0 through 2 must be present. If a permutation is entered in cyclic form, it can be entered without singletons and the ``size`` specified so those values can be filled in, otherwise the array form will only extend to the maximum value in the cycles: >>> Permutation([[1, 4], [3, 5, 2]], size=10) Permutation([0, 4, 3, 5, 1, 2], size=10) >>> _.array_form [0, 4, 3, 5, 1, 2, 6, 7, 8, 9] """ size = kwargs.pop('size', None) if size is not None: size = int(size) #a) () #b) (1) = identity #c) (1, 2) = cycle #d) ([1, 2, 3]) = array form #e) ([[1, 2]]) = cyclic form #f) (Cycle) = conversion to permutation #g) (Permutation) = adjust size or return copy ok = True if not args: # a return _af_new(list(range(size or 0))) elif len(args) > 1: # c return _af_new(Cycle(*args).list(size)) if len(args) == 1: a = args[0] if isinstance(a, Perm): # g if size is None or size == a.size: return a return Perm(a.array_form, size=size) if isinstance(a, Cycle): # f return _af_new(a.list(size)) if not is_sequence(a): # b return _af_new(list(range(a + 1))) if has_variety(is_sequence(ai) for ai in a): ok = False else: ok = False if not ok: raise ValueError("Permutation argument must be a list of ints, " "a list of lists, Permutation or Cycle.") # safe to assume args are valid; this also makes a copy # of the args args = list(args[0]) is_cycle = args and is_sequence(args[0]) if is_cycle: # e args = [[int(i) for i in c] for c in args] else: # d args = [int(i) for i in args] # if there are n elements present, 0, 1, ..., n-1 should be present # unless a cycle notation has been provided. A 0 will be added # for convenience in case one wants to enter permutations where # counting starts from 1. temp = flatten(args) if has_dups(temp): if is_cycle: raise ValueError('there were repeated elements; to resolve ' 'cycles use Cycle%s.' % ''.join([str(tuple(c)) for c in args])) else: raise ValueError('there were repeated elements.') temp = set(temp) if not is_cycle and \ any(i not in temp for i in range(len(temp))): raise ValueError("Integers 0 through %s must be present." % max(temp)) if is_cycle: # it's not necessarily canonical so we won't store # it -- use the array form instead c = Cycle() for ci in args: c = c(*ci) aform = c.list() else: aform = list(args) if size and size > len(aform): # don't allow for truncation of permutation which # might split a cycle and lead to an invalid aform # but do allow the permutation size to be increased aform.extend(list(range(len(aform), size))) size = len(aform) obj = Basic.__new__(cls, aform) obj._array_form = aform obj._size = size return obj @staticmethod def _af_new(perm): """A method to produce a Permutation object from a list; the list is bound to the _array_form attribute, so it must not be modified; this method is meant for internal use only; the list ``a`` is supposed to be generated as a temporary value in a method, so p = Perm._af_new(a) is the only object to hold a reference to ``a``:: Examples ======== >>> from sympy.combinatorics.permutations import Perm >>> Perm.print_cyclic = False >>> a = [2,1,3,0] >>> p = Perm._af_new(a) >>> p Permutation([2, 1, 3, 0]) """ p = Basic.__new__(Perm, perm) p._array_form = perm p._size = len(perm) return p def _hashable_content(self): # the array_form (a list) is the Permutation arg, so we need to # return a tuple, instead return tuple(self.array_form) @property def array_form(self): """ Return a copy of the attribute _array_form Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([[2,0], [3,1]]) >>> p.array_form [2, 3, 0, 1] >>> Permutation([[2,0,3,1]]).array_form [3, 2, 0, 1] >>> Permutation([2,0,3,1]).array_form [2, 0, 3, 1] >>> Permutation([[1, 2], [4, 5]]).array_form [0, 2, 1, 3, 5, 4] """ return self._array_form[:] def list(self, size=None): """Return the permutation as an explicit list, possibly trimming unmoved elements if size is less than the maximum element in the permutation; if this is desired, setting ``size=-1`` will guarantee such trimming. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation(2, 3)(4, 5) >>> p.list() [0, 1, 3, 2, 5, 4] >>> p.list(10) [0, 1, 3, 2, 5, 4, 6, 7, 8, 9] Passing a length too small will trim trailing, unchanged elements in the permutation: >>> Permutation(2, 4)(1, 2, 4).list(-1) [0, 2, 1] >>> Permutation(3).list(-1) [] """ if not self and size is None: raise ValueError('must give size for empty Cycle') rv = self.array_form if size is not None: if size > self.size: rv.extend(list(range(self.size, size))) else: # find first value from rhs where rv[i] != i i = self.size - 1 while rv: if rv[-1] != i: break rv.pop() i -= 1 return rv @property def cyclic_form(self): """ This is used to convert to the cyclic notation from the canonical notation. Singletons are omitted. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([0, 3, 1, 2]) >>> p.cyclic_form [[1, 3, 2]] >>> Permutation([1, 0, 2, 4, 3, 5]).cyclic_form [[0, 1], [3, 4]] See Also ======== array_form, full_cyclic_form """ if self._cyclic_form is not None: return list(self._cyclic_form) array_form = self.array_form unchecked = [True] * len(array_form) cyclic_form = [] for i in range(len(array_form)): if unchecked[i]: cycle = [] cycle.append(i) unchecked[i] = False j = i while unchecked[array_form[j]]: j = array_form[j] cycle.append(j) unchecked[j] = False if len(cycle) > 1: cyclic_form.append(cycle) assert cycle == list(minlex(cycle, is_set=True)) cyclic_form.sort() self._cyclic_form = cyclic_form[:] return cyclic_form @property def full_cyclic_form(self): """Return permutation in cyclic form including singletons. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation([0, 2, 1]).full_cyclic_form [[0], [1, 2]] """ need = set(range(self.size)) - set(flatten(self.cyclic_form)) rv = self.cyclic_form rv.extend([[i] for i in need]) rv.sort() return rv @property def size(self): """ Returns the number of elements in the permutation. Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([[3, 2], [0, 1]]).size 4 See Also ======== cardinality, length, order, rank """ return self._size def support(self): """Return the elements in permutation, P, for which P[i] != i. Examples ======== >>> from sympy.combinatorics import Permutation >>> p = Permutation([[3, 2], [0, 1], [4]]) >>> p.array_form [1, 0, 3, 2, 4] >>> p.support() [0, 1, 2, 3] """ a = self.array_form return [i for i, e in enumerate(a) if a[i] != i] def __add__(self, other): """Return permutation that is other higher in rank than self. The rank is the lexicographical rank, with the identity permutation having rank of 0. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> I = Permutation([0, 1, 2, 3]) >>> a = Permutation([2, 1, 3, 0]) >>> I + a.rank() == a True See Also ======== __sub__, inversion_vector """ rank = (self.rank() + other) % self.cardinality rv = Perm.unrank_lex(self.size, rank) rv._rank = rank return rv def __sub__(self, other): """Return the permutation that is other lower in rank than self. See Also ======== __add__ """ return self.__add__(-other) @staticmethod def rmul(*args): """ Return product of Permutations [a, b, c, ...] as the Permutation whose ith value is a(b(c(i))). a, b, c, ... can be Permutation objects or tuples. Examples ======== >>> from sympy.combinatorics.permutations import _af_rmul, Permutation >>> Permutation.print_cyclic = False >>> a, b = [1, 0, 2], [0, 2, 1] >>> a = Permutation(a); b = Permutation(b) >>> list(Permutation.rmul(a, b)) [1, 2, 0] >>> [a(b(i)) for i in range(3)] [1, 2, 0] This handles the operands in reverse order compared to the ``*`` operator: >>> a = Permutation(a); b = Permutation(b) >>> list(a*b) [2, 0, 1] >>> [b(a(i)) for i in range(3)] [2, 0, 1] Notes ===== All items in the sequence will be parsed by Permutation as necessary as long as the first item is a Permutation: >>> Permutation.rmul(a, [0, 2, 1]) == Permutation.rmul(a, b) True The reverse order of arguments will raise a TypeError. """ rv = args[0] for i in range(1, len(args)): rv = args[i]*rv return rv @staticmethod def rmul_with_af(*args): """ same as rmul, but the elements of args are Permutation objects which have _array_form """ a = [x._array_form for x in args] rv = _af_new(_af_rmuln(*a)) return rv def mul_inv(self, other): """ other*~self, self and other have _array_form """ a = _af_invert(self._array_form) b = other._array_form return _af_new(_af_rmul(a, b)) def __rmul__(self, other): """This is needed to coerse other to Permutation in rmul.""" return Perm(other)*self def __mul__(self, other): """ Return the product a*b as a Permutation; the ith value is b(a(i)). Examples ======== >>> from sympy.combinatorics.permutations import _af_rmul, Permutation >>> Permutation.print_cyclic = False >>> a, b = [1, 0, 2], [0, 2, 1] >>> a = Permutation(a); b = Permutation(b) >>> list(a*b) [2, 0, 1] >>> [b(a(i)) for i in range(3)] [2, 0, 1] This handles operands in reverse order compared to _af_rmul and rmul: >>> al = list(a); bl = list(b) >>> _af_rmul(al, bl) [1, 2, 0] >>> [al[bl[i]] for i in range(3)] [1, 2, 0] It is acceptable for the arrays to have different lengths; the shorter one will be padded to match the longer one: >>> b*Permutation([1, 0]) Permutation([1, 2, 0]) >>> Permutation([1, 0])*b Permutation([2, 0, 1]) It is also acceptable to allow coercion to handle conversion of a single list to the left of a Permutation: >>> [0, 1]*a # no change: 2-element identity Permutation([1, 0, 2]) >>> [[0, 1]]*a # exchange first two elements Permutation([0, 1, 2]) You cannot use more than 1 cycle notation in a product of cycles since coercion can only handle one argument to the left. To handle multiple cycles it is convenient to use Cycle instead of Permutation: >>> [[1, 2]]*[[2, 3]]*Permutation([]) # doctest: +SKIP >>> from sympy.combinatorics.permutations import Cycle >>> Cycle(1, 2)(2, 3) Cycle(1, 3, 2) """ a = self.array_form # __rmul__ makes sure the other is a Permutation b = other.array_form if not b: perm = a else: b.extend(list(range(len(b), len(a)))) perm = [b[i] for i in a] + b[len(a):] return _af_new(perm) def commutes_with(self, other): """ Checks if the elements are commuting. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> a = Permutation([1,4,3,0,2,5]) >>> b = Permutation([0,1,2,3,4,5]) >>> a.commutes_with(b) True >>> b = Permutation([2,3,5,4,1,0]) >>> a.commutes_with(b) False """ a = self.array_form b = other.array_form return _af_commutes_with(a, b) def __pow__(self, n): """ Routine for finding powers of a permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([2,0,3,1]) >>> p.order() 4 >>> p**4 Permutation([0, 1, 2, 3]) """ if type(n) == Perm: raise NotImplementedError( 'p**p is not defined; do you mean p^p (conjugate)?') n = int(n) return _af_new(_af_pow(self.array_form, n)) def __rxor__(self, i): """Return self(i) when ``i`` is an int. Examples ======== >>> from sympy.combinatorics import Permutation >>> p = Permutation(1, 2, 9) >>> 2^p == p(2) == 9 True """ if int(i) == i: return self(i) else: raise NotImplementedError( "i^p = p(i) when i is an integer, not %s." % i) def __xor__(self, h): """Return the conjugate permutation ``~h*self*h` `. If ``a`` and ``b`` are conjugates, ``a = h*b*~h`` and ``b = ~h*a*h`` and both have the same cycle structure. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = True >>> p = Permutation(1, 2, 9) >>> q = Permutation(6, 9, 8) >>> p*q != q*p True Calculate and check properties of the conjugate: >>> c = p^q >>> c == ~q*p*q and p == q*c*~q True The expression q^p^r is equivalent to q^(p*r): >>> r = Permutation(9)(4,6,8) >>> q^p^r == q^(p*r) True If the term to the left of the conjugate operator, i, is an integer then this is interpreted as selecting the ith element from the permutation to the right: >>> all(i^p == p(i) for i in range(p.size)) True Note that the * operator as higher precedence than the ^ operator: >>> q^r*p^r == q^(r*p)^r == Permutation(9)(1, 6, 4) True Notes ===== In Python the precedence rule is p^q^r = (p^q)^r which differs in general from p^(q^r) >>> q^p^r Permutation(9)(1, 4, 8) >>> q^(p^r) Permutation(9)(1, 8, 6) For a given r and p, both of the following are conjugates of p: ~r*p*r and r*p*~r. But these are not necessarily the same: >>> ~r*p*r == r*p*~r True >>> p = Permutation(1, 2, 9)(5, 6) >>> ~r*p*r == r*p*~r False The conjugate ~r*p*r was chosen so that ``p^q^r`` would be equivalent to ``p^(q*r)`` rather than ``p^(r*q)``. To obtain r*p*~r, pass ~r to this method: >>> p^~r == r*p*~r True """ if self.size != h.size: raise ValueError("The permutations must be of equal size.") a = [None]*self.size h = h._array_form p = self._array_form for i in range(self.size): a[h[i]] = h[p[i]] return _af_new(a) def transpositions(self): """ Return the permutation decomposed into a list of transpositions. It is always possible to express a permutation as the product of transpositions, see [1] Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([[1, 2, 3], [0, 4, 5, 6, 7]]) >>> t = p.transpositions() >>> t [(0, 7), (0, 6), (0, 5), (0, 4), (1, 3), (1, 2)] >>> print(''.join(str(c) for c in t)) (0, 7)(0, 6)(0, 5)(0, 4)(1, 3)(1, 2) >>> Permutation.rmul(*[Permutation([ti], size=p.size) for ti in t]) == p True References ========== 1. http://en.wikipedia.org/wiki/Transposition_%28mathematics%29#Properties """ a = self.cyclic_form res = [] for x in a: nx = len(x) if nx == 2: res.append(tuple(x)) elif nx > 2: first = x[0] for y in x[nx - 1:0:-1]: res.append((first, y)) return res @classmethod def from_sequence(self, i, key=None): """Return the permutation needed to obtain ``i`` from the sorted elements of ``i``. If custom sorting is desired, a key can be given. Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> Permutation.from_sequence('SymPy') Permutation(4)(0, 1, 3) >>> _(sorted("SymPy")) ['S', 'y', 'm', 'P', 'y'] >>> Permutation.from_sequence('SymPy', key=lambda x: x.lower()) Permutation(4)(0, 2)(1, 3) """ ic = list(zip(i, list(range(len(i))))) if key: ic.sort(key=lambda x: key(x[0])) else: ic.sort() return ~Permutation([i[1] for i in ic]) def __invert__(self): """ Return the inverse of the permutation. A permutation multiplied by its inverse is the identity permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([[2,0], [3,1]]) >>> ~p Permutation([2, 3, 0, 1]) >>> _ == p**-1 True >>> p*~p == ~p*p == Permutation([0, 1, 2, 3]) True """ return _af_new(_af_invert(self._array_form)) def __iter__(self): """Yield elements from array form. Examples ======== >>> from sympy.combinatorics import Permutation >>> list(Permutation(range(3))) [0, 1, 2] """ for i in self.array_form: yield i def __call__(self, *i): """ Allows applying a permutation instance as a bijective function. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([[2,0], [3,1]]) >>> p.array_form [2, 3, 0, 1] >>> [p(i) for i in range(4)] [2, 3, 0, 1] If an array is given then the permutation selects the items from the array (i.e. the permutation is applied to the array): >>> from sympy.abc import x >>> p([x, 1, 0, x**2]) [0, x**2, x, 1] """ # list indices can be Integer or int; leave this # as it is (don't test or convert it) because this # gets called a lot and should be fast if len(i) == 1: i = i[0] try: # P(1) return self._array_form[i] except TypeError: try: # P([a, b, c]) return [i[j] for j in self._array_form] except Exception: raise TypeError('unrecognized argument') else: # P(1, 2, 3) return self*Permutation(Cycle(*i), size=self.size) def atoms(self): """ Returns all the elements of a permutation Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([0, 1, 2, 3, 4, 5]).atoms() set([0, 1, 2, 3, 4, 5]) >>> Permutation([[0, 1], [2, 3], [4, 5]]).atoms() set([0, 1, 2, 3, 4, 5]) """ return set(self.array_form) def next_lex(self): """ Returns the next permutation in lexicographical order. If self is the last permutation in lexicographical order it returns None. See [4] section 2.4. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([2, 3, 1, 0]) >>> p = Permutation([2, 3, 1, 0]); p.rank() 17 >>> p = p.next_lex(); p.rank() 18 See Also ======== rank, unrank_lex """ perm = self.array_form[:] n = len(perm) i = n - 2 while perm[i + 1] < perm[i]: i -= 1 if i == -1: return None else: j = n - 1 while perm[j] < perm[i]: j -= 1 perm[j], perm[i] = perm[i], perm[j] i += 1 j = n - 1 while i < j: perm[j], perm[i] = perm[i], perm[j] i += 1 j -= 1 return _af_new(perm) @classmethod def unrank_nonlex(self, n, r): """ This is a linear time unranking algorithm that does not respect lexicographic order [3]. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> Permutation.unrank_nonlex(4, 5) Permutation([2, 0, 3, 1]) >>> Permutation.unrank_nonlex(4, -1) Permutation([0, 1, 2, 3]) See Also ======== next_nonlex, rank_nonlex """ def _unrank1(n, r, a): if n > 0: a[n - 1], a[r % n] = a[r % n], a[n - 1] _unrank1(n - 1, r//n, a) id_perm = list(range(n)) n = int(n) r = r % ifac(n) _unrank1(n, r, id_perm) return _af_new(id_perm) def rank_nonlex(self, inv_perm=None): """ This is a linear time ranking algorithm that does not enforce lexicographic order [3]. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.rank_nonlex() 23 See Also ======== next_nonlex, unrank_nonlex """ def _rank1(n, perm, inv_perm): if n == 1: return 0 s = perm[n - 1] t = inv_perm[n - 1] perm[n - 1], perm[t] = perm[t], s inv_perm[n - 1], inv_perm[s] = inv_perm[s], t return s + n*_rank1(n - 1, perm, inv_perm) if inv_perm is None: inv_perm = (~self).array_form if not inv_perm: return 0 perm = self.array_form[:] r = _rank1(len(perm), perm, inv_perm) return r def next_nonlex(self): """ Returns the next permutation in nonlex order [3]. If self is the last permutation in this order it returns None. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([2, 0, 3, 1]); p.rank_nonlex() 5 >>> p = p.next_nonlex(); p Permutation([3, 0, 1, 2]) >>> p.rank_nonlex() 6 See Also ======== rank_nonlex, unrank_nonlex """ r = self.rank_nonlex() if r == ifac(self.size) - 1: return None return Perm.unrank_nonlex(self.size, r + 1) def rank(self): """ Returns the lexicographic rank of the permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0, 1, 2, 3]) >>> p.rank() 0 >>> p = Permutation([3, 2, 1, 0]) >>> p.rank() 23 See Also ======== next_lex, unrank_lex, cardinality, length, order, size """ if not self._rank is None: return self._rank rank = 0 rho = self.array_form[:] n = self.size - 1 size = n + 1 psize = int(ifac(n)) for j in range(size - 1): rank += rho[j]*psize for i in range(j + 1, size): if rho[i] > rho[j]: rho[i] -= 1 psize //= n n -= 1 self._rank = rank return rank @property def cardinality(self): """ Returns the number of all possible permutations. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.cardinality 24 See Also ======== length, order, rank, size """ return int(ifac(self.size)) def parity(self): """ Computes the parity of a permutation. The parity of a permutation reflects the parity of the number of inversions in the permutation, i.e., the number of pairs of x and y such that ``x > y`` but ``p[x] < p[y]``. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.parity() 0 >>> p = Permutation([3,2,0,1]) >>> p.parity() 1 See Also ======== _af_parity """ if self._cyclic_form is not None: return (self.size - self.cycles) % 2 return _af_parity(self.array_form) @property def is_even(self): """ Checks if a permutation is even. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.is_even True >>> p = Permutation([3,2,1,0]) >>> p.is_even True See Also ======== is_odd """ return not self.is_odd @property def is_odd(self): """ Checks if a permutation is odd. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.is_odd False >>> p = Permutation([3,2,0,1]) >>> p.is_odd True See Also ======== is_even """ return bool(self.parity() % 2) @property def is_Singleton(self): """ Checks to see if the permutation contains only one number and is thus the only possible permutation of this set of numbers Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([0]).is_Singleton True >>> Permutation([0, 1]).is_Singleton False See Also ======== is_Empty """ return self.size == 1 @property def is_Empty(self): """ Checks to see if the permutation is a set with zero elements Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([]).is_Empty True >>> Permutation([0]).is_Empty False See Also ======== is_Singleton """ return self.size == 0 @property def is_Identity(self): """ Returns True if the Permutation is an identity permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([]) >>> p.is_Identity True >>> p = Permutation([[0], [1], [2]]) >>> p.is_Identity True >>> p = Permutation([0, 1, 2]) >>> p.is_Identity True >>> p = Permutation([0, 2, 1]) >>> p.is_Identity False See Also ======== order """ af = self.array_form return not af or all(i == af[i] for i in xrange(self.size)) def ascents(self): """ Returns the positions of ascents in a permutation, ie, the location where p[i] < p[i+1] Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([4,0,1,3,2]) >>> p.ascents() [1, 2] See Also ======== descents, inversions, min, max """ a = self.array_form pos = [i for i in range(len(a) - 1) if a[i] < a[i + 1]] return pos def descents(self): """ Returns the positions of descents in a permutation, ie, the location where p[i] > p[i+1] Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([4,0,1,3,2]) >>> p.descents() [0, 3] See Also ======== ascents, inversions, min, max """ a = self.array_form pos = [i for i in range(len(a) - 1) if a[i] > a[i + 1]] return pos def max(self): """ The maximum element moved by the permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([1,0,2,3,4]) >>> p.max() 1 See Also ======== min, descents, ascents, inversions """ max = 0 a = self.array_form for i in range(len(a)): if a[i] != i and a[i] > max: max = a[i] return max def min(self): """ The minimum element moved by the permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,4,3,2]) >>> p.min() 2 See Also ======== max, descents, ascents, inversions """ a = self.array_form min = len(a) for i in range(len(a)): if a[i] != i and a[i] < min: min = a[i] return min def inversions(self): """ Computes the number of inversions of a permutation. An inversion is where i > j but p[i] < p[j]. For small length of p, it iterates over all i and j values and calculates the number of inversions. For large length of p, it uses a variation of merge sort to calculate the number of inversions. References ========== [1] http://www.cp.eng.chula.ac.th/~piak/teaching/algo/algo2008/count-inv.htm Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3,4,5]) >>> p.inversions() 0 >>> Permutation([3,2,1,0]).inversions() 6 See Also ======== descents, ascents, min, max """ inversions = 0 a = self.array_form n = len(a) if n < 130: for i in range(n - 1): b = a[i] for c in a[i + 1:]: if b > c: inversions += 1 else: k = 1 right = 0 arr = a[:] temp = a[:] while k < n: i = 0 while i + k < n: right = i + k * 2 - 1 if right >= n: right = n - 1 inversions += _merge(arr, temp, i, i + k, right) i = i + k * 2 k = k * 2 return inversions def commutator(self, x): """Return the commutator of self and x: ``~x*~self*x*self`` If f and g are part of a group, G, then the commutator of f and g is the group identity iff f and g commute, i.e. fg == gf. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([0, 2, 3, 1]) >>> x = Permutation([2, 0, 3, 1]) >>> c = p.commutator(x); c Permutation([2, 1, 3, 0]) >>> c == ~x*~p*x*p True >>> I = Permutation(3) >>> p = [I + i for i in range(6)] >>> for i in range(len(p)): ... for j in range(len(p)): ... c = p[i].commutator(p[j]) ... if p[i]*p[j] == p[j]*p[i]: ... assert c == I ... else: ... assert c != I ... References ========== http://en.wikipedia.org/wiki/Commutator """ a = self.array_form b = x.array_form n = len(a) if len(b) != n: raise ValueError("The permutations must be of equal size.") inva = [None]*n for i in range(n): inva[a[i]] = i invb = [None]*n for i in range(n): invb[b[i]] = i return _af_new([a[b[inva[i]]] for i in invb]) def signature(self): """ Gives the signature of the permutation needed to place the elements of the permutation in canonical order. The signature is calculated as (-1)^<number of inversions> Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2]) >>> p.inversions() 0 >>> p.signature() 1 >>> q = Permutation([0,2,1]) >>> q.inversions() 1 >>> q.signature() -1 See Also ======== inversions """ if self.is_even: return 1 return -1 def order(self): """ Computes the order of a permutation. When the permutation is raised to the power of its order it equals the identity permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([3, 1, 5, 2, 4, 0]) >>> p.order() 4 >>> (p**(p.order())) Permutation([], size=6) See Also ======== identity, cardinality, length, rank, size """ return reduce(lcm, [len(cycle) for cycle in self.cyclic_form], 1) def length(self): """ Returns the number of integers moved by a permutation. Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([0, 3, 2, 1]).length() 2 >>> Permutation([[0, 1], [2, 3]]).length() 4 See Also ======== min, max, suppport, cardinality, order, rank, size """ return len(self.support()) @property def cycle_structure(self): """Return the cycle structure of the permutation as a dictionary indicating the multiplicity of each cycle length. Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation.print_cyclic = True >>> Permutation(3).cycle_structure {1: 4} >>> Permutation(0, 4, 3)(1, 2)(5, 6).cycle_structure {2: 2, 3: 1} """ if self._cycle_structure: rv = self._cycle_structure else: rv = defaultdict(int) singletons = self.size for c in self.cyclic_form: rv[len(c)] += 1 singletons -= len(c) if singletons: rv[1] = singletons self._cycle_structure = rv return dict(rv) # make a copy @property def cycles(self): """ Returns the number of cycles contained in the permutation (including singletons). Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation([0, 1, 2]).cycles 3 >>> Permutation([0, 1, 2]).full_cyclic_form [[0], [1], [2]] >>> Permutation(0, 1)(2, 3).cycles 2 See Also ======== sympy.functions.combinatorial.numbers.stirling """ return len(self.full_cyclic_form) def index(self): """ Returns the index of a permutation. The index of a permutation is the sum of all subscripts j such that p[j] is greater than p[j+1]. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([3, 0, 2, 1, 4]) >>> p.index() 2 """ a = self.array_form return sum([j for j in range(len(a) - 1) if a[j] > a[j + 1]]) def runs(self): """ Returns the runs of a permutation. An ascending sequence in a permutation is called a run [5]. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([2,5,7,3,6,0,1,4,8]) >>> p.runs() [[2, 5, 7], [3, 6], [0, 1, 4, 8]] >>> q = Permutation([1,3,2,0]) >>> q.runs() [[1, 3], [2], [0]] """ return runs(self.array_form) def inversion_vector(self): """Return the inversion vector of the permutation. The inversion vector consists of elements whose value indicates the number of elements in the permutation that are lesser than it and lie on its right hand side. The inversion vector is the same as the Lehmer encoding of a permutation. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([4, 8, 0, 7, 1, 5, 3, 6, 2]) >>> p.inversion_vector() [4, 7, 0, 5, 0, 2, 1, 1] >>> p = Permutation([3, 2, 1, 0]) >>> p.inversion_vector() [3, 2, 1] The inversion vector increases lexicographically with the rank of the permutation, the -ith element cycling through 0..i. >>> p = Permutation(2) >>> while p: ... print('%s %s %s' % (p, p.inversion_vector(), p.rank())) ... p = p.next_lex() ... Permutation([0, 1, 2]) [0, 0] 0 Permutation([0, 2, 1]) [0, 1] 1 Permutation([1, 0, 2]) [1, 0] 2 Permutation([1, 2, 0]) [1, 1] 3 Permutation([2, 0, 1]) [2, 0] 4 Permutation([2, 1, 0]) [2, 1] 5 See Also ======== from_inversion_vector """ self_array_form = self.array_form n = len(self_array_form) inversion_vector = [0] * (n - 1) for i in range(n - 1): val = 0 for j in range(i + 1, n): if self_array_form[j] < self_array_form[i]: val += 1 inversion_vector[i] = val return inversion_vector def rank_trotterjohnson(self): """ Returns the Trotter Johnson rank, which we get from the minimal change algorithm. See [4] section 2.4. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0,1,2,3]) >>> p.rank_trotterjohnson() 0 >>> p = Permutation([0,2,1,3]) >>> p.rank_trotterjohnson() 7 See Also ======== unrank_trotterjohnson, next_trotterjohnson """ if self.array_form == [] or self.is_Identity: return 0 if self.array_form == [1, 0]: return 1 perm = self.array_form n = self.size rank = 0 for j in range(1, n): k = 1 i = 0 while perm[i] != j: if perm[i] < j: k += 1 i += 1 j1 = j + 1 if rank % 2 == 0: rank = j1*rank + j1 - k else: rank = j1*rank + k - 1 return rank @classmethod def unrank_trotterjohnson(self, size, rank): """ Trotter Johnson permutation unranking. See [4] section 2.4. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.unrank_trotterjohnson(5, 10) Permutation([0, 3, 1, 2, 4]) See Also ======== rank_trotterjohnson, next_trotterjohnson """ perm = [0]*size r2 = 0 n = ifac(size) pj = 1 for j in range(2, size + 1): pj *= j r1 = (rank * pj) // n k = r1 - j*r2 if r2 % 2 == 0: for i in range(j - 1, j - k - 1, -1): perm[i] = perm[i - 1] perm[j - k - 1] = j - 1 else: for i in range(j - 1, k, -1): perm[i] = perm[i - 1] perm[k] = j - 1 r2 = r1 return _af_new(perm) def next_trotterjohnson(self): """ Returns the next permutation in Trotter-Johnson order. If self is the last permutation it returns None. See [4] section 2.4. If it is desired to generate all such permutations, they can be generated in order more quickly with the ``generate_bell`` function. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> p = Permutation([3, 0, 2, 1]) >>> p.rank_trotterjohnson() 4 >>> p = p.next_trotterjohnson(); p Permutation([0, 3, 2, 1]) >>> p.rank_trotterjohnson() 5 See Also ======== rank_trotterjohnson, unrank_trotterjohnson, sympy.utilities.iterables.generate_bell """ pi = self.array_form[:] n = len(pi) st = 0 rho = pi[:] done = False m = n-1 while m > 0 and not done: d = rho.index(m) for i in range(d, m): rho[i] = rho[i + 1] par = _af_parity(rho[:m]) if par == 1: if d == m: m -= 1 else: pi[st + d], pi[st + d + 1] = pi[st + d + 1], pi[st + d] done = True else: if d == 0: m -= 1 st += 1 else: pi[st + d], pi[st + d - 1] = pi[st + d - 1], pi[st + d] done = True if m == 0: return None return _af_new(pi) def get_precedence_matrix(self): """ Gets the precedence matrix. This is used for computing the distance between two permutations. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation.josephus(3,6,1) >>> p Permutation([2, 5, 3, 1, 4, 0]) >>> p.get_precedence_matrix() Matrix([ [0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 1, 0], [1, 1, 0, 1, 1, 1], [1, 1, 0, 0, 1, 0], [1, 0, 0, 0, 0, 0], [1, 1, 0, 1, 1, 0]]) See Also ======== get_precedence_distance, get_adjacency_matrix, get_adjacency_distance """ m = zeros(self.size) perm = self.array_form for i in range(m.rows): for j in range(i + 1, m.cols): m[perm[i], perm[j]] = 1 return m def get_precedence_distance(self, other): """ Computes the precedence distance between two permutations. Suppose p and p' represent n jobs. The precedence metric counts the number of times a job j is prededed by job i in both p and p'. This metric is commutative. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([2, 0, 4, 3, 1]) >>> q = Permutation([3, 1, 2, 4, 0]) >>> p.get_precedence_distance(q) 7 >>> q.get_precedence_distance(p) 7 See Also ======== get_precedence_matrix, get_adjacency_matrix, get_adjacency_distance """ if self.size != other.size: raise ValueError("The permutations must be of equal size.") self_prec_mat = self.get_precedence_matrix() other_prec_mat = other.get_precedence_matrix() n_prec = 0 for i in range(self.size): for j in range(self.size): if i == j: continue if self_prec_mat[i, j] * other_prec_mat[i, j] == 1: n_prec += 1 d = self.size * (self.size - 1)//2 - n_prec return d def get_adjacency_matrix(self): """ Computes the adjacency matrix of a permutation. If job i is adjacent to job j in a permutation p then we set m[i, j] = 1 where m is the adjacency matrix of p. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation.josephus(3,6,1) >>> p.get_adjacency_matrix() Matrix([ [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 1], [0, 1, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0]]) >>> q = Permutation([0, 1, 2, 3]) >>> q.get_adjacency_matrix() Matrix([ [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1], [0, 0, 0, 0]]) See Also ======== get_precedence_matrix, get_precedence_distance, get_adjacency_distance """ m = zeros(self.size) perm = self.array_form for i in range(self.size - 1): m[perm[i], perm[i + 1]] = 1 return m def get_adjacency_distance(self, other): """ Computes the adjacency distance between two permutations. This metric counts the number of times a pair i,j of jobs is adjacent in both p and p'. If n_adj is this quantity then the adjacency distance is n - n_adj - 1 [1] [1] Reeves, Colin R. Landscapes, Operators and Heuristic search, Annals of Operational Research, 86, pp 473-490. (1999) Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0, 3, 1, 2, 4]) >>> q = Permutation.josephus(4, 5, 2) >>> p.get_adjacency_distance(q) 3 >>> r = Permutation([0, 2, 1, 4, 3]) >>> p.get_adjacency_distance(r) 4 See Also ======== get_precedence_matrix, get_precedence_distance, get_adjacency_matrix """ if self.size != other.size: raise ValueError("The permutations must be of the same size.") self_adj_mat = self.get_adjacency_matrix() other_adj_mat = other.get_adjacency_matrix() n_adj = 0 for i in range(self.size): for j in range(self.size): if i == j: continue if self_adj_mat[i, j] * other_adj_mat[i, j] == 1: n_adj += 1 d = self.size - n_adj - 1 return d def get_positional_distance(self, other): """ Computes the positional distance between two permutations. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> p = Permutation([0, 3, 1, 2, 4]) >>> q = Permutation.josephus(4, 5, 2) >>> r = Permutation([3, 1, 4, 0, 2]) >>> p.get_positional_distance(q) 12 >>> p.get_positional_distance(r) 12 See Also ======== get_precedence_distance, get_adjacency_distance """ a = self.array_form b = other.array_form if len(a) != len(b): raise ValueError("The permutations must be of the same size.") return sum([abs(a[i] - b[i]) for i in range(len(a))]) @classmethod def josephus(self, m, n, s=1): """Return as a permutation the shuffling of range(n) using the Josephus scheme in which every m-th item is selected until all have been chosen. The returned permutation has elements listed by the order in which they were selected. The parameter ``s`` stops the selection process when there are ``s`` items remaining and these are selected by countinuing the selection, counting by 1 rather than by ``m``. Consider selecting every 3rd item from 6 until only 2 remain:: choices chosen ======== ====== 012345 01 345 2 01 34 25 01 4 253 0 4 2531 0 25314 253140 Examples ======== >>> from sympy.combinatorics import Permutation >>> Permutation.josephus(3, 6, 2).array_form [2, 5, 3, 1, 4, 0] References ========== 1. http://en.wikipedia.org/wiki/Flavius_Josephus 2. http://en.wikipedia.org/wiki/Josephus_problem 3. http://www.wou.edu/~burtonl/josephus.html """ from collections import deque m -= 1 Q = deque(list(range(n))) perm = [] while len(Q) > max(s, 1): for dp in range(m): Q.append(Q.popleft()) perm.append(Q.popleft()) perm.extend(list(Q)) return Perm(perm) @classmethod def from_inversion_vector(self, inversion): """ Calculates the permutation from the inversion vector. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> Permutation.from_inversion_vector([3, 2, 1, 0, 0]) Permutation([3, 2, 1, 0, 4, 5]) """ size = len(inversion) N = list(range(size + 1)) perm = [] try: for k in range(size): val = N[inversion[k]] perm.append(val) N.remove(val) except IndexError: raise ValueError("The inversion vector is not valid.") perm.extend(N) return _af_new(perm) @classmethod def random(self, n): """ Generates a random permutation of length ``n``. Uses the underlying Python psuedo-random number generator. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.random(2) in (Permutation([1, 0]), Permutation([0, 1])) True """ perm_array = list(range(n)) random.shuffle(perm_array) return _af_new(perm_array) @classmethod def unrank_lex(self, size, rank): """ Lexicographic permutation unranking. Examples ======== >>> from sympy.combinatorics.permutations import Permutation >>> Permutation.print_cyclic = False >>> a = Permutation.unrank_lex(5, 10) >>> a.rank() 10 >>> a Permutation([0, 2, 4, 1, 3]) See Also ======== rank, next_lex """ perm_array = [0] * size psize = 1 for i in range(size): new_psize = psize*(i + 1) d = (rank % new_psize) // psize rank -= d*psize perm_array[size - i - 1] = d for j in range(size - i, size): if perm_array[j] > d - 1: perm_array[j] += 1 psize = new_psize return _af_new(perm_array) # global flag to control how permutations are printed # when True, Permutation([0, 2, 1, 3]) -> Cycle(1, 2) # when False, Permutation([0, 2, 1, 3]) -> Permutation([0, 2, 1]) print_cyclic = True def _merge(arr, temp, left, mid, right): """ Merges two sorted arrays and calculates the inversion count. Helper function for calculating inversions. This method is for internal use only. """ i = k = left j = mid inv_count = 0 while i < mid and j <= right: if arr[i] < arr[j]: temp[k] = arr[i] k += 1 i += 1 else: temp[k] = arr[j] k += 1 j += 1 inv_count += (mid -i) while i < mid: temp[k] = arr[i] k += 1 i += 1 if j <= right: k += right - j + 1 j += right - j + 1 arr[left:k + 1] = temp[left:k + 1] else: arr[left:right + 1] = temp[left:right + 1] return inv_count Perm = Permutation _af_new = Perm._af_new
27.895796
91
0.511
cf1cc6bf6b2894bf6e3e534ab0fd58905c530177
3,204
py
Python
kf_lib_data_ingest/etl/load/load_v2.py
kids-first/kf-lib-data-ingest
92889efef082c64744a00a9c110d778da7383959
[ "Apache-2.0" ]
3
2018-10-30T17:56:44.000Z
2020-05-27T16:18:05.000Z
kf_lib_data_ingest/etl/load/load_v2.py
kids-first/kf-lib-data-ingest
92889efef082c64744a00a9c110d778da7383959
[ "Apache-2.0" ]
344
2018-11-01T16:47:56.000Z
2022-02-23T20:36:21.000Z
kf_lib_data_ingest/etl/load/load_v2.py
kids-first/kf-lib-data-ingest
92889efef082c64744a00a9c110d778da7383959
[ "Apache-2.0" ]
1
2020-08-19T21:25:25.000Z
2020-08-19T21:25:25.000Z
""" For Version 2 Target Service Plugins """ from pprint import pformat from kf_lib_data_ingest.common import constants from kf_lib_data_ingest.etl.load.load_base import LoadStageBase class LoadStage(LoadStageBase): def __init__(self, *args, query_url="", **kwargs): """ :param query_url: Alternative API query URL instead of asking the load target :type query_url: str, optional """ super().__init__(*args, **kwargs) self.query_url = query_url def _get_target_id_from_record(self, entity_class, record): """ Find the target service ID for the given record and entity class. :param entity_class: one of the classes contained in the all_targets list :type entity_class: class :param record: a record of extracted data :type record: dict :return: the target service ID :rtype: str """ # check if target ID is given tic = record.get(entity_class.target_id_concept) if tic and (tic != constants.COMMON.NOT_REPORTED): return tic # check the cache try: key_components = self._do_target_get_key(entity_class, record) tic = self._get_target_id_from_key( entity_class.class_name, str(key_components) ) except Exception: return None if tic: return tic # check the server if self.dry_run and not self.query_url: return None err = False try: tic_list = entity_class.query_target_ids( self.query_url or self.target_url, key_components ) if tic_list: if len(tic_list) > 1: err = True raise Exception( "Ambiguous query. Multiple target identifiers found.\n" "Sent:\n" f"{pformat(key_components)}\n" "Found:\n" f"{tic_list}" ) tic = tic_list[0] if tic and (tic != constants.COMMON.NOT_REPORTED): self._store_target_id_for_key( entity_class.class_name, str(key_components), tic, self.dry_run, ) return tic except Exception: if err: raise return None def _do_target_submit(self, entity_class, body): """Shim for target API submission across loader versions""" return entity_class.submit(self.target_url, body) def _do_target_get_key(self, entity_class, record): """Shim for target API key building across loader versions""" return entity_class.get_key_components( record, self._get_target_id_from_record ) def _do_target_get_entity(self, entity_class, record, keystring): """Shim for target API entity building across loader versions""" return entity_class.build_entity( record, self._get_target_id_from_record )
33.375
85
0.566792
c762c7264762e2ed42c2e89cf8a5a351659b6407
1,336
py
Python
cnxman/logging.py
patdaburu/cnxman
f0094def9c6a7b77f0c44b8c08638bfba6d8f5d6
[ "MIT" ]
null
null
null
cnxman/logging.py
patdaburu/cnxman
f0094def9c6a7b77f0c44b8c08638bfba6d8f5d6
[ "MIT" ]
null
null
null
cnxman/logging.py
patdaburu/cnxman
f0094def9c6a7b77f0c44b8c08638bfba6d8f5d6
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- """ .. currentmodule:: cnxman.logging .. moduleauthor:: Pat Daburu <pat@daburu.net> Dear diary... """ import logging # TODO: This module should eventually be broken out so it may be reused in other projects. def loggable_class(logger_name: str=None): """ This is a decorator you can apply to a class to set it up with a Python ``logger`` property suitable for your logging needs. :param logger_name: a custom logger name :type logger_name: ``str`` .. note:: If you don't supply a custom logger name, a standard formula that uses the module name and the class name is used. """ # We need an inner function that actually adds the logger instance to the class. def add_logger(cls): # Establish what the name of the logger is going to be. If the original caller didn't supply one, we'll use # a default to construct one. _logger_name = logger_name if logger_name is not None else '{module}.{cls}'.format(module=cls.__module__, cls=cls.__name__) # Add a logger property to the class. cls.logger = logging.getLogger(_logger_name) return cls # Return the inner function. return add_logger
35.157895
116
0.633234
092950238f17d798165075d36f0bf97755aa87c5
1,542
py
Python
Main.py
sunxyq/py-data-clean
1597aa6ae1aa7a03449315f57fb17404a926b506
[ "Apache-2.0" ]
1
2019-03-28T09:29:51.000Z
2019-03-28T09:29:51.000Z
Main.py
sunxyq/py-data-clean
1597aa6ae1aa7a03449315f57fb17404a926b506
[ "Apache-2.0" ]
null
null
null
Main.py
sunxyq/py-data-clean
1597aa6ae1aa7a03449315f57fb17404a926b506
[ "Apache-2.0" ]
null
null
null
#coding=utf-8 import DBUtil def main() : util = DBUtil.DBUtil() DBUtil.DBUtil.digit_fence(util) # print(FileUtil.count_lines('/Users/xiangyongqing/Documents/crawler-data-1797910-1522984840544.csv')) # print(CSVUtil.CSVUtil.get_length(CSVUtil, '/Users/xiangyongqing/Documents/crawler-data-1797910-1522984840544.csv')) # CSVUtil.CSVUtil.split_data_by_city(CSVUtil, '/Users/xiangyongqing/Documents/crawler-data-1797909-1523092432926.csv', # '/Users/xiangyongqing/Documents/output2') #CSVUtil.CSVUtil.extract_data_from_csv_all(Constant, Constant.LIFE_SERVICE, Constant.OUT_PATH) #CSVUtil.CSVUtil.extract_data_from_csv_all(Constant, Constant.RESTAURANT, Constant.OUT_PATH) #CSVUtil.CSVUtil.extract_data_from_csv_all(Constant, Constant.SHOPPING, Constant.OUT_PATH) # DBUtil.DBUtil.read_csv_to_db(DBUtil, Constant.LIFE_SERVICE_ONLINE) # DBUtil.DBUtil.read_csv_to_db(DBUtil, Constant.RESTAURANT_ONLINE) # DBUtil.DBUtil.read_csv_to_db(DBUtil, Constant.SHOPPING_ONLINE) #CSVUtil.CSVUtil.extract_data_from_takeout_csv(DBUtil, Constant.TAKEOUT_SHOP, Constant.TAKEOUT_OUT_PATH) #DBUtil.DBUtil.read_takeout_csv_to_db(DBUtil, Constant.TAKEOUT_SHOP) #DBUtil.DBUtil.read_xlsx_to_db(DBUtil, Constant.DIGIT_FENCE) #extract data for jiaming # file_path = "/Users/xiangyongqing/Desktop/meituan_data.xls" # out_path = "/Users/xiangyongqing/Desktop/out" # ExcelUtil.ExcelUtil.split_excel(ExcelUtil, file_path, out_path) if(__name__== '__main__') : print(__name__) main()
42.833333
122
0.780156
54701104f5aebd31b7a711d22cbf968db61f0bf8
240
py
Python
scripts/checkpoint.py
tjclement/ukraine-defense-firewall-rules
ed82ab21cd2d055e09480108f83ca8c76bac63dd
[ "CC0-1.0" ]
null
null
null
scripts/checkpoint.py
tjclement/ukraine-defense-firewall-rules
ed82ab21cd2d055e09480108f83ca8c76bac63dd
[ "CC0-1.0" ]
null
null
null
scripts/checkpoint.py
tjclement/ukraine-defense-firewall-rules
ed82ab21cd2d055e09480108f83ca8c76bac63dd
[ "CC0-1.0" ]
1
2022-02-27T22:40:24.000Z
2022-02-27T22:40:24.000Z
def checkpoint_save(lists): for name, sublists in lists.items(): for subname, ips in sublists.items(): with open(f"checkpoint/greynoise_{name}_{subname}.txt", "wt") as file: file.write("\n".join(ips))
48
82
0.6125
7ed80fd0298a4c402bfe7153fa14c67a8a66f80d
8,514
py
Python
docs/conf.py
stfp/flask-presst
8d10cc04d390d412c9b949fcd81f696ab87b85ad
[ "MIT" ]
1
2018-07-17T03:56:04.000Z
2018-07-17T03:56:04.000Z
docs/conf.py
stfp/flask-presst
8d10cc04d390d412c9b949fcd81f696ab87b85ad
[ "MIT" ]
null
null
null
docs/conf.py
stfp/flask-presst
8d10cc04d390d412c9b949fcd81f696ab87b85ad
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- # # Flask-Presst documentation build configuration file, created by # sphinx-quickstart on Fri Mar 28 16:41:50 2014. # # This file is execfile()d with the current directory set to its containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys, os # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. sys.path.append(os.path.abspath('_themes')) sys.path.insert(0, os.path.abspath('../flask_presst')) # -- General configuration ----------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.intersphinx' ] intersphinx_mapping = { 'restful': ('http://flask-restful.readthedocs.org/en/latest/', None), 'sqlalchemy': ('http://docs.sqlalchemy.org/en/latest/', None), 'werkzeug': ('http://werkzeug.pocoo.org/docs/', None), 'blinker': ('http://pythonhosted.org/blinker/', None) } autodoc_member_order = 'bysource' # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'Flask-Presst' copyright = u'2014, Lars Schöning' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = '0.2' # The full version, including alpha/beta/rc tags. release = '0.2.5' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] # The reST default role (used for this markup: `text`) to use for all documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'flask_theme_support.FlaskyStyle' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # -- Options for HTML output --------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. sys.path.append(os.path.abspath('_themes')) html_theme_path = ['_themes'] html_theme = 'flask' # html_theme_options = { # 'github_fork': 'biosustain/flask-presst' # } # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # "<project> v<release> documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. html_sidebars = { 'index': ['sidebarintro.html', 'sourcelink.html', 'searchbox.html'] } # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a <link> tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'Flask-Presstdoc' # -- Options for LaTeX output -------------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ ('index', 'Flask-Presst.tex', u'Flask-Presst Documentation', u'Lars Schoning', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output -------------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'flask-presst', u'Flask-Presst Documentation', [u'Lars Schoning'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------------ # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'Flask-Presst', u'Flask-Presst Documentation', u'Lars Schoning', 'Flask-Presst', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' def setup(app): app.add_stylesheet('custom.css')
31.533333
80
0.712004
fac20796c0d678f71408549ef1bd98505a863837
20,657
py
Python
soniox/speech_service_pb2_grpc.py
soniox/soniox_python
b0a1e2dc126e11e64b1147939fb4025efe675a3b
[ "MIT" ]
null
null
null
soniox/speech_service_pb2_grpc.py
soniox/soniox_python
b0a1e2dc126e11e64b1147939fb4025efe675a3b
[ "MIT" ]
1
2021-06-01T22:08:28.000Z
2021-06-01T22:08:28.000Z
soniox/speech_service_pb2_grpc.py
soniox/soniox_python
b0a1e2dc126e11e64b1147939fb4025efe675a3b
[ "MIT" ]
null
null
null
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from soniox import speech_service_pb2 as soniox_dot_speech__service__pb2 class SpeechServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.Transcribe = channel.unary_unary( '/soniox.speech_service.SpeechService/Transcribe', request_serializer=soniox_dot_speech__service__pb2.TranscribeRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.TranscribeResponse.FromString, ) self.TranscribeStream = channel.stream_stream( '/soniox.speech_service.SpeechService/TranscribeStream', request_serializer=soniox_dot_speech__service__pb2.TranscribeStreamRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.TranscribeStreamResponse.FromString, ) self.TranscribeAsync = channel.stream_unary( '/soniox.speech_service.SpeechService/TranscribeAsync', request_serializer=soniox_dot_speech__service__pb2.TranscribeAsyncRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.TranscribeAsyncResponse.FromString, ) self.GetTranscribeAsyncStatus = channel.unary_unary( '/soniox.speech_service.SpeechService/GetTranscribeAsyncStatus', request_serializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusResponse.FromString, ) self.GetTranscribeAsyncResult = channel.unary_stream( '/soniox.speech_service.SpeechService/GetTranscribeAsyncResult', request_serializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncResultRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncResultResponse.FromString, ) self.DeleteTranscribeAsyncFile = channel.unary_unary( '/soniox.speech_service.SpeechService/DeleteTranscribeAsyncFile', request_serializer=soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileResponse.FromString, ) self.CreateSpeechContext = channel.unary_unary( '/soniox.speech_service.SpeechService/CreateSpeechContext', request_serializer=soniox_dot_speech__service__pb2.CreateSpeechContextRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.CreateSpeechContextResponse.FromString, ) self.DeleteSpeechContext = channel.unary_unary( '/soniox.speech_service.SpeechService/DeleteSpeechContext', request_serializer=soniox_dot_speech__service__pb2.DeleteSpeechContextRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.DeleteSpeechContextResponse.FromString, ) self.ListSpeechContextNames = channel.unary_unary( '/soniox.speech_service.SpeechService/ListSpeechContextNames', request_serializer=soniox_dot_speech__service__pb2.ListSpeechContextNamesRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.ListSpeechContextNamesResponse.FromString, ) self.GetSpeechContext = channel.unary_unary( '/soniox.speech_service.SpeechService/GetSpeechContext', request_serializer=soniox_dot_speech__service__pb2.GetSpeechContextRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.GetSpeechContextResponse.FromString, ) self.UpdateSpeechContext = channel.unary_unary( '/soniox.speech_service.SpeechService/UpdateSpeechContext', request_serializer=soniox_dot_speech__service__pb2.UpdateSpeechContextRequest.SerializeToString, response_deserializer=soniox_dot_speech__service__pb2.UpdateSpeechContextResponse.FromString, ) class SpeechServiceServicer(object): """Missing associated documentation comment in .proto file.""" def Transcribe(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TranscribeStream(self, request_iterator, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def TranscribeAsync(self, request_iterator, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetTranscribeAsyncStatus(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetTranscribeAsyncResult(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteTranscribeAsyncFile(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CreateSpeechContext(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteSpeechContext(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ListSpeechContextNames(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetSpeechContext(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def UpdateSpeechContext(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_SpeechServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'Transcribe': grpc.unary_unary_rpc_method_handler( servicer.Transcribe, request_deserializer=soniox_dot_speech__service__pb2.TranscribeRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.TranscribeResponse.SerializeToString, ), 'TranscribeStream': grpc.stream_stream_rpc_method_handler( servicer.TranscribeStream, request_deserializer=soniox_dot_speech__service__pb2.TranscribeStreamRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.TranscribeStreamResponse.SerializeToString, ), 'TranscribeAsync': grpc.stream_unary_rpc_method_handler( servicer.TranscribeAsync, request_deserializer=soniox_dot_speech__service__pb2.TranscribeAsyncRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.TranscribeAsyncResponse.SerializeToString, ), 'GetTranscribeAsyncStatus': grpc.unary_unary_rpc_method_handler( servicer.GetTranscribeAsyncStatus, request_deserializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusResponse.SerializeToString, ), 'GetTranscribeAsyncResult': grpc.unary_stream_rpc_method_handler( servicer.GetTranscribeAsyncResult, request_deserializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncResultRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.GetTranscribeAsyncResultResponse.SerializeToString, ), 'DeleteTranscribeAsyncFile': grpc.unary_unary_rpc_method_handler( servicer.DeleteTranscribeAsyncFile, request_deserializer=soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileResponse.SerializeToString, ), 'CreateSpeechContext': grpc.unary_unary_rpc_method_handler( servicer.CreateSpeechContext, request_deserializer=soniox_dot_speech__service__pb2.CreateSpeechContextRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.CreateSpeechContextResponse.SerializeToString, ), 'DeleteSpeechContext': grpc.unary_unary_rpc_method_handler( servicer.DeleteSpeechContext, request_deserializer=soniox_dot_speech__service__pb2.DeleteSpeechContextRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.DeleteSpeechContextResponse.SerializeToString, ), 'ListSpeechContextNames': grpc.unary_unary_rpc_method_handler( servicer.ListSpeechContextNames, request_deserializer=soniox_dot_speech__service__pb2.ListSpeechContextNamesRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.ListSpeechContextNamesResponse.SerializeToString, ), 'GetSpeechContext': grpc.unary_unary_rpc_method_handler( servicer.GetSpeechContext, request_deserializer=soniox_dot_speech__service__pb2.GetSpeechContextRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.GetSpeechContextResponse.SerializeToString, ), 'UpdateSpeechContext': grpc.unary_unary_rpc_method_handler( servicer.UpdateSpeechContext, request_deserializer=soniox_dot_speech__service__pb2.UpdateSpeechContextRequest.FromString, response_serializer=soniox_dot_speech__service__pb2.UpdateSpeechContextResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'soniox.speech_service.SpeechService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class SpeechService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def Transcribe(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/Transcribe', soniox_dot_speech__service__pb2.TranscribeRequest.SerializeToString, soniox_dot_speech__service__pb2.TranscribeResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TranscribeStream(request_iterator, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.stream_stream(request_iterator, target, '/soniox.speech_service.SpeechService/TranscribeStream', soniox_dot_speech__service__pb2.TranscribeStreamRequest.SerializeToString, soniox_dot_speech__service__pb2.TranscribeStreamResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def TranscribeAsync(request_iterator, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.stream_unary(request_iterator, target, '/soniox.speech_service.SpeechService/TranscribeAsync', soniox_dot_speech__service__pb2.TranscribeAsyncRequest.SerializeToString, soniox_dot_speech__service__pb2.TranscribeAsyncResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetTranscribeAsyncStatus(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/GetTranscribeAsyncStatus', soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusRequest.SerializeToString, soniox_dot_speech__service__pb2.GetTranscribeAsyncStatusResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetTranscribeAsyncResult(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_stream(request, target, '/soniox.speech_service.SpeechService/GetTranscribeAsyncResult', soniox_dot_speech__service__pb2.GetTranscribeAsyncResultRequest.SerializeToString, soniox_dot_speech__service__pb2.GetTranscribeAsyncResultResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DeleteTranscribeAsyncFile(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/DeleteTranscribeAsyncFile', soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileRequest.SerializeToString, soniox_dot_speech__service__pb2.DeleteTranscribeAsyncFileResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CreateSpeechContext(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/CreateSpeechContext', soniox_dot_speech__service__pb2.CreateSpeechContextRequest.SerializeToString, soniox_dot_speech__service__pb2.CreateSpeechContextResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DeleteSpeechContext(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/DeleteSpeechContext', soniox_dot_speech__service__pb2.DeleteSpeechContextRequest.SerializeToString, soniox_dot_speech__service__pb2.DeleteSpeechContextResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def ListSpeechContextNames(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/ListSpeechContextNames', soniox_dot_speech__service__pb2.ListSpeechContextNamesRequest.SerializeToString, soniox_dot_speech__service__pb2.ListSpeechContextNamesResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetSpeechContext(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/GetSpeechContext', soniox_dot_speech__service__pb2.GetSpeechContextRequest.SerializeToString, soniox_dot_speech__service__pb2.GetSpeechContextResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def UpdateSpeechContext(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/soniox.speech_service.SpeechService/UpdateSpeechContext', soniox_dot_speech__service__pb2.UpdateSpeechContextRequest.SerializeToString, soniox_dot_speech__service__pb2.UpdateSpeechContextResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
52.032746
129
0.700344
37ce18bcb95c06316178d52077446df676bb3c0c
7,511
py
Python
pyneal_scanner/getSeries.py
jeffmacinnes/pyneal
750f0ec5a231ccfa77aea960242de9b5019ba493
[ "MIT" ]
24
2017-03-15T16:53:10.000Z
2022-02-08T18:43:01.000Z
pyneal_scanner/getSeries.py
jeffmacinnes/pyneal
750f0ec5a231ccfa77aea960242de9b5019ba493
[ "MIT" ]
4
2017-03-16T01:36:46.000Z
2020-02-05T07:37:24.000Z
pyneal_scanner/getSeries.py
jeffmacinnes/pyneal
750f0ec5a231ccfa77aea960242de9b5019ba493
[ "MIT" ]
8
2017-03-21T14:38:26.000Z
2021-11-15T14:01:30.000Z
""" Create a Nifti file from specified series data Take the data in the specified series directory and convert it to a 4D nifti image in RAS+ orientation, and then save the new data to disk. If the series is an anatomical scan, the output Nifti will be 3D. If the series is a functional scan, the output Nifti will be 4D. In all cases, the affine transformation in the Nifti header will simply convert from voxel space to mm space using the image voxel sizes (and not moving the origin at all) """ import os import sys from os.path import join from utils.general_utils import initializeSession # Get the full path to where the pyneal_scanner directory is. This assumes # getSeries.py lives in the pyneal_scanner directory. pynealScannerDir = os.path.dirname(os.path.abspath(__file__)) def getSeries_GE(scannerDirs): """ Build nifti image from series data, GE format Assumes series data are represented as dicom files, one per slice. The path to the output Nifti file will be printed to stdOut upon completion (in general, expect to find it in the pyneal_scanner/data directory) Parameters ---------- scannerDirs : object instance of `GE_utils.GE_DirStructure`. Has attributes for the relevant paths for the current session. `scannerDirs` is one of the variables returned by running `general_utils.initializeSession()` """ from utils.GE_utils import GE_BuildNifti # prompt user to specifiy a series. Make sure that it is a valid # series before continuing seriesDirs = scannerDirs.get_seriesDirs() while True: selectedSeries = input('Which Series?: ') if selectedSeries in seriesDirs: break else: print('{} is not a valid series choice!'.format(selectedSeries)) # prompt user to specify an output name, and format to remove any spaces outputPrefix = input('Output Prefix: ') outputPrefix = outputPrefix.replace(' ', '') # progress updates print('='*5) print('Building Nifti...') print('\tinput series: {}'.format(selectedSeries)) print('\toutput prefix: {}'.format(outputPrefix)) # get the full path to the series dir seriesDir = join(scannerDirs.sessionDir, selectedSeries) # create an instance of the GE_NiftiBuilder niftiBuilder = GE_BuildNifti(seriesDir) output_fName = '{}_{}.nii.gz'.format(outputPrefix, selectedSeries) print('Successfully built Nifti image: {}\n'.format(output_fName)) # save Nifti image output_path = join(pynealScannerDir, 'data', output_fName) saveNifti(niftiBuilder, output_path) def getSeries_Philips(scannerDirs): """ Build nifti image from series data, Philips format Assumes series data are represented as par/rec file pairs, one per volume. The path to the output Nifti file will be printed to stdOut upon completion (in general, expect to find it in the pyneal_scanner/data directory) Parameters ---------- scannerDirs : object instance of `Philips_utils.Philips_DirStructure`. Has attributes for the relvant paths for the current session. `scannerDirs` is one of the variables returned by running `general_utils.initializeSession()` """ from utils.Philips_utils import Philips_BuildNifti # prompt user to specifiy a series. Make sure that it is a valid # series before continuing seriesDirs = scannerDirs.get_seriesDirs() while True: selectedSeries = input('Which Series?: ') if selectedSeries in seriesDirs: break else: print('{} is not a valid series choice!'.format(selectedSeries)) # prompt user to specify an output name, and format to remove any spaces outputPrefix = input('Output Prefix: ') outputPrefix = outputPrefix.replace(' ', '') # progress updates print('='*5) print('Building Nifti...') print('\tinput series: {}'.format(selectedSeries)) print('\toutput name: {}'.format(outputPrefix)) # get the full path to the series dir seriesDir = join(scannerDirs.sessionDir, selectedSeries) # create an instance of the Siemens_NiftiBuilder niftiBuilder = Philips_BuildNifti(seriesDir) output_fName = '{}_{}.nii.gz'.format(outputPrefix, selectedSeries) print('Successfully built Nifti image: {}\n'.format(output_fName)) # save Nifti image output_path = join(pynealScannerDir, 'data', output_fName) saveNifti(niftiBuilder, output_path) def getSeries_Siemens(scannerDirs): """ Build nifti image from series data, Siemens format Assumes series data are represented as dicom mosaic files, one per volume. The path to the output Nifti file will be printed to stdOut upon completion (in general, expect to find it in the pyneal_scanner/data directory) Parameters ---------- scannerDirs : object instance of `Siemens_utils.Siemens_DirStructure`. Has attributes for the relvant paths for the current session. `scannerDirs` is one of the variables returned by running `general_utils.initializeSession()` """ from utils.Siemens_utils import Siemens_BuildNifti # prompt user to specifiy a series. Make sure that it is a valid # series before continuing currentSeries = scannerDirs.getUniqueSeries() while True: selectedSeries = input('Which Series?: ') if selectedSeries.zfill(6) in currentSeries: break else: print('{} is not a valid series choice!'.format(selectedSeries)) # prompt user to specify an output name, and format to remove any spaces outputPrefix = input('Output Prefix: ') outputPrefix = outputPrefix.replace(' ', '') # progress updates print('='*5) print('Building Nifti...') print('\tinput series: {}'.format(selectedSeries)) print('\toutput name: {}'.format(outputPrefix)) # create an instance of the Siemens_NiftiBuilder niftiBuilder = Siemens_BuildNifti(scannerDirs.sessionDir, selectedSeries) output_fName = '{}_{}.nii.gz'.format(outputPrefix, selectedSeries) print('Successfully built Nifti image: {}\n'.format(output_fName)) # save the nifti image output_path = join(pynealScannerDir, 'data', output_fName) saveNifti(niftiBuilder, output_path) def saveNifti(niftiBuilder, outputPath): """ Save the nifti file to disk. Path to output file printed to stdOut Parameters ---------- niftiBuilder : object instance of the niftiBuilder class for this scanning environment outputPath : string full path to where you want to save nifti file """ # make sure the output dir exists outputDir, fName = os.path.split(outputPath) if not os.path.exists(outputDir): os.makedirs(outputDir) niftiBuilder.write_nifti(outputPath) print('saved at: {}'.format(outputPath)) if __name__ == '__main__': # initialize the session classes: scannerSettings, scannerDirs = initializeSession() # print all of the current series dirs to the terminal scannerDirs.print_currentSeries() # load the appropriate tools for this scanning environment scannerMake = scannerSettings.allSettings['scannerMake'] if scannerMake == 'GE': getSeries_GE(scannerDirs) elif scannerMake == 'Philips': getSeries_Philips(scannerDirs) elif scannerMake == 'Siemens': getSeries_Siemens(scannerDirs) else: print('Unrecognized scanner make: {}'.format(scannerMake))
36.285024
79
0.703901
444089a72332e12a86790988791f0e7493e7be39
139
py
Python
py/compat/conftest.py
woodrow/pyoac
b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7
[ "MIT" ]
1
2019-05-27T00:58:46.000Z
2019-05-27T00:58:46.000Z
py/compat/conftest.py
woodrow/pyoac
b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7
[ "MIT" ]
null
null
null
py/compat/conftest.py
woodrow/pyoac
b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7
[ "MIT" ]
null
null
null
import py class Directory(py.test.collect.Directory): def collect(self): py.test.skip("compat tests need to be run manually")
23.166667
60
0.705036
8cc2fc222cc9aba4caf79580dcfe1e161e51cff0
777
py
Python
setup.py
nestauk/AFS_analysis_childcare_providers
be2def68aca3c334a0c42c2bb1390e0dcbf2324e
[ "MIT" ]
null
null
null
setup.py
nestauk/AFS_analysis_childcare_providers
be2def68aca3c334a0c42c2bb1390e0dcbf2324e
[ "MIT" ]
3
2021-07-01T14:47:33.000Z
2021-07-12T09:15:11.000Z
setup.py
nestauk/AFS_analysis_childcare_providers
be2def68aca3c334a0c42c2bb1390e0dcbf2324e
[ "MIT" ]
null
null
null
"""afs_analysis_childcare_providers.""" from pathlib import Path from setuptools import find_packages from setuptools import setup def read_lines(path): """Read lines of `path`.""" with open(path) as f: return f.read().splitlines() BASE_DIR = Path(__file__).parent setup( name="afs_analysis_childcare_providers", long_description=open(BASE_DIR / "README.md").read(), install_requires=read_lines(BASE_DIR / "requirements.txt"), extras_require={"dev": read_lines(BASE_DIR / "requirements_dev.txt")}, packages=find_packages(exclude=["docs"]), version="0.1.0", description="Data analysis work around childcare providers takeup and the effect of covid on school readiness for early years.", author="Nesta", license="MIT", )
28.777778
132
0.718147
f872b81c6f1087d2f5aa97b2b6429848ebf4c7c3
15,670
py
Python
topopy/MorseComplex.py
vishalbelsare/topopy
73ccc9510bd34be2ead875bc3bc1081ccad26b1f
[ "BSD-3-Clause" ]
12
2018-04-18T00:04:00.000Z
2021-02-11T13:47:25.000Z
topopy/MorseComplex.py
vishalbelsare/topopy
73ccc9510bd34be2ead875bc3bc1081ccad26b1f
[ "BSD-3-Clause" ]
40
2018-01-19T21:40:14.000Z
2021-09-11T12:19:48.000Z
topopy/MorseComplex.py
vishalbelsare/topopy
73ccc9510bd34be2ead875bc3bc1081ccad26b1f
[ "BSD-3-Clause" ]
3
2019-07-09T04:57:07.000Z
2021-09-07T10:51:08.000Z
import sys import time import collections import json import numpy as np from .topology import MorseComplexFloat, vectorFloat, mapIntSetInt from .TopologicalObject import TopologicalObject class MorseComplex(TopologicalObject): """ A wrapper class for the C++ approximate Morse complex Object Parameters ---------- graph : nglpy.Graph A graph object used for determining neighborhoods in gradient estimation gradient : str An optional string specifying the type of gradient estimator to use. Currently the only available option is 'steepest'. normalization : str An optional string specifying whether the inputs/output should be scaled before computing. Currently, two modes are supported 'zscore' and 'feature'. 'zscore' will ensure the data has a mean of zero and a standard deviation of 1 by subtracting the mean and dividing by the variance. 'feature' scales the data into the unit hypercube. simplification : str An optional string specifying how we will compute the simplification hierarchy. Currently, three modes are supported 'difference', 'probability' and 'count'. 'difference' will take the function value difference of the extrema and its closest function valued neighboring saddle (standard persistence simplification), 'probability' will augment this value by multiplying the probability of the extremum and its saddle, and count will order the simplification by the size (number of points) in each manifold such that smaller features will be absorbed into neighboring larger features first. aggregator : str An optional string that specifies what type of aggregation to do when duplicates are found in the domain space. Default value is None meaning the code will error if duplicates are identified. debug : bool An optional boolean flag for whether debugging output should be enabled. """ def __init__( self, graph=None, gradient="steepest", normalization=None, simplification="difference", aggregator=None, debug=False, ): super(MorseComplex, self).__init__( graph=graph, gradient=gradient, normalization=normalization, aggregator=aggregator, debug=debug, ) self.simplification = simplification def reset(self): """ Empties all internal storage containers Returns ------- None """ super(MorseComplex, self).reset() self.base_partitions = {} self.merge_sequence = {} self.persistences = [] self.max_indices = [] # State properties self.persistence = 0. def build(self, X, Y, w=None): """ Assigns data to this object and builds the Morse Complex Uses an internal graph given in the constructor to build a Morse complex on the passed in data. Weights are currently ignored. Parameters ---------- X : np.ndarray An m-by-n array of values specifying m n-dimensional samples Y : np.array An m vector of values specifying the output responses corresponding to the m samples specified by X w : np.array An optional m vector of values specifying the weights associated to each of the m samples used. Default of None means all points will be equally weighted Returns ------- None """ super(MorseComplex, self).build(X, Y, w) if self.debug: sys.stdout.write("Decomposition: ") start = time.perf_counter() edges = mapIntSetInt() for key, items in self.graph.full_graph().items(): items = tuple(items) edges[key] = items morse_complex = MorseComplexFloat( vectorFloat(self.Xnorm.flatten()), vectorFloat(self.Y), str(self.gradient), str(self.simplification), vectorFloat(self.w), edges, self.debug, ) self.__amc = morse_complex self.persistences = [] self.merge_sequence = {} morse_complex_json = json.loads(morse_complex.to_json()) hierarchy = morse_complex_json["Hierarchy"] for merge in hierarchy: self.persistences.append(merge["Persistence"]) self.merge_sequence[merge["Dying"]] = ( merge["Persistence"], merge["Surviving"], merge["Saddle"], ) self.persistences = sorted(list(set(self.persistences))) partitions = morse_complex_json["Partitions"] self.base_partitions = {} for i, label in enumerate(partitions): if label not in self.base_partitions: self.base_partitions[label] = [] self.base_partitions[label].append(i) self.max_indices = list(self.base_partitions.keys()) if self.debug: end = time.perf_counter() sys.stdout.write("%f s\n" % (end - start)) def _build_for_morse_smale_complex(self, morse_smale_complex, negate=False): Y = morse_smale_complex.Y X = morse_smale_complex.Xnorm N = len(Y) - 1 complex_type = "Stable" edges = mapIntSetInt() for key, items in morse_smale_complex.graph.full_graph().items(): items = tuple(items) edges[key] = items if negate: Y = -Y[::-1] X = X[::-1] complex_type = "Unstable" reversed_edges = {} for key, neighbors in edges.items(): reversed_edges[N - key] = tuple([N - i for i in neighbors]) edges = reversed_edges if self.debug: sys.stdout.write(complex_type + " Decomposition: ") start = time.perf_counter() morse_complex = MorseComplexFloat( vectorFloat(X.flatten()), vectorFloat(Y), str(morse_smale_complex.gradient), str(morse_smale_complex.simplification), vectorFloat(morse_smale_complex.w), mapIntSetInt(edges), morse_smale_complex.debug, ) self.persistences = [] self.merge_sequence = {} morse_complex_json = json.loads(morse_complex.to_json()) hierarchy = morse_complex_json["Hierarchy"] for merge in hierarchy: self.persistences.append(merge["Persistence"]) if negate: self.merge_sequence[N - merge["Dying"]] = ( merge["Persistence"], N - merge["Surviving"], N - merge["Saddle"], ) else: self.merge_sequence[merge["Dying"]] = ( merge["Persistence"], merge["Surviving"], merge["Saddle"], ) self.persistences = sorted(list(set(self.persistences))) partitions = morse_complex_json["Partitions"] self.base_partitions = {} for i, label in enumerate(partitions): if negate: real_label = N - label real_index = N - i else: real_label = label real_index = i if real_label not in self.base_partitions: self.base_partitions[real_label] = [] self.base_partitions[real_label].append(real_index) self.max_indices = list(self.base_partitions.keys()) if self.debug: end = time.perf_counter() sys.stdout.write("%f s\n" % (end - start)) def save(self, filename=None): """ Saves a constructed Morse Complex in json file Parameters ---------- filename : str A filename for storing the hierarchical merging of features and the base level partitions of the data Returns ------- None """ if filename is None: filename = "morse_complex.json" with open(filename, "w") as fp: fp.write(self.to_json()) # Depending on the persistence simplification strategy, this could # alter the hierarchy, so let's remove this feature until further # notice, also the weighting feature is still pretty experimental: # def set_weights(self, w=None): # """ Sets the weights associated to the m input samples # @ In, w, optional m vector specifying the new weights to # use for the data points. Default is None and resets the # weights to be uniform. # """ # if w is not None: # self.w = np.array(w) # elif len(self.Y) > 0: # self.w = np.ones(len(self.Y))*1.0/float(len(self.Y)) def get_merge_sequence(self): """ Returns a data structure holding the ordered merge sequence of extrema simplification Returns ------- dict of int: tuple(float, int, int) A dictionary of tuples where the key is the dying extrema and the tuple is the the persistence, parent index, and the saddle index associated to the dying index, in that order. """ return self.merge_sequence def get_partitions(self, persistence=None): """ Returns the partitioned data based on a specified persistence level Parameters ---------- persistence : float A floating point value specifying the size of the smallest feature we want to track. Default = None means consider all features. Returns ------- dict of int: list of int A dictionary lists where each key is a integer specifying the index of the extremum. Each entry will hold a list of indices specifying points that are associated to this extremum. """ if persistence is None: persistence = self.persistence partitions = {} # TODO: Possibly cache at the critical persistence values, # previously caching was done at every query level, but that # does not make sense as the partitions will only change once # the next value in self.persistences is attained. Honestly, # this is probably not a necessary optimization that needs to # be made. Consider instead, Yarden's way of storing the points # such that merged arrays will be adjacent. for key, items in self.base_partitions.items(): new_key = key while ( self.merge_sequence[new_key][0] < persistence and self.merge_sequence[new_key][1] != new_key ): new_key = self.merge_sequence[new_key][1] if new_key not in partitions: partitions[new_key] = [] partitions[new_key].extend(items) for key in partitions: partitions[key] = sorted(list(set(partitions[key]))) return partitions def get_persistence(self): """ Retrieves the persistence simplfication level being used for this complex Returns ------- float Floating point value specifying the current persistence setting """ return self.persistence def set_persistence(self, p): """ Sets the persistence simplfication level to be used for representing this complex Parameters ---------- p : float A floating point value specifying the internally held size of the smallest feature we want to track. Returns ------- None """ self.persistence = p def get_label(self, indices=None): """ Returns the label indices requested by the user Parameters ---------- indices : list of int A list of non-negative integers specifying the row indices to return Returns ------- list of int A list of integers specifying the extremum index of the specified rows. """ if indices is None: indices = list(range(0, self.get_sample_size())) elif isinstance(indices, collections.Iterable): indices = sorted(list(set(indices))) else: indices = [indices] if len(indices) == 0: return [] partitions = self.get_partitions(self.persistence) labels = self.X.shape[0] * [None] for label, partition_indices in partitions.items(): for idx in np.intersect1d(partition_indices, indices): labels[idx] = label labels = np.array(labels) if len(indices) == 1: return labels[indices][0] return labels[indices] def get_current_labels(self): """ Returns a list of tuples that specifies the extremum index labels associated to each input sample Returns ------- list of tuple(int, int) a list of non-negative integers specifying the extremum-flow indices associated to each input sample at the current level of persistence """ partitions = self.get_partitions(self.persistence) return partitions.keys() def get_sample_size(self, key=None): """ Returns the number of samples in the input data Parameters ---------- key : int An optional integer specifying a max id used for determining which partition size should be returned. If not specified then the size of the entire data set will be returned. Returns ------- int An integer specifying the number of samples. """ if key is None: return len(self.Y) else: return len(self.get_partitions(self.persistence)[key]) def get_classification(self, idx): """ Given an index, this function will report whether that sample is a local maximum or a regular point. Parameters ---------- idx : int A non-negative integer less than the sample size of the input data. Returns ------- str A string specifying the classification type of the input sample: will be 'maximum' or 'regular.' """ if idx in self.max_indices: return "maximum" return "regular" def to_json(self): """ Writes the complete Morse complex merge hierarchy to a string Returns ------- str A string storing the entire merge hierarchy of all maxima """ capsule = {} capsule["Hierarchy"] = [] for ( dying, (persistence, surviving, saddle), ) in self.merge_sequence.items(): capsule["Hierarchy"].append( { "Persistence": persistence, "Dying": dying, "Surviving": surviving, "Saddle": saddle, } ) capsule["Partitions"] = [] base = np.array([None] * len(self.Y)) for label, items in self.base_partitions.items(): base[items] = label capsule["Partitions"] = base.tolist() return json.dumps(capsule, separators=(",", ":"))
33.269639
80
0.580089
63274abe198fbdf0e2a370a5fc2e472b3f3abba2
2,989
py
Python
ijal_interlinear/tests/test_Line.py
davidjamesbeck/IJAL-interlinear
cb5dbb1d6aea98cce76668aa868a9189f31baf3f
[ "BSD-2-Clause" ]
null
null
null
ijal_interlinear/tests/test_Line.py
davidjamesbeck/IJAL-interlinear
cb5dbb1d6aea98cce76668aa868a9189f31baf3f
[ "BSD-2-Clause" ]
null
null
null
ijal_interlinear/tests/test_Line.py
davidjamesbeck/IJAL-interlinear
cb5dbb1d6aea98cce76668aa868a9189f31baf3f
[ "BSD-2-Clause" ]
null
null
null
import re import sys sys.path.append("..") from line import * import importlib import os import pdb #---------------------------------------------------------------------------------------------------- pd.set_option('display.width', 1000) #---------------------------------------------------------------------------------------------------- def runTests(): test_buildTable() showVariedTables() test_extractAudio() def test_buildTable(): print("--- test_buildTable") filename = "../testData/lokono/LOKONO_IJAL_2.eaf" doc = etree.parse(filename) x3 = Line(doc, 3) tbl = x3.getTable() assert(tbl.shape == (14,13)) assert(tbl['ANNOTATION_ID'].tolist() == ['a26', 'a969', 'a12134', 'a12135', 'a12136', 'a12137', 'a20533', 'a22390', 'a20534', 'a22391', 'a20535', 'a22392', 'a20536', 'a22393']) assert(tbl['TIER_ID'].tolist() == ['Orthographic represntation', 'English translation', 'Word division-cp', 'Word division-cp', 'Word division-cp', 'Word division-cp', 'morpheme', 'gloss', 'morpheme', 'gloss', 'morpheme', 'gloss', 'morpheme', 'gloss']) # first element is empty, confusingly parsed out of xml as math.nan. don't test for it - too peculiar assert(tbl['ANNOTATION_REF'].tolist()[1:] == ['a26', 'a26', 'a26', 'a26', 'a26', 'a12134', 'a12134', 'a12135', 'a12135', 'a12136', 'a12136', 'a12137', 'a12137']) def test_stamdardizeTable(): xmlFilename = "../testData/lokono/LOKONO_IJAL_2.eaf" tierGuideFile = "../testData/lokono/tierGuide.yaml" doc = etree.parse(filename) x3 = Line(doc, 3) tbl = x3.getTable() with open(tierGuideFile, 'r') as f: tierGuide = yaml.load(f) tbl2 = standardizeTable(tbl, tierGuide) def showVariedTables(): filename = "../testData/lokono/LOKONO_IJAL_2.eaf" doc = etree.parse(filename) x3 = Line(doc, 3) print(x3.getTable()) filename = "../testData/monkeyAndThunder/AYA1_MonkeyandThunder.eaf" doc = etree.parse(filename) x0 = Line(doc, 0) print(x0.getTable()) x6 = Line(doc, 6) print(x6.getTable()) filename = "../testData/harryMosesDaylight/daylight_1_4.eaf" doc = etree.parse(filename) x1 = Line(doc, 1) print(x1.getTable()) def test_extractAudio(): print("--- test_extractAudio") filename = "../testData/monkeyAndThunder/AYA1_MonkeyandThunder.eaf" assert(os.path.exists(filename)) xmlDoc = etree.parse(filename) mediaDescriptors = xmlDoc.findall("HEADER/MEDIA_DESCRIPTOR") assert(len(mediaDescriptors) == 1) soundFileElement = mediaDescriptors[0] soundFileURI = soundFileElement.attrib["RELATIVE_MEDIA_URL"] directory = os.path.dirname(os.path.abspath(filename)) fullPath = os.path.join(directory, soundFileURI) assert(os.path.exists(fullPath)) if __name__ == '__main__': runTests()
35.583333
115
0.583473
4675daefd56742486878081501d692df36033f2d
35,311
py
Python
plaso/cli/storage_media_tool.py
pyllyukko/plaso
7533db2d1035ca71d264d6281ebd5db2d073c587
[ "Apache-2.0" ]
null
null
null
plaso/cli/storage_media_tool.py
pyllyukko/plaso
7533db2d1035ca71d264d6281ebd5db2d073c587
[ "Apache-2.0" ]
null
null
null
plaso/cli/storage_media_tool.py
pyllyukko/plaso
7533db2d1035ca71d264d6281ebd5db2d073c587
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- """The storage media CLI tool.""" import codecs import getpass import os from dfvfs.analyzer import analyzer as dfvfs_analyzer from dfvfs.analyzer import fvde_analyzer_helper from dfvfs.credentials import manager as credentials_manager from dfvfs.helpers import command_line as dfvfs_command_line from dfvfs.helpers import source_scanner from dfvfs.lib import definitions as dfvfs_definitions from dfvfs.lib import errors as dfvfs_errors from dfvfs.path import factory as path_spec_factory from dfvfs.volume import apfs_volume_system from dfvfs.volume import gpt_volume_system from dfvfs.volume import lvm_volume_system from dfvfs.volume import tsk_volume_system from dfvfs.volume import vshadow_volume_system from plaso.cli import tools from plaso.engine import configurations from plaso.lib import errors try: # Disable experimental FVDE support. dfvfs_analyzer.Analyzer.DeregisterHelper( fvde_analyzer_helper.FVDEAnalyzerHelper()) except KeyError: pass class StorageMediaToolMediator(dfvfs_command_line.CLIVolumeScannerMediator): """Mediator between the storage media tool and user input.""" def _PrintAPFSVolumeIdentifiersOverview( self, volume_system, volume_identifiers): """Prints an overview of APFS volume identifiers. Args: volume_system (dfvfs.APFSVolumeSystem): volume system. volume_identifiers (list[str]): allowed volume identifiers. Raises: SourceScannerError: if a volume cannot be resolved from the volume identifier. """ super(StorageMediaToolMediator, self)._PrintAPFSVolumeIdentifiersOverview( volume_system, volume_identifiers) self._output_writer.Write('\n') def _PrintLVMVolumeIdentifiersOverview( self, volume_system, volume_identifiers): """Prints an overview of LVM volume identifiers. Args: volume_system (dfvfs.LVMVolumeSystem): volume system. volume_identifiers (list[str]): allowed volume identifiers. Raises: SourceScannerError: if a volume cannot be resolved from the volume identifier. """ super(StorageMediaToolMediator, self)._PrintLVMVolumeIdentifiersOverview( volume_system, volume_identifiers) self._output_writer.Write('\n') def _PrintTSKPartitionIdentifiersOverview( self, volume_system, volume_identifiers): """Prints an overview of TSK partition identifiers. Args: volume_system (dfvfs.TSKVolumeSystem): volume system. volume_identifiers (list[str]): allowed volume identifiers. Raises: SourceScannerError: if a volume cannot be resolved from the volume identifier. """ super(StorageMediaToolMediator, self)._PrintPartitionIdentifiersOverview( volume_system, volume_identifiers) self._output_writer.Write('\n') def _PrintVSSStoreIdentifiersOverview( self, volume_system, volume_identifiers): """Prints an overview of VSS store identifiers. Args: volume_system (dfvfs.VShadowVolumeSystem): volume system. volume_identifiers (list[str]): allowed volume identifiers. Raises: SourceScannerError: if a volume cannot be resolved from the volume identifier. """ super(StorageMediaToolMediator, self)._PrintVSSStoreIdentifiersOverview( volume_system, volume_identifiers) self._output_writer.Write('\n') # pylint: disable=arguments-differ # TODO: replace this method by the one defined by CLIVolumeScannerMediator def ParseVolumeIdentifiersString( self, volume_identifiers_string, prefix='v'): """Parses a user specified volume identifiers string. Args: volume_identifiers_string (str): user specified volume identifiers. A range of volumes can be defined as: "3..5". Multiple volumes can be defined as: "1,3,5" (a list of comma separated values). Ranges and lists can also be combined as: "1,3..5". The first volume is 1. All volumes can be defined as: "all". prefix (Optional[str]): volume identifier prefix. Returns: list[str]: volume identifiers with prefix or the string "all". Raises: ValueError: if the volume identifiers string is invalid. """ return self._ParseVolumeIdentifiersString( volume_identifiers_string, prefix=prefix) def PromptUserForEncryptedVolumeCredential( self, source_scanner_object, scan_context, locked_scan_node, credentials): """Prompts the user to provide a credential for an encrypted volume. Args: source_scanner_object (SourceScanner): source scanner. scan_context (dfvfs.SourceScannerContext): source scanner context. locked_scan_node (dfvfs.SourceScanNode): locked scan node. credentials (dfvfs.Credentials): credentials supported by the locked scan node. Returns: tuple: contains: bool: True if the volume was unlocked. credential_identifier (str): credential identifier used to unlock the scan node. credential_data (bytes): credential data used to unlock the scan node. """ # TODO: print volume description. if locked_scan_node.type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_APFS_CONTAINER): header = 'Found an APFS encrypted volume.' elif locked_scan_node.type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_BDE): header = 'Found a BitLocker encrypted volume.' elif locked_scan_node.type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_FVDE): header = 'Found a CoreStorage (FVDE) encrypted volume.' else: header = 'Found an encrypted volume.' self._output_writer.Write(header) credentials_list = sorted(credentials.CREDENTIALS) credentials_list.append('skip') self._output_writer.Write('Supported credentials:\n\n') for index, name in enumerate(credentials_list): available_credential = ' {0:d}. {1:s}\n'.format(index + 1, name) self._output_writer.Write(available_credential) self._output_writer.Write('\nNote that you can abort with Ctrl^C.\n\n') is_unlocked = False credential_type = None credential_data = None while not is_unlocked: self._output_writer.Write('Select a credential to unlock the volume: ') input_line = self._input_reader.Read() input_line = input_line.strip() if input_line in credentials_list: credential_type = input_line else: try: credential_type = int(input_line, 10) credential_type = credentials_list[credential_type - 1] except (IndexError, ValueError): self._output_writer.Write( 'Unsupported credential: {0:s}\n'.format(input_line)) continue if credential_type == 'skip': break credential_data = getpass.getpass('Enter credential data: ') self._output_writer.Write('\n') if credential_type == 'key': try: credential_data = codecs.decode(credential_data, 'hex') except TypeError: self._output_writer.Write('Unsupported credential data.\n') continue is_unlocked = source_scanner_object.Unlock( scan_context, locked_scan_node.path_spec, credential_type, credential_data) if is_unlocked: self._output_writer.Write('Volume unlocked.\n\n') break self._output_writer.Write('Unable to unlock volume.\n\n') return is_unlocked, credential_type, credential_data def PromptUserForVSSCurrentVolume(self): """Prompts the user if the current volume with VSS should be processed. Returns: bool: True if the current volume with VSS should be processed. """ while True: self._output_writer.Write( 'Volume Shadow Snapshots (VSS) were selected also process current\n' 'volume? [yes, no]\n') process_current_volume = self._input_reader.Read() process_current_volume = process_current_volume.strip() process_current_volume = process_current_volume.lower() if (not process_current_volume or process_current_volume in ('no', 'yes')): break self._output_writer.Write( '\n' 'Unsupported option, please try again or abort with Ctrl^C.\n' '\n') self._output_writer.Write('\n') return not process_current_volume or process_current_volume == 'yes' class StorageMediaTool(tools.CLITool): """CLI tool that supports a storage media device or image as input.""" # TODO: remove this redirect. _SOURCE_OPTION = 'source' _BINARY_DATA_CREDENTIAL_TYPES = ['key_data'] _SUPPORTED_CREDENTIAL_TYPES = [ 'key_data', 'password', 'recovery_password', 'startup_key'] def __init__(self, input_reader=None, output_writer=None): """Initializes a CLI tool that supports storage media as input. Args: input_reader (Optional[InputReader]): input reader, where None indicates that the stdin input reader should be used. output_writer (Optional[OutputWriter]): output writer, where None indicates that the stdout output writer should be used. """ super(StorageMediaTool, self).__init__( input_reader=input_reader, output_writer=output_writer) self._custom_artifacts_path = None self._artifact_definitions_path = None self._artifact_filters = None self._credentials = [] self._credential_configurations = [] self._filter_file = None self._mediator = StorageMediaToolMediator( input_reader=input_reader, output_writer=output_writer) self._partitions = None self._process_vss = False self._source_scanner = source_scanner.SourceScanner() self._source_path = None self._source_path_specs = [] self._volumes = None self._vss_only = False self._vss_stores = None def _AddCredentialConfiguration( self, path_spec, credential_type, credential_data): """Adds a credential configuration. Args: path_spec (dfvfs.PathSpec): path specification. credential_type (str): credential type. credential_data (bytes): credential data. """ credential_configuration = configurations.CredentialConfiguration( credential_data=credential_data, credential_type=credential_type, path_spec=path_spec) self._credential_configurations.append(credential_configuration) def _GetAPFSVolumeIdentifiers(self, scan_node): """Determines the APFS volume identifiers. Args: scan_node (dfvfs.SourceScanNode): scan node. Returns: list[str]: APFS volume identifiers. Raises: SourceScannerError: if the scan node is invalid or more than 1 volume was found but no volumes were specified. UserAbort: if the user requested to abort. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid scan node.') volume_system = apfs_volume_system.APFSVolumeSystem() volume_system.Open(scan_node.path_spec) volume_identifiers = self._source_scanner.GetVolumeIdentifiers( volume_system) if not volume_identifiers: return [] # TODO: refactor self._volumes to use scan options. if self._volumes: if self._volumes == 'all': volumes = volume_system.volume_identifiers else: volumes = self._mediator.ParseVolumeIdentifiersString( self._volumes, prefix='apfs') selected_volume_identifiers = self._NormalizedVolumeIdentifiers( volume_system, volumes, prefix='apfs') if not set(selected_volume_identifiers).difference(volume_identifiers): return selected_volume_identifiers if len(volume_identifiers) > 1: if self._unattended_mode: raise errors.SourceScannerError( 'More than 1 volume found but no volumes specified.') try: volume_identifiers = self._mediator.GetAPFSVolumeIdentifiers( volume_system, volume_identifiers) except KeyboardInterrupt: raise errors.UserAbort('File system scan aborted.') return self._NormalizedVolumeIdentifiers( volume_system, volume_identifiers, prefix='apfs') def _GetLVMVolumeIdentifiers(self, scan_node): """Determines the LVM volume identifiers. Args: scan_node (dfvfs.SourceScanNode): scan node. Returns: list[str]: LVM volume identifiers. Raises: SourceScannerError: if the scan node is invalid or more than 1 volume was found but no volumes were specified. UserAbort: if the user requested to abort. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid scan node.') volume_system = lvm_volume_system.LVMVolumeSystem() volume_system.Open(scan_node.path_spec) volume_identifiers = self._source_scanner.GetVolumeIdentifiers( volume_system) if not volume_identifiers: return [] # TODO: refactor self._volumes to use scan options. if self._volumes: if self._volumes == 'all': volumes = volume_system.volume_identifiers else: volumes = self._mediator.ParseVolumeIdentifiersString( self._volumes, prefix='lvm') selected_volume_identifiers = self._NormalizedVolumeIdentifiers( volume_system, volumes, prefix='lvm') if not set(selected_volume_identifiers).difference(volume_identifiers): return selected_volume_identifiers if len(volume_identifiers) > 1: if self._unattended_mode: raise errors.SourceScannerError( 'More than 1 volume found but no volumes specified.') try: volume_identifiers = self._mediator.GetLVMVolumeIdentifiers( volume_system, volume_identifiers) except KeyboardInterrupt: raise errors.UserAbort('File system scan aborted.') return self._NormalizedVolumeIdentifiers( volume_system, volume_identifiers, prefix='lvm') def _GetTSKPartitionIdentifiers(self, scan_node): """Determines the TSK partition identifiers. This method first checks for the preferred partition number, then falls back to prompt the user if no usable preferences were specified. Args: scan_node (dfvfs.SourceScanNode): scan node. Returns: list[str]: TSK partition identifiers. Raises: RuntimeError: if the volume for a specific identifier cannot be retrieved. SourceScannerError: if the scan node is invalid or more than 1 volume was found but no volumes were specified. UserAbort: if the user requested to abort. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid scan node.') if scan_node.path_spec.type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_GPT): volume_system = gpt_volume_system.GPTVolumeSystem() else: volume_system = tsk_volume_system.TSKVolumeSystem() volume_system.Open(scan_node.path_spec) volume_identifiers = self._source_scanner.GetVolumeIdentifiers( volume_system) if not volume_identifiers: return [] # TODO: refactor self._partitions to use scan options. if self._partitions: if self._partitions == 'all': partitions = volume_system.volume_identifiers else: partitions = self._mediator.ParseVolumeIdentifiersString( self._partitions, prefix='p') selected_volume_identifiers = self._NormalizedVolumeIdentifiers( volume_system, partitions, prefix='p') if not set(selected_volume_identifiers).difference(volume_identifiers): return selected_volume_identifiers if len(volume_identifiers) > 1: if self._unattended_mode: raise errors.SourceScannerError( 'More than 1 partition found but no partitions specified.') try: volume_identifiers = self._mediator.GetPartitionIdentifiers( volume_system, volume_identifiers) except KeyboardInterrupt: raise errors.UserAbort('File system scan aborted.') return self._NormalizedVolumeIdentifiers( volume_system, volume_identifiers, prefix='p') def _GetVSSStoreIdentifiers(self, scan_node): """Determines the VSS store identifiers. Args: scan_node (dfvfs.SourceScanNode): scan node. Returns: list[str]: VSS store identifiers. Raises: SourceScannerError: if the scan node is invalid. UserAbort: if the user requested to abort. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid scan node.') volume_system = vshadow_volume_system.VShadowVolumeSystem() volume_system.Open(scan_node.path_spec) volume_identifiers = self._source_scanner.GetVolumeIdentifiers( volume_system) if not volume_identifiers: return [] # TODO: refactor to use scan options. if self._vss_stores: if self._vss_stores == 'all': vss_stores = volume_system.volume_identifiers else: vss_stores = self._mediator.ParseVolumeIdentifiersString( self._vss_stores, prefix='vss') selected_volume_identifiers = self._NormalizedVolumeIdentifiers( volume_system, vss_stores, prefix='vss') if not set(selected_volume_identifiers).difference(volume_identifiers): return selected_volume_identifiers if self._unattended_mode: return [] try: volume_identifiers = self._mediator.GetVSSStoreIdentifiers( volume_system, volume_identifiers) except KeyboardInterrupt: raise errors.UserAbort('File system scan aborted.') return self._NormalizedVolumeIdentifiers( volume_system, volume_identifiers, prefix='vss') def _NormalizedVolumeIdentifiers( self, volume_system, volume_identifiers, prefix='v'): """Normalizes volume identifiers. Args: volume_system (VolumeSystem): volume system. volume_identifiers (list[int|str]): allowed volume identifiers, formatted as an integer or string with prefix. prefix (Optional[str]): volume identifier prefix. Returns: list[str]: volume identifiers with prefix. Raises: SourceScannerError: if the volume identifier is not supported or no volume could be found that corresponds with the identifier. """ normalized_volume_identifiers = [] for volume_identifier in volume_identifiers: if isinstance(volume_identifier, int): volume_identifier = '{0:s}{1:d}'.format(prefix, volume_identifier) elif not volume_identifier.startswith(prefix): try: volume_identifier = int(volume_identifier, 10) volume_identifier = '{0:s}{1:d}'.format(prefix, volume_identifier) except (TypeError, ValueError): pass try: volume = volume_system.GetVolumeByIdentifier(volume_identifier) except KeyError: volume = None if not volume: raise errors.SourceScannerError( 'Volume missing for identifier: {0:s}.'.format(volume_identifier)) normalized_volume_identifiers.append(volume_identifier) return normalized_volume_identifiers def _ParseCredentialOptions(self, options): """Parses the credential options. Args: options (argparse.Namespace): command line arguments. Raises: BadConfigOption: if the options are invalid. """ credentials = getattr(options, 'credentials', []) if not isinstance(credentials, list): raise errors.BadConfigOption('Unsupported credentials value.') for credential_string in credentials: credential_type, _, credential_data = credential_string.partition(':') if not credential_type or not credential_data: raise errors.BadConfigOption( 'Badly formatted credential: {0:s}.'.format(credential_string)) if credential_type not in self._SUPPORTED_CREDENTIAL_TYPES: raise errors.BadConfigOption( 'Unsupported credential type for: {0:s}.'.format( credential_string)) if credential_type in self._BINARY_DATA_CREDENTIAL_TYPES: try: credential_data = codecs.decode(credential_data, 'hex') except TypeError: raise errors.BadConfigOption( 'Unsupported credential data for: {0:s}.'.format( credential_string)) self._credentials.append((credential_type, credential_data)) def _ParseSourcePathOption(self, options): """Parses the source path option. Args: options (argparse.Namespace): command line arguments. Raises: BadConfigOption: if the options are invalid. """ self._source_path = self.ParseStringOption(options, self._SOURCE_OPTION) if not self._source_path: raise errors.BadConfigOption('Missing source path.') self._source_path = os.path.abspath(self._source_path) def _ParseStorageMediaOptions(self, options): """Parses the storage media options. Args: options (argparse.Namespace): command line arguments. Raises: BadConfigOption: if the options are invalid. """ self._ParseStorageMediaImageOptions(options) self._ParseVSSProcessingOptions(options) self._ParseCredentialOptions(options) self._ParseSourcePathOption(options) def _ParseStorageMediaImageOptions(self, options): """Parses the storage media image options. Args: options (argparse.Namespace): command line arguments. Raises: BadConfigOption: if the options are invalid. """ self._partitions = getattr(options, 'partitions', None) if self._partitions: try: self._mediator.ParseVolumeIdentifiersString( self._partitions, prefix='p') except ValueError: raise errors.BadConfigOption('Unsupported partitions') self._volumes = getattr(options, 'volumes', None) if self._volumes: try: self._mediator.ParseVolumeIdentifiersString( self._volumes, prefix='apfs') except ValueError: raise errors.BadConfigOption('Unsupported volumes') def _ParseVSSProcessingOptions(self, options): """Parses the VSS processing options. Args: options (argparse.Namespace): command line arguments. Raises: BadConfigOption: if the options are invalid. """ vss_only = False vss_stores = None self._process_vss = not getattr(options, 'no_vss', False) if self._process_vss: vss_only = getattr(options, 'vss_only', False) vss_stores = getattr(options, 'vss_stores', None) if vss_stores: try: self._mediator.ParseVolumeIdentifiersString(vss_stores, prefix='vss') except ValueError: raise errors.BadConfigOption('Unsupported VSS stores') self._vss_only = vss_only self._vss_stores = vss_stores def _ScanEncryptedVolume(self, scan_context, scan_node): """Scans an encrypted volume scan node for volume and file systems. Args: scan_context (SourceScannerContext): source scanner context. scan_node (SourceScanNode): volume scan node. Raises: SourceScannerError: if the format of or within the source is not supported, the scan node is invalid or there are no credentials defined for the format. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid or missing scan node.') credentials = credentials_manager.CredentialsManager.GetCredentials( scan_node.path_spec) if not credentials: raise errors.SourceScannerError('Missing credentials for scan node.') credentials_dict = dict(self._credentials) is_unlocked = False for credential_type in sorted(credentials.CREDENTIALS): credential_data = credentials_dict.get(credential_type, None) if not credential_data: continue is_unlocked = self._source_scanner.Unlock( scan_context, scan_node.path_spec, credential_type, credential_data) if is_unlocked: self._AddCredentialConfiguration( scan_node.path_spec, credential_type, credential_data) break if not is_unlocked and self._unattended_mode: is_unlocked, credential_type, credential_data = ( self._mediator.PromptUserForEncryptedVolumeCredential( self._source_scanner, scan_context, scan_node, credentials)) if is_unlocked: self._AddCredentialConfiguration( scan_node.path_spec, credential_type, credential_data) self._source_scanner.Scan( scan_context, scan_path_spec=scan_node.path_spec) def _ScanFileSystem(self, scan_node, base_path_specs): """Scans a file system scan node for file systems. Args: scan_node (SourceScanNode): file system scan node. base_path_specs (list[PathSpec]): file system base path specifications. Raises: SourceScannerError: if the scan node is invalid. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError( 'Invalid or missing file system scan node.') if self._vss_only: if scan_node.parent_node.sub_nodes[0].type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_VSHADOW): return base_path_specs.append(scan_node.path_spec) def _ScanVolume(self, scan_context, scan_node, base_path_specs): """Scans a volume scan node for volume and file systems. Args: scan_context (SourceScannerContext): source scanner context. scan_node (SourceScanNode): volume scan node. base_path_specs (list[PathSpec]): file system base path specifications. Raises: SourceScannerError: if the format of or within the source is not supported or the scan node is invalid. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid or missing scan node.') if scan_context.IsLockedScanNode(scan_node.path_spec): # The source scanner found a locked volume and we need a credential to # unlock it. self._ScanEncryptedVolume(scan_context, scan_node) if scan_context.IsLockedScanNode(scan_node.path_spec): return if scan_node.IsVolumeSystemRoot(): self._ScanVolumeSystemRoot(scan_context, scan_node, base_path_specs) elif scan_node.IsFileSystem(): self._ScanFileSystem(scan_node, base_path_specs) elif scan_node.type_indicator == dfvfs_definitions.TYPE_INDICATOR_VSHADOW: if self._process_vss: # TODO: look into building VSS store on demand. # We "optimize" here for user experience, alternatively we could scan # for a file system instead of hard coding a child path specification. if dfvfs_definitions.PREFERRED_NTFS_BACK_END == ( dfvfs_definitions.TYPE_INDICATOR_TSK): location = '/' else: location = '\\' path_spec = path_spec_factory.Factory.NewPathSpec( dfvfs_definitions.PREFERRED_NTFS_BACK_END, location=location, parent=scan_node.path_spec) base_path_specs.append(path_spec) else: for sub_scan_node in scan_node.sub_nodes: self._ScanVolume(scan_context, sub_scan_node, base_path_specs) def _ScanVolumeSystemRoot(self, scan_context, scan_node, base_path_specs): """Scans a volume system root scan node for volume and file systems. Args: scan_context (SourceScannerContext): source scanner context. scan_node (SourceScanNode): volume system root scan node. base_path_specs (list[PathSpec]): file system base path specifications. Raises: SourceScannerError: if the scan node is invalid, the scan node type is not supported or if a sub scan node cannot be retrieved. """ if not scan_node or not scan_node.path_spec: raise errors.SourceScannerError('Invalid scan node.') if scan_node.type_indicator == ( dfvfs_definitions.TYPE_INDICATOR_APFS_CONTAINER): volume_identifiers = self._GetAPFSVolumeIdentifiers(scan_node) elif scan_node.type_indicator == dfvfs_definitions.TYPE_INDICATOR_LVM: volume_identifiers = self._GetLVMVolumeIdentifiers(scan_node) elif scan_node.type_indicator == dfvfs_definitions.TYPE_INDICATOR_VSHADOW: if not self._process_vss: volume_identifiers = [] else: volume_identifiers = self._GetVSSStoreIdentifiers(scan_node) # Process VSS stores (snapshots) starting with the most recent one. volume_identifiers.reverse() if (not self._vss_only and not self._unattended_mode and volume_identifiers): self._vss_only = not self._mediator.PromptUserForVSSCurrentVolume() else: raise errors.SourceScannerError( 'Unsupported volume system type: {0:s}.'.format( scan_node.type_indicator)) for volume_identifier in volume_identifiers: location = '/{0:s}'.format(volume_identifier) sub_scan_node = scan_node.GetSubNodeByLocation(location) if not sub_scan_node: raise errors.SourceScannerError( 'Scan node missing for volume identifier: {0:s}.'.format( volume_identifier)) self._ScanVolume(scan_context, sub_scan_node, base_path_specs) def AddCredentialOptions(self, argument_group): """Adds the credential options to the argument group. The credential options are use to unlock encrypted volumes. Args: argument_group (argparse._ArgumentGroup): argparse argument group. """ argument_group.add_argument( '--credential', action='append', default=[], type=str, dest='credentials', metavar='TYPE:DATA', help=( 'Define a credentials that can be used to unlock encrypted ' 'volumes e.g. BitLocker. The credential is defined as type:data ' 'e.g. "password:BDE-test". Supported credential types are: ' '{0:s}. Binary key data is expected to be passed in BASE-16 ' 'encoding (hexadecimal). WARNING credentials passed via command ' 'line arguments can end up in logs, so use this option with ' 'care.').format(', '.join(self._SUPPORTED_CREDENTIAL_TYPES))) def AddStorageMediaImageOptions(self, argument_group): """Adds the storage media image options to the argument group. Args: argument_group (argparse._ArgumentGroup): argparse argument group. """ argument_group.add_argument( '--partitions', '--partition', dest='partitions', action='store', type=str, default=None, help=( 'Define partitions to be processed. A range of ' 'partitions can be defined as: "3..5". Multiple partitions can ' 'be defined as: "1,3,5" (a list of comma separated values). ' 'Ranges and lists can also be combined as: "1,3..5". The first ' 'partition is 1. All partitions can be specified with: "all".')) argument_group.add_argument( '--volumes', '--volume', dest='volumes', action='store', type=str, default=None, help=( 'Define volumes to be processed. A range of volumes can be defined ' 'as: "3..5". Multiple volumes can be defined as: "1,3,5" (a list ' 'of comma separated values). Ranges and lists can also be combined ' 'as: "1,3..5". The first volume is 1. All volumes can be specified ' 'with: "all".')) def AddVSSProcessingOptions(self, argument_group): """Adds the VSS processing options to the argument group. Args: argument_group (argparse._ArgumentGroup): argparse argument group. """ argument_group.add_argument( '--no_vss', '--no-vss', dest='no_vss', action='store_true', default=False, help=( 'Do not scan for Volume Shadow Snapshots (VSS). This means that ' 'Volume Shadow Snapshots (VSS) are not processed.')) argument_group.add_argument( '--vss_only', '--vss-only', dest='vss_only', action='store_true', default=False, help=( 'Do not process the current volume if Volume Shadow Snapshots ' '(VSS) have been selected.')) argument_group.add_argument( '--vss_stores', '--vss-stores', dest='vss_stores', action='store', type=str, default=None, help=( 'Define Volume Shadow Snapshots (VSS) (or stores that need to be ' 'processed. A range of stores can be defined as: "3..5". ' 'Multiple stores can be defined as: "1,3,5" (a list of comma ' 'separated values). Ranges and lists can also be combined as: ' '"1,3..5". The first store is 1. All stores can be defined as: ' '"all".')) def ScanSource(self, source_path): """Scans the source path for volume and file systems. This function sets the internal source path specification and source type values. Args: source_path (str): path to the source. Returns: dfvfs.SourceScannerContext: source scanner context. Raises: SourceScannerError: if the format of or within the source is not supported. """ # Symbolic links are resolved here and not earlier to preserve the user # specified source path in storage and reporting. if os.path.islink(source_path): source_path = os.path.realpath(source_path) if (not source_path.startswith('\\\\.\\') and not os.path.exists(source_path)): raise errors.SourceScannerError( 'No such device, file or directory: {0:s}.'.format(source_path)) scan_context = source_scanner.SourceScannerContext() scan_context.OpenSourcePath(source_path) try: self._source_scanner.Scan(scan_context) except (ValueError, dfvfs_errors.BackEndError) as exception: raise errors.SourceScannerError( 'Unable to scan source with error: {0!s}.'.format(exception)) if scan_context.source_type not in ( scan_context.SOURCE_TYPE_STORAGE_MEDIA_DEVICE, scan_context.SOURCE_TYPE_STORAGE_MEDIA_IMAGE): scan_node = scan_context.GetRootScanNode() self._source_path_specs.append(scan_node.path_spec) return scan_context # Get the first node where where we need to decide what to process. scan_node = scan_context.GetRootScanNode() while len(scan_node.sub_nodes) == 1: scan_node = scan_node.sub_nodes[0] base_path_specs = [] if scan_node.type_indicator not in ( dfvfs_definitions.TYPE_INDICATOR_GPT, dfvfs_definitions.TYPE_INDICATOR_TSK_PARTITION): self._ScanVolume(scan_context, scan_node, base_path_specs) else: # Determine which partition needs to be processed. partition_identifiers = self._GetTSKPartitionIdentifiers(scan_node) if not partition_identifiers: raise errors.SourceScannerError('No partitions found.') for partition_identifier in partition_identifiers: location = '/{0:s}'.format(partition_identifier) sub_scan_node = scan_node.GetSubNodeByLocation(location) self._ScanVolume(scan_context, sub_scan_node, base_path_specs) if not base_path_specs: raise errors.SourceScannerError( 'No supported file system found in source.') self._source_path_specs = base_path_specs return scan_context
35.958248
80
0.701821
590cd8fd2841add72e825219d29700e24439ac1d
4,781
py
Python
tests/test_single_triangle_camera_fisheye.py
numericalBoy/redner
a68d631b1ac8dca0acf9f253987b7596533d35d5
[ "MIT" ]
null
null
null
tests/test_single_triangle_camera_fisheye.py
numericalBoy/redner
a68d631b1ac8dca0acf9f253987b7596533d35d5
[ "MIT" ]
null
null
null
tests/test_single_triangle_camera_fisheye.py
numericalBoy/redner
a68d631b1ac8dca0acf9f253987b7596533d35d5
[ "MIT" ]
null
null
null
import pyredner import numpy as np import torch # Optimize fisheye camera parameters of a single triangle rendering # Use GPU if available pyredner.set_use_gpu(torch.cuda.is_available()) # Set up the scene using Pytorch tensor position = torch.tensor([0.0, 0.0, -1.0]) look_at = torch.tensor([0.0, 0.0, 0.0]) up = torch.tensor([0.0, 1.0, 0.0]) fov = torch.tensor([45.0]) clip_near = 1e-2 resolution = (256, 256) cam = pyredner.Camera(position = position, look_at = look_at, up = up, fov = fov, clip_near = clip_near, resolution = resolution, fisheye = True) mat_grey = pyredner.Material(\ diffuse_reflectance = torch.tensor([0.5, 0.5, 0.5], device = pyredner.get_device())) materials = [mat_grey] vertices = torch.tensor([[-1.7,1.0,0.0], [1.0,1.0,0.0], [-0.5,-1.0,0.0]], device = pyredner.get_device()) indices = torch.tensor([[0, 1, 2]], dtype = torch.int32, device = pyredner.get_device()) shape_triangle = pyredner.Shape(vertices, indices, None, None, 0) light_vertices = torch.tensor([[-1.0,-1.0,-9.0],[1.0,-1.0,-9.0],[-1.0,1.0,-9.0],[1.0,1.0,-9.0]], device = pyredner.get_device()) light_indices = torch.tensor([[0,1,2],[1,3,2]], dtype = torch.int32, device = pyredner.get_device()) shape_light = pyredner.Shape(light_vertices, light_indices, None, None, 0) shapes = [shape_triangle, shape_light] light_intensity = torch.tensor([30.0,30.0,30.0]) light = pyredner.AreaLight(1, light_intensity) area_lights = [light] scene = pyredner.Scene(cam, shapes, materials, area_lights) args = pyredner.RenderFunction.serialize_scene(\ scene = scene, num_samples = 16, max_bounces = 1) # Alias of the render function render = pyredner.RenderFunction.apply # Render our target img = render(0, *args) pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/target.exr') pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/target.png') target = pyredner.imread('results/test_single_triangle_camera_fisheye/target.exr') if pyredner.get_use_gpu(): target = target.cuda(device = pyredner.get_device()) # Perturb the scene, this is our initial guess position = torch.tensor([0.5, -0.5, -3.0], requires_grad = True) scene.camera = pyredner.Camera(position = position, look_at = look_at, up = up, fov = fov, clip_near = clip_near, resolution = resolution, fisheye = True) args = pyredner.RenderFunction.serialize_scene(\ scene = scene, num_samples = 16, max_bounces = 1) # Render the initial guess img = render(1, *args) pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/init.png') diff = torch.abs(target - img) pyredner.imwrite(diff.cpu(), 'results/test_single_triangle_camera_fisheye/init_diff.png') # Optimize for camera pose optimizer = torch.optim.Adam([position], lr=5e-2) for t in range(200): print('iteration:', t) optimizer.zero_grad() # Need to rerun the Camera constructor for PyTorch autodiff to compute the derivatives scene.camera = pyredner.Camera(position = position, look_at = look_at, up = up, fov = fov, clip_near = clip_near, resolution = resolution, fisheye = True) args = pyredner.RenderFunction.serialize_scene(\ scene = scene, num_samples = 4, max_bounces = 1) img = render(t+1, *args) pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/iter_{}.png'.format(t)) loss = (img - target).pow(2).sum() print('loss:', loss.item()) loss.backward() print('position.grad:', position.grad) optimizer.step() print('position:', position) args = pyredner.RenderFunction.serialize_scene(\ scene = scene, num_samples = 16, max_bounces = 1) img = render(202, *args) pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/final.exr') pyredner.imwrite(img.cpu(), 'results/test_single_triangle_camera_fisheye/final.png') pyredner.imwrite(torch.abs(target - img).cpu(), 'results/test_single_triangle_camera_fisheye/final_diff.png') from subprocess import call call(["ffmpeg", "-framerate", "24", "-i", "results/test_single_triangle_camera_fisheye/iter_%d.png", "-vb", "20M", "results/test_single_triangle_camera_fisheye/out.mp4"])
40.863248
109
0.627065
527b816b01c6f99ac2b2039ff6def528c2e9ad66
836
py
Python
src/restapi/project/views.py
agbilotia1998/backend
c8e7654fe4cdd2faa8d0c6f7cfe12486a403ad17
[ "Apache-2.0" ]
null
null
null
src/restapi/project/views.py
agbilotia1998/backend
c8e7654fe4cdd2faa8d0c6f7cfe12486a403ad17
[ "Apache-2.0" ]
null
null
null
src/restapi/project/views.py
agbilotia1998/backend
c8e7654fe4cdd2faa8d0c6f7cfe12486a403ad17
[ "Apache-2.0" ]
null
null
null
import uuid from djoser.views import UserView, UserDeleteView from djoser import serializers from rest_framework import views, permissions, status, permissions, generics, filters from rest_framework.response import Response from . import models from . import serializers from .serializers import ProjectSerializer from rest_framework.decorators import api_view class ProjectView(generics.ListCreateAPIView): """Use this endpoint to add projects in the backend.""" def get_queryset(self): queryset = models.Project.objects.all() project_id = self.request.query_params.get('id', None) if project_id is None: return queryset else: return queryset.filter(id=project_id) permission_classes = [permissions.AllowAny] serializer_class = serializers.ProjectSerializer
32.153846
85
0.754785
6f794a8a40528a0568fc07bb6c08a4f81c738229
3,351
py
Python
stubs.min/System/Diagnostics/__init___parts/StackFrame.py
ricardyn/ironpython-stubs
4d2b405eda3ceed186e8adca55dd97c332c6f49d
[ "MIT" ]
1
2021-02-02T13:39:16.000Z
2021-02-02T13:39:16.000Z
stubs.min/System/Diagnostics/__init___parts/StackFrame.py
hdm-dt-fb/ironpython-stubs
4d2b405eda3ceed186e8adca55dd97c332c6f49d
[ "MIT" ]
null
null
null
stubs.min/System/Diagnostics/__init___parts/StackFrame.py
hdm-dt-fb/ironpython-stubs
4d2b405eda3ceed186e8adca55dd97c332c6f49d
[ "MIT" ]
null
null
null
class StackFrame(object): """ Provides information about a System.Diagnostics.StackFrame,which represents a function call on the call stack for the current thread. StackFrame() StackFrame(fNeedFileInfo: bool) StackFrame(skipFrames: int) StackFrame(skipFrames: int,fNeedFileInfo: bool) StackFrame(fileName: str,lineNumber: int) StackFrame(fileName: str,lineNumber: int,colNumber: int) """ def GetFileColumnNumber(self): """ GetFileColumnNumber(self: StackFrame) -> int Gets the column number in the file that contains the code that is executing. This information is typically extracted from the debugging symbols for the executable. Returns: The file column number,or 0 (zero) if the file column number cannot be determined. """ pass def GetFileLineNumber(self): """ GetFileLineNumber(self: StackFrame) -> int Gets the line number in the file that contains the code that is executing. This information is typically extracted from the debugging symbols for the executable. Returns: The file line number,or 0 (zero) if the file line number cannot be determined. """ pass def GetFileName(self): """ GetFileName(self: StackFrame) -> str Gets the file name that contains the code that is executing. This information is typically extracted from the debugging symbols for the executable. Returns: The file name,or null if the file name cannot be determined. """ pass def GetILOffset(self): """ GetILOffset(self: StackFrame) -> int Gets the offset from the start of the Microsoft intermediate language (MSIL) code for the method that is executing. This offset might be an approximation depending on whether or not the just-in-time (JIT) compiler is generating debugging code. The generation of this debugging information is controlled by the System.Diagnostics.DebuggableAttribute. Returns: The offset from the start of the MSIL code for the method that is executing. """ pass def GetMethod(self): """ GetMethod(self: StackFrame) -> MethodBase Gets the method in which the frame is executing. Returns: The method in which the frame is executing. """ pass def GetNativeOffset(self): """ GetNativeOffset(self: StackFrame) -> int Gets the offset from the start of the native just-in-time (JIT)-compiled code for the method that is being executed. The generation of this debugging information is controlled by the System.Diagnostics.DebuggableAttribute class. Returns: The offset from the start of the JIT-compiled code for the method that is being executed. """ pass def ToString(self): """ ToString(self: StackFrame) -> str Builds a readable representation of the stack trace. Returns: A readable representation of the stack trace. """ pass @staticmethod def __new__(self,*__args): """ __new__(cls: type) __new__(cls: type,fNeedFileInfo: bool) __new__(cls: type,skipFrames: int) __new__(cls: type,skipFrames: int,fNeedFileInfo: bool) __new__(cls: type,fileName: str,lineNumber: int) __new__(cls: type,fileName: str,lineNumber: int,colNumber: int) """ pass OFFSET_UNKNOWN=-1
33.848485
136
0.697105
5fc420cb4f1efbf2153a500e4e1b6552441ee543
421
py
Python
tests/test_optimize.py
LucaCappelletti94/pygifsicle
4f05d0eead3b002295212d985fdbc9ca8e7f4a8f
[ "MIT" ]
42
2019-10-14T11:30:53.000Z
2022-03-28T06:55:20.000Z
tests/test_optimize.py
LucaCappelletti94/pygifsicle
4f05d0eead3b002295212d985fdbc9ca8e7f4a8f
[ "MIT" ]
8
2019-10-13T02:54:19.000Z
2021-10-02T17:47:40.000Z
tests/test_optimize.py
LucaCappelletti94/pygifsicle
4f05d0eead3b002295212d985fdbc9ca8e7f4a8f
[ "MIT" ]
8
2019-09-23T18:59:39.000Z
2022-02-25T22:38:44.000Z
from pygifsicle import optimize import os from pathlib import Path def test_optimize(): optimize("tests/big.gif", "small.gif") optimize("small.gif") os.remove("small.gif") def test_optimize_pathlib(): here = Path(__file__).parent.resolve() source = here / "big.gif" destination = here / "small.gif" optimize(source, destination) optimize(destination) os.remove(destination)
23.388889
42
0.68171
ca1f4cbb6673de1a9b14525f10bf7fcb6f961fc0
3,411
py
Python
input/control/model_control.py
CUrW-SL/distributed_hechms
0ae72d55f5b724dd41a5c322ac96804b4bbf1ee2
[ "MIT" ]
null
null
null
input/control/model_control.py
CUrW-SL/distributed_hechms
0ae72d55f5b724dd41a5c322ac96804b4bbf1ee2
[ "MIT" ]
null
null
null
input/control/model_control.py
CUrW-SL/distributed_hechms
0ae72d55f5b724dd41a5c322ac96804b4bbf1ee2
[ "MIT" ]
null
null
null
from config import CONTROL_TEMPLATE, HEC_HMS_VERSION, CONTROL_FILE_NAME from datetime import datetime import pandas as pd def create_control_file_by_rain_file(model_name, rain_filename): rf_data_frame = pd.read_csv(rain_filename, sep=',') start_datetime = rf_data_frame.iloc[2][0] end_datetime = rf_data_frame.iloc[-1][0] print('start_datetime : ', start_datetime) print('end_datetime : ', end_datetime) control_file_path = CONTROL_FILE_NAME.replace('{MODEL_NAME}', model_name) control_file = CONTROL_TEMPLATE.replace('{MODEL_NAME}', model_name) control_file = control_file.replace('{HEC_HMS_VERSION}', HEC_HMS_VERSION) current_date_time = datetime.now() last_modified_date = current_date_time.strftime('%d %B %Y') last_modified_time = current_date_time.strftime('%H:%M') control_file = control_file.replace('{LAST_MODIFIED_DATE}', last_modified_date) control_file = control_file.replace('{LAST_MODIFIED_TIME}', last_modified_time) start_datetime = datetime.strptime(start_datetime, '%Y-%m-%d %H:%M:%S') end_datetime = datetime.strptime(end_datetime, '%Y-%m-%d %H:%M:%S') start_date = start_datetime.strftime('%d %B %Y') start_time = start_datetime.strftime('%H:%M') end_date = end_datetime.strftime('%d %B %Y') end_time = end_datetime.strftime('%H:%M') control_file = control_file.replace('{START_DATE}', start_date) control_file = control_file.replace('{START_TIME}', start_time) control_file = control_file.replace('{END_DATE}', end_date) control_file = control_file.replace('{END_TIME}', end_time) time_interval = str(int(((end_datetime-start_datetime).total_seconds())/60)) control_file = control_file.replace('{TIME_INTERVAL}', time_interval) with open(control_file_path, 'w') as file: file.write(control_file) file.write('\n\n') file.close() def create_control_file(model_name, start_datetime, end_datetime): control_file_path = CONTROL_FILE_NAME.replace('{MODEL_NAME}', model_name) control_file = CONTROL_TEMPLATE.replace('{MODEL_NAME}', model_name) control_file = control_file.replace('{HEC_HMS_VERSION}', HEC_HMS_VERSION) current_date_time = datetime.now() last_modified_date = current_date_time.strftime('%d %B %Y') last_modified_time = current_date_time.strftime('%H:%M') control_file = control_file.replace('{LAST_MODIFIED_DATE}', last_modified_date) control_file = control_file.replace('{LAST_MODIFIED_TIME}', last_modified_time) start_datetime = datetime.strptime(start_datetime, '%Y-%m-%d %H:%M:%S') end_datetime = datetime.strptime(end_datetime, '%Y-%m-%d %H:%M:%S') start_date = start_datetime.strftime('%d %B %Y') start_time = start_datetime.strftime('%H:%M') end_date = end_datetime.strftime('%d %B %Y') end_time = end_datetime.strftime('%H:%M') control_file = control_file.replace('{START_DATE}', start_date) control_file = control_file.replace('{START_TIME}', start_time) control_file = control_file.replace('{END_DATE}', end_date) control_file = control_file.replace('{END_TIME}', end_time) time_interval = str(int(((end_datetime-start_datetime).total_seconds())/60)) control_file = control_file.replace('{TIME_INTERVAL}', time_interval) with open(control_file_path, 'w') as file: file.write(control_file) file.write('\n\n') file.close()
42.111111
83
0.724421
cb1c34b66902c8e18cc96643bdc3b68a0d02235d
446
py
Python
python/pyglet/label.py
jeremiedecock/snippets
4bd4e7f459eee610d5cf19f845299ca942ff4b64
[ "MIT" ]
23
2015-06-08T13:01:00.000Z
2021-12-30T08:20:04.000Z
python/pyglet/label.py
jeremiedecock/snippets
4bd4e7f459eee610d5cf19f845299ca942ff4b64
[ "MIT" ]
1
2020-10-22T02:36:10.000Z
2020-10-22T02:36:10.000Z
python/pyglet/label.py
jeremiedecock/snippets
4bd4e7f459eee610d5cf19f845299ca942ff4b64
[ "MIT" ]
7
2017-10-31T09:48:14.000Z
2022-01-04T15:59:45.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pyglet window = pyglet.window.Window() label = pyglet.text.Label('Hello, world', font_name='Times New Roman', font_size=36, x=window.width//2, y=window.height//2, anchor_x='center', anchor_y='center') @window.event def on_draw(): window.clear() label.draw() pyglet.app.run()
22.3
64
0.522422
96089c4f8766bc0a9c7adb55e503a4d254135ad7
1,907
py
Python
data/synthia_dataset.py
uta-smile/ASSUDA
e4af3a51846d30529a2b9d6b1d5c383fcd108051
[ "MIT" ]
6
2021-09-11T19:51:17.000Z
2022-02-06T17:31:47.000Z
data/synthia_dataset.py
uta-smile/ASSUDA
e4af3a51846d30529a2b9d6b1d5c383fcd108051
[ "MIT" ]
2
2021-09-09T08:02:09.000Z
2021-12-13T17:23:57.000Z
data/synthia_dataset.py
uta-smile/ASSUDA
e4af3a51846d30529a2b9d6b1d5c383fcd108051
[ "MIT" ]
1
2022-02-07T12:54:58.000Z
2022-02-07T12:54:58.000Z
import os import os.path as osp import numpy as np import random import collections import torch import torchvision from torch.utils import data from PIL import Image class SYNDataSet(data.Dataset): def __init__(self, root, list_path, max_iters=None, crop_size=(321, 321), mean=(128, 128, 128), ignore_label=255): self.root = root self.list_path = list_path self.crop_size = crop_size self.ignore_label = ignore_label self.mean = mean self.img_ids = [i_id.strip()[4:] for i_id in open(list_path)] if not max_iters==None: self.img_ids = self.img_ids * int(np.ceil(float(max_iters) / len(self.img_ids))) self.files = [] self.id_to_trainid = {3: 0, 4: 1, 2: 2, 21: 3, 5: 4, 7: 5, 15: 6, 9: 7, 6: 8, 16: 9, 1: 10, 10: 11, 17: 12, 8: 13, 18: 14, 19: 15, 20: 16, 12: 17, 11: 18} def __len__(self): return len(self.img_ids) def __getitem__(self, index): name = self.img_ids[index] image = Image.open(osp.join(self.root, "RGB/%s" % name)).convert('RGB') label = Image.open(osp.join(self.root, "synthia_mapped_to_cityscapes/%s" % name)) # resize image = image.resize(self.crop_size, Image.BICUBIC) label = label.resize(self.crop_size, Image.NEAREST) image = np.asarray(image, np.float32) label = np.asarray(label, np.float32) # re-assign labels to match the format of Cityscapes label_copy = self.ignore_label * np.ones(label.shape, dtype=np.float32) for k, v in self.id_to_trainid.items(): label_copy[label == k] = v size = image.shape image = image[:, :, ::-1] # change to BGR image -= self.mean image = image.transpose((2, 0, 1)) return image.copy(), label_copy.copy(), np.array(size), name
35.981132
118
0.596224
f8e946685e7e97a87076bbd68c74a37160b98416
1,396
py
Python
server.py
ryzbaka/BoyOfSilence_v2
6975c8bf435c7c56d92d889f51f90b208afe5635
[ "MIT" ]
null
null
null
server.py
ryzbaka/BoyOfSilence_v2
6975c8bf435c7c56d92d889f51f90b208afe5635
[ "MIT" ]
null
null
null
server.py
ryzbaka/BoyOfSilence_v2
6975c8bf435c7c56d92d889f51f90b208afe5635
[ "MIT" ]
null
null
null
import json from flask import Flask,render_template import time import tweepy from textblob import TextBlob import pandas as pd import numpy as np import sys ###API AUTHORIZATION### consumer_key="Ee0lw604kCAuzTbFp3pcn5lck" consumer_secret="uuedTNbrDhmhsI8QBeOeCcEaOxtoe4nXDPDcRd8XkLF67yzjQ1" access_token="857652506079490048-pPDneGr61On9KS4KQ5yWG4wHZCvvdMz" access_token_secret="kZEayyj3UM56Lf9xkk10yNgr8wCod6JXgnu0BueKcN5f7" auth=tweepy.OAuthHandler(consumer_key,consumer_secret) auth.set_access_token(access_token,access_token_secret) api=tweepy.API(auth) ####################### #####ROUTING##### app=Flask(__name__) app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0 @app.route("/") @app.route("/<message>") def get_homepage(message="nothing"): return render_template('index.html',message=message) @app.route("/something<name>") def return_something(name): object=json.dumps({'message':name}) return object @app.route("/sentiment<keyword>") def return_sentiment(keyword): public_tweets=api.search(keyword) sentiment=0 subjectivity=0 for tweet in public_tweets: analysis=TextBlob(tweet.text) sentiment+=analysis.sentiment[0] subjectivity+=analysis.sentiment[1] object={'sentiment':round(sentiment/len(public_tweets),2),'status':'okay'} json_object=json.dumps(object) return json_object ################# app.run(port=5500)
27.372549
78
0.750716
c1ffdb325151b98c75c9c1e82d8d44c5198b11fe
5,709
py
Python
lib/train.py
SudeepSarkar/equilibrium-propagation
ba6d9ee5426445e9ad91c96c816fa5287ff97258
[ "MIT" ]
18
2020-01-07T11:25:45.000Z
2022-01-24T18:25:13.000Z
lib/train.py
SudeepSarkar/equilibrium-propagation
ba6d9ee5426445e9ad91c96c816fa5287ff97258
[ "MIT" ]
null
null
null
lib/train.py
SudeepSarkar/equilibrium-propagation
ba6d9ee5426445e9ad91c96c816fa5287ff97258
[ "MIT" ]
5
2020-06-26T23:37:22.000Z
2021-09-04T12:22:49.000Z
# MIT License # Copyright (c) 2020 Simon Schug, João Sacramento # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. import logging import torch from lib import config def predict_batch(model, x_batch, dynamics, fast_init): """ Compute the softmax prediction probabilities for a given data batch. Args: model: EnergyBasedModel x_batch: Batch of input tensors dynamics: Dictionary containing the keyword arguments for the relaxation dynamics on u fast_init: Boolean to specify if fast feedforward initilization is used for the prediction Returns: Softmax classification probabilities for the given data batch """ # Initialize the neural state variables model.reset_state() # Clamp the input to the test sample, and remove nudging from ouput model.clamp_layer(0, x_batch.view(-1, model.dimensions[0])) model.set_C_target(None) # Generate the prediction if fast_init: model.fast_init() else: model.u_relax(**dynamics) return torch.nn.functional.softmax(model.u[-1].detach(), dim=1) def test(model, test_loader, dynamics, fast_init): """ Evaluate prediction accuracy of an energy-based model on a given test set. Args: model: EnergyBasedModel test_loader: Dataloader containing the test dataset dynamics: Dictionary containing the keyword arguments for the relaxation dynamics on u fast_init: Boolean to specify if fast feedforward initilization is used for the prediction Returns: Test accuracy Mean energy of the model per batch """ test_E, correct, total = 0.0, 0.0, 0.0 for x_batch, y_batch in test_loader: # Prepare the new batch x_batch, y_batch = x_batch.to(config.device), y_batch.to(config.device) # Extract prediction as the output unit with the strongest activity output = predict_batch(model, x_batch, dynamics, fast_init) prediction = torch.argmax(output, 1) with torch.no_grad(): # Compute test batch accuracy, energy and store number of seen batches correct += float(torch.sum(prediction == y_batch.argmax(dim=1))) test_E += float(torch.sum(model.E)) total += x_batch.size(0) return correct / total, test_E / total def train(model, train_loader, dynamics, w_optimizer, fast_init): """ Use equilibrium propagation to train an energy-based model. Args: model: EnergyBasedModel train_loader: Dataloader containing the training dataset dynamics: Dictionary containing the keyword arguments for the relaxation dynamics on u w_optimizer: torch.optim.Optimizer object for the model parameters fast_init: Boolean to specify if fast feedforward initilization is used for the prediction """ for batch_idx, (x_batch, y_batch) in enumerate(train_loader): x_batch, y_batch = x_batch.to(config.device), y_batch.to(config.device) # Reinitialize the neural state variables model.reset_state() # Clamp the input to the training sample model.clamp_layer(0, x_batch.view(-1, model.dimensions[0])) # Free phase if fast_init: # Skip the free phase using fast feed-forward initialization instead model.fast_init() free_grads = [torch.zeros_like(p) for p in model.parameters()] else: # Run free phase until settled to fixed point and collect the free phase derivates model.set_C_target(None) dE = model.u_relax(**dynamics) free_grads = model.w_get_gradients() # Run nudged phase until settled to fixed point and collect the nudged phase derivates model.set_C_target(y_batch) dE = model.u_relax(**dynamics) nudged_grads = model.w_get_gradients() # Optimize the parameters using the contrastive Hebbian style update model.w_optimize(free_grads, nudged_grads, w_optimizer) # Logging key statistics if batch_idx % (len(train_loader) // 10) == 0: # Extract prediction as the output unit with the strongest activity output = predict_batch(model, x_batch, dynamics, fast_init) prediction = torch.argmax(output, 1) # Log energy and batch accuracy batch_acc = float(torch.sum(prediction == y_batch.argmax(dim=1))) / x_batch.size(0) logging.info('{:.0f}%:\tE: {:.2f}\tdE {:.2f}\tbatch_acc {:.4f}'.format( 100. * batch_idx / len(train_loader), torch.mean(model.E), dE, batch_acc))
38.574324
95
0.683833
cb2ebf4ea9fa51ded0a07116a761dc850691bc8f
1,199
py
Python
sudden_death/__init__.py
dev-hato/sudden-death
89fb9827bc67f03822e279704ad6af24f47e8fb0
[ "MIT" ]
null
null
null
sudden_death/__init__.py
dev-hato/sudden-death
89fb9827bc67f03822e279704ad6af24f47e8fb0
[ "MIT" ]
127
2020-07-11T02:25:31.000Z
2022-03-30T03:04:22.000Z
sudden_death/__init__.py
dev-hato/sudden-death
89fb9827bc67f03822e279704ad6af24f47e8fb0
[ "MIT" ]
null
null
null
""" _人人人人人人人_ > 鳩は唐揚げ <  ̄^Y^Y^Y^Y^Y^Y^Y ̄ を作る """ import unicodedata import click import pyperclip def text_len(text: str) -> int: """ 一行の長さを出す """ count = 0 for character in text: count += 2 if unicodedata.east_asian_width(character) in 'FWA' else 1 return count def generator(msg: str) -> str: """ _人人人人人人人_ > 鳩は唐揚げ <  ̄^Y^Y^Y^Y^Y^Y^Y ̄ を作る """ messages = msg.split('\n') length = list(map(text_len, messages)) max_length = max(length) generating = '_人' for _ in range(max_length//2): generating += '人' generating += '人_\n' for leng, message in zip(length, messages): padding = ' ' * ((max_length - leng) // 2) generating += '> ' + padding + message + padding + ' <\n' generating += ' ̄^Y' for _ in range(max_length//2): generating += '^Y' generating += '^Y ̄' return generating @click.command() @click.argument('msg') def cmd(msg: str = "") -> None: """ コマンド """ result = generator(msg) pyperclip.copy(result) click.echo(result) def main() -> None: """ メイン関数 """ cmd() if __name__ == '__main__': main()
16.652778
77
0.538782
b4e937386d47fd01e7f5c1d6f857ed3155f21153
7,926
py
Python
aibg-ai/brainer_layers.py
BalderOdinson/ai-battleground-environment
b5a0a21ee90df113d34ab0f821ab9722007cc25c
[ "MIT" ]
null
null
null
aibg-ai/brainer_layers.py
BalderOdinson/ai-battleground-environment
b5a0a21ee90df113d34ab0f821ab9722007cc25c
[ "MIT" ]
1
2021-09-02T07:58:16.000Z
2021-09-02T07:58:16.000Z
aibg-ai/brainer_layers.py
BalderOdinson/ai-battleground-environment
b5a0a21ee90df113d34ab0f821ab9722007cc25c
[ "MIT" ]
null
null
null
import tensorflow as tf from tensorflow.keras import layers, models, initializers def identity_block(x, f, filters, stage, block): """ Implementation of the identity block as defined in Figure 3 Arguments: x -- input tensor of shape (m, n_H_prev, n_W_prev, n_C_prev) f -- integer, specifying the shape of the middle CONV's window for the main path filters -- python list of integers, defining the number of filters in the CONV layers of the main path stage -- integer, used to name the layers, depending on their position in the network block -- string/character, used to name the layers, depending on their position in the network Returns: x -- output of the identity block, tensor of shape (n_H, n_W, n_C) """ # defining name basis conv_name_base = 'res' + str(stage) + block + '_branch' bn_name_base = 'bn' + str(stage) + block + '_branch' # Retrieve Filters f1, f2, f3 = filters # Save the input value. You'll need this later to add back to the main path. x_shortcut = x # first component of main path x = layers.Conv2D(filters=f1, kernel_size=(1, 1), strides=(1, 1), padding='valid', name=conv_name_base + '2a', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2a')(x) x = layers.Activation('relu')(x) # Second component of main path (≈3 lines) x = layers.Conv2D(filters=f2, kernel_size=(f, f), strides=(1, 1), padding='same', name=conv_name_base + '2b', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2b')(x) x = layers.Activation('relu')(x) # Third component of main path (≈2 lines) x = layers.Conv2D(filters=f3, kernel_size=(1, 1), strides=(1, 1), padding='valid', name=conv_name_base + '2c', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2c')(x) # Final step: Add shortcut value to main path, and pass it through a RELU activation (≈2 lines) x = layers.Add()([x, x_shortcut]) x = layers.Activation('relu')(x) return x def convolutional_block(x, f, filters, stage, block, s=2): """ Implementation of the convolutional block as defined in figure 4 Arguments: x -- input tensor of shape (m, n_H_prev, n_W_prev, n_C_prev) f -- integer, specifying the shape of the middle CONV's window for the main path filters -- python list of integers, defining the number of filters in the CONV layers of the main path stage -- integer, used to name the layers, depending on their position in the network block -- string/character, used to name the layers, depending on their position in the network s -- Integer, specifying the stride to be used Returns: x -- output of the convolutional block, tensor of shape (n_H, n_W, n_C) """ # defining name basis conv_name_base = 'res' + str(stage) + block + '_branch' bn_name_base = 'bn' + str(stage) + block + '_branch' # Retrieve filters f1, f2, f3 = filters # Save the input value x_shortcut = x # MAIN PATH # first component of main path x = layers.Conv2D(f1, (1, 1), strides=(s, s), name=conv_name_base + '2a', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2a')(x) x = layers.Activation('relu')(x) # Second component of main path (≈3 lines) x = layers.Conv2D(filters=f2, kernel_size=(f, f), strides=(1, 1), padding='same', name=conv_name_base + '2b', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2b')(x) x = layers.Activation('relu')(x) # Third component of main path (≈2 lines) x = layers.Conv2D(filters=f3, kernel_size=(1, 1), strides=(1, 1), padding='valid', name=conv_name_base + '2c', kernel_initializer=initializers.glorot_uniform(seed=0))(x) x = layers.BatchNormalization(axis=3, name=bn_name_base + '2c')(x) # SHORTCUT PATH (≈2 lines) x_shortcut = layers.Conv2D(filters=f3, kernel_size=(1, 1), strides=(s, s), padding='valid', name=conv_name_base + '1', kernel_initializer=initializers.glorot_uniform(seed=0))(x_shortcut) x_shortcut = layers.BatchNormalization(axis=3, name=bn_name_base + '1')(x_shortcut) # Final step: Add shortcut value to main path, and pass it through a RELU activation (≈2 lines) x = layers.Add()([x, x_shortcut]) x = layers.Activation('relu')(x) return x def conv2d_map_block(input_layer, padding): x = layers.ZeroPadding2D(padding, name='crop_map')(input_layer) x = layers.Conv2D(8, (5, 5), (2, 2), name='conv2d_map')(x) x = layers.BatchNormalization(name='batchnorm_map')(x) x = layers.MaxPool2D((2, 2))(x) x = convolutional_block(x, 3, [8, 8, 16], 2, 'm_a', s=1) x = identity_block(x, 3, [8, 8, 16], 2, 'm_b') x = identity_block(x, 3, [8, 8, 16], 2, 'm_c') x = convolutional_block(x, 3, [16, 16, 32], 3, 'm_a', s=2) x = identity_block(x, 3, [16, 16, 32], 3, 'm_b') x = identity_block(x, 3, [16, 16, 32], 3, 'm_c') x = identity_block(x, 3, [16, 16, 32], 3, 'm_d') x = convolutional_block(x, 3, [32, 32, 64], 4, 'm_a', s=2) x = identity_block(x, 3, [32, 32, 64], 4, 'm_b') x = identity_block(x, 3, [32, 32, 64], 4, 'm_c') x = identity_block(x, 3, [32, 32, 64], 4, 'm_d') x = convolutional_block(x, 3, [64, 64, 64], 5, 'm_a', s=2) x = identity_block(x, 3, [64, 64, 64], 5, 'm_b') x = identity_block(x, 3, [64, 64, 64], 5, 'm_c') x = identity_block(x, 3, [64, 64, 64], 5, 'm_d') return layers.AveragePooling2D((2, 2))(x) def conv2d_stats_block(input_layer, cropping, stats_block): x = layers.Cropping2D(cropping, name='crop_' + stats_block)(input_layer) x = layers.Conv2D(8, (5, 5), (2, 2), name='conv2d_' + stats_block)(x) x = layers.BatchNormalization(name='batchnorm_' + stats_block)(x) x = layers.MaxPool2D((2, 2))(x) x = convolutional_block(x, 3, [8, 8, 16], 2, stats_block + '_a', s=1) x = identity_block(x, 3, [8, 8, 16], 2, stats_block + '_b') x = identity_block(x, 3, [8, 8, 16], 2, stats_block + '_c') x = convolutional_block(x, 3, [16, 16, 32], 3, stats_block + '_a', s=2) x = identity_block(x, 3, [16, 16, 32], 3, stats_block + '_b') x = identity_block(x, 3, [16, 16, 32], 3, stats_block + '_c') x = identity_block(x, 3, [16, 16, 32], 3, stats_block + '_d') x = convolutional_block(x, 3, [32, 32, 64], 4, stats_block + '_a', s=2) x = identity_block(x, 3, [32, 32, 64], 4, stats_block + '_b') x = identity_block(x, 3, [32, 32, 64], 4, stats_block + '_c') x = identity_block(x, 3, [32, 32, 64], 4, stats_block + '_d') return layers.AveragePooling2D((3, 3))(x) def brainer_net_V1(input_shape=None): if input_shape is None: input_shape = [200, 355, 3] height = input_shape[0] width = input_shape[1] diff_w_h = width - height up = int(diff_w_h / 2) down = up if up * 2 == diff_w_h else up + 1 inputs = layers.Input(shape=input_shape) x = conv2d_stats_block(inputs, ((0, 0), (0, diff_w_h)), stats_block='l_s') y = conv2d_map_block(inputs, ((up, down), (0, 0))) z = conv2d_stats_block(inputs, ((0, 0), (diff_w_h, 0)), stats_block='r_s') out = layers.Add()([x, y, z]) return models.Model(inputs, layers.AveragePooling2D((2, 2))(out), name='brainer_net_V1') class Sampling(layers.Layer): def call(self, inputs, **kwargs): mean, log_var = inputs epsilon = tf.keras.backend.random_normal(tf.shape(mean)) return mean + tf.exp(0.5 * log_var) * epsilon
43.311475
114
0.633485
32eff85ea20f590ad0222dde4f598221822533c1
28,315
py
Python
dcos_test_utils/dcos_api.py
Klarrio/dcos-test-utils
f45f0938582fc166354a96c80ead0ea716adf3f3
[ "Apache-2.0" ]
8
2018-02-01T20:32:18.000Z
2020-01-23T17:02:16.000Z
dcos_test_utils/dcos_api.py
Klarrio/dcos-test-utils
f45f0938582fc166354a96c80ead0ea716adf3f3
[ "Apache-2.0" ]
52
2017-07-27T16:51:07.000Z
2020-09-28T11:18:52.000Z
dcos_test_utils/dcos_api.py
Klarrio/dcos-test-utils
f45f0938582fc166354a96c80ead0ea716adf3f3
[ "Apache-2.0" ]
22
2017-07-21T16:07:03.000Z
2022-03-01T13:43:56.000Z
""" Utilities for interacting with a DC/OS instance via REST API Most DC/OS deployments will have auth enabled, so this module includes DcosUser and DcosAuth to be attached to a DcosApiSession. Additionally, it is sometimes necessary to query specific nodes within a DC/OS cluster, so there is ARNodeApiClientMixin to allow querying nodes without boilerplate to set the correct port and scheme. """ import copy import logging import os from typing import List, Optional import requests import retrying from dcos_test_utils import ( diagnostics, jobs, marathon, package, helpers ) log = logging.getLogger(__name__) class DcosUser: """ Representation of a DC/OS user used for authentication :param credentials: representation of the JSON used to log in :type credentials: dict """ def __init__(self, credentials: dict): self.credentials = credentials self.auth_token = None self.auth_cookie = None @property def auth_header(self) -> dict: """ Property for the auth header provided at authentication time :returns: representation of HTTP headers to use :rtype: dict """ return {'Authorization': 'token={}'.format(self.auth_token)} class DcosAuth(requests.auth.AuthBase): """ Child of AuthBase for specifying how to handle DC/OS auth per request :param auth_token: token generated by authenticating with access control :type auth_token: str """ def __init__(self, auth_token: str): self.auth_token = auth_token def __call__(self, request): request.headers['Authorization'] = 'token={}'.format(self.auth_token) return request class Exhibitor(helpers.RetryCommonHttpErrorsMixin, helpers.ApiClientSession): """ Exhibitor can have a password set, in which case a different auth model is needed :param default_url: Url object for the exhibitor instance :type default_url: helpers.Url :param session: optional session for bootstrapping this session (a new one is created otherwise) :type session: requests.Session :param exhibitor_admin_password: password for exhibitor (not always set) :type exhibitor_admin_password: str """ def __init__(self, default_url: helpers.Url, session: Optional[requests.Session]=None, exhibitor_admin_password: Optional[str]=None): super().__init__(default_url) if session is not None: self.session = session if exhibitor_admin_password is not None: # Override auth to use HTTP basic auth with the provided admin password. self.session.auth = requests.auth.HTTPBasicAuth('admin', exhibitor_admin_password) class DcosApiSession(helpers.ARNodeApiClientMixin, helpers.RetryCommonHttpErrorsMixin, helpers.ApiClientSession): """Proxy class for DC/OS clusters. If any of the host lists (masters, slaves, public_slaves) are provided, the wait_for_dcos function of this class will wait until provisioning is complete. If these lists are not provided, then there is no ground truth and the cluster will be assumed the be in a completed state. :param dcos_url: address for the DC/OS web UI. :type dcos_url: helpers.Url :param masters: list of Mesos master advertised IP addresses. :type masters: list :param slaves: list of Mesos slave/agent advertised IP addresses. :type slaves: list :param public_slaves: list of public Mesos slave/agent advertised IP addresses. :type public_slaves: list :param auth_user: use this user's auth for all requests. Note: user must be authenticated explicitly or call self.wait_for_dcos() :type auth_user: DcosUser """ def __init__( self, dcos_url: str, masters: Optional[List[str]], slaves: Optional[List[str]], public_slaves: Optional[List[str]], auth_user: Optional[DcosUser], exhibitor_admin_password: Optional[str]=None): super().__init__(helpers.Url.from_string(dcos_url)) self.master_list = masters self.slave_list = slaves self.public_slave_list = public_slaves self.auth_user = auth_user self.exhibitor_admin_password = exhibitor_admin_password @classmethod def create(cls): """ Uses environment variables defined in :func:`DcosApiSession.get_args_from_env` to create a new DcosApiSession instance """ api = cls(**cls.get_args_from_env()) api.login_default_user() return api @staticmethod def get_args_from_env() -> dict: """ This method will use environment variables to generate the arguments necessary to initialize a :class:`DcosApiSession` Environment Variables: * **DCOS_DNS_ADDRESS**: the URL for the DC/OS cluster to be used. If not set, leader.mesos will be used * **DCOS_ACS_TOKEN**: authentication token that can be taken from dcos-cli after login in order to authenticate If not given, a hard-coded dummy login token will be used to create the authentication token. * **MASTER_HOSTS**: a complete list of the expected master IPs (optional) * **SLAVE_HOSTS**: a complete list of the expected private slaves IPs (optional) * **PUBLIC_SLAVE_HOSTS**: a complete list of the public slave IPs (optional) :returns: arguments to initialize a DcosApiSesssion :rtype: dict """ dcos_acs_token = os.getenv('DCOS_ACS_TOKEN') if dcos_acs_token is None: auth_user = DcosUser(helpers.CI_CREDENTIALS) else: auth_user = DcosUser(None) auth_user.auth_token = dcos_acs_token masters = os.getenv('MASTER_HOSTS') slaves = os.getenv('SLAVE_HOSTS') windows_slaves = os.getenv('WINDOWS_HOSTS') public_slaves = os.getenv('PUBLIC_SLAVE_HOSTS') windows_public_slaves = os.getenv('WINDOWS_PUBLIC_HOSTS') if windows_slaves: slaves = ",".join((slaves, windows_slaves)) if windows_public_slaves: public_slaves = ",".join((public_slaves, windows_public_slaves)) return { 'auth_user': auth_user, 'dcos_url': os.getenv('DCOS_DNS_ADDRESS', 'http://leader.mesos'), 'masters': masters.split(',') if masters is not None else None, 'slaves': slaves.split(',') if slaves is not None else [], 'public_slaves': public_slaves.split(',') if public_slaves is not None else []} @property def masters(self) -> List[str]: """ Property which returns a sorted list of master IP strings for this cluster """ return sorted(self.master_list) @property def slaves(self) -> List[str]: """ Property which returns a sorted list of private slave IP strings for this cluster """ return sorted(self.slave_list) @property def public_slaves(self) -> List[str]: """ Property which retruns a sorted list of public slave IP strings for this cluster """ return sorted(self.public_slave_list) @property def all_slaves(self) -> List[str]: """ Property which returns a sorted list of all slave IP strings for this cluster """ return sorted(self.slaves + self.public_slaves) def set_node_lists_if_unset(self): """ Sets the expected cluster topology to be the observed cluster topology from exhibitor and mesos. I.E. if masters, slave, or public_slaves were not provided, accept whatever is currently available """ if self.master_list is None: log.debug('Master list not provided, setting from exhibitor...') r = self.get('/exhibitor/exhibitor/v1/cluster/list') r.raise_for_status() self.master_list = sorted(r.json()['servers']) log.info('Master list set as: {}'.format(self.masters)) if self.slave_list is not None and self.public_slave_list is not None: return r = self.get('/mesos/slaves') r.raise_for_status() slaves_json = r.json()['slaves'] if self.slave_list is None: log.debug('Private slave list not provided; fetching from mesos...') self.slave_list = sorted( [s['hostname'] for s in slaves_json if s['attributes'].get('public_ip') != 'true']) log.info('Private slave list set as: {}'.format(self.slaves)) if self.public_slave_list is None: log.debug('Public slave list not provided; fetching from mesos...') self.public_slave_list = sorted( [s['hostname'] for s in slaves_json if s['attributes'].get('public_ip') == 'true']) log.info('Public slave list set as: {}'.format(self.public_slaves)) @retrying.retry(wait_fixed=5000, stop_max_delay=120 * 1000) def login_default_user(self): """retry default user login because in some deployments, the login endpoint might not be routable immediately after Admin Router is up. We wait 5 seconds between retries to avoid DoS-ing the IAM. Raises: requests.HTTPException: In case the login fails due to wrong username or password of the default user. """ if self.auth_user is None: log.info('No credentials are defined') return if self.auth_user.auth_token is not None: log.info('Already logged in as default user') self.session.auth = DcosAuth(self.auth_user.auth_token) return log.info('Attempting default user login') # Explicitly request the default user authentication token by logging in. r = self.post('/acs/api/v1/auth/login', json=self.auth_user.credentials, auth=None) r.raise_for_status() log.info('Received authentication token: {}'.format(r.json())) self.auth_user.auth_token = r.json()['token'] self.auth_user.auth_cookie = r.cookies['dcos-acs-auth-cookie'] log.info('Login successful') # Set requests auth self.session.auth = DcosAuth(self.auth_user.auth_token) @retrying.retry(wait_fixed=1000, stop_max_delay=5*60*1000, retry_on_result=lambda ret: ret is False, retry_on_exception=lambda x: False) def _wait_for_marathon_up(self): r = self.get('/marathon/v2/info') # http://mesosphere.github.io/marathon/api-console/index.html # 200 at /marathon/v2/info indicates marathon is up. if r.status_code == 200: log.info("Marathon is up.") return True else: msg = "Waiting for Marathon, resp code is: {}" log.info(msg.format(r.status_code)) return False @retrying.retry(wait_fixed=1000, stop_max_delay=5*60*1000) def _wait_for_zk_quorum(self): """Queries exhibitor to ensure all master ZKs have joined """ r = self.get('/exhibitor/exhibitor/v1/cluster/status') if not r.ok: log.warning('Exhibitor status not available') r.raise_for_status() status = r.json() log.info('Exhibitor cluster status: {}'.format(status)) zk_nodes = sorted([n['hostname'] for n in status]) # zk nodes will be private but masters can be public assert len(zk_nodes) == len(self.masters), 'ZooKeeper has not formed the expected quorum' @retrying.retry(wait_fixed=1000, stop_max_delay=5*60*1000, retry_on_result=lambda ret: ret is False, retry_on_exception=lambda x: False) def _wait_for_slaves_to_join(self): r = self.get('/mesos/master/slaves') if r.status_code != 200: msg = "Mesos master returned status code {} != 200 " msg += "continuing to wait..." log.info(msg.format(r.status_code)) return False data = r.json() # Check that there are all the slaves the test knows about. They are all # needed to pass the test. num_slaves = len(data['slaves']) if num_slaves >= len(self.all_slaves): msg = "Sufficient ({} >= {}) number of slaves have joined the cluster" log.info(msg.format(num_slaves, self.all_slaves)) return True else: msg = "Current number of slaves: {} < {}, continuing to wait..." log.info(msg.format(num_slaves, self.all_slaves)) return False @retrying.retry(wait_fixed=1000, stop_max_delay=5*60*1000, retry_on_result=lambda ret: ret is False, retry_on_exception=lambda x: False) def _wait_for_adminrouter_up(self): try: # Yeah, we can also put it in retry_on_exception, but # this way we will loose debug messages self.get('/') except requests.ConnectionError as e: msg = "Cannot connect to nginx, error string: '{}', continuing to wait" log.info(msg.format(e)) return False else: log.info("Nginx is UP!") return True # Retry if returncode is False, do not retry on exceptions. # We don't want to infinite retries while waiting for agent endpoints, # when we are retrying on both HTTP 502 and 404 statuses # Added a stop_max_attempt to 60. @retrying.retry(wait_fixed=2000, retry_on_result=lambda r: r is False, retry_on_exception=lambda _: False, stop_max_attempt_number=60) def _wait_for_srouter_slaves_endpoints(self): # Get currently known agents. This request is served straight from # Mesos (no AdminRouter-based caching is involved). r = self.get('/mesos/master/slaves') # If the agent has restarted, the mesos endpoint can give 502 # for a brief moment. if r.status_code == 502: return False assert r.status_code == 200 data = r.json() # only check against the slaves we expect to be in the cluster # so we can check that cluster has returned after a failure # in which case will will have new slaves and dead slaves slaves_ids = sorted(x['id'] for x in data['slaves'] if x['hostname'] in self.all_slaves) for slave_id in slaves_ids: in_progress_status_codes = ( # AdminRouter's slave endpoint internally uses cached Mesos # state data. That is, slave IDs of just recently joined # slaves can be unknown here. For those, this endpoint # returns a 404. Retry in this case, until this endpoint # is confirmed to work for all known agents. 404, # During a node restart or a DC/OS upgrade, this # endpoint returns a 502 temporarily, until the agent has # started up and the Mesos agent HTTP server can be reached. 502, # We have seen this endpoint return 503 with body # b'Agent has not finished recovery' on a cluster which # later became healthy. 503, ) uri = '/slave/{}/slave%281%29/state'.format(slave_id) r = self.get(uri) if r.status_code in in_progress_status_codes: return False assert r.status_code == 200, ( 'Expecting status code 200 for GET request to {uri} but got ' '{status_code} with body {content}' ).format(uri=uri, status_code=r.status_code, content=r.content) data = r.json() assert "id" in data assert data["id"] == slave_id @retrying.retry(wait_fixed=2000, stop_max_delay=5*60*1000, retry_on_result=lambda r: r is False, retry_on_exception=lambda _: False) def _wait_for_metronome(self): # Although this is named `wait_for_metronome`, some of the waiting # done in this function is, implicitly, for Admin Router. r = self.get('/service/metronome/v1/jobs') expected_error_codes = { 404: ('It may be the case that Admin Router is returning a 404 ' 'despite the Metronome service existing because it uses a cache. ' 'This cache is updated periodically.'), 504: ('Metronome is returning a Gateway Timeout Error.' 'It may be that the service is still starting up.') } log.info('Metronome status code:') log.info(r.status_code) log.info('Metronome response body:') log.info(r.text) if r.status_code in expected_error_codes or r.status_code >= 500: error_message = expected_error_codes.get(r.status_code) if error_message: log.info(error_message) log.info('Continuing to wait for Metronome') return False assert r.status_code == 200, "Expecting status code 200 for Metronome but got {} with body {}"\ .format(r.status_code, r.content) @retrying.retry(wait_fixed=2000, retry_on_result=lambda r: r is False, retry_on_exception=lambda _: False) def _wait_for_all_healthy_services(self): r = self.health.get('/units') r.raise_for_status() all_healthy = True for unit in r.json()['units']: if unit['health'] != 0: log.info("{} service health: {}".format(unit['id'], unit['health'])) all_healthy = False return all_healthy def wait_for_dcos(self): """ This method will wait for: * cluster endpoints to come up immediately after deployment has completed * authentication with DC/OS to be successful * all DC/OS services becoming healthy * all explicitly declared nodes register to register """ self._wait_for_adminrouter_up() self.login_default_user() wait_for_hosts = os.getenv('WAIT_FOR_HOSTS', 'true') == 'true' master_list_set = self.master_list is not None slave_list_set = self.slave_list is not None public_slave_list_set = self.public_slave_list is not None node_lists_set = all([master_list_set, slave_list_set, public_slave_list_set]) if wait_for_hosts and not node_lists_set: raise Exception( 'This cluster is set to wait for hosts, however, not all host lists ' 'were supplied. Please set all three environment variables of MASTER_HOSTS, ' 'SLAVE_HOSTS, and PUBLIC_SLAVE_HOSTS to the appropriate cluster IPs (comma separated). ' 'Alternatively, set WAIT_FOR_HOSTS=false in the environment to use whichever hosts ' 'are currently registered.') self.set_node_lists_if_unset() self._wait_for_marathon_up() self._wait_for_zk_quorum() self._wait_for_slaves_to_join() self._wait_for_srouter_slaves_endpoints() self._wait_for_metronome() self._wait_for_all_healthy_services() def copy(self): """ Create a new client session from this one without cookies, with the authentication intact. """ new = copy.deepcopy(self) new.session.cookies.clear() return new def get_user_session(self, user: DcosUser): """Returns a copy of this client session with a new user :param user: The user with which the new DcosApiSession will authenticate (can be None) :type user: DcosUser """ new = self.copy() new.session.auth = None new.auth_user = None if user is not None: new.auth_user = user new.login_default_user() return new @property def exhibitor(self): """ Property which creates a new :class:`Exhibitor` """ if self.exhibitor_admin_password is None: # No basic HTTP auth. Access Exhibitor via the adminrouter. default_url = self.default_url.copy(path='exhibitor') else: # Exhibitor is protected with HTTP basic auth, which conflicts with adminrouter's auth. We must bypass # the adminrouter and access Exhibitor directly. default_url = helpers.Url.from_string('http://{}:8181'.format(self.masters[0])) return Exhibitor( default_url=default_url, session=self.copy().session, exhibitor_admin_password=self.exhibitor_admin_password) @property def marathon(self): """ Property which returns a :class:`dcos_test_utils.marathon.Marathon` derived from this session """ return marathon.Marathon( default_url=self.default_url.copy(path='marathon'), session=self.copy().session) @property def metronome(self): """ Property which returns a copy of this session where all requests are prefaced with /service/metronome """ new = self.copy() new.default_url = self.default_url.copy(path='service/metronome') return new @property def jobs(self): """ Property which returns a :class:`dcos_test_utils.jobs.Jobs` derived from this session """ return jobs.Jobs( default_url=self.default_url.copy(path='service/metronome'), session=self.copy().session) @property def cosmos(self): """ Property which returns a :class:`dcos_test_utils.package.Cosmos` derived from this session """ return package.Cosmos( default_url=self.default_url.copy(path="package"), session=self.copy().session) @property def health(self): """ Property which returns a :class:`dcos_test_utils.diagnostics.Diagnostics` derived from this session """ health_url = self.default_url.copy(query='cache=0', path='system/health/v1') return diagnostics.Diagnostics( health_url, self.masters, self.all_slaves, session=self.copy().session) @property def logs(self): """ Property which returns a copy of this session where all requests are prefaced with /system/v1/logs """ new = self.copy() new.default_url = self.default_url.copy(path='system/v1/logs') return new @property def metrics(self): """ Property which returns a copy of this session where all requests are prefaced with /system/v1/metrics/v0 """ new = self.copy() new.default_url = self.default_url.copy(path='/system/v1/metrics/v0') return new def metronome_one_off( self, job_definition: dict, timeout: int=300, ignore_failures: bool=False) -> None: """Run a job on metronome and block until it returns success :param job_definition: metronome job JSON to be triggered once :type job_definition: dict :param timeout: how long to wait (in seconds) for the job to complete :type timeout: int :param ignore_failures: if True, failures will not block or raise an exception :type ignore_failures: bool """ _jobs = self.jobs job_id = job_definition['id'] log.info('Creating metronome job: ' + repr(job_definition)) _jobs.create(job_definition) log.info('Starting metronome job') status, run, job = _jobs.run(job_id, timeout=timeout) if not status: log.info('Job failed, run info: {}'.format(run)) if not ignore_failures: raise Exception('Metronome job failed!: ' + repr(job)) else: log.info('Metronome one-off successful') log.info('Deleting metronome one-off') _jobs.destroy(job_id) def mesos_sandbox_directory(self, slave_id: str, framework_id: str, task_id: str) -> str: """ Gets the mesos sandbox directory for a specific task :param slave_id: slave ID to pull sandbox from :type slave_id: str :param framework_id: framework_id to pull sandbox from :type frameowork_id: str :param task_id: task ID to pull directory sandbox from :type task_id: str :returns: the directory of the sandbox :rtype: str """ r = self.get('/agent/{}/state'.format(slave_id)) r.raise_for_status() agent_state = r.json() try: framework = next(f for f in agent_state['frameworks'] if f['id'] == framework_id) except StopIteration: raise Exception('Framework {} not found on agent {}'.format(framework_id, slave_id)) try: executor = next(e for e in framework['executors'] if e['id'] == task_id) except StopIteration: raise Exception('Executor {} not found on framework {} on agent {}'.format(task_id, framework_id, slave_id)) return executor['directory'] def mesos_sandbox_file(self, slave_id: str, framework_id: str, task_id: str, filename: str) -> str: """ Gets a specific file from a task sandbox and returns the text content :param slave_id: ID of the slave running the task :type slave_id: str :param framework_id: ID of the framework of the task :type framework_id: str :param task_id: ID of the task :type task_id: str :param filename: filename in the sandbox :type filename: str :returns: sandbox text contents """ r = self.get( '/agent/{}/files/download'.format(slave_id), params={'path': self.mesos_sandbox_directory(slave_id, framework_id, task_id) + '/' + filename} ) r.raise_for_status() return r.text def mesos_pod_sandbox_directory(self, slave_id: str, framework_id: str, executor_id: str, task_id: str) -> str: """ Gets the mesos sandbox directory for a specific task in a pod which is currently running :param slave_id: slave ID to pull sandbox from :type slave_id: str :param framework_id: framework_id to pull sandbox from :type frameowork_id: str :param executor_id: executor ID to pull directory sandbox from :type executor_id: str :param task_id: task ID to pull directory sandbox from :type task_id: str :returns: the directory of the sandbox :rtype: str """ return '{}/tasks/{}'.format(self.mesos_sandbox_directory(slave_id, framework_id, executor_id), task_id) def mesos_pod_sandbox_file( self, slave_id: str, framework_id: str, executor_id: str, task_id: str, filename: str) -> str: """ Gets a specific file from a currently-running pod's task sandbox and returns the text content :param slave_id: ID of the slave running the task :type slave_id: str :param framework_id: ID of the framework of the task :type framework_id: str :param executor_id: ID of the executor :type executor_id: str :param task_id: ID of the task :type task_id: str :param filename: filename in the sandbox :type filename: str :returns: sandbox text contents """ r = self.get( '/agent/{}/files/download'.format(slave_id), params={'path': self.mesos_pod_sandbox_directory( slave_id, framework_id, executor_id, task_id) + '/' + filename} ) r.raise_for_status() return r.text def get_version(self) -> str: """ Queries the DC/OS version endpoint to get DC/OS version :returns: version for DC/OS """ version_metadata = self.get('/dcos-metadata/dcos-version.json') version_metadata.raise_for_status() data = version_metadata.json() return data["version"]
41.155523
120
0.627689
b2fa86b24974f79c03e8b40da42d1bc2de292b02
4,258
py
Python
PhotographyWebsite/settings.py
antonarnaudov/Django-Framework
ada16a0610c8a522c98fae6b6287ae2a3fa55c32
[ "MIT" ]
null
null
null
PhotographyWebsite/settings.py
antonarnaudov/Django-Framework
ada16a0610c8a522c98fae6b6287ae2a3fa55c32
[ "MIT" ]
null
null
null
PhotographyWebsite/settings.py
antonarnaudov/Django-Framework
ada16a0610c8a522c98fae6b6287ae2a3fa55c32
[ "MIT" ]
null
null
null
""" Django settings for PhotographyWebsite project. Generated by 'django-admin startproject' using Django 3.1.1. For more information on this file, see https://docs.djangoproject.com/en/3.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.1/ref/settings/ """ from os.path import join from pathlib import Path # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'x&4x9@x^m_hzvwa2)80z3q=kg@3@k%nw*g+h1feq1qe04shfb2' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['*'] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'drf_yasg', 'bootstrap4', 'rest_framework', 'django_filters', 'Photos', 'Auth', 'Api' ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'PhotographyWebsite.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [BASE_DIR / 'templates'], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', 'django.template.context_processors.media' ], }, }, ] WSGI_APPLICATION = 'PhotographyWebsite.wsgi.application' # Database # https://docs.djangoproject.com/en/3.1/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.postgresql', 'NAME': 'PhotographyWebsite_db', 'USER': 'postgres', 'PASSWORD': '1234', 'HOST': 'localhost', 'PORT': '5432', } } # Password validation # https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.1/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = '' STATICFILES_DIRS = [ join(BASE_DIR / 'static'), ] MEDIA_URL = '/media/' MEDIA_ROOT = join(BASE_DIR, 'media/') LOGIN_URL = '/auth/login' REST_FRAMEWORK = { 'DEFAULT_FILTER_BACKENDS': ['django_filters.rest_framework.DjangoFilterBackend'], 'DEFAULT_AUTHENTICATION_CLASSES': ( 'rest_framework.authentication.SessionAuthentication', 'rest_framework.authentication.TokenAuthentication', ), # Setting default pagination class that will appear on every list-view 'DEFAULT_PAGINATION_CLASS': 'rest_framework.pagination.CursorPagination', 'PAGE_SIZE': 3, # Parser is used for Swagger adding serializer fields in autogen documentation # 'DEFAULT_PARSER_CLASSES': [ # 'rest_framework.parsers.FormParser', # 'rest_framework.parsers.MultiPartParser' # ] }
26.949367
91
0.694223
e41e13eb35dd8eea5c791746108165dbd0767621
5,053
py
Python
server/apps/staff/app_specific/shipping/forms.py
iotile/iotile_cloud
9dc65ac86d3a730bba42108ed7d9bbb963d22ba6
[ "MIT" ]
null
null
null
server/apps/staff/app_specific/shipping/forms.py
iotile/iotile_cloud
9dc65ac86d3a730bba42108ed7d9bbb963d22ba6
[ "MIT" ]
null
null
null
server/apps/staff/app_specific/shipping/forms.py
iotile/iotile_cloud
9dc65ac86d3a730bba42108ed7d9bbb963d22ba6
[ "MIT" ]
null
null
null
from django import forms from django.contrib.auth import get_user_model from django.db.models import Q from django.forms import ModelForm from django.template.defaultfilters import slugify from crispy_forms.bootstrap import FieldWithButtons from crispy_forms.helper import FormHelper from crispy_forms.layout import HTML, Div, Layout, Submit from apps.org.models import Org from apps.project.models import Project from apps.projecttemplate.models import ProjectTemplate from apps.staff.forms import GetDeviceForm user_model = get_user_model() class NewShippingOrgForm(ModelForm): short_name = forms.CharField(label='Short Name', max_length=15, required=False, help_text='Leave empty if no support account is needed') owner = forms.ChoiceField( label='Create organization as: ', help_text='For new organizations, choice to create new account', choices=[], required=True ) class Meta: model = Org fields = ['short_name', 'name', 'owner',] def __init__(self, *args, **kwargs): self.helper = FormHelper() self.helper.form_method = 'post' self.helper.layout = Layout( Div( Div('name', css_class='col-sm-8, col-xs-12'), Div('short_name', css_class='col-sm-4, col-xs-12'), css_class='row' ), 'owner', HTML('<br>'), ) self.helper.add_input(Submit('submit', 'Create New Company', css_class='btn btn-success submit')) super(NewShippingOrgForm, self).__init__(*args, **kwargs) self.fields['owner'].choices = [ ('new', 'Create new support account'), ('user', 'Use my account as owner') ] users = user_model.objects.all().order_by('username') for user in users: self.fields['owner'].choices.append((user.slug, user.email)) def clean_short_name(self): short_name = self.cleaned_data.get('short_name') # Check that username is not used already if self.instance: username = 'support-{}'.format(slugify(short_name)) qs = user_model.objects.filter(username=username) if qs.exists(): raise forms.ValidationError('Support account {} already exists'.format(username)) return short_name class NewShippingProjectForm(ModelForm): class Meta: model = Project fields = ['name', 'org'] def __init__(self, *args, **kwargs): self.helper = FormHelper() self.helper.form_method = 'post' self.helper.add_input(Submit('submit', 'Submit', css_class='btn btn-success btn-block submit')) super(NewShippingProjectForm, self).__init__(*args, **kwargs) class ShippingDeviceClaimForm(GetDeviceForm): project = forms.ModelChoiceField( label='Claim into shipping project:', queryset=Project.objects.filter( project_template__in=ProjectTemplate.objects.filter(name__contains='Shipping') ).order_by('org__name', 'name'), required=True ) def __init__(self, *args, **kwargs): description = """ <p> After checking that the device can be claimed, and is compatible with a Shipping App, the device will be claimed and set to inactive. </p> """ self.helper = FormHelper() self.helper.form_method = 'post' self.helper.layout = Layout( HTML('<h3 style="color:blue"><i class="fa fa-info" aria-hidden="true"></i> Make sure you understand the Claim Process</h3>'), HTML('<br>'), HTML(description), HTML('<br>'), 'device_id', HTML('<p> *Use regular integers (e.g. "10") or hex format (e.g. "0xa")</p>'), 'project', HTML('<br>') ) self.helper.add_input(Submit('submit', 'Claim Device', css_class='btn btn-success btn-block submit')) super(GetDeviceForm, self).__init__(*args, **kwargs) class ShippingDeviceTimestampFixForm(GetDeviceForm): def __init__(self, *args, **kwargs): description = """ <p> If the device rebooted during or after the trip ended, it is possible that the workers were unable to fix up all timestamps correctly. </p> <p> This form will schedule a worker task to use the Start/End times recorded by the Phone to fix all data and event timestamps </p> """ self.helper = FormHelper() self.helper.form_method = 'post' self.helper.layout = Layout( HTML(description), HTML('<br>'), 'device_id', HTML('<p> *Use regular integers (e.g. "10") or hex format (e.g. "0xa")</p>'), HTML('<br>') ) self.helper.add_input(Submit('submit', 'Schedule Fix', css_class='btn btn-success btn-block submit')) super(ShippingDeviceTimestampFixForm, self).__init__(*args, **kwargs)
35.584507
137
0.612903
92d44439aa8a23b8a9b65b42ccac7b949059113c
1,796
py
Python
deepthinking/data_analysis/get_names_and_info.py
aks2203/deep-thinking
089fc5d04a0997ccdbad601b3e025f547a8b6327
[ "MIT" ]
19
2022-02-11T18:49:46.000Z
2022-03-13T18:40:18.000Z
deepthinking/data_analysis/get_names_and_info.py
aks2203/deep-thinking
089fc5d04a0997ccdbad601b3e025f547a8b6327
[ "MIT" ]
null
null
null
deepthinking/data_analysis/get_names_and_info.py
aks2203/deep-thinking
089fc5d04a0997ccdbad601b3e025f547a8b6327
[ "MIT" ]
1
2022-03-13T18:45:41.000Z
2022-03-13T18:45:41.000Z
import argparse import glob import json import os.path from omegaconf import OmegaConf from tabulate import tabulate def get_trained_checkpoints(filepath, model_list, alpha_list): checkpoints = [] num_checkpoints = 0 for f_name in glob.iglob(f"{filepath}/**/*training*/", recursive=True): cfg_name = os.path.join(f_name, ".hydra/config.yaml") cfg = OmegaConf.load(cfg_name) if model_list is None or cfg.problem.model.model in model_list: if alpha_list is None or cfg.problem.hyp.alpha in alpha_list: checkpoints.append((cfg.run_id, cfg.problem.model.model, cfg.problem.hyp.alpha)) num_checkpoints += 1 return checkpoints, num_checkpoints def main(): parser = argparse.ArgumentParser(description="Analysis parser") parser.add_argument("filepath", type=str) parser.add_argument("--alpha_list", type=float, nargs="+", default=None, help="only plot models with model name in given list") parser.add_argument("--filter", type=float, default=0, help="cutoff for filtering by training acc?") parser.add_argument("--model_list", type=str, nargs="+", default=None, help="only plot models with model name in given list") args = parser.parse_args() checkpoints, num_checkopints = get_trained_checkpoints(args.filepath, args.model_list, args.alpha_list) head = ["Model Path", "Model", "Alpha"] print(f"I see {num_checkopints} runs") print(tabulate(checkpoints, headers=head)) if __name__ == "__main__": main()
39.043478
78
0.603007
8d1f9b6aaba8701ba4f42867764172ddd58b525d
910
py
Python
vmfw.py
whs/OvzCP
5c672f54f543dc07f234e86fd2b04b675511d362
[ "Apache-1.1" ]
1
2015-04-21T01:08:17.000Z
2015-04-21T01:08:17.000Z
vmfw.py
whs/OvzCP
5c672f54f543dc07f234e86fd2b04b675511d362
[ "Apache-1.1" ]
null
null
null
vmfw.py
whs/OvzCP
5c672f54f543dc07f234e86fd2b04b675511d362
[ "Apache-1.1" ]
null
null
null
import os, sys, ConfigParser sys.path.insert(0, os.path.join(os.getcwd(), "Jinja2-2.3-py2.5.egg")) sys.path.append(os.path.join(os.getcwd(), "netifaces-0.5-py2.5-linux-i686.egg")) import jinja2, netifaces _config = ConfigParser.SafeConfigParser() _config.read("config.ini") # iptables forwarding configuration generator def update(data): jinja = jinja2.Environment(loader=jinja2.loaders.FileSystemLoader("template")) ip={} for iface in netifaces.interfaces(): try: ip[iface] = netifaces.ifaddresses(iface)[netifaces.AF_INET][0]['addr'] except KeyError: pass except ValueError: pass d = jinja.get_template("vmfw.sh").render(port=data, ip=ip, vmip=_config.get("iface", "vmIP")) open("sysconf/vmfw.sh", "w").write(d) def restart(): os.system("sysconf/vmfw.sh") if __name__ == "__main__": from models import PortForward update(PortForward.select()) restart()
31.37931
95
0.705495
95c7cc728e98668cace3379e63b25a9f44e21641
6,683
py
Python
nnuncert/models/_pred_base.py
pjoachims/nnuncert
45dede54fdb714926926d719be2c9b9b542b2601
[ "MIT" ]
2
2021-12-30T06:25:43.000Z
2022-01-25T00:41:22.000Z
nnuncert/models/_pred_base.py
pjoachims/nnuncert
45dede54fdb714926926d719be2c9b9b542b2601
[ "MIT" ]
1
2022-01-25T00:35:28.000Z
2022-03-28T15:23:16.000Z
nnuncert/models/_pred_base.py
pjoachims/nnuncert
45dede54fdb714926926d719be2c9b9b542b2601
[ "MIT" ]
null
null
null
from typing import Tuple, Union, Iterable, List, Callable, Dict, Optional import numpy as np import pandas as pd import scipy.stats as spstats import scipy.integrate as spint import properscoring as ps class MCPredictions(np.ndarray): def __new__(cls, a): obj = np.asarray(a).view(cls) return obj def quantile(self, q): return np.quantile(self, q, axis=1) def contains(self, y): return (y >= self.min(axis=1)) & (y <= self.max(axis=1)) def in_95(self, y): q2p5, q97p5 = np.quantile(self, [0.025, 0.975], axis=1) ratio = sum((y >= q2p5) & (y <= q97p5)) / len(y) return ratio, (q97p5-q2p5).mean() def median(self, *args, **kwargs): return np.median(self, *args, **kwargs) def map(self, pts_grid=100): def find_peak(x, pts_grid=pts_grid): x = np.array(x).ravel() kde = sp.stats.gaussian_kde(x) x_grid = np.linspace(min(x), max(x), pts_grid) map = np.argmax(kde(x_grid)) return x_grid[map] return np.array([find_peak(y_) for y_ in self.lst]) @property def lst(self): return list(self) @property def np(self): return np.array(self) class BasePred(): def __init__(self, xlen): self.xlen = xlen def pdf(self, y): raise NotImplementedError() def logpdf(self, y): raise NotImplementedError() def cdf(self, y): raise NotImplementedError() def ppf(self, q: float): raise NotImplementedError("Need to fix bug in Dist -> Fx first...") def pdfi(self, i: int, x): raise NotImplementedError() def cdfi(self, i: int, x): raise NotImplementedError() @property def pred_mean(self): raise NotImplementedError() @property def var_aleatoric(self): """Get pred. aleatoric variance.""" return np.zeros(self.xlen) @property def var_epistemic(self): return np.zeros(self.xlen) @property def var_total(self): return self.var_aleatoric + self.var_epistemic @property def std_total(self): return self.var_total**0.5 @property def q2p5(self): return self.ppf(0.025) @property def q97p5(self): return self.ppf(0.975) def marginals(self, y0, recalc: bool = True): if recalc is False and hasattr(self, "_marginals"): return self._marginals self._marginals = np.array([self.pdf(np.ones(self.xlen) * y_) for y_ in y0]).mean(axis=1) return self._marginals # ================================= SCORES ================================= def rmse(self, y): return np.mean((self.pred_mean - y)**2)**0.5 def log_score(self, y): assert len(y) == self.xlen, "x, y length missmatch." self._log_scores = self.logpdf(y) return self._log_scores.mean() def log_score_x(self, y, frac: float = 0.99): N = int(len(y)*frac) return pd.Series(self.logpdf(y)).nlargest(N).mean() def crps(self, y): raise NotImplementedError() def picp(self, y): return np.mean((y >= self.q2p5) & (y <= self.q97p5)) @property def mpiw(self): return np.mean(self.q97p5 - self.q2p5) class PredConditionalGaussian(BasePred): def pdf(self, y): return self.gaussians.pdf(y) def pdfi(self, i: int, y): mean, std = self.pred_mean[i], self.std_total[i] return spstats.norm.pdf(y, mean, std) def logpdf(self, y): return self.gaussians.logpdf(y) def cdf(self, y): return self.gaussians.cdf(y) def cdfi(self, i: int, y): mean, std = self.pred_mean[i], self.std_total[i] return spstats.norm.cdf(y, mean, std) def ppf(self, q: float): return self.gaussians.ppf(q) def crps(self, y): self._crps = np.array([ps.crps_gaussian(x, mu=m, sig=s) for (x, m, s) in list(zip(y, self.pred_mean, self.std_total))]) return self._crps.mean() def _make_gaussians(self): class Gaussian(): def __init__(self, mean, std_total): self.params = np.vstack((mean, std_total)).T.tolist() def pdf(self, y, *args, **kwds): return np.array([spstats.norm.pdf(y_, m, s, *args, **kwds) for y_, (m, s) in list(zip(y, self.params))]) def logpdf(self, y, *args, **kwds): return np.array([spstats.norm.logpdf(y_, m, s, *args, **kwds) for y_, (m, s) in list(zip(y, self.params))]) def cdf(self, y, *args, **kwds): return np.array([spstats.norm.cdf(y_, m, s, *args, **kwds) for y_, (m, s) in list(zip(y, self.params))]) def ppf(self, q, *args, **kwds): return np.array([spstats.norm.ppf(q, m, s, *args, **kwds) for (m, s) in self.params]) self.gaussians = Gaussian(self.pred_mean, self.std_total) class BasePredKDE(BasePred): def pdf(self, y): return np.array([d.pdf(y_) for (d, y_) in list(zip(self.dists, y))]) def pdfi(self, i, y): return self.dists[i].pdf(y) def logpdf(self, y): return np.log(self.pdf(y)) def cdf(self, y): return np.array([d.cdf(y_) for (d, y_) in list(zip(self.dists, y))]) def cdfi(self, i, y): return self.dists[i].cdf(y) def ppf(self, q): return np.array([d.ppf(q) for d in self.dists]) def crps(self, y, N=100, eps=1e-5): # def get_support(self, eps=1e-5): # supp_left = np.argmin(self.Fx < eps) - 1 # supp_right = np.argmax(self.Fx > 1 - eps) # return (supp_left, supp_right) assert len(y) == self.xlen, "x, y length missmatch." def calc_crps(dist, y): supp_left, supp_right = dist.get_support(eps) lhs = 0 rhs = 0 if y >= supp_left: ls_lhs = np.linspace(supp_left, y, N) val_lhs = dist.cdf(ls_lhs)**2 lhs = spint.simps(val_lhs, ls_lhs) if y <= supp_right: ls_rhs = np.linspace(y, supp_right, N) val_rhs = (dist.cdf(ls_rhs) - 1)**2 rhs = spint.simps(val_rhs, ls_rhs) return lhs + rhs self._crps = np.array([calc_crps(d, y_) for (d, y_) in list(zip(self.dists, y))]) return self._crps.mean()
29.702222
97
0.539279
cfc6ff72d9fea6e2b32e8799abd6d9b6ce3eb861
139
py
Python
hypixelio/_async/__init__.py
FoxNerdSaysMoo/HypixelIO
aca8fd6535c0afb2bb733172db2dcbd68590118d
[ "MIT" ]
16
2020-10-28T01:49:31.000Z
2022-03-13T23:19:31.000Z
hypixelio/_async/__init__.py
FoxNerdSaysMoo/HypixelIO
aca8fd6535c0afb2bb733172db2dcbd68590118d
[ "MIT" ]
20
2021-03-17T07:32:14.000Z
2022-03-07T02:48:00.000Z
hypixelio/_async/__init__.py
FoxNerdSaysMoo/HypixelIO
aca8fd6535c0afb2bb733172db2dcbd68590118d
[ "MIT" ]
5
2020-10-21T13:53:27.000Z
2021-09-02T15:47:45.000Z
from .client import AsyncClient from .converters import AsyncConverters from .portal import Portal, create_portal from .utils import Utils
27.8
41
0.841727
dc5c16898bcc2aa3acd5f05c841775192a499bd8
1,864
py
Python
toontown/building/PetshopBuildingAI.py
CrankySupertoon01/Toontown-2
60893d104528a8e7eb4aced5d0015f22e203466d
[ "MIT" ]
1
2021-02-13T22:40:50.000Z
2021-02-13T22:40:50.000Z
toontown/building/PetshopBuildingAI.py
CrankySupertoonArchive/Toontown-2
60893d104528a8e7eb4aced5d0015f22e203466d
[ "MIT" ]
1
2018-07-28T20:07:04.000Z
2018-07-30T18:28:34.000Z
toontown/building/PetshopBuildingAI.py
CrankySupertoonArchive/Toontown-2
60893d104528a8e7eb4aced5d0015f22e203466d
[ "MIT" ]
2
2019-12-02T01:39:10.000Z
2021-02-13T22:41:00.000Z
from panda3d.core import * from direct.directnotify import DirectNotifyGlobal import DistributedDoorAI import DistributedPetshopInteriorAI import FADoorCodes import DoorTypes from toontown.toon import NPCToons from toontown.toonbase import ToontownGlobals from toontown.quest import Quests from toontown.hood import ZoneUtil class PetshopBuildingAI: notify = DirectNotifyGlobal.directNotify.newCategory('PetshopBuildingAI') def __init__(self, air, exteriorZone, interiorZone, blockNumber): self.air = air self.exteriorZone = exteriorZone self.interiorZone = interiorZone self.setup(blockNumber) def cleanup(self): for npc in self.npcs: npc.requestDelete() del self.npcs self.door.requestDelete() del self.door self.insideDoor.requestDelete() del self.insideDoor self.interior.requestDelete() del self.interior def setup(self, blockNumber): self.interior = DistributedPetshopInteriorAI.DistributedPetshopInteriorAI( blockNumber, self.air, self.interiorZone) self.interior.generateWithRequired(self.interiorZone) self.npcs = NPCToons.createNpcsInZone(self.air, self.interiorZone) door = DistributedDoorAI.DistributedDoorAI( self.air, blockNumber, DoorTypes.EXT_STANDARD) insideDoor = DistributedDoorAI.DistributedDoorAI( self.air, blockNumber, DoorTypes.INT_STANDARD) door.setOtherDoor(insideDoor) insideDoor.setOtherDoor(door) door.zoneId = self.exteriorZone insideDoor.zoneId = self.interiorZone door.generateWithRequired(self.exteriorZone) insideDoor.generateWithRequired(self.interiorZone) self.door = door self.insideDoor = insideDoor def createPet(self, ownerId, seed): return
34.518519
82
0.717275
06eaaeb542168b5c4435cd6b23a2046d6b2d1139
2,122
py
Python
VizKG/charts/heatmap.py
espinraf/vizkg
b4461a556b69c34580b96922ccb9c0e5c237b34f
[ "MIT" ]
12
2021-07-30T07:20:26.000Z
2022-03-24T10:11:55.000Z
VizKG/charts/heatmap.py
espinraf/vizkg
b4461a556b69c34580b96922ccb9c0e5c237b34f
[ "MIT" ]
4
2021-06-04T16:09:27.000Z
2022-03-24T10:11:48.000Z
VizKG/charts/heatmap.py
espinraf/vizkg
b4461a556b69c34580b96922ccb9c0e5c237b34f
[ "MIT" ]
2
2021-09-01T16:46:00.000Z
2022-01-14T12:28:20.000Z
from .chart import Chart import matplotlib.pyplot as plt import seaborn as sns class HeatMap(Chart): def __init__(self, dataframe, kwargs): """ Constructs all the necessary attributes for the HeatMap object Parameters: dataframe (pandas.Dataframe): The dataframe """ Chart.__init__(self, dataframe, kwargs) def promote_to_candidate(self): is_promote = self._is_var_exist(self._numerical_column, 2) return is_promote def plot(self): """ Generate visualization """ if self.promote_to_candidate(): self.draw() else: pass def draw(self): """ Generate HeatMap visualization """ if self._is_var_exist(self._numerical_column, 2): self.figsize = self.__set_figsize(self.kwargs.get('figsize')) #check if param figsize exist if self.figsize is not None: plt.figure(figsize=self.figsize) sns.heatmap(self.dataframe.corr(), annot = True) plt.show(block=True) else: #plot HeatMap plt.figure(figsize=(13,8)) sns.heatmap(self.dataframe.corr(), annot = True) plt.show(block=True) @staticmethod def __set_figsize(figsize_input): """ Setter of figsize based on figsize input for matplotlib chart Parameters: (tuple) figsize_input: The figsize input Returns: (tuple) figsize: The result figsize """ figsize = None is_numeric_value = None try: if figsize_input is not None and len(figsize_input) == 2: is_numeric_value = all(isinstance(v, int) or isinstance(v, float) for v in figsize_input) else: is_numeric_value = False except: is_numeric_value = False if is_numeric_value: figsize = figsize_input else: figsize = None return figsize
27.921053
105
0.558907
9801b5f124db72a16a9e4cf08d5888ad3af84442
1,486
py
Python
lib/bes/unix/brew/brew.py
reconstruir/bes
82ff54b2dadcaef6849d7de424787f1dedace85c
[ "Apache-2.0" ]
null
null
null
lib/bes/unix/brew/brew.py
reconstruir/bes
82ff54b2dadcaef6849d7de424787f1dedace85c
[ "Apache-2.0" ]
null
null
null
lib/bes/unix/brew/brew.py
reconstruir/bes
82ff54b2dadcaef6849d7de424787f1dedace85c
[ "Apache-2.0" ]
null
null
null
#-*- coding:utf-8; mode:python; indent-tabs-mode: nil; c-basic-offset: 2; tab-width: 2 -*- import re from bes.common.check import check from bes.system.execute import execute from bes.system.host import host from bes.system.log import logger from bes.system.which import which from .brew_error import brew_error class brew(object): 'Class to install and uninstall brew on unix.' _log = logger('brew') @classmethod def has_brew(clazz): 'Return True if brew is installed.' clazz.check_system() return clazz.brew_exe() != None @classmethod def check_system(clazz): if host.SYSTEM in [ host.MACOS, host.LINUX ]: return raise brew_error('brew is only for macos or linux: "{}"'.format(host.SYSTEM)) @classmethod def brew_exe(clazz): 'Return the brew exe path.' return which.which('brew') @classmethod def version(clazz): 'Return the version of brew.' if not clazz.has_brew(): raise brew_error('brew not installed') rv = clazz.call_brew([ '--version' ]) f = re.findall(r'^Homebrew\s+(.+)\n', rv.stdout) if not f: raise brew_error('failed to determine brew version.') if len(f) != 1: raise brew_error('failed to determine brew version.') return f[0] @classmethod def call_brew(clazz, args): 'Call brew.' if not clazz.has_brew(): raise brew_error('brew not installed') cmd = [ clazz.brew_exe() ] + args return execute.execute(cmd, raise_error = False)
26.535714
90
0.671602
038516040b88797161563e3ee489da61681e498f
17,560
py
Python
models/recycle_gan_model.py
andrewk1/Recycle-GAN
390d3b3c2492a27e38d9b3a0b69bb95865dda7ea
[ "MIT" ]
null
null
null
models/recycle_gan_model.py
andrewk1/Recycle-GAN
390d3b3c2492a27e38d9b3a0b69bb95865dda7ea
[ "MIT" ]
null
null
null
models/recycle_gan_model.py
andrewk1/Recycle-GAN
390d3b3c2492a27e38d9b3a0b69bb95865dda7ea
[ "MIT" ]
null
null
null
import numpy as np import torch import os from collections import OrderedDict from torch.autograd import Variable import itertools import util.util as util from util.image_pool import ImagePool from .base_model import BaseModel from . import networks import sys class RecycleGANModel(BaseModel): def name(self): return 'RecycleGANModel' def initialize(self, opt): BaseModel.initialize(self, opt) nb = opt.batchSize size = opt.fineSize self.input_A0 = self.Tensor(nb, opt.input_nc, size, size) self.input_A1 = self.Tensor(nb, opt.input_nc, size, size) self.input_A2 = self.Tensor(nb, opt.input_nc, size, size) self.input_B0 = self.Tensor(nb, opt.output_nc, size, size) self.input_B1 = self.Tensor(nb, opt.output_nc, size, size) self.input_B2 = self.Tensor(nb, opt.output_nc, size, size) # load/define networks # The naming conversion is different from those used in the paper # Code (paper): G_A (G), G_B (F), D_A (D_Y), D_B (D_X) self.netG_A = networks.define_G(opt.input_nc, opt.output_nc, opt.ngf, opt.which_model_netG, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) self.netG_B = networks.define_G(opt.output_nc, opt.input_nc, opt.ngf, opt.which_model_netG, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) self.which_model_netP = opt.which_model_netP if opt.which_model_netP == 'prediction': self.netP_A = networks.define_G(opt.input_nc, opt.input_nc, opt.npf, opt.which_model_netP, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) self.netP_B = networks.define_G(opt.output_nc, opt.output_nc, opt.npf, opt.which_model_netP, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) else: self.netP_A = networks.define_G(2 * opt.input_nc, opt.input_nc, opt.ngf, opt.which_model_netP, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) self.netP_B = networks.define_G(2 * opt.output_nc, opt.output_nc, opt.ngf, opt.which_model_netP, opt.norm, not opt.no_dropout, opt.init_type, self.gpu_ids) if self.isTrain: use_sigmoid = opt.no_lsgan self.netD_A = networks.define_D(opt.output_nc, opt.ndf, opt.which_model_netD, opt.n_layers_D, opt.norm, use_sigmoid, opt.init_type, self.gpu_ids) self.netD_B = networks.define_D(opt.input_nc, opt.ndf, opt.which_model_netD, opt.n_layers_D, opt.norm, use_sigmoid, opt.init_type, self.gpu_ids) if not self.isTrain or opt.continue_train: which_epoch = opt.which_epoch self.load_network(self.netG_A, 'G_A', which_epoch) self.load_network(self.netG_B, 'G_B', which_epoch) self.load_network(self.netP_A, 'P_A', which_epoch) self.load_network(self.netP_B, 'P_B', which_epoch) if self.isTrain: self.load_network(self.netD_A, 'D_A', which_epoch) self.load_network(self.netD_B, 'D_B', which_epoch) if self.isTrain: self.old_lr = opt.lr self.fake_A_pool = ImagePool(opt.pool_size) self.fake_B_pool = ImagePool(opt.pool_size) # define loss functions self.criterionGAN = networks.GANLoss(use_lsgan=not opt.no_lsgan, tensor=self.Tensor) self.criterionCycle = torch.nn.L1Loss() self.criterionIdt = torch.nn.L1Loss() # initialize optimizers self.optimizer_G = torch.optim.Adam( itertools.chain(self.netG_A.parameters(), self.netG_B.parameters(), self.netP_A.parameters(), self.netP_B.parameters()), lr=opt.lr, betas=(opt.beta1, 0.999)) self.optimizer_D_A = torch.optim.Adam(self.netD_A.parameters(), lr=opt.lr, betas=(opt.beta1, 0.999)) self.optimizer_D_B = torch.optim.Adam(self.netD_B.parameters(), lr=opt.lr, betas=(opt.beta1, 0.999)) self.optimizers = [] self.schedulers = [] self.optimizers.append(self.optimizer_G) self.optimizers.append(self.optimizer_D_A) self.optimizers.append(self.optimizer_D_B) for optimizer in self.optimizers: self.schedulers.append(networks.get_scheduler(optimizer, opt)) print('---------- Networks initialized -------------') networks.print_network(self.netG_A) networks.print_network(self.netG_B) networks.print_network(self.netP_A) networks.print_network(self.netP_B) if self.isTrain: networks.print_network(self.netD_A) networks.print_network(self.netD_B) print('-----------------------------------------------') def set_input(self, input): AtoB = self.opt.which_direction == 'AtoB' input_A0 = input['A0'] input_A1 = input['A1'] input_A2 = input['A2'] input_B0 = input['B0'] input_B1 = input['B1'] input_B2 = input['B2'] self.input_A0.resize_(input_A0.size()).copy_(input_A0) self.input_A1.resize_(input_A1.size()).copy_(input_A1) self.input_A2.resize_(input_A2.size()).copy_(input_A2) self.input_B0.resize_(input_B0.size()).copy_(input_B0) self.input_B1.resize_(input_B1.size()).copy_(input_B1) self.input_B2.resize_(input_B2.size()).copy_(input_B2) self.image_paths = input['A_paths' if AtoB else 'B_paths'] def forward(self): self.real_A0 = Variable(self.input_A0) self.real_A1 = Variable(self.input_A1) self.real_A2 = Variable(self.input_A2) self.real_B0 = Variable(self.input_B0) self.real_B1 = Variable(self.input_B1) self.real_B2 = Variable(self.input_B2) def test(self): real_A0 = Variable(self.input_A0, volatile=True) real_A1 = Variable(self.input_A1, volatile=True) fake_B0 = self.netG_A(real_A0) fake_B1 = self.netG_A(real_A1) # fake_B2 = self.netP_B(torch.cat((fake_B0, fake_B1),1)) if self.which_model_netP == 'prediction': fake_B2 = self.netP_B(fake_B0, fake_B1) else: fake_B2 = self.netP_B(torch.cat((fake_B0, fake_B1), 1)) self.rec_A = self.netG_B(fake_B2).data self.fake_B0 = fake_B0.data self.fake_B1 = fake_B1.data self.fake_B2 = fake_B2.data real_B0 = Variable(self.input_B0, volatile=True) real_B1 = Variable(self.input_B1, volatile=True) fake_A0 = self.netG_B(real_B0) fake_A1 = self.netG_B(real_B1) # fake_A2 = self.netP_A(torch.cat((fake_A0, fake_A1),1)) if self.which_model_netP == 'prediction': fake_A2 = self.netP_A(fake_A0, fake_A1) else: fake_A2 = self.netP_A(torch.cat((fake_A0, fake_A1), 1)) self.rec_B = self.netG_A(fake_A2).data self.fake_A0 = fake_A0.data self.fake_A1 = fake_A1.data self.fake_A2 = fake_A2.data # pred_A2 = self.netP_A(torch.cat((real_A0, real_A1),1)) if self.which_model_netP == 'prediction': pred_A2 = self.netP_A(real_A0, real_A1) pred_B2 = self.netP_B(real_B0, real_B1) else: pred_A2 = self.netP_A(torch.cat((real_A0, real_A1), 1)) pred_B2 = self.netP_B(torch.cat((real_B0, real_B1), 1)) self.pred_A2 = pred_A2.data self.pred_B2 = pred_B2.data # get image paths def get_image_paths(self): return self.image_paths def backward_D_basic(self, netD, real, fake): # Real pred_real = netD(real) loss_D_real = self.criterionGAN(pred_real, True) # Fake pred_fake = netD(fake.detach()) loss_D_fake = self.criterionGAN(pred_fake, False) # Combined loss loss_D = (loss_D_real + loss_D_fake) * 0.5 # backward loss_D.backward() return loss_D def backward_D_A(self): fake_B0 = self.fake_B_pool.query(self.fake_B0) loss_D_A0 = self.backward_D_basic(self.netD_A, self.real_B0, fake_B0) fake_B1 = self.fake_B_pool.query(self.fake_B1) loss_D_A1 = self.backward_D_basic(self.netD_A, self.real_B1, fake_B1) fake_B2 = self.fake_B_pool.query(self.fake_B2) loss_D_A2 = self.backward_D_basic(self.netD_A, self.real_B2, fake_B2) pred_B = self.fake_B_pool.query(self.pred_B2) loss_D_A3 = self.backward_D_basic(self.netD_A, self.real_B2, pred_B) self.loss_D_A = loss_D_A0.data[0] + loss_D_A1.data[0] + loss_D_A2.data[ 0] + loss_D_A3.data[0] def backward_D_B(self): fake_A0 = self.fake_A_pool.query(self.fake_A0) loss_D_B0 = self.backward_D_basic(self.netD_B, self.real_A0, fake_A0) fake_A1 = self.fake_A_pool.query(self.fake_A1) loss_D_B1 = self.backward_D_basic(self.netD_B, self.real_A1, fake_A1) fake_A2 = self.fake_A_pool.query(self.fake_A2) loss_D_B2 = self.backward_D_basic(self.netD_B, self.real_A2, fake_A2) pred_A = self.fake_A_pool.query(self.pred_A2) loss_D_B3 = self.backward_D_basic(self.netD_B, self.real_A2, pred_A) self.loss_D_B = loss_D_B0.data[0] + loss_D_B1.data[0] + loss_D_B2.data[ 0] + loss_D_B3.data[0] def backward_G(self): lambda_idt = self.opt.identity lambda_A = self.opt.lambda_A lambda_B = self.opt.lambda_B # Identity loss if lambda_idt > 0: loss_idt_A = 0 loss_idt_B = 0 self.loss_idt_A = 0 self.loss_idt_B = 0 else: loss_idt_A = 0 loss_idt_B = 0 self.loss_idt_A = 0 self.loss_idt_B = 0 # GAN loss D_A(G_A(A)) fake_B0 = self.netG_A(self.real_A0) pred_fake = self.netD_A(fake_B0) loss_G_A0 = self.criterionGAN(pred_fake, True) fake_B1 = self.netG_A(self.real_A1) pred_fake = self.netD_A(fake_B1) loss_G_A1 = self.criterionGAN(pred_fake, True) # fake_B2 = self.netP_B(torch.cat((fake_B0,fake_B1),1)) if self.which_model_netP == 'prediction': fake_B2 = self.netP_B(fake_B0, fake_B1) else: fake_B2 = self.netP_B(torch.cat((fake_B0, fake_B1), 1)) pred_fake = self.netD_A(fake_B2) loss_G_A2 = self.criterionGAN(pred_fake, True) # GAN loss D_B(G_B(B)) fake_A0 = self.netG_B(self.real_B0) pred_fake = self.netD_B(fake_A0) loss_G_B0 = self.criterionGAN(pred_fake, True) fake_A1 = self.netG_B(self.real_B1) pred_fake = self.netD_B(fake_A1) loss_G_B1 = self.criterionGAN(pred_fake, True) # fake_A2 = self.netP_A(torch.cat((fake_A0,fake_A1),1)) if self.which_model_netP == 'prediction': fake_A2 = self.netP_A(fake_A0, fake_A1) else: fake_A2 = self.netP_A(torch.cat((fake_A0, fake_A1), 1)) pred_fake = self.netD_B(fake_A2) loss_G_B2 = self.criterionGAN(pred_fake, True) # prediction loss -- # pred_A2 = self.netP_A(torch.cat((self.real_A0, self.real_A1),1)) if self.which_model_netP == 'prediction': pred_A2 = self.netP_A(self.real_A0, self.real_A1) else: pred_A2 = self.netP_A(torch.cat((self.real_A0, self.real_A1), 1)) loss_pred_A = self.criterionCycle(pred_A2, self.real_A2) * lambda_A # pred_B2 = self.netP_B(torch.cat((self.real_B0, self.real_B1),1)) if self.which_model_netP == 'prediction': pred_B2 = self.netP_B(self.real_B0, self.real_B1) else: pred_B2 = self.netP_B(torch.cat((self.real_B0, self.real_B1), 1)) loss_pred_B = self.criterionCycle(pred_B2, self.real_B2) * lambda_B # Forward cycle loss rec_A = self.netG_B(fake_B2) loss_cycle_A = self.criterionCycle(rec_A, self.real_A2) * lambda_A # Backward cycle loss rec_B = self.netG_A(fake_A2) loss_cycle_B = self.criterionCycle(rec_B, self.real_B2) * lambda_B # combined loss loss_G = loss_G_A0 + loss_G_A1 + loss_G_A2 + loss_G_B0 + loss_G_B1 + loss_G_B2 + loss_cycle_A + loss_cycle_B + loss_pred_A + loss_pred_B + loss_idt_A + loss_idt_B loss_G.backward() self.fake_B0 = fake_B0.data self.fake_B1 = fake_B1.data self.fake_B2 = fake_B2.data self.pred_B2 = pred_B2.data self.fake_A0 = fake_A0.data self.fake_A1 = fake_A1.data self.fake_A2 = fake_A2.data self.pred_A2 = pred_A2.data self.rec_A = rec_A.data self.rec_B = rec_B.data self.loss_G_A = loss_G_A0.data[0] + loss_G_A1.data[0] + loss_G_A2.data[ 0] self.loss_G_B = loss_G_B0.data[0] + loss_G_B1.data[0] + loss_G_B2.data[ 0] self.loss_cycle_A = loss_cycle_A.data[0] self.loss_cycle_B = loss_cycle_B.data[0] self.loss_pred_A = loss_pred_A.data[0] self.loss_pred_B = loss_pred_B.data[0] def optimize_parameters(self): # forward self.forward() # G_A and G_B self.optimizer_G.zero_grad() self.backward_G() self.optimizer_G.step() # D_A self.optimizer_D_A.zero_grad() self.backward_D_A() self.optimizer_D_A.step() # D_B self.optimizer_D_B.zero_grad() self.backward_D_B() self.optimizer_D_B.step() def get_current_errors(self): ret_errors = OrderedDict( [('D_A', self.loss_D_A), ('G_A', self.loss_G_A), ('Cyc_A', self.loss_cycle_A), ('Pred_A', self.loss_pred_A), ('D_B', self.loss_D_B), ('G_B', self.loss_G_B), ('Cyc_B', self.loss_cycle_B), ('Pred_B', self.loss_pred_B)]) if self.opt.identity > 0.0: ret_errors['idt_A'] = self.loss_idt_A ret_errors['idt_B'] = self.loss_idt_B return ret_errors def get_current_visuals(self): real_A0 = util.tensor2im(self.input_A0) real_A1 = util.tensor2im(self.input_A1) real_A2 = util.tensor2im(self.input_A2) fake_B0 = util.tensor2im(self.fake_B0) fake_B1 = util.tensor2im(self.fake_B1) fake_B2 = util.tensor2im(self.fake_B2) rec_A = util.tensor2im(self.rec_A) real_B0 = util.tensor2im(self.input_B0) real_B1 = util.tensor2im(self.input_B1) real_B2 = util.tensor2im(self.input_B2) fake_A0 = util.tensor2im(self.fake_A0) fake_A1 = util.tensor2im(self.fake_A1) fake_A2 = util.tensor2im(self.fake_A2) rec_B = util.tensor2im(self.rec_B) pred_A2 = util.tensor2im(self.pred_A2) pred_B2 = util.tensor2im(self.pred_B2) ret_visuals = OrderedDict([('real_A0', real_A0), ('fake_B0', fake_B0), ('real_A1', real_A1), ('fake_B1', fake_B1), ('fake_B2', fake_B2), ('rec_A', rec_A), ('real_A2', real_A2), ('real_B0', real_B0), ('fake_A0', fake_A0), ('real_B1', real_B1), ('fake_A1', fake_A1), ('fake_A2', fake_A2), ('rec_B', rec_B), ('real_B2', real_B2), ('real_A2', real_A2), ('pred_A2', pred_A2), ('real_B2', real_B2), ('pred_B2', pred_B2)]) if self.opt.isTrain and self.opt.identity > 0.0: ret_visuals['idt_A'] = util.tensor2im(self.idt_A) ret_visuals['idt_B'] = util.tensor2im(self.idt_B) return ret_visuals def save(self, label): self.save_network(self.netG_A, 'G_A', label, self.gpu_ids) self.save_network(self.netD_A, 'D_A', label, self.gpu_ids) self.save_network(self.netG_B, 'G_B', label, self.gpu_ids) self.save_network(self.netD_B, 'D_B', label, self.gpu_ids) self.save_network(self.netP_A, 'P_A', label, self.gpu_ids) self.save_network(self.netP_B, 'P_B', label, self.gpu_ids)
41.611374
170
0.569989
b595abad2e706a3bc3c0b0e1dd5a442975add970
5,487
py
Python
.venv/lib/python3.8/site-packages/sympy/polys/domains/polynomialring.py
RivtLib/replit01
ce1ae18b446a9c844f40e88a51c71fbc45ab3ad7
[ "MIT" ]
603
2020-12-23T13:49:32.000Z
2022-03-31T23:38:03.000Z
.venv/lib/python3.8/site-packages/sympy/polys/domains/polynomialring.py
RivtLib/replit01
ce1ae18b446a9c844f40e88a51c71fbc45ab3ad7
[ "MIT" ]
387
2020-12-15T14:54:04.000Z
2022-03-31T07:00:21.000Z
.venv/lib/python3.8/site-packages/sympy/polys/domains/polynomialring.py
RivtLib/replit01
ce1ae18b446a9c844f40e88a51c71fbc45ab3ad7
[ "MIT" ]
35
2021-03-26T03:12:04.000Z
2022-03-23T10:15:10.000Z
"""Implementation of :class:`PolynomialRing` class. """ from sympy.polys.domains.ring import Ring from sympy.polys.domains.compositedomain import CompositeDomain from sympy.polys.polyerrors import CoercionFailed, GeneratorsError from sympy.utilities import public @public class PolynomialRing(Ring, CompositeDomain): """A class for representing multivariate polynomial rings. """ is_PolynomialRing = is_Poly = True has_assoc_Ring = True has_assoc_Field = True def __init__(self, domain_or_ring, symbols=None, order=None): from sympy.polys.rings import PolyRing if isinstance(domain_or_ring, PolyRing) and symbols is None and order is None: ring = domain_or_ring else: ring = PolyRing(symbols, domain_or_ring, order) self.ring = ring self.dtype = ring.dtype self.gens = ring.gens self.ngens = ring.ngens self.symbols = ring.symbols self.domain = ring.domain if symbols: if ring.domain.is_Field and ring.domain.is_Exact and len(symbols)==1: self.is_PID = True # TODO: remove this self.dom = self.domain def new(self, element): return self.ring.ring_new(element) @property def zero(self): return self.ring.zero @property def one(self): return self.ring.one @property def order(self): return self.ring.order def __str__(self): return str(self.domain) + '[' + ','.join(map(str, self.symbols)) + ']' def __hash__(self): return hash((self.__class__.__name__, self.dtype.ring, self.domain, self.symbols)) def __eq__(self, other): """Returns `True` if two domains are equivalent. """ return isinstance(other, PolynomialRing) and \ (self.dtype.ring, self.domain, self.symbols) == \ (other.dtype.ring, other.domain, other.symbols) def is_unit(self, a): """Returns ``True`` if ``a`` is a unit of ``self``""" if not a.is_ground: return False K = self.domain return K.is_unit(K.convert_from(a, self)) def to_sympy(self, a): """Convert `a` to a SymPy object. """ return a.as_expr() def from_sympy(self, a): """Convert SymPy's expression to `dtype`. """ return self.ring.from_expr(a) def from_ZZ_python(K1, a, K0): """Convert a Python `int` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_QQ_python(K1, a, K0): """Convert a Python `Fraction` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_ZZ_gmpy(K1, a, K0): """Convert a GMPY `mpz` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_QQ_gmpy(K1, a, K0): """Convert a GMPY `mpq` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_GaussianIntegerRing(K1, a, K0): """Convert a `GaussianInteger` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_GaussianRationalField(K1, a, K0): """Convert a `GaussianRational` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_RealField(K1, a, K0): """Convert a mpmath `mpf` object to `dtype`. """ return K1(K1.domain.convert(a, K0)) def from_AlgebraicField(K1, a, K0): """Convert an algebraic number to ``dtype``. """ if K1.domain == K0: return K1.new(a) def from_PolynomialRing(K1, a, K0): """Convert a polynomial to ``dtype``. """ try: return a.set_ring(K1.ring) except (CoercionFailed, GeneratorsError): return None def from_FractionField(K1, a, K0): """Convert a rational function to ``dtype``. """ q, r = K0.numer(a).div(K0.denom(a)) if r.is_zero: return K1.from_PolynomialRing(q, K0.field.ring.to_domain()) else: return None def from_GlobalPolynomialRing(K1, a, K0): """Convert from old poly ring to ``dtype``. """ if K1.symbols == K0.gens: ad = a.to_dict() if K1.domain != K0.domain: ad = {m: K1.domain.convert(c) for m, c in ad.items()} return K1(ad) elif a.is_ground and K0.domain == K1: return K1.convert_from(a.to_list()[0], K0.domain) def get_field(self): """Returns a field associated with `self`. """ return self.ring.to_field().to_domain() def is_positive(self, a): """Returns True if `LC(a)` is positive. """ return self.domain.is_positive(a.LC) def is_negative(self, a): """Returns True if `LC(a)` is negative. """ return self.domain.is_negative(a.LC) def is_nonpositive(self, a): """Returns True if `LC(a)` is non-positive. """ return self.domain.is_nonpositive(a.LC) def is_nonnegative(self, a): """Returns True if `LC(a)` is non-negative. """ return self.domain.is_nonnegative(a.LC) def gcdex(self, a, b): """Extended GCD of `a` and `b`. """ return a.gcdex(b) def gcd(self, a, b): """Returns GCD of `a` and `b`. """ return a.gcd(b) def lcm(self, a, b): """Returns LCM of `a` and `b`. """ return a.lcm(b) def factorial(self, a): """Returns factorial of `a`. """ return self.dtype(self.domain.factorial(a))
30.653631
90
0.587753
1b7b0c47afe0e564f7530c99f8c18b8810938072
696
py
Python
converter/converter/__init__.py
pcrane70/thinapp_factory
5910839b29bf79e6565291bff51a555de0795176
[ "Apache-2.0" ]
26
2015-01-06T03:28:20.000Z
2019-11-27T11:55:06.000Z
converter/converter/__init__.py
pcrane70/thinapp_factory
5910839b29bf79e6565291bff51a555de0795176
[ "Apache-2.0" ]
1
2021-07-20T16:13:11.000Z
2021-07-20T16:13:11.000Z
converter/converter/__init__.py
pcrane70/thinapp_factory
5910839b29bf79e6565291bff51a555de0795176
[ "Apache-2.0" ]
15
2015-06-30T12:19:24.000Z
2019-10-15T16:00:47.000Z
# VMware ThinApp Factory # Copyright (c) 2009-2013 VMware, Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pkg_resources pkg_resources.declare_namespace(__name__)
36.631579
74
0.771552
b2ab368d00c63579afc7ae254815e8b4d42e5489
4,251
py
Python
kombu/tests/transport/test_filesystem.py
mikejohnsonjr/kombu
c32278f327b9fef2c18f42b6eea63703ea93c93f
[ "BSD-3-Clause" ]
3
2016-07-29T16:38:29.000Z
2021-01-14T21:07:39.000Z
kombu/tests/transport/test_filesystem.py
alanjds/kombu
3b6aa9b4e5719314ddb6f8df705b1d556a298e66
[ "BSD-3-Clause" ]
null
null
null
kombu/tests/transport/test_filesystem.py
alanjds/kombu
3b6aa9b4e5719314ddb6f8df705b1d556a298e66
[ "BSD-3-Clause" ]
2
2019-05-09T03:17:21.000Z
2020-03-11T08:02:19.000Z
from __future__ import absolute_import, unicode_literals import tempfile from kombu import Connection, Exchange, Queue, Consumer, Producer from case.skip import SkipTest from kombu.tests.case import Case, skip @skip.if_win32() class test_FilesystemTransport(Case): def setup(self): try: data_folder_in = tempfile.mkdtemp() data_folder_out = tempfile.mkdtemp() except Exception: raise SkipTest('filesystem transport: cannot create tempfiles') self.c = Connection(transport='filesystem', transport_options={ 'data_folder_in': data_folder_in, 'data_folder_out': data_folder_out, }) self.p = Connection(transport='filesystem', transport_options={ 'data_folder_in': data_folder_out, 'data_folder_out': data_folder_in, }) self.e = Exchange('test_transport_filesystem') self.q = Queue('test_transport_filesystem', exchange=self.e, routing_key='test_transport_filesystem') self.q2 = Queue('test_transport_filesystem2', exchange=self.e, routing_key='test_transport_filesystem2') def test_produce_consume_noack(self): producer = Producer(self.p.channel(), self.e) consumer = Consumer(self.c.channel(), self.q, no_ack=True) for i in range(10): producer.publish({'foo': i}, routing_key='test_transport_filesystem') _received = [] def callback(message_data, message): _received.append(message) consumer.register_callback(callback) consumer.consume() while 1: if len(_received) == 10: break self.c.drain_events() self.assertEqual(len(_received), 10) def test_produce_consume(self): producer_channel = self.p.channel() consumer_channel = self.c.channel() producer = Producer(producer_channel, self.e) consumer1 = Consumer(consumer_channel, self.q) consumer2 = Consumer(consumer_channel, self.q2) self.q2(consumer_channel).declare() for i in range(10): producer.publish({'foo': i}, routing_key='test_transport_filesystem') for i in range(10): producer.publish({'foo': i}, routing_key='test_transport_filesystem2') _received1 = [] _received2 = [] def callback1(message_data, message): _received1.append(message) message.ack() def callback2(message_data, message): _received2.append(message) message.ack() consumer1.register_callback(callback1) consumer2.register_callback(callback2) consumer1.consume() consumer2.consume() while 1: if len(_received1) + len(_received2) == 20: break self.c.drain_events() self.assertEqual(len(_received1) + len(_received2), 20) # compression producer.publish({'compressed': True}, routing_key='test_transport_filesystem', compression='zlib') m = self.q(consumer_channel).get() self.assertDictEqual(m.payload, {'compressed': True}) # queue.delete for i in range(10): producer.publish({'foo': i}, routing_key='test_transport_filesystem') self.assertTrue(self.q(consumer_channel).get()) self.q(consumer_channel).delete() self.q(consumer_channel).declare() self.assertIsNone(self.q(consumer_channel).get()) # queue.purge for i in range(10): producer.publish({'foo': i}, routing_key='test_transport_filesystem2') self.assertTrue(self.q2(consumer_channel).get()) self.q2(consumer_channel).purge() self.assertIsNone(self.q2(consumer_channel).get())
34.560976
75
0.569043
3eb75dff5e90b20ebe23fdac4284bc012576a827
3,496
py
Python
test/functional/s3api/test_service.py
JMD110/swift
58ddca8fa5ccb99447f7dcc0745cc619449a5513
[ "Apache-2.0" ]
1
2022-03-07T06:11:06.000Z
2022-03-07T06:11:06.000Z
test/functional/s3api/test_service.py
JMD110/swift
58ddca8fa5ccb99447f7dcc0745cc619449a5513
[ "Apache-2.0" ]
null
null
null
test/functional/s3api/test_service.py
JMD110/swift
58ddca8fa5ccb99447f7dcc0745cc619449a5513
[ "Apache-2.0" ]
null
null
null
# Copyright (c) 2015 OpenStack Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import os import test.functional as tf from swift.common.middleware.s3api.etree import fromstring from test.functional.s3api import S3ApiBase from test.functional.s3api.s3_test_client import Connection from test.functional.s3api.utils import get_error_code def setUpModule(): tf.setup_package() def tearDownModule(): tf.teardown_package() class TestS3ApiService(S3ApiBase): def setUp(self): super(TestS3ApiService, self).setUp() def test_service(self): # GET Service(without bucket) status, headers, body = self.conn.make_request('GET') self.assertEqual(status, 200) self.assertCommonResponseHeaders(headers) self.assertTrue(headers['content-type'] is not None) # TODO; requires consideration # self.assertEqual(headers['transfer-encoding'], 'chunked') elem = fromstring(body, 'ListAllMyBucketsResult') buckets = elem.findall('./Buckets/Bucket') self.assertEqual(list(buckets), []) owner = elem.find('Owner') self.assertEqual(self.conn.user_id, owner.find('ID').text) self.assertEqual(self.conn.user_id, owner.find('DisplayName').text) # GET Service(with Bucket) req_buckets = ('bucket', 'bucket2') for bucket in req_buckets: self.conn.make_request('PUT', bucket) status, headers, body = self.conn.make_request('GET') self.assertEqual(status, 200) elem = fromstring(body, 'ListAllMyBucketsResult') resp_buckets = elem.findall('./Buckets/Bucket') self.assertEqual(len(list(resp_buckets)), 2) for b in resp_buckets: self.assertTrue(b.find('Name').text in req_buckets) self.assertTrue(b.find('CreationDate') is not None) def test_service_error_signature_not_match(self): auth_error_conn = Connection(aws_secret_key='invalid') status, headers, body = auth_error_conn.make_request('GET') self.assertEqual(get_error_code(body), 'SignatureDoesNotMatch') self.assertEqual(headers['content-type'], 'application/xml') def test_service_error_no_date_header(self): # Without x-amz-date/Date header, that makes 403 forbidden status, headers, body = self.conn.make_request( 'GET', headers={'Date': '', 'x-amz-date': ''}) self.assertEqual(status, 403) self.assertEqual(get_error_code(body), 'AccessDenied') self.assertIn(b'AWS authentication requires a valid Date ' b'or x-amz-date header', body) class TestS3ApiServiceSigV4(TestS3ApiService): @classmethod def setUpClass(cls): os.environ['S3_USE_SIGV4'] = "True" @classmethod def tearDownClass(cls): del os.environ['S3_USE_SIGV4'] def setUp(self): super(TestS3ApiServiceSigV4, self).setUp() if __name__ == '__main__': unittest.main()
34.27451
75
0.687929
72c15a37ab0e20c6b5dfc3609fcb8f12c6c5a1cf
2,586
py
Python
output/python-flask/openapi_server/controllers/api_mnemonic_controller.py
tys-hiroshi/openapi3-codegen
c411878c4164799bb3f786b3b947cdcaeb810542
[ "MIT" ]
null
null
null
output/python-flask/openapi_server/controllers/api_mnemonic_controller.py
tys-hiroshi/openapi3-codegen
c411878c4164799bb3f786b3b947cdcaeb810542
[ "MIT" ]
null
null
null
output/python-flask/openapi_server/controllers/api_mnemonic_controller.py
tys-hiroshi/openapi3-codegen
c411878c4164799bb3f786b3b947cdcaeb810542
[ "MIT" ]
1
2020-08-06T06:21:36.000Z
2020-08-06T06:21:36.000Z
import connexion import six from openapi_server.models.request_add_address_model import RequestAddAddressModel # noqa: E501 from openapi_server.models.request_mnemonic_model import RequestMnemonicModel # noqa: E501 from openapi_server.models.request_upload_text_model import RequestUploadTextModel # noqa: E501 from openapi_server.models.response_add_address_model import ResponseAddAddressModel # noqa: E501 from openapi_server.models.response_mnemonic_model import ResponseMnemonicModel # noqa: E501 from openapi_server.models.response_tx_model import ResponseTxModel # noqa: E501 from openapi_server.models.response_upload_model import ResponseUploadModel # noqa: E501 from openapi_server.models.response_upload_text_model import ResponseUploadTextModel # noqa: E501 from openapi_server import util from pymongo import DESCENDING, ASCENDING import connexion import six import multiprocessing from openapi_server import app, mongo, bootstrap from openapi_server.libraires.whats_on_chain_lib import WhatsOnChainLib import bitsv from openapi_server.bip39mnemonic import Bip39Mnemonic def api_mnemonic(): # noqa: E501 """convert mnemonic words to wif, asset on Bitcoin SV. convert mnemonic words to wif, asset on Bitcoin SV. # noqa: E501 :param body: request /api/mnemonic :type body: dict | bytes :rtype: ResponseMnemonicModel """ # if connexion.request.is_json: # body = RequestMnemonicModel.from_dict(connexion.request.get_json()) # noqa: E501 # return 'do some magic!' try: app.app.logger.info("start /api/mnemonic") if connexion.request.is_json: body = RequestMnemonicModel.from_dict(connexion.request.get_json()) # noqa: E501 mnemonic = body.mnemonic #app.config['TESTNET_MNEMONIC'] bip39Mnemonic = Bip39Mnemonic(mnemonic, passphrase="", network="test") privateKey = bitsv.Key(bip39Mnemonic.privatekey_wif, network = 'test') address = privateKey.address balance_satoshi = privateKey.get_balance() #balance_bsv = float(balance_satoshi) / float(100000000) # html = render_template( # 'mnemonic.html', # privatekey_wif = bip39Mnemonic.privatekey_wif, # address = address, # balance_satoshi = balance_satoshi, # balance_bsv = balance_bsv, # title="mnemonic") return ResponseMnemonicModel(0, bip39Mnemonic.privatekey_wif, address, balance_satoshi).to_str(), 200 except Exception as e: print(e) return {}, 500
43.1
109
0.735112
06f74122050ea6061651be68b7219829f169ee44
54,326
py
Python
python/pyspark/pandas/window.py
zhaox1n/spark
1f150b9392706293946278dd35e8f5a5016ed6df
[ "BSD-2-Clause", "Apache-2.0", "CC0-1.0", "MIT", "MIT-0", "ECL-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
2
2021-06-03T09:59:31.000Z
2021-06-12T14:40:30.000Z
python/pyspark/pandas/window.py
zhaox1n/spark
1f150b9392706293946278dd35e8f5a5016ed6df
[ "BSD-2-Clause", "Apache-2.0", "CC0-1.0", "MIT", "MIT-0", "ECL-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
26
2016-10-27T06:07:00.000Z
2018-01-26T00:21:32.000Z
python/pyspark/pandas/window.py
zhaox1n/spark
1f150b9392706293946278dd35e8f5a5016ed6df
[ "BSD-2-Clause", "Apache-2.0", "CC0-1.0", "MIT", "MIT-0", "ECL-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
2
2020-11-04T17:36:17.000Z
2021-04-16T15:57:07.000Z
# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from functools import partial from typing import Any, Union, TYPE_CHECKING from pyspark.sql import Window from pyspark.sql import functions as F from pyspark.pandas.missing.window import ( MissingPandasLikeRolling, MissingPandasLikeRollingGroupby, MissingPandasLikeExpanding, MissingPandasLikeExpandingGroupby, ) # For running doctests and reference resolution in PyCharm. from pyspark import pandas as ps # noqa: F401 from pyspark.pandas.internal import NATURAL_ORDER_COLUMN_NAME, SPARK_INDEX_NAME_FORMAT from pyspark.pandas.utils import scol_for if TYPE_CHECKING: from pyspark.pandas.frame import DataFrame # noqa: F401 (SPARK-34943) from pyspark.pandas.series import Series # noqa: F401 (SPARK-34943) class RollingAndExpanding(object): def __init__(self, kdf_or_kser, window, min_periods): self._kdf_or_kser = kdf_or_kser self._window = window # This unbounded Window is later used to handle 'min_periods' for now. self._unbounded_window = Window.orderBy(NATURAL_ORDER_COLUMN_NAME).rowsBetween( Window.unboundedPreceding, Window.currentRow ) self._min_periods = min_periods def _apply_as_series_or_frame(self, func): """ Wraps a function that handles Spark column in order to support it in both pandas-on-Spark Series and DataFrame. Note that the given `func` name should be same as the API's method name. """ raise NotImplementedError( "A class that inherits this class should implement this method " "to handle the index and columns of output." ) def count(self) -> Union["Series", "DataFrame"]: def count(scol): return F.count(scol).over(self._window) return self._apply_as_series_or_frame(count).astype("float64") def sum(self) -> Union["Series", "DataFrame"]: def sum(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.sum(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(sum) def min(self) -> Union["Series", "DataFrame"]: def min(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.min(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(min) def max(self) -> Union["Series", "DataFrame"]: def max(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.max(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(max) def mean(self) -> Union["Series", "DataFrame"]: def mean(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.mean(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(mean) def std(self) -> Union["Series", "DataFrame"]: def std(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.stddev(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(std) def var(self) -> Union["Series", "DataFrame"]: def var(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.variance(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(var) class Rolling(RollingAndExpanding): def __init__(self, kdf_or_kser, window, min_periods=None): from pyspark.pandas import DataFrame, Series if window < 0: raise ValueError("window must be >= 0") if (min_periods is not None) and (min_periods < 0): raise ValueError("min_periods must be >= 0") if min_periods is None: # TODO: 'min_periods' is not equivalent in pandas because it does not count NA as # a value. min_periods = window if not isinstance(kdf_or_kser, (DataFrame, Series)): raise TypeError( "kdf_or_kser must be a series or dataframe; however, got: %s" % type(kdf_or_kser) ) window = Window.orderBy(NATURAL_ORDER_COLUMN_NAME).rowsBetween( Window.currentRow - (window - 1), Window.currentRow ) super().__init__(kdf_or_kser, window, min_periods) def __getattr__(self, item: str) -> Any: if hasattr(MissingPandasLikeRolling, item): property_or_func = getattr(MissingPandasLikeRolling, item) if isinstance(property_or_func, property): return property_or_func.fget(self) # type: ignore else: return partial(property_or_func, self) raise AttributeError(item) def _apply_as_series_or_frame(self, func): return self._kdf_or_kser._apply_series_op( lambda kser: kser._with_new_scol(func(kser.spark.column)), # TODO: dtype? should_resolve=True, ) def count(self) -> Union["Series", "DataFrame"]: """ The rolling count of any non-NaN observations inside the window. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.count : Count of the full Series. DataFrame.count : Count of the full DataFrame. Examples -------- >>> s = ps.Series([2, 3, float("nan"), 10]) >>> s.rolling(1).count() 0 1.0 1 1.0 2 0.0 3 1.0 dtype: float64 >>> s.rolling(3).count() 0 1.0 1 2.0 2 2.0 3 2.0 dtype: float64 >>> s.to_frame().rolling(1).count() 0 0 1.0 1 1.0 2 0.0 3 1.0 >>> s.to_frame().rolling(3).count() 0 0 1.0 1 2.0 2 2.0 3 2.0 """ return super().count() def sum(self) -> Union["Series", "DataFrame"]: """ Calculate rolling summation of given DataFrame or Series. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Same type as the input, with the same index, containing the rolling summation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.sum : Reducing sum for Series. DataFrame.sum : Reducing sum for DataFrame. Examples -------- >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s 0 4 1 3 2 5 3 2 4 6 dtype: int64 >>> s.rolling(2).sum() 0 NaN 1 7.0 2 8.0 3 7.0 4 8.0 dtype: float64 >>> s.rolling(3).sum() 0 NaN 1 NaN 2 12.0 3 10.0 4 13.0 dtype: float64 For DataFrame, each rolling summation is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 4 16 1 3 9 2 5 25 3 2 4 4 6 36 >>> df.rolling(2).sum() A B 0 NaN NaN 1 7.0 25.0 2 8.0 34.0 3 7.0 29.0 4 8.0 40.0 >>> df.rolling(3).sum() A B 0 NaN NaN 1 NaN NaN 2 12.0 50.0 3 10.0 38.0 4 13.0 65.0 """ return super().sum() def min(self) -> Union["Series", "DataFrame"]: """ Calculate the rolling minimum. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with a Series. DataFrame.rolling : Calling object with a DataFrame. Series.min : Similar method for Series. DataFrame.min : Similar method for DataFrame. Examples -------- >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s 0 4 1 3 2 5 3 2 4 6 dtype: int64 >>> s.rolling(2).min() 0 NaN 1 3.0 2 3.0 3 2.0 4 2.0 dtype: float64 >>> s.rolling(3).min() 0 NaN 1 NaN 2 3.0 3 2.0 4 2.0 dtype: float64 For DataFrame, each rolling minimum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 4 16 1 3 9 2 5 25 3 2 4 4 6 36 >>> df.rolling(2).min() A B 0 NaN NaN 1 3.0 9.0 2 3.0 9.0 3 2.0 4.0 4 2.0 4.0 >>> df.rolling(3).min() A B 0 NaN NaN 1 NaN NaN 2 3.0 9.0 3 2.0 4.0 4 2.0 4.0 """ return super().min() def max(self) -> Union["Series", "DataFrame"]: """ Calculate the rolling maximum. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Return type is determined by the caller. See Also -------- Series.rolling : Series rolling. DataFrame.rolling : DataFrame rolling. Series.max : Similar method for Series. DataFrame.max : Similar method for DataFrame. Examples -------- >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s 0 4 1 3 2 5 3 2 4 6 dtype: int64 >>> s.rolling(2).max() 0 NaN 1 4.0 2 5.0 3 5.0 4 6.0 dtype: float64 >>> s.rolling(3).max() 0 NaN 1 NaN 2 5.0 3 5.0 4 6.0 dtype: float64 For DataFrame, each rolling maximum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 4 16 1 3 9 2 5 25 3 2 4 4 6 36 >>> df.rolling(2).max() A B 0 NaN NaN 1 4.0 16.0 2 5.0 25.0 3 5.0 25.0 4 6.0 36.0 >>> df.rolling(3).max() A B 0 NaN NaN 1 NaN NaN 2 5.0 25.0 3 5.0 25.0 4 6.0 36.0 """ return super().max() def mean(self) -> Union["Series", "DataFrame"]: """ Calculate the rolling mean of the values. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.mean : Equivalent method for Series. DataFrame.mean : Equivalent method for DataFrame. Examples -------- >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s 0 4 1 3 2 5 3 2 4 6 dtype: int64 >>> s.rolling(2).mean() 0 NaN 1 3.5 2 4.0 3 3.5 4 4.0 dtype: float64 >>> s.rolling(3).mean() 0 NaN 1 NaN 2 4.000000 3 3.333333 4 4.333333 dtype: float64 For DataFrame, each rolling mean is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 4 16 1 3 9 2 5 25 3 2 4 4 6 36 >>> df.rolling(2).mean() A B 0 NaN NaN 1 3.5 12.5 2 4.0 17.0 3 3.5 14.5 4 4.0 20.0 >>> df.rolling(3).mean() A B 0 NaN NaN 1 NaN NaN 2 4.000000 16.666667 3 3.333333 12.666667 4 4.333333 21.666667 """ return super().mean() def std(self) -> Union["Series", "DataFrame"]: """ Calculate rolling standard deviation. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returns the same object type as the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.std : Equivalent method for Series. DataFrame.std : Equivalent method for DataFrame. numpy.std : Equivalent method for Numpy array. Examples -------- >>> s = ps.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.rolling(3).std() 0 NaN 1 NaN 2 0.577350 3 1.000000 4 1.000000 5 1.154701 6 0.000000 dtype: float64 For DataFrame, each rolling standard deviation is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.rolling(2).std() A B 0 NaN NaN 1 0.000000 0.000000 2 0.707107 7.778175 3 0.707107 9.192388 4 1.414214 16.970563 5 0.000000 0.000000 6 0.000000 0.000000 """ return super().std() def var(self) -> Union["Series", "DataFrame"]: """ Calculate unbiased rolling variance. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returns the same object type as the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.var : Equivalent method for Series. DataFrame.var : Equivalent method for DataFrame. numpy.var : Equivalent method for Numpy array. Examples -------- >>> s = ps.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.rolling(3).var() 0 NaN 1 NaN 2 0.333333 3 1.000000 4 1.000000 5 1.333333 6 0.000000 dtype: float64 For DataFrame, each unbiased rolling variance is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.rolling(2).var() A B 0 NaN NaN 1 0.0 0.0 2 0.5 60.5 3 0.5 84.5 4 2.0 288.0 5 0.0 0.0 6 0.0 0.0 """ return super().var() class RollingGroupby(Rolling): def __init__(self, groupby, window, min_periods=None): from pyspark.pandas.groupby import SeriesGroupBy from pyspark.pandas.groupby import DataFrameGroupBy if isinstance(groupby, SeriesGroupBy): kdf_or_kser = groupby._kser elif isinstance(groupby, DataFrameGroupBy): kdf_or_kser = groupby._kdf else: raise TypeError( "groupby must be a SeriesGroupBy or DataFrameGroupBy; " "however, got: %s" % type(groupby) ) super().__init__(kdf_or_kser, window, min_periods) self._groupby = groupby self._window = self._window.partitionBy(*[ser.spark.column for ser in groupby._groupkeys]) self._unbounded_window = self._unbounded_window.partitionBy( *[ser.spark.column for ser in groupby._groupkeys] ) def __getattr__(self, item: str) -> Any: if hasattr(MissingPandasLikeRollingGroupby, item): property_or_func = getattr(MissingPandasLikeRollingGroupby, item) if isinstance(property_or_func, property): return property_or_func.fget(self) # type: ignore else: return partial(property_or_func, self) raise AttributeError(item) def _apply_as_series_or_frame(self, func): """ Wraps a function that handles Spark column in order to support it in both pandas-on-Spark Series and DataFrame. Note that the given `func` name should be same as the API's method name. """ from pyspark.pandas import DataFrame from pyspark.pandas.series import first_series from pyspark.pandas.groupby import SeriesGroupBy groupby = self._groupby kdf = groupby._kdf # Here we need to include grouped key as an index, and shift previous index. # [index_column0, index_column1] -> [grouped key, index_column0, index_column1] new_index_scols = [] new_index_spark_column_names = [] new_index_names = [] new_index_dtypes = [] for groupkey in groupby._groupkeys: index_column_name = SPARK_INDEX_NAME_FORMAT(len(new_index_scols)) new_index_scols.append(groupkey.spark.column.alias(index_column_name)) new_index_spark_column_names.append(index_column_name) new_index_names.append(groupkey._column_label) new_index_dtypes.append(groupkey.dtype) for new_index_scol, index_name, index_dtype in zip( kdf._internal.index_spark_columns, kdf._internal.index_names, kdf._internal.index_dtypes ): index_column_name = SPARK_INDEX_NAME_FORMAT(len(new_index_scols)) new_index_scols.append(new_index_scol.alias(index_column_name)) new_index_spark_column_names.append(index_column_name) new_index_names.append(index_name) new_index_dtypes.append(index_dtype) if groupby._agg_columns_selected: agg_columns = groupby._agg_columns else: agg_columns = [ kdf._kser_for(label) for label in kdf._internal.column_labels if label not in groupby._column_labels_to_exlcude ] applied = [] for agg_column in agg_columns: applied.append(agg_column._with_new_scol(func(agg_column.spark.column))) # TODO: dtype? # Seems like pandas filters out when grouped key is NA. cond = groupby._groupkeys[0].spark.column.isNotNull() for c in groupby._groupkeys[1:]: cond = cond | c.spark.column.isNotNull() sdf = kdf._internal.spark_frame.filter(cond).select( new_index_scols + [c.spark.column for c in applied] ) internal = kdf._internal.copy( spark_frame=sdf, index_spark_columns=[scol_for(sdf, col) for col in new_index_spark_column_names], index_names=new_index_names, index_dtypes=new_index_dtypes, column_labels=[c._column_label for c in applied], data_spark_columns=[ scol_for(sdf, c._internal.data_spark_column_names[0]) for c in applied ], data_dtypes=[c.dtype for c in applied], ) ret = DataFrame(internal) if isinstance(groupby, SeriesGroupBy): return first_series(ret) else: return ret def count(self) -> Union["Series", "DataFrame"]: """ The rolling count of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.count : Count of the full Series. DataFrame.count : Count of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).rolling(3).count().sort_index() 2 0 1.0 1 2.0 3 2 1.0 3 2.0 4 3.0 4 5 1.0 6 2.0 7 3.0 8 3.0 5 9 1.0 10 2.0 dtype: float64 For DataFrame, each rolling count is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).rolling(2).count().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 1.0 1.0 1 2.0 2.0 3 2 1.0 1.0 3 2.0 2.0 4 2.0 2.0 4 5 1.0 1.0 6 2.0 2.0 7 2.0 2.0 8 2.0 2.0 5 9 1.0 1.0 10 2.0 2.0 """ return super().count() def sum(self) -> Union["Series", "DataFrame"]: """ The rolling summation of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.sum : Sum of the full Series. DataFrame.sum : Sum of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).rolling(3).sum().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 9.0 4 5 NaN 6 NaN 7 12.0 8 12.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each rolling summation is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).rolling(2).sum().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 4.0 8.0 3 2 NaN NaN 3 6.0 18.0 4 6.0 18.0 4 5 NaN NaN 6 8.0 32.0 7 8.0 32.0 8 8.0 32.0 5 9 NaN NaN 10 10.0 50.0 """ return super().sum() def min(self) -> Union["Series", "DataFrame"]: """ The rolling minimum of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.min : Min of the full Series. DataFrame.min : Min of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).rolling(3).min().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each rolling minimum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).rolling(2).min().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().min() def max(self) -> Union["Series", "DataFrame"]: """ The rolling maximum of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.max : Max of the full Series. DataFrame.max : Max of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).rolling(3).max().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each rolling maximum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).rolling(2).max().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().max() def mean(self) -> Union["Series", "DataFrame"]: """ The rolling mean of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.mean : Mean of the full Series. DataFrame.mean : Mean of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).rolling(3).mean().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each rolling mean is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).rolling(2).mean().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().mean() def std(self) -> Union["Series", "DataFrame"]: """ Calculate rolling standard deviation. Returns ------- Series or DataFrame Returns the same object type as the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.std : Equivalent method for Series. DataFrame.std : Equivalent method for DataFrame. numpy.std : Equivalent method for Numpy array. """ return super().std() def var(self) -> Union["Series", "DataFrame"]: """ Calculate unbiased rolling variance. Returns ------- Series or DataFrame Returns the same object type as the caller of the rolling calculation. See Also -------- Series.rolling : Calling object with Series data. DataFrame.rolling : Calling object with DataFrames. Series.var : Equivalent method for Series. DataFrame.var : Equivalent method for DataFrame. numpy.var : Equivalent method for Numpy array. """ return super().var() class Expanding(RollingAndExpanding): def __init__(self, kdf_or_kser, min_periods=1): from pyspark.pandas import DataFrame, Series if min_periods < 0: raise ValueError("min_periods must be >= 0") if not isinstance(kdf_or_kser, (DataFrame, Series)): raise TypeError( "kdf_or_kser must be a series or dataframe; however, got: %s" % type(kdf_or_kser) ) window = Window.orderBy(NATURAL_ORDER_COLUMN_NAME).rowsBetween( Window.unboundedPreceding, Window.currentRow ) super().__init__(kdf_or_kser, window, min_periods) def __getattr__(self, item: str) -> Any: if hasattr(MissingPandasLikeExpanding, item): property_or_func = getattr(MissingPandasLikeExpanding, item) if isinstance(property_or_func, property): return property_or_func.fget(self) # type: ignore else: return partial(property_or_func, self) raise AttributeError(item) # TODO: when add 'center' and 'axis' parameter, should add to here too. def __repr__(self): return "Expanding [min_periods={}]".format(self._min_periods) _apply_as_series_or_frame = Rolling._apply_as_series_or_frame def count(self) -> Union["Series", "DataFrame"]: """ The expanding count of any non-NaN observations inside the window. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.count : Count of the full Series. DataFrame.count : Count of the full DataFrame. Examples -------- >>> s = ps.Series([2, 3, float("nan"), 10]) >>> s.expanding().count() 0 1.0 1 2.0 2 2.0 3 3.0 dtype: float64 >>> s.to_frame().expanding().count() 0 0 1.0 1 2.0 2 2.0 3 3.0 """ def count(scol): return F.when( F.row_number().over(self._unbounded_window) >= self._min_periods, F.count(scol).over(self._window), ).otherwise(F.lit(None)) return self._apply_as_series_or_frame(count).astype("float64") # type: ignore def sum(self) -> Union["Series", "DataFrame"]: """ Calculate expanding summation of given DataFrame or Series. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Same type as the input, with the same index, containing the expanding summation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.sum : Reducing sum for Series. DataFrame.sum : Reducing sum for DataFrame. Examples -------- >>> s = ps.Series([1, 2, 3, 4, 5]) >>> s 0 1 1 2 2 3 3 4 4 5 dtype: int64 >>> s.expanding(3).sum() 0 NaN 1 NaN 2 6.0 3 10.0 4 15.0 dtype: float64 For DataFrame, each expanding summation is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 1 1 1 2 4 2 3 9 3 4 16 4 5 25 >>> df.expanding(3).sum() A B 0 NaN NaN 1 NaN NaN 2 6.0 14.0 3 10.0 30.0 4 15.0 55.0 """ return super().sum() def min(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding minimum. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with a Series. DataFrame.expanding : Calling object with a DataFrame. Series.min : Similar method for Series. DataFrame.min : Similar method for DataFrame. Examples -------- Performing a expanding minimum with a window size of 3. >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s.expanding(3).min() 0 NaN 1 NaN 2 3.0 3 2.0 4 2.0 dtype: float64 """ return super().min() def max(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding maximum. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Return type is determined by the caller. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.max : Similar method for Series. DataFrame.max : Similar method for DataFrame. Examples -------- Performing a expanding minimum with a window size of 3. >>> s = ps.Series([4, 3, 5, 2, 6]) >>> s.expanding(3).max() 0 NaN 1 NaN 2 5.0 3 5.0 4 6.0 dtype: float64 """ return super().max() def mean(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding mean of the values. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.mean : Equivalent method for Series. DataFrame.mean : Equivalent method for DataFrame. Examples -------- The below examples will show expanding mean calculations with window sizes of two and three, respectively. >>> s = ps.Series([1, 2, 3, 4]) >>> s.expanding(2).mean() 0 NaN 1 1.5 2 2.0 3 2.5 dtype: float64 >>> s.expanding(3).mean() 0 NaN 1 NaN 2 2.0 3 2.5 dtype: float64 """ return super().mean() def std(self) -> Union["Series", "DataFrame"]: """ Calculate expanding standard deviation. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returns the same object type as the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.std : Equivalent method for Series. DataFrame.std : Equivalent method for DataFrame. numpy.std : Equivalent method for Numpy array. Examples -------- >>> s = ps.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.expanding(3).std() 0 NaN 1 NaN 2 0.577350 3 0.957427 4 0.894427 5 0.836660 6 0.786796 dtype: float64 For DataFrame, each expanding standard deviation variance is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.expanding(2).std() A B 0 NaN NaN 1 0.000000 0.000000 2 0.577350 6.350853 3 0.957427 11.412712 4 0.894427 10.630146 5 0.836660 9.928075 6 0.786796 9.327379 """ return super().std() def var(self) -> Union["Series", "DataFrame"]: """ Calculate unbiased expanding variance. .. note:: the current implementation of this API uses Spark's Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset. Returns ------- Series or DataFrame Returns the same object type as the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.var : Equivalent method for Series. DataFrame.var : Equivalent method for DataFrame. numpy.var : Equivalent method for Numpy array. Examples -------- >>> s = ps.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.expanding(3).var() 0 NaN 1 NaN 2 0.333333 3 0.916667 4 0.800000 5 0.700000 6 0.619048 dtype: float64 For DataFrame, each unbiased expanding variance is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.expanding(2).var() A B 0 NaN NaN 1 0.000000 0.000000 2 0.333333 40.333333 3 0.916667 130.250000 4 0.800000 113.000000 5 0.700000 98.566667 6 0.619048 87.000000 """ return super().var() class ExpandingGroupby(Expanding): def __init__(self, groupby, min_periods=1): from pyspark.pandas.groupby import SeriesGroupBy from pyspark.pandas.groupby import DataFrameGroupBy if isinstance(groupby, SeriesGroupBy): kdf_or_kser = groupby._kser elif isinstance(groupby, DataFrameGroupBy): kdf_or_kser = groupby._kdf else: raise TypeError( "groupby must be a SeriesGroupBy or DataFrameGroupBy; " "however, got: %s" % type(groupby) ) super().__init__(kdf_or_kser, min_periods) self._groupby = groupby self._window = self._window.partitionBy(*[ser.spark.column for ser in groupby._groupkeys]) self._unbounded_window = self._window.partitionBy( *[ser.spark.column for ser in groupby._groupkeys] ) def __getattr__(self, item: str) -> Any: if hasattr(MissingPandasLikeExpandingGroupby, item): property_or_func = getattr(MissingPandasLikeExpandingGroupby, item) if isinstance(property_or_func, property): return property_or_func.fget(self) # type: ignore else: return partial(property_or_func, self) raise AttributeError(item) _apply_as_series_or_frame = RollingGroupby._apply_as_series_or_frame # type: ignore def count(self) -> Union["Series", "DataFrame"]: """ The expanding count of any non-NaN observations inside the window. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.count : Count of the full Series. DataFrame.count : Count of the full DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).expanding(3).count().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 3.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each expanding count is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).expanding(2).count().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 2.0 3 2 NaN NaN 3 2.0 2.0 4 3.0 3.0 4 5 NaN NaN 6 2.0 2.0 7 3.0 3.0 8 4.0 4.0 5 9 NaN NaN 10 2.0 2.0 """ return super().count() def sum(self) -> Union["Series", "DataFrame"]: """ Calculate expanding summation of given DataFrame or Series. Returns ------- Series or DataFrame Same type as the input, with the same index, containing the expanding summation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.sum : Reducing sum for Series. DataFrame.sum : Reducing sum for DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).expanding(3).sum().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 9.0 4 5 NaN 6 NaN 7 12.0 8 16.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each expanding summation is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).expanding(2).sum().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 4.0 8.0 3 2 NaN NaN 3 6.0 18.0 4 9.0 27.0 4 5 NaN NaN 6 8.0 32.0 7 12.0 48.0 8 16.0 64.0 5 9 NaN NaN 10 10.0 50.0 """ return super().sum() def min(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding minimum. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with a Series. DataFrame.expanding : Calling object with a DataFrame. Series.min : Similar method for Series. DataFrame.min : Similar method for DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).expanding(3).min().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each expanding minimum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).expanding(2).min().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().min() def max(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding maximum. Returns ------- Series or DataFrame Return type is determined by the caller. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.max : Similar method for Series. DataFrame.max : Similar method for DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).expanding(3).max().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each expanding maximum is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).expanding(2).max().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().max() def mean(self) -> Union["Series", "DataFrame"]: """ Calculate the expanding mean of the values. Returns ------- Series or DataFrame Returned object type is determined by the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.mean : Equivalent method for Series. DataFrame.mean : Equivalent method for DataFrame. Examples -------- >>> s = ps.Series([2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]) >>> s.groupby(s).expanding(3).mean().sort_index() 2 0 NaN 1 NaN 3 2 NaN 3 NaN 4 3.0 4 5 NaN 6 NaN 7 4.0 8 4.0 5 9 NaN 10 NaN dtype: float64 For DataFrame, each expanding mean is computed column-wise. >>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df.groupby(df.A).expanding(2).mean().sort_index() # doctest: +NORMALIZE_WHITESPACE A B A 2 0 NaN NaN 1 2.0 4.0 3 2 NaN NaN 3 3.0 9.0 4 3.0 9.0 4 5 NaN NaN 6 4.0 16.0 7 4.0 16.0 8 4.0 16.0 5 9 NaN NaN 10 5.0 25.0 """ return super().mean() def std(self) -> Union["Series", "DataFrame"]: """ Calculate expanding standard deviation. Returns ------- Series or DataFrame Returns the same object type as the caller of the expanding calculation. See Also -------- Series.expanding: Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.std : Equivalent method for Series. DataFrame.std : Equivalent method for DataFrame. numpy.std : Equivalent method for Numpy array. """ return super().std() def var(self) -> Union["Series", "DataFrame"]: """ Calculate unbiased expanding variance. Returns ------- Series or DataFrame Returns the same object type as the caller of the expanding calculation. See Also -------- Series.expanding : Calling object with Series data. DataFrame.expanding : Calling object with DataFrames. Series.var : Equivalent method for Series. DataFrame.var : Equivalent method for DataFrame. numpy.var : Equivalent method for Numpy array. """ return super().var() def _test(): import os import doctest import sys from pyspark.sql import SparkSession import pyspark.pandas.window os.chdir(os.environ["SPARK_HOME"]) globs = pyspark.pandas.window.__dict__.copy() globs["ps"] = pyspark.pandas spark = ( SparkSession.builder.master("local[4]").appName("pyspark.pandas.window tests").getOrCreate() ) (failure_count, test_count) = doctest.testmod( pyspark.pandas.window, globs=globs, optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE, ) spark.stop() if failure_count: sys.exit(-1) if __name__ == "__main__": _test()
30.727376
100
0.527758
d92d71692e0f7e170a038cd347f7ef6e9151cbb9
3,827
py
Python
ucscentralsdk/mometa/fabric/FabricPooledVlan.py
ragupta-git/ucscentralsdk
2678008b5fb6b0fafafec388d0874147e95a1086
[ "Apache-2.0" ]
null
null
null
ucscentralsdk/mometa/fabric/FabricPooledVlan.py
ragupta-git/ucscentralsdk
2678008b5fb6b0fafafec388d0874147e95a1086
[ "Apache-2.0" ]
null
null
null
ucscentralsdk/mometa/fabric/FabricPooledVlan.py
ragupta-git/ucscentralsdk
2678008b5fb6b0fafafec388d0874147e95a1086
[ "Apache-2.0" ]
null
null
null
"""This module contains the general information for FabricPooledVlan ManagedObject.""" from ...ucscentralmo import ManagedObject from ...ucscentralcoremeta import UcsCentralVersion, MoPropertyMeta, MoMeta from ...ucscentralmeta import VersionMeta class FabricPooledVlanConsts(): CONS_CNT_ASSIGNED_TO_SINGLE = "assigned-to-single" CONS_CNT_AVAILABLE = "available" class FabricPooledVlan(ManagedObject): """This is FabricPooledVlan class.""" consts = FabricPooledVlanConsts() naming_props = set([u'name']) mo_meta = MoMeta("FabricPooledVlan", "fabricPooledVlan", "net-[name]", VersionMeta.Version111a, "InputOutput", 0x1f, [], ["admin", "ext-lan-config", "ext-lan-policy"], [], [], ["Add", "Get", "Remove"]) prop_meta = { "assigned_to_dn": MoPropertyMeta("assigned_to_dn", "assignedToDn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, 0, 256, None, [], []), "block_dn": MoPropertyMeta("block_dn", "blockDn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, 0, 510, None, [], []), "child_action": MoPropertyMeta("child_action", "childAction", "string", VersionMeta.Version111a, MoPropertyMeta.INTERNAL, None, None, None, r"""((deleteAll|ignore|deleteNonPresent),){0,2}(deleteAll|ignore|deleteNonPresent){0,1}""", [], []), "cons_cnt": MoPropertyMeta("cons_cnt", "consCnt", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, None, None, None, ["assigned-to-single", "available"], ["0-4294967295"]), "dn": MoPropertyMeta("dn", "dn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, 0x2, 0, 256, None, [], []), "id_released_time": MoPropertyMeta("id_released_time", "idReleasedTime", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, None, None, r"""([0-9]){4}-([0-9]){2}-([0-9]){2}T([0-9]){2}:([0-9]){2}:([0-9]){2}((\.([0-9]){3})){0,1}""", [], []), "name": MoPropertyMeta("name", "name", "string", VersionMeta.Version111a, MoPropertyMeta.NAMING, 0x4, 1, 510, None, [], []), "peer_dn": MoPropertyMeta("peer_dn", "peerDn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, 0, 256, None, [], []), "poolable_dn": MoPropertyMeta("poolable_dn", "poolableDn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, 0, 256, None, [], []), "prev_assigned_to_dn": MoPropertyMeta("prev_assigned_to_dn", "prevAssignedToDn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, None, 0, 256, None, [], []), "rn": MoPropertyMeta("rn", "rn", "string", VersionMeta.Version111a, MoPropertyMeta.READ_ONLY, 0x8, 0, 256, None, [], []), "status": MoPropertyMeta("status", "status", "string", VersionMeta.Version111a, MoPropertyMeta.READ_WRITE, 0x10, None, None, r"""((removed|created|modified|deleted),){0,3}(removed|created|modified|deleted){0,1}""", [], []), } prop_map = { "assignedToDn": "assigned_to_dn", "blockDn": "block_dn", "childAction": "child_action", "consCnt": "cons_cnt", "dn": "dn", "idReleasedTime": "id_released_time", "name": "name", "peerDn": "peer_dn", "poolableDn": "poolable_dn", "prevAssignedToDn": "prev_assigned_to_dn", "rn": "rn", "status": "status", } def __init__(self, parent_mo_or_dn, name, **kwargs): self._dirty_mask = 0 self.name = name self.assigned_to_dn = None self.block_dn = None self.child_action = None self.cons_cnt = None self.id_released_time = None self.peer_dn = None self.poolable_dn = None self.prev_assigned_to_dn = None self.status = None ManagedObject.__init__(self, "FabricPooledVlan", parent_mo_or_dn, **kwargs)
57.984848
264
0.652208
80382c45a02787bbdae23f63e7fe2ba18d9fb319
88
py
Python
Python Pattern Programs/Alphabetic Patterns/Pattern 2 Alternative.py
trial1user/Printing-Pattern-Programs
dde29e056b8e067fb3a824edb7ecb7dd9c9a776a
[ "MIT" ]
null
null
null
Python Pattern Programs/Alphabetic Patterns/Pattern 2 Alternative.py
trial1user/Printing-Pattern-Programs
dde29e056b8e067fb3a824edb7ecb7dd9c9a776a
[ "MIT" ]
null
null
null
Python Pattern Programs/Alphabetic Patterns/Pattern 2 Alternative.py
trial1user/Printing-Pattern-Programs
dde29e056b8e067fb3a824edb7ecb7dd9c9a776a
[ "MIT" ]
null
null
null
#Alternative for x in 'ABCDE': for y in 'ABCDE': print(y,end="") print()
17.6
23
0.534091
4a86fa4255e4f6058bdbadb7986c9b30c008f086
16,978
py
Python
Geometry/HcalCommonData/python/testGeometry17aXML_cfi.py
eric-moreno/cmssw
3dc2c26f276632ac8357ac7b52675f04649e3903
[ "Apache-2.0" ]
null
null
null
Geometry/HcalCommonData/python/testGeometry17aXML_cfi.py
eric-moreno/cmssw
3dc2c26f276632ac8357ac7b52675f04649e3903
[ "Apache-2.0" ]
7
2016-07-17T02:34:54.000Z
2019-08-13T07:58:37.000Z
Geometry/HcalCommonData/python/testGeometry17aXML_cfi.py
eric-moreno/cmssw
3dc2c26f276632ac8357ac7b52675f04649e3903
[ "Apache-2.0" ]
2
2019-09-27T08:33:22.000Z
2019-11-14T10:52:30.000Z
import FWCore.ParameterSet.Config as cms XMLIdealGeometryESSource = cms.ESSource("XMLIdealGeometryESSource", geomXMLFiles = cms.vstring('Geometry/CMSCommonData/data/materials.xml', 'Geometry/CMSCommonData/data/rotations.xml', 'Geometry/CMSCommonData/data/extend/cmsextent.xml', 'Geometry/CMSCommonData/data/cms/2017/v1/cms.xml', 'Geometry/CMSCommonData/data/cmsMother.xml', 'Geometry/CMSCommonData/data/eta3/etaMax.xml', 'Geometry/CMSCommonData/data/cmsTracker.xml', 'Geometry/CMSCommonData/data/caloBase/2017/v1/caloBase.xml', 'Geometry/CMSCommonData/data/cmsCalo.xml', 'Geometry/CMSCommonData/data/muonBase.xml', 'Geometry/CMSCommonData/data/cmsMuon.xml', 'Geometry/CMSCommonData/data/mgnt.xml', 'Geometry/CMSCommonData/data/beampipe/2017/v1/beampipe.xml', 'Geometry/CMSCommonData/data/cmsBeam.xml', 'Geometry/CMSCommonData/data/muonMB.xml', 'Geometry/CMSCommonData/data/muonMagnet.xml', 'Geometry/CMSCommonData/data/cavern.xml', 'Geometry/TrackerCommonData/data/PhaseI/trackerParameters.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdMaterials.xml', 'Geometry/TrackerCommonData/data/pixfwdCommon.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdCylinder.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwd.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdDisks.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdSupportRingParameters.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdInnerDiskZplus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdInnerDiskZminus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdOuterDiskZplus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdOuterDiskZminus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdbladeInnerZplus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdbladeInnerZminus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdbladeOuterZplus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixfwdbladeOuterZminus.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarmaterial.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarladder.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarladderfull0.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarladderfull1.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarladderfull2.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarladderfull3.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarlayer.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarlayer0.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarlayer1.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarlayer2.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbarlayer3.xml', 'Geometry/TrackerCommonData/data/PhaseI/pixbar.xml', 'Geometry/TrackerCommonData/data/Run2/trackerpatchpannel.xml', 'Geometry/TrackerCommonData/data/Run2/trackerpixelnose.xml', 'Geometry/TrackerCommonData/data/tibtidcommonmaterial.xml', 'Geometry/TrackerCommonData/data/tibmaterial.xml', 'Geometry/TrackerCommonData/data/tibmodpar.xml', 'Geometry/TrackerCommonData/data/tibmodule0.xml', 'Geometry/TrackerCommonData/data/tibmodule0a.xml', 'Geometry/TrackerCommonData/data/tibmodule0b.xml', 'Geometry/TrackerCommonData/data/tibmodule2.xml', 'Geometry/TrackerCommonData/data/tibstringpar.xml', 'Geometry/TrackerCommonData/data/tibstring0ll.xml', 'Geometry/TrackerCommonData/data/tibstring0lr.xml', 'Geometry/TrackerCommonData/data/tibstring0ul.xml', 'Geometry/TrackerCommonData/data/tibstring0ur.xml', 'Geometry/TrackerCommonData/data/tibstring0.xml', 'Geometry/TrackerCommonData/data/tibstring1ll.xml', 'Geometry/TrackerCommonData/data/tibstring1lr.xml', 'Geometry/TrackerCommonData/data/tibstring1ul.xml', 'Geometry/TrackerCommonData/data/tibstring1ur.xml', 'Geometry/TrackerCommonData/data/tibstring1.xml', 'Geometry/TrackerCommonData/data/tibstring2ll.xml', 'Geometry/TrackerCommonData/data/tibstring2lr.xml', 'Geometry/TrackerCommonData/data/tibstring2ul.xml', 'Geometry/TrackerCommonData/data/tibstring2ur.xml', 'Geometry/TrackerCommonData/data/tibstring2.xml', 'Geometry/TrackerCommonData/data/tibstring3ll.xml', 'Geometry/TrackerCommonData/data/tibstring3lr.xml', 'Geometry/TrackerCommonData/data/tibstring3ul.xml', 'Geometry/TrackerCommonData/data/tibstring3ur.xml', 'Geometry/TrackerCommonData/data/tibstring3.xml', 'Geometry/TrackerCommonData/data/tiblayerpar.xml', 'Geometry/TrackerCommonData/data/tiblayer0.xml', 'Geometry/TrackerCommonData/data/tiblayer1.xml', 'Geometry/TrackerCommonData/data/tiblayer2.xml', 'Geometry/TrackerCommonData/data/tiblayer3.xml', 'Geometry/TrackerCommonData/data/tib.xml', 'Geometry/TrackerCommonData/data/tidmaterial.xml', 'Geometry/TrackerCommonData/data/tidmodpar.xml', 'Geometry/TrackerCommonData/data/tidmodule0.xml', 'Geometry/TrackerCommonData/data/tidmodule0r.xml', 'Geometry/TrackerCommonData/data/tidmodule0l.xml', 'Geometry/TrackerCommonData/data/tidmodule1.xml', 'Geometry/TrackerCommonData/data/tidmodule1r.xml', 'Geometry/TrackerCommonData/data/tidmodule1l.xml', 'Geometry/TrackerCommonData/data/tidmodule2.xml', 'Geometry/TrackerCommonData/data/tidringpar.xml', 'Geometry/TrackerCommonData/data/tidring0.xml', 'Geometry/TrackerCommonData/data/tidring0f.xml', 'Geometry/TrackerCommonData/data/tidring0b.xml', 'Geometry/TrackerCommonData/data/tidring1.xml', 'Geometry/TrackerCommonData/data/tidring1f.xml', 'Geometry/TrackerCommonData/data/tidring1b.xml', 'Geometry/TrackerCommonData/data/tidring2.xml', 'Geometry/TrackerCommonData/data/tid.xml', 'Geometry/TrackerCommonData/data/tidf.xml', 'Geometry/TrackerCommonData/data/tidb.xml', 'Geometry/TrackerCommonData/data/tibtidservices.xml', 'Geometry/TrackerCommonData/data/tibtidservicesf.xml', 'Geometry/TrackerCommonData/data/tibtidservicesb.xml', 'Geometry/TrackerCommonData/data/tobmaterial.xml', 'Geometry/TrackerCommonData/data/tobmodpar.xml', 'Geometry/TrackerCommonData/data/tobmodule0.xml', 'Geometry/TrackerCommonData/data/tobmodule2.xml', 'Geometry/TrackerCommonData/data/tobmodule4.xml', 'Geometry/TrackerCommonData/data/tobrodpar.xml', 'Geometry/TrackerCommonData/data/tobrod0c.xml', 'Geometry/TrackerCommonData/data/tobrod0l.xml', 'Geometry/TrackerCommonData/data/tobrod0h.xml', 'Geometry/TrackerCommonData/data/tobrod0.xml', 'Geometry/TrackerCommonData/data/tobrod1l.xml', 'Geometry/TrackerCommonData/data/tobrod1h.xml', 'Geometry/TrackerCommonData/data/tobrod1.xml', 'Geometry/TrackerCommonData/data/tobrod2c.xml', 'Geometry/TrackerCommonData/data/tobrod2l.xml', 'Geometry/TrackerCommonData/data/tobrod2h.xml', 'Geometry/TrackerCommonData/data/tobrod2.xml', 'Geometry/TrackerCommonData/data/tobrod3l.xml', 'Geometry/TrackerCommonData/data/tobrod3h.xml', 'Geometry/TrackerCommonData/data/tobrod3.xml', 'Geometry/TrackerCommonData/data/tobrod4c.xml', 'Geometry/TrackerCommonData/data/tobrod4l.xml', 'Geometry/TrackerCommonData/data/tobrod4h.xml', 'Geometry/TrackerCommonData/data/tobrod4.xml', 'Geometry/TrackerCommonData/data/tobrod5l.xml', 'Geometry/TrackerCommonData/data/tobrod5h.xml', 'Geometry/TrackerCommonData/data/tobrod5.xml', 'Geometry/TrackerCommonData/data/v2/tob.xml', 'Geometry/TrackerCommonData/data/tecmaterial.xml', 'Geometry/TrackerCommonData/data/tecmodpar.xml', 'Geometry/TrackerCommonData/data/tecmodule0.xml', 'Geometry/TrackerCommonData/data/tecmodule0r.xml', 'Geometry/TrackerCommonData/data/tecmodule0s.xml', 'Geometry/TrackerCommonData/data/tecmodule1.xml', 'Geometry/TrackerCommonData/data/tecmodule1r.xml', 'Geometry/TrackerCommonData/data/tecmodule1s.xml', 'Geometry/TrackerCommonData/data/tecmodule2.xml', 'Geometry/TrackerCommonData/data/tecmodule3.xml', 'Geometry/TrackerCommonData/data/tecmodule4.xml', 'Geometry/TrackerCommonData/data/tecmodule4r.xml', 'Geometry/TrackerCommonData/data/tecmodule4s.xml', 'Geometry/TrackerCommonData/data/tecmodule5.xml', 'Geometry/TrackerCommonData/data/tecmodule6.xml', 'Geometry/TrackerCommonData/data/tecpetpar.xml', 'Geometry/TrackerCommonData/data/tecring0.xml', 'Geometry/TrackerCommonData/data/tecring1.xml', 'Geometry/TrackerCommonData/data/tecring2.xml', 'Geometry/TrackerCommonData/data/tecring3.xml', 'Geometry/TrackerCommonData/data/tecring4.xml', 'Geometry/TrackerCommonData/data/tecring5.xml', 'Geometry/TrackerCommonData/data/tecring6.xml', 'Geometry/TrackerCommonData/data/tecring0f.xml', 'Geometry/TrackerCommonData/data/tecring1f.xml', 'Geometry/TrackerCommonData/data/tecring2f.xml', 'Geometry/TrackerCommonData/data/tecring3f.xml', 'Geometry/TrackerCommonData/data/tecring4f.xml', 'Geometry/TrackerCommonData/data/tecring5f.xml', 'Geometry/TrackerCommonData/data/tecring6f.xml', 'Geometry/TrackerCommonData/data/tecring0b.xml', 'Geometry/TrackerCommonData/data/tecring1b.xml', 'Geometry/TrackerCommonData/data/tecring2b.xml', 'Geometry/TrackerCommonData/data/tecring3b.xml', 'Geometry/TrackerCommonData/data/tecring4b.xml', 'Geometry/TrackerCommonData/data/tecring5b.xml', 'Geometry/TrackerCommonData/data/tecring6b.xml', 'Geometry/TrackerCommonData/data/tecpetalf.xml', 'Geometry/TrackerCommonData/data/tecpetalb.xml', 'Geometry/TrackerCommonData/data/tecpetal0.xml', 'Geometry/TrackerCommonData/data/tecpetal0f.xml', 'Geometry/TrackerCommonData/data/tecpetal0b.xml', 'Geometry/TrackerCommonData/data/tecpetal3.xml', 'Geometry/TrackerCommonData/data/tecpetal3f.xml', 'Geometry/TrackerCommonData/data/tecpetal3b.xml', 'Geometry/TrackerCommonData/data/tecpetal6f.xml', 'Geometry/TrackerCommonData/data/tecpetal6b.xml', 'Geometry/TrackerCommonData/data/tecpetal8f.xml', 'Geometry/TrackerCommonData/data/tecpetal8b.xml', 'Geometry/TrackerCommonData/data/tecwheel.xml', 'Geometry/TrackerCommonData/data/tecwheela.xml', 'Geometry/TrackerCommonData/data/tecwheelb.xml', 'Geometry/TrackerCommonData/data/tecwheelc.xml', 'Geometry/TrackerCommonData/data/tecwheeld.xml', 'Geometry/TrackerCommonData/data/tecwheel6.xml', 'Geometry/TrackerCommonData/data/tecservices.xml', 'Geometry/TrackerCommonData/data/tecbackplate.xml', 'Geometry/TrackerCommonData/data/tec.xml', 'Geometry/TrackerCommonData/data/Run2/trackermaterial.xml', 'Geometry/TrackerCommonData/data/Run2/tracker.xml', 'Geometry/TrackerCommonData/data/trackerpixbar.xml', 'Geometry/TrackerCommonData/data/PhaseI/trackerpixfwd.xml', 'Geometry/TrackerCommonData/data/trackertibtidservices.xml', 'Geometry/TrackerCommonData/data/trackertib.xml', 'Geometry/TrackerCommonData/data/trackertid.xml', 'Geometry/TrackerCommonData/data/trackertob.xml', 'Geometry/TrackerCommonData/data/trackertec.xml', 'Geometry/TrackerCommonData/data/v2/trackerbulkhead.xml', 'Geometry/TrackerCommonData/data/trackerother.xml', 'Geometry/EcalCommonData/data/eregalgo/2017/v1/eregalgo.xml', 'Geometry/EcalCommonData/data/ebalgo.xml', 'Geometry/EcalCommonData/data/ebcon.xml', 'Geometry/EcalCommonData/data/ebrot.xml', 'Geometry/EcalCommonData/data/eecon.xml', 'Geometry/EcalCommonData/data/eefixed.xml', 'Geometry/EcalCommonData/data/eehier.xml', 'Geometry/EcalCommonData/data/eealgo.xml', 'Geometry/EcalCommonData/data/escon.xml', 'Geometry/EcalCommonData/data/esalgo.xml', 'Geometry/EcalCommonData/data/eeF.xml', 'Geometry/EcalCommonData/data/eeB.xml', 'Geometry/EcalCommonData/data/ectkcable.xml', 'Geometry/HcalCommonData/data/hcalrotations.xml', 'Geometry/HcalCommonData/data/hcal/PhaseI/hcalalgo.xml', 'Geometry/HcalCommonData/data/hcalcablealgo.xml', 'Geometry/HcalCommonData/data/hcalbarrelalgo.xml', 'Geometry/HcalCommonData/data/hcalendcap/PhaseI/hcalendcapalgo.xml', 'Geometry/HcalCommonData/data/hcalouteralgo.xml', 'Geometry/HcalCommonData/data/hcalforwardalgo.xml', 'Geometry/HcalCommonData/data/average/hcalforwardmaterial.xml', 'Geometry/HcalCommonData/data/hcalSimNumbering/2017Plan0/hcalSimNumbering.xml', 'Geometry/HcalCommonData/data/hcalRecNumbering/2017/hcalRecNumbering.xml', 'Geometry/MuonCommonData/data/mbCommon/2017/v1/mbCommon.xml', 'Geometry/MuonCommonData/data/mb1/2015/v1/mb1.xml', 'Geometry/MuonCommonData/data/mb2/2015/v1/mb2.xml', 'Geometry/MuonCommonData/data/mb3/2015/v1/mb3.xml', 'Geometry/MuonCommonData/data/mb4/2015/v1/mb4.xml', 'Geometry/MuonCommonData/data/design/muonYoke.xml', 'Geometry/MuonCommonData/data/mf/2017/v1/mf.xml', 'Geometry/MuonCommonData/data/rpcf/2015/v1/rpcf.xml', 'Geometry/MuonCommonData/data/csc/2015/v1/csc.xml', 'Geometry/MuonCommonData/data/mfshield/2017/v1/mfshield.xml', 'Geometry/MuonCommonData/data/gemf/TDR_BaseLine/gemf.xml', 'Geometry/MuonCommonData/data/gem11/2017/v1/gem11.xml', 'Geometry/ForwardCommonData/data/forward.xml', 'Geometry/ForwardCommonData/data/forwardshield/2015/v1/forwardshield.xml', 'Geometry/ForwardCommonData/data/brmrotations.xml', 'Geometry/ForwardCommonData/data/brm.xml', 'Geometry/ForwardCommonData/data/Run2/totemMaterials.xml', 'Geometry/ForwardCommonData/data/totemRotations.xml', 'Geometry/ForwardCommonData/data/Run2/totemt1.xml', 'Geometry/ForwardCommonData/data/Run2/totemt2.xml', 'Geometry/ForwardCommonData/data/ionpump.xml', 'Geometry/ForwardCommonData/data/Run2/castor.xml', 'Geometry/ForwardCommonData/data/zdcmaterials.xml', 'Geometry/ForwardCommonData/data/lumimaterials.xml', 'Geometry/ForwardCommonData/data/zdcrotations.xml', 'Geometry/ForwardCommonData/data/lumirotations.xml', 'Geometry/ForwardCommonData/data/zdc.xml', 'Geometry/ForwardCommonData/data/zdclumi.xml', 'Geometry/ForwardCommonData/data/cmszdc.xml')+cms.vstring( 'Geometry/MuonCommonData/data/muonNumbering/2017/v1/muonNumbering.xml', 'Geometry/TrackerCommonData/data/PhaseI/trackerStructureTopology.xml', 'Geometry/TrackerSimData/data/PhaseI/trackersens.xml', 'Geometry/TrackerRecoData/data/PhaseI/trackerRecoMaterial.xml', 'Geometry/EcalSimData/data/ecalsens.xml', 'Geometry/HcalCommonData/data/hcalsenspmf.xml', 'Geometry/HcalSimData/data/hf.xml', 'Geometry/HcalSimData/data/hfpmt.xml', 'Geometry/HcalSimData/data/hffibrebundle.xml', 'Geometry/HcalSimData/data/CaloUtil.xml', 'Geometry/MuonSimData/data/v2/muonSens.xml', 'Geometry/DTGeometryBuilder/data/dtSpecsFilter.xml', 'Geometry/CSCGeometryBuilder/data/cscSpecsFilter.xml', 'Geometry/CSCGeometryBuilder/data/cscSpecs.xml', 'Geometry/RPCGeometryBuilder/data/RPCSpecs.xml', 'Geometry/GEMGeometryBuilder/data/GEMSpecsFilter17.xml', 'Geometry/GEMGeometryBuilder/data/v4/GEMSpecs.xml', 'Geometry/ForwardCommonData/data/brmsens.xml', 'Geometry/ForwardSimData/data/castorsens.xml', 'Geometry/ForwardSimData/data/zdcsens.xml', 'Geometry/HcalSimData/data/HcalProdCuts.xml', 'Geometry/EcalSimData/data/EcalProdCuts.xml', 'Geometry/EcalSimData/data/ESProdCuts.xml', 'Geometry/TrackerSimData/data/PhaseI/trackerProdCuts.xml', 'Geometry/TrackerSimData/data/trackerProdCutsBEAM.xml', 'Geometry/MuonSimData/data/muonProdCuts.xml', 'Geometry/ForwardSimData/data/CastorProdCuts.xml', 'Geometry/ForwardSimData/data/zdcProdCuts.xml', 'Geometry/ForwardSimData/data/ForwardShieldProdCuts.xml', 'Geometry/CMSCommonData/data/FieldParameters.xml'), rootNodeName = cms.string('cms:OCMS') )
58.544828
88
0.72482
e7a78f2b8ee17762e3b0dc88b35c3e4724709ba3
123
py
Python
udemy_pythonparatodos/mysql_connector.py
soamazyng/cursos-python
1a9d428597eca10bf0a0c9656625f2d36f67097f
[ "MIT" ]
null
null
null
udemy_pythonparatodos/mysql_connector.py
soamazyng/cursos-python
1a9d428597eca10bf0a0c9656625f2d36f67097f
[ "MIT" ]
null
null
null
udemy_pythonparatodos/mysql_connector.py
soamazyng/cursos-python
1a9d428597eca10bf0a0c9656625f2d36f67097f
[ "MIT" ]
null
null
null
import mysql.connector conexao = mysql.connector.connect(user='root', password='', host='', database='') conexao.close()
20.5
81
0.715447
1c0b1c9931c61e187a68163d88e3dc650f1f14a5
7,939
py
Python
satstac/sentinel/main.py
samsammurphy/sat-stac-sentinel
2ffbcc8e47cec32809e9661995c6e157b034fb26
[ "MIT" ]
1
2020-03-02T09:43:32.000Z
2020-03-02T09:43:32.000Z
satstac/sentinel/main.py
samsammurphy/sat-stac-sentinel
2ffbcc8e47cec32809e9661995c6e157b034fb26
[ "MIT" ]
null
null
null
satstac/sentinel/main.py
samsammurphy/sat-stac-sentinel
2ffbcc8e47cec32809e9661995c6e157b034fb26
[ "MIT" ]
null
null
null
import boto3 import gzip import json import logging import requests import sys import numpy as np import os.path as op from shapely.geometry import MultiPoint, Point from shapely import geometry from datetime import datetime, timedelta from dateutil.parser import parse from pyproj import Proj, transform as reproj from satstac import Collection, Item, utils from .utils import get_matching_s3_keys, read_from_s3 from .version import __version__ logger = logging.getLogger(__name__) _collection = Collection.open(op.join(op.dirname(__file__), 'sentinel-2-l1c.json')) SETTINGS = { 'roda_url': 'https://roda.sentinel-hub.com/sentinel-s2-l1c', 's3_url': 'https://sentinel-s2-l1c.s3.amazonaws.com', 'inv_bucket': 'sentinel-inventory', 'inv_key': 'sentinel-s2-l1c/sentinel-s2-l1c-inventory', 'path_pattern': '${sentinel:utm_zone}/${sentinel:latitude_band}/${sentinel:grid_square}', 'fname_pattern': '${date}/${id}' } def add_items(catalog, records, start_date=None, end_date=None, s3meta=False, prefix=None, publish=None): """ Stream records to a collection with a transform function Keyword arguments: start_date -- Process this date and after end_date -- Process this date and earlier s3meta -- Retrieve metadata from s3 rather than Sinergise URL (roda) """ # use existing collection or create new one if it doesn't exist cols = {c.id: c for c in catalog.collections()} if 'sentinel-2-l1c' not in cols.keys(): catalog.add_catalog(_collection) cols = {c.id: c for c in catalog.collections()} collection = cols['sentinel-2-l1c'] client = None if publish: parts = publish.split(':') client = boto3.client('sns', region_name=parts[3]) duration = [] # iterate through records for i, record in enumerate(records): start = datetime.now() if i % 50000 == 0: logger.info('%s: Scanned %s records' % (start, str(i))) dt = record['datetime'].date() if prefix is not None: # if path doesn't match provided prefix skip to next record if record['path'][:len(prefix)] != prefix: continue if s3meta: url = op.join(SETTINGS['s3_url'], record['path']) else: url = op.join(SETTINGS['roda_url'], record['path']) #if i == 10: # break if (start_date is not None and dt < start_date) or (end_date is not None and dt > end_date): # skip to next if before start_date continue try: if s3meta: signed_url, headers = utils.get_s3_signed_url(url, requestor_pays=True) resp = requests.get(signed_url, headers=headers) metadata = json.loads(resp.text) else: metadata = read_remote(url) item = transform(metadata) except Exception as err: logger.error('Error creating STAC Item %s: %s' % (record['path'], err)) continue try: collection.add_item(item, path=SETTINGS['path_pattern'], filename=SETTINGS['fname_pattern']) if client: client.publish(TopicArn=publish, Message=json.dumps(item.data)) duration.append((datetime.now()-start).total_seconds()) logger.info('Ingested %s in %s' % (item.filename, duration[-1])) except Exception as err: logger.error('Error adding %s: %s' % (item.id, err)) logger.info('Read in %s records averaging %4.2f sec (%4.2f stddev)' % (i, np.mean(duration), np.std(duration))) def read_inventory(filename): """ Create generator from inventory file """ with open(filename) as f: line = f.readline() if 'datetime' not in line: parts = line.split(',') yield { 'datetime': parse(parts[0]), 'path': parts[1].strip('\n') } for line in f.readlines(): parts = line.split(',') yield { 'datetime': parse(parts[0]), 'path': parts[1].strip('\n') } def latest_inventory(): """ Return generator function for list of scenes """ s3 = boto3.client('s3') # get latest file today = datetime.now() key = None for dt in [today, today - timedelta(1)]: prefix = op.join(SETTINGS['inv_key'], dt.strftime('%Y-%m-%d')) keys = [k for k in get_matching_s3_keys(SETTINGS['inv_bucket'], prefix=prefix, suffix='manifest.json')] if len(keys) == 1: key = keys[0] break if key: manifest = json.loads(read_from_s3(SETTINGS['inv_bucket'], key)) for f in manifest.get('files', []): inv = read_from_s3(SETTINGS['inv_bucket'], f['key']).split('\n') inv = [i.replace('"', '').split(',') for i in inv if 'tileInfo.json' in i] for info in inv: yield { 'datetime': parse(info[3]), 'path': info[1] } def transform(data): """ Transform Sentinel metadata (from tileInfo.json) into a STAC item """ dt = parse(data['timestamp']) epsg = data['tileOrigin']['crs']['properties']['name'].split(':')[-1] url = op.join(SETTINGS['s3_url'], data['path']) roda_url = op.join(SETTINGS['roda_url'], data['path']) # geo coordinates = data['tileDataGeometry']['coordinates'] ys = [c[1] for c in coordinates[0]] xs = [c[0] for c in coordinates[0]] p1 = Proj(init='epsg:%s' % epsg) p2 = Proj(init='epsg:4326') lons, lats = reproj(p1, p2, xs, ys) bbox = [min(lons), min(lats), max(lons), max(lats)] coordinates = [[[lons[i], lats[i]] for i in range(0, len(lons))]] geom = geometry.mapping(geometry.Polygon(coordinates[0]).convex_hull) assets = _collection.data['assets'] assets = utils.dict_merge(assets, { 'thumbnail': {'href': op.join(roda_url, 'preview.jpg')}, 'info': {'href': op.join(roda_url, 'tileInfo.json')}, 'metadata': {'href': op.join(roda_url, 'metadata.xml')}, 'tki': {'href': op.join(url, 'TKI.jp2')}, 'B01': {'href': op.join(url, 'B01.jp2')}, 'B02': {'href': op.join(url, 'B02.jp2')}, 'B03': {'href': op.join(url, 'B03.jp2')}, 'B04': {'href': op.join(url, 'B04.jp2')}, 'B05': {'href': op.join(url, 'B05.jp2')}, 'B06': {'href': op.join(url, 'B06.jp2')}, 'B07': {'href': op.join(url, 'B07.jp2')}, 'B08': {'href': op.join(url, 'B08.jp2')}, 'B8A': {'href': op.join(url, 'B08.jp2')}, 'B09': {'href': op.join(url, 'B09.jp2')}, 'B10': {'href': op.join(url, 'B10.jp2')}, 'B11': {'href': op.join(url, 'B11.jp2')}, 'B12': {'href': op.join(url, 'B11.jp2')} }) #if dt < datetime(2016,12,6): # del assets['tki'] props = { 'collection': 'sentinel-2-l1c', 'datetime': dt.isoformat(), 'eo:platform': 'sentinel-2%s' % data['productName'][2].lower(), 'eo:cloud_cover': float(data['cloudyPixelPercentage']), 'sentinel:utm_zone': data['utmZone'], 'sentinel:latitude_band': data['latitudeBand'], 'sentinel:grid_square': data['gridSquare'], 'sentinel:sequence': data['path'].split('/')[-1], 'sentinel:product_id': data['productName'] } sid = str(data['utmZone']) + data['latitudeBand'] + data['gridSquare'] id = '%s_%s_%s_%s' % (data['productName'][0:3], sid, dt.strftime('%Y%m%d'), props['sentinel:sequence'] ) _item = { 'type': 'Feature', 'id': id, 'bbox': bbox, 'geometry': geom, 'properties':props, 'assets': assets } return Item(_item) def read_remote(url): """ Retrieve remote JSON """ # Read JSON file remotely r = requests.get(url, stream=True) metadata = json.loads(r.text) return metadata
36.75463
115
0.577655
b5e6638d2411b9a3e2c298a92f87035f0062c35a
44,203
py
Python
nova/virt/libvirt/config.py
osrg/nova
14b6bc655145c832bd9c822e48f877818e0e53ff
[ "Apache-2.0" ]
null
null
null
nova/virt/libvirt/config.py
osrg/nova
14b6bc655145c832bd9c822e48f877818e0e53ff
[ "Apache-2.0" ]
null
null
null
nova/virt/libvirt/config.py
osrg/nova
14b6bc655145c832bd9c822e48f877818e0e53ff
[ "Apache-2.0" ]
null
null
null
# vim: tabstop=4 shiftwidth=4 softtabstop=4 # Copyright (C) 2012-2013 Red Hat, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """ Configuration for libvirt objects. Classes to represent the configuration of various libvirt objects and support conversion to/from XML. These classes are solely concerned by providing direct Object <-> XML document conversions. No policy or operational decisions should be made by code in these classes. Such policy belongs in the 'designer.py' module which provides simplified helpers for populating up config object instances. """ from nova import exception from nova.openstack.common.gettextutils import _ from nova.openstack.common import log as logging from nova.openstack.common import units from lxml import etree LOG = logging.getLogger(__name__) class LibvirtConfigObject(object): def __init__(self, **kwargs): super(LibvirtConfigObject, self).__init__() self.root_name = kwargs.get("root_name") self.ns_prefix = kwargs.get('ns_prefix') self.ns_uri = kwargs.get('ns_uri') @staticmethod def _text_node(name, value): child = etree.Element(name) child.text = str(value) return child def format_dom(self): if self.ns_uri is None: return etree.Element(self.root_name) else: return etree.Element("{" + self.ns_uri + "}" + self.root_name, nsmap={self.ns_prefix: self.ns_uri}) def parse_str(self, xmlstr): self.parse_dom(etree.fromstring(xmlstr)) def parse_dom(self, xmldoc): if self.root_name != xmldoc.tag: raise exception.InvalidInput( "Root element name should be '%s' not '%s'" % (self.root_name, xmldoc.tag)) def to_xml(self, pretty_print=True): root = self.format_dom() xml_str = etree.tostring(root, pretty_print=pretty_print) LOG.debug(_("Generated XML %s "), (xml_str,)) return xml_str class LibvirtConfigCaps(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigCaps, self).__init__(root_name="capabilities", **kwargs) self.host = None self.guests = [] def parse_dom(self, xmldoc): super(LibvirtConfigCaps, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "host": host = LibvirtConfigCapsHost() host.parse_dom(c) self.host = host elif c.tag == "guest": guest = LibvirtConfigCapsGuest() guest.parse_dom(c) self.guests.append(guest) def format_dom(self): caps = super(LibvirtConfigCaps, self).format_dom() if self.host: caps.append(self.host.format_dom()) for g in self.guests: caps.append(g.format_dom()) return caps class LibvirtConfigCapsHost(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigCapsHost, self).__init__(root_name="host", **kwargs) self.cpu = None self.uuid = None def parse_dom(self, xmldoc): super(LibvirtConfigCapsHost, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "cpu": cpu = LibvirtConfigCPU() cpu.parse_dom(c) self.cpu = cpu elif c.tag == "uuid": self.uuid = c.text def format_dom(self): caps = super(LibvirtConfigCapsHost, self).format_dom() if self.uuid: caps.append(self._text_node("uuid", self.uuid)) if self.cpu: caps.append(self.cpu.format_dom()) return caps class LibvirtConfigCapsGuest(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigCapsGuest, self).__init__(root_name="guest", **kwargs) self.arch = None self.ostype = None self.domtype = list() def parse_dom(self, xmldoc): super(LibvirtConfigCapsGuest, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "os_type": self.ostype = c.text elif c.tag == "arch": self.arch = c.get("name") for sc in c.getchildren(): if sc.tag == "domain": self.domtype.append(sc.get("type")) def format_dom(self): caps = super(LibvirtConfigCapsGuest, self).format_dom() if self.ostype is not None: caps.append(self._text_node("os_type", self.ostype)) if self.arch: arch = etree.Element("arch", name=self.arch) for dt in self.domtype: dte = etree.Element("domain") dte.set("type", dt) arch.append(dte) caps.append(arch) return caps class LibvirtConfigGuestTimer(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestTimer, self).__init__(root_name="timer", **kwargs) self.name = "platform" self.track = None self.tickpolicy = None self.present = None def format_dom(self): tm = super(LibvirtConfigGuestTimer, self).format_dom() tm.set("name", self.name) if self.track is not None: tm.set("track", self.track) if self.tickpolicy is not None: tm.set("tickpolicy", self.tickpolicy) if self.present is not None: if self.present: tm.set("present", "yes") else: tm.set("present", "no") return tm class LibvirtConfigGuestClock(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestClock, self).__init__(root_name="clock", **kwargs) self.offset = "utc" self.adjustment = None self.timezone = None self.timers = [] def format_dom(self): clk = super(LibvirtConfigGuestClock, self).format_dom() clk.set("offset", self.offset) if self.adjustment: clk.set("adjustment", self.adjustment) elif self.timezone: clk.set("timezone", self.timezone) for tm in self.timers: clk.append(tm.format_dom()) return clk def add_timer(self, tm): self.timers.append(tm) class LibvirtConfigCPUFeature(LibvirtConfigObject): def __init__(self, name=None, **kwargs): super(LibvirtConfigCPUFeature, self).__init__(root_name='feature', **kwargs) self.name = name def parse_dom(self, xmldoc): super(LibvirtConfigCPUFeature, self).parse_dom(xmldoc) self.name = xmldoc.get("name") def format_dom(self): ft = super(LibvirtConfigCPUFeature, self).format_dom() ft.set("name", self.name) return ft class LibvirtConfigCPU(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigCPU, self).__init__(root_name='cpu', **kwargs) self.arch = None self.vendor = None self.model = None self.sockets = None self.cores = None self.threads = None self.features = [] def parse_dom(self, xmldoc): super(LibvirtConfigCPU, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "arch": self.arch = c.text elif c.tag == "model": self.model = c.text elif c.tag == "vendor": self.vendor = c.text elif c.tag == "topology": self.sockets = int(c.get("sockets")) self.cores = int(c.get("cores")) self.threads = int(c.get("threads")) elif c.tag == "feature": f = LibvirtConfigCPUFeature() f.parse_dom(c) self.add_feature(f) def format_dom(self): cpu = super(LibvirtConfigCPU, self).format_dom() if self.arch is not None: cpu.append(self._text_node("arch", self.arch)) if self.model is not None: cpu.append(self._text_node("model", self.model)) if self.vendor is not None: cpu.append(self._text_node("vendor", self.vendor)) if (self.sockets is not None and self.cores is not None and self.threads is not None): top = etree.Element("topology") top.set("sockets", str(self.sockets)) top.set("cores", str(self.cores)) top.set("threads", str(self.threads)) cpu.append(top) for f in self.features: cpu.append(f.format_dom()) return cpu def add_feature(self, feat): self.features.append(feat) class LibvirtConfigGuestCPUFeature(LibvirtConfigCPUFeature): def __init__(self, name=None, **kwargs): super(LibvirtConfigGuestCPUFeature, self).__init__(name, **kwargs) self.policy = "require" def format_dom(self): ft = super(LibvirtConfigGuestCPUFeature, self).format_dom() ft.set("policy", self.policy) return ft class LibvirtConfigGuestCPU(LibvirtConfigCPU): def __init__(self, **kwargs): super(LibvirtConfigGuestCPU, self).__init__(**kwargs) self.mode = None self.match = "exact" def parse_dom(self, xmldoc): super(LibvirtConfigGuestCPU, self).parse_dom(xmldoc) self.mode = xmldoc.get('mode') self.match = xmldoc.get('match') def format_dom(self): cpu = super(LibvirtConfigGuestCPU, self).format_dom() if self.mode: cpu.set("mode", self.mode) cpu.set("match", self.match) return cpu class LibvirtConfigGuestSMBIOS(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestSMBIOS, self).__init__(root_name="smbios", **kwargs) self.mode = "sysinfo" def format_dom(self): smbios = super(LibvirtConfigGuestSMBIOS, self).format_dom() smbios.set("mode", self.mode) return smbios class LibvirtConfigGuestSysinfo(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestSysinfo, self).__init__(root_name="sysinfo", **kwargs) self.type = "smbios" self.bios_vendor = None self.bios_version = None self.system_manufacturer = None self.system_product = None self.system_version = None self.system_serial = None self.system_uuid = None def format_dom(self): sysinfo = super(LibvirtConfigGuestSysinfo, self).format_dom() sysinfo.set("type", self.type) bios = None system = None if self.bios_vendor is not None: if bios is None: bios = etree.Element("bios") info = etree.Element("entry", name="vendor") info.text = self.bios_vendor bios.append(info) if self.bios_version is not None: if bios is None: bios = etree.Element("bios") info = etree.Element("entry", name="version") info.text = self.bios_version bios.append(info) if self.system_manufacturer is not None: if system is None: system = etree.Element("system") info = etree.Element("entry", name="manufacturer") info.text = self.system_manufacturer system.append(info) if self.system_product is not None: if system is None: system = etree.Element("system") info = etree.Element("entry", name="product") info.text = self.system_product system.append(info) if self.system_version is not None: if system is None: system = etree.Element("system") info = etree.Element("entry", name="version") info.text = self.system_version system.append(info) if self.system_serial is not None: if system is None: system = etree.Element("system") info = etree.Element("entry", name="serial") info.text = self.system_serial system.append(info) if self.system_uuid is not None: if system is None: system = etree.Element("system") info = etree.Element("entry", name="uuid") info.text = self.system_uuid system.append(info) if bios is not None: sysinfo.append(bios) if system is not None: sysinfo.append(system) return sysinfo class LibvirtConfigGuestDevice(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestDevice, self).__init__(**kwargs) class LibvirtConfigGuestDisk(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestDisk, self).__init__(root_name="disk", **kwargs) self.source_type = "file" self.source_device = "disk" self.driver_name = None self.driver_format = None self.driver_cache = None self.source_path = None self.source_protocol = None self.source_name = None self.source_hosts = [] self.source_ports = [] self.target_dev = None self.target_path = None self.target_bus = None self.auth_username = None self.auth_secret_type = None self.auth_secret_uuid = None self.serial = None self.disk_read_bytes_sec = None self.disk_read_iops_sec = None self.disk_write_bytes_sec = None self.disk_write_iops_sec = None self.disk_total_bytes_sec = None self.disk_total_iops_sec = None self.logical_block_size = None self.physical_block_size = None self.readonly = False self.snapshot = None def format_dom(self): dev = super(LibvirtConfigGuestDisk, self).format_dom() dev.set("type", self.source_type) dev.set("device", self.source_device) if (self.driver_name is not None or self.driver_format is not None or self.driver_cache is not None): drv = etree.Element("driver") if self.driver_name is not None: drv.set("name", self.driver_name) if self.driver_format is not None: drv.set("type", self.driver_format) if self.driver_cache is not None: drv.set("cache", self.driver_cache) dev.append(drv) if self.source_type == "file": dev.append(etree.Element("source", file=self.source_path)) elif self.source_type == "block": dev.append(etree.Element("source", dev=self.source_path)) elif self.source_type == "mount": dev.append(etree.Element("source", dir=self.source_path)) elif self.source_type == "network": source = etree.Element("source", protocol=self.source_protocol) if self.source_name is not None: source.set('name', self.source_name) hosts_info = zip(self.source_hosts, self.source_ports) for name, port in hosts_info: host = etree.Element('host', name=name) if port is not None: host.set('port', port) source.append(host) dev.append(source) if self.auth_secret_type is not None: auth = etree.Element("auth") auth.set("username", self.auth_username) auth.append(etree.Element("secret", type=self.auth_secret_type, uuid=self.auth_secret_uuid)) dev.append(auth) if self.source_type == "mount": dev.append(etree.Element("target", dir=self.target_path)) else: dev.append(etree.Element("target", dev=self.target_dev, bus=self.target_bus)) if self.serial is not None: dev.append(self._text_node("serial", self.serial)) iotune = etree.Element("iotune") if self.disk_read_bytes_sec is not None: iotune.append(self._text_node("read_bytes_sec", self.disk_read_bytes_sec)) if self.disk_read_iops_sec is not None: iotune.append(self._text_node("read_iops_sec", self.disk_read_iops_sec)) if self.disk_write_bytes_sec is not None: iotune.append(self._text_node("write_bytes_sec", self.disk_write_bytes_sec)) if self.disk_write_iops_sec is not None: iotune.append(self._text_node("write_iops_sec", self.disk_write_iops_sec)) if self.disk_total_bytes_sec is not None: iotune.append(self._text_node("total_bytes_sec", self.disk_total_bytes_sec)) if self.disk_total_iops_sec is not None: iotune.append(self._text_node("total_iops_sec", self.disk_total_iops_sec)) if len(iotune) > 0: dev.append(iotune) # Block size tuning if (self.logical_block_size is not None or self.physical_block_size is not None): blockio = etree.Element("blockio") if self.logical_block_size is not None: blockio.set('logical_block_size', self.logical_block_size) if self.physical_block_size is not None: blockio.set('physical_block_size', self.physical_block_size) dev.append(blockio) if self.readonly: dev.append(etree.Element("readonly")) return dev def parse_dom(self, xmldoc): super(LibvirtConfigGuestDisk, self).parse_dom(xmldoc) self.source_type = xmldoc.get('type') self.snapshot = xmldoc.get('snapshot') for c in xmldoc.getchildren(): if c.tag == 'driver': self.driver_name = c.get('name') self.driver_format = c.get('type') self.driver_cache = c.get('cache') elif c.tag == 'source': if self.source_type == 'file': self.source_path = c.get('file') elif self.source_type == 'block': self.source_path = c.get('dev') elif self.source_type == 'mount': self.source_path = c.get('dir') elif self.source_type == 'network': self.source_protocol = c.get('protocol') self.source_name = c.get('name') elif c.tag == 'serial': self.serial = c.text for c in xmldoc.getchildren(): if c.tag == 'target': if self.source_type == 'mount': self.target_path = c.get('dir') else: self.target_dev = c.get('dev') self.target_bus = c.get('bus', None) class LibvirtConfigGuestSnapshotDisk(LibvirtConfigObject): """Disk class for handling disk information in snapshots. Similar to LibvirtConfigGuestDisk, but used to represent disk entities in <domainsnapshot> structures rather than real devices. These typically have fewer members, and different expectations for which fields are required. """ def __init__(self, **kwargs): super(LibvirtConfigGuestSnapshotDisk, self).__init__(root_name="disk", **kwargs) self.source_type = None self.source_device = None self.name = None self.snapshot = None self.driver_name = None self.driver_format = None self.driver_cache = None self.source_path = None self.source_protocol = None self.source_name = None self.source_hosts = [] self.source_ports = [] self.target_dev = None self.target_path = None self.target_bus = None self.auth_username = None self.auth_secret_type = None self.auth_secret_uuid = None self.serial = None def format_dom(self): dev = super(LibvirtConfigGuestSnapshotDisk, self).format_dom() if self.name: dev.attrib['name'] = self.name if self.snapshot: dev.attrib['snapshot'] = self.snapshot if self.source_type: dev.set("type", self.source_type) if self.source_device: dev.set("device", self.source_device) if (self.driver_name is not None or self.driver_format is not None or self.driver_cache is not None): drv = etree.Element("driver") if self.driver_name is not None: drv.set("name", self.driver_name) if self.driver_format is not None: drv.set("type", self.driver_format) if self.driver_cache is not None: drv.set("cache", self.driver_cache) dev.append(drv) if self.source_type == "file": dev.append(etree.Element("source", file=self.source_path)) elif self.source_type == "block": dev.append(etree.Element("source", dev=self.source_path)) elif self.source_type == "mount": dev.append(etree.Element("source", dir=self.source_path)) elif self.source_type == "network": source = etree.Element("source", protocol=self.source_protocol) if self.source_name is not None: source.set('name', self.source_name) hosts_info = zip(self.source_hosts, self.source_ports) for name, port in hosts_info: host = etree.Element('host', name=name) if port is not None: host.set('port', port) source.append(host) dev.append(source) if self.auth_secret_type is not None: auth = etree.Element("auth") auth.set("username", self.auth_username) auth.append(etree.Element("secret", type=self.auth_secret_type, uuid=self.auth_secret_uuid)) dev.append(auth) if self.source_type == "mount": dev.append(etree.Element("target", dir=self.target_path)) else: if self.target_bus and self.target_dev: dev.append(etree.Element("target", dev=self.target_dev, bus=self.target_bus)) return dev def parse_dom(self, xmldoc): super(LibvirtConfigGuestSnapshotDisk, self).parse_dom(xmldoc) self.source_type = xmldoc.get('type') self.snapshot = xmldoc.get('snapshot') for c in xmldoc.getchildren(): if c.tag == 'driver': self.driver_name = c.get('name') self.driver_format = c.get('type') self.driver_cache = c.get('cache') elif c.tag == 'source': if self.source_type == 'file': self.source_path = c.get('file') elif self.source_type == 'block': self.source_path = c.get('dev') elif self.source_type == 'mount': self.source_path = c.get('dir') elif self.source_type == 'network': self.source_protocol = c.get('protocol') self.source_name = c.get('name') elif c.tag == 'serial': self.serial = c.text for c in xmldoc.getchildren(): if c.tag == 'target': if self.source_type == 'mount': self.target_path = c.get('dir') else: self.target_dev = c.get('dev') self.target_bus = c.get('bus', None) class LibvirtConfigGuestFilesys(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestFilesys, self).__init__(root_name="filesystem", **kwargs) self.source_type = "mount" self.source_dir = None self.target_dir = "/" def format_dom(self): dev = super(LibvirtConfigGuestFilesys, self).format_dom() dev.set("type", self.source_type) dev.append(etree.Element("source", dir=self.source_dir)) dev.append(etree.Element("target", dir=self.target_dir)) return dev class LibvirtConfigGuestInterface(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestInterface, self).__init__( root_name="interface", **kwargs) self.net_type = None self.target_dev = None self.model = None self.mac_addr = None self.script = None self.source_dev = None self.source_mode = "private" self.vporttype = None self.vportparams = [] self.filtername = None self.filterparams = [] self.driver_name = None self.vif_inbound_peak = None self.vif_inbound_burst = None self.vif_inbound_average = None self.vif_outbound_peak = None self.vif_outbound_burst = None self.vif_outbound_average = None def format_dom(self): dev = super(LibvirtConfigGuestInterface, self).format_dom() dev.set("type", self.net_type) dev.append(etree.Element("mac", address=self.mac_addr)) if self.model: dev.append(etree.Element("model", type=self.model)) if self.driver_name: dev.append(etree.Element("driver", name=self.driver_name)) if self.net_type == "ethernet": if self.script is not None: dev.append(etree.Element("script", path=self.script)) elif self.net_type == "direct": dev.append(etree.Element("source", dev=self.source_dev, mode=self.source_mode)) else: dev.append(etree.Element("source", bridge=self.source_dev)) if self.target_dev is not None: dev.append(etree.Element("target", dev=self.target_dev)) if self.vporttype is not None: vport = etree.Element("virtualport", type=self.vporttype) for p in self.vportparams: param = etree.Element("parameters") param.set(p['key'], p['value']) vport.append(param) dev.append(vport) if self.filtername is not None: filter = etree.Element("filterref", filter=self.filtername) for p in self.filterparams: filter.append(etree.Element("parameter", name=p['key'], value=p['value'])) dev.append(filter) if self.vif_inbound_average or self.vif_outbound_average: bandwidth = etree.Element("bandwidth") if self.vif_inbound_average is not None: vif_inbound = etree.Element("inbound", average=str(self.vif_inbound_average)) if self.vif_inbound_peak is not None: vif_inbound.set("peak", str(self.vif_inbound_peak)) if self.vif_inbound_burst is not None: vif_inbound.set("burst", str(self.vif_inbound_burst)) bandwidth.append(vif_inbound) if self.vif_outbound_average is not None: vif_outbound = etree.Element("outbound", average=str(self.vif_outbound_average)) if self.vif_outbound_peak is not None: vif_outbound.set("peak", str(self.vif_outbound_peak)) if self.vif_outbound_burst is not None: vif_outbound.set("burst", str(self.vif_outbound_burst)) bandwidth.append(vif_outbound) dev.append(bandwidth) return dev def add_filter_param(self, key, value): self.filterparams.append({'key': key, 'value': value}) def add_vport_param(self, key, value): self.vportparams.append({'key': key, 'value': value}) class LibvirtConfigGuestInput(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestInput, self).__init__(root_name="input", **kwargs) self.type = "tablet" self.bus = "usb" def format_dom(self): dev = super(LibvirtConfigGuestInput, self).format_dom() dev.set("type", self.type) dev.set("bus", self.bus) return dev class LibvirtConfigGuestGraphics(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestGraphics, self).__init__(root_name="graphics", **kwargs) self.type = "vnc" self.autoport = True self.keymap = None self.listen = None def format_dom(self): dev = super(LibvirtConfigGuestGraphics, self).format_dom() dev.set("type", self.type) if self.autoport: dev.set("autoport", "yes") else: dev.set("autoport", "no") if self.keymap: dev.set("keymap", self.keymap) if self.listen: dev.set("listen", self.listen) return dev class LibvirtConfigGuestVideo(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestVideo, self).__init__(root_name="video", **kwargs) self.type = 'cirrus' self.vram = None self.heads = None def format_dom(self): dev = super(LibvirtConfigGuestVideo, self).format_dom() model = etree.Element("model") model.set("type", self.type) if self.vram: model.set("vram", str(self.vram)) if self.heads: model.set("heads", str(self.heads)) dev.append(model) return dev class LibvirtConfigGuestHostdev(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestHostdev, self).\ __init__(root_name="hostdev", **kwargs) self.mode = kwargs.get('mode') self.type = kwargs.get('type') self.managed = 'yes' def format_dom(self): dev = super(LibvirtConfigGuestHostdev, self).format_dom() dev.set("mode", self.mode) dev.set("type", self.type) dev.set("managed", self.managed) return dev def parse_dom(self, xmldoc): super(LibvirtConfigGuestHostdev, self).parse_dom(xmldoc) self.mode = xmldoc.get('mode') self.type = xmldoc.get('type') self.managed = xmldoc.get('managed') return xmldoc.getchildren() class LibvirtConfigGuestHostdevPCI(LibvirtConfigGuestHostdev): def __init__(self, **kwargs): super(LibvirtConfigGuestHostdevPCI, self).\ __init__(mode='subsystem', type='pci', **kwargs) self.domain = None self.bus = None self.slot = None self.function = None def format_dom(self): dev = super(LibvirtConfigGuestHostdevPCI, self).format_dom() address = etree.Element("address", domain='0x' + self.domain, bus='0x' + self.bus, slot='0x' + self.slot, function='0x' + self.function) source = etree.Element("source") source.append(address) dev.append(source) return dev def parse_dom(self, xmldoc): childs = super(LibvirtConfigGuestHostdevPCI, self).parse_dom(xmldoc) for c in childs: if c.tag == "source": for sub in c.getchildren(): if sub.tag == 'address': self.domain = sub.get('domain') self.bus = sub.get('bus') self.slot = sub.get('slot') self.function = sub.get('function') class LibvirtConfigGuestCharBase(LibvirtConfigGuestDevice): def __init__(self, **kwargs): super(LibvirtConfigGuestCharBase, self).__init__(**kwargs) self.type = "pty" self.source_path = None def format_dom(self): dev = super(LibvirtConfigGuestCharBase, self).format_dom() dev.set("type", self.type) if self.type == "file": dev.append(etree.Element("source", path=self.source_path)) elif self.type == "unix": dev.append(etree.Element("source", mode="bind", path=self.source_path)) return dev class LibvirtConfigGuestChar(LibvirtConfigGuestCharBase): def __init__(self, **kwargs): super(LibvirtConfigGuestChar, self).__init__(**kwargs) self.target_port = None def format_dom(self): dev = super(LibvirtConfigGuestChar, self).format_dom() if self.target_port is not None: dev.append(etree.Element("target", port=str(self.target_port))) return dev class LibvirtConfigGuestSerial(LibvirtConfigGuestChar): def __init__(self, **kwargs): super(LibvirtConfigGuestSerial, self).__init__(root_name="serial", **kwargs) class LibvirtConfigGuestConsole(LibvirtConfigGuestChar): def __init__(self, **kwargs): super(LibvirtConfigGuestConsole, self).__init__(root_name="console", **kwargs) class LibvirtConfigGuestChannel(LibvirtConfigGuestCharBase): def __init__(self, **kwargs): super(LibvirtConfigGuestChannel, self).__init__(root_name="channel", **kwargs) self.target_type = "virtio" self.target_name = None def format_dom(self): dev = super(LibvirtConfigGuestChannel, self).format_dom() target = etree.Element("target", type=self.target_type) if self.target_name is not None: target.set("name", self.target_name) dev.append(target) return dev class LibvirtConfigGuest(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuest, self).__init__(root_name="domain", **kwargs) self.virt_type = None self.uuid = None self.name = None self.memory = 500 * units.Mi self.vcpus = 1 self.cpuset = None self.cpu = None self.cpu_shares = None self.cpu_quota = None self.cpu_period = None self.acpi = False self.apic = False self.clock = None self.sysinfo = None self.os_type = None self.os_loader = None self.os_kernel = None self.os_initrd = None self.os_cmdline = None self.os_root = None self.os_init_path = None self.os_boot_dev = [] self.os_smbios = None self.devices = [] def _format_basic_props(self, root): root.append(self._text_node("uuid", self.uuid)) root.append(self._text_node("name", self.name)) root.append(self._text_node("memory", self.memory)) if self.cpuset is not None: vcpu = self._text_node("vcpu", self.vcpus) vcpu.set("cpuset", self.cpuset) root.append(vcpu) else: root.append(self._text_node("vcpu", self.vcpus)) def _format_os(self, root): os = etree.Element("os") os.append(self._text_node("type", self.os_type)) if self.os_kernel is not None: os.append(self._text_node("kernel", self.os_kernel)) if self.os_loader is not None: os.append(self._text_node("loader", self.os_loader)) if self.os_initrd is not None: os.append(self._text_node("initrd", self.os_initrd)) if self.os_cmdline is not None: os.append(self._text_node("cmdline", self.os_cmdline)) if self.os_root is not None: os.append(self._text_node("root", self.os_root)) if self.os_init_path is not None: os.append(self._text_node("init", self.os_init_path)) for boot_dev in self.os_boot_dev: os.append(etree.Element("boot", dev=boot_dev)) if self.os_smbios is not None: os.append(self.os_smbios.format_dom()) root.append(os) def _format_features(self, root): if self.acpi or self.apic: features = etree.Element("features") if self.acpi: features.append(etree.Element("acpi")) if self.apic: features.append(etree.Element("apic")) root.append(features) def _format_cputune(self, root): cputune = etree.Element("cputune") if self.cpu_shares is not None: cputune.append(self._text_node("shares", self.cpu_shares)) if self.cpu_quota is not None: cputune.append(self._text_node("quota", self.cpu_quota)) if self.cpu_period is not None: cputune.append(self._text_node("period", self.cpu_period)) if len(cputune) > 0: root.append(cputune) def _format_devices(self, root): if len(self.devices) == 0: return devices = etree.Element("devices") for dev in self.devices: devices.append(dev.format_dom()) root.append(devices) def format_dom(self): root = super(LibvirtConfigGuest, self).format_dom() root.set("type", self.virt_type) self._format_basic_props(root) if self.sysinfo is not None: root.append(self.sysinfo.format_dom()) self._format_os(root) self._format_features(root) self._format_cputune(root) if self.clock is not None: root.append(self.clock.format_dom()) if self.cpu is not None: root.append(self.cpu.format_dom()) self._format_devices(root) return root def parse_dom(self, xmldoc): # Note: This cover only for: LibvirtConfigGuestDisks # LibvirtConfigGuestHostdevPCI # LibvirtConfigGuestCPU for c in xmldoc.getchildren(): if c.tag == 'devices': for d in c.getchildren(): if d.tag == 'disk': obj = LibvirtConfigGuestDisk() obj.parse_dom(d) self.devices.append(obj) elif d.tag == 'hostdev' and d.get('type') == 'pci': obj = LibvirtConfigGuestHostdevPCI() obj.parse_dom(d) self.devices.append(obj) elif c.tag == 'cpu': obj = LibvirtConfigGuestCPU() obj.parse_dom(c) self.cpu = obj def add_device(self, dev): self.devices.append(dev) def set_clock(self, clk): self.clock = clk class LibvirtConfigGuestSnapshot(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigGuestSnapshot, self).__init__( root_name="domainsnapshot", **kwargs) self.name = None self.disks = [] def format_dom(self): ss = super(LibvirtConfigGuestSnapshot, self).format_dom() if self.name: ss.append(self._text_node("name", self.name)) disks = etree.Element('disks') for disk in self.disks: disks.append(disk.format_dom()) ss.append(disks) return ss def add_disk(self, disk): self.disks.append(disk) class LibvirtConfigNodeDevice(LibvirtConfigObject): """Libvirt Node Devices parser""" def __init__(self, **kwargs): super(LibvirtConfigNodeDevice, self).__init__(root_name="device", **kwargs) self.name = None self.parent = None self.driver = None self.pci_capability = None def parse_dom(self, xmldoc): super(LibvirtConfigNodeDevice, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "name": self.name = c.text elif c.tag == "parent": self.parent = c.text elif c.tag == "capability" and c.get("type") == 'pci': pcicap = LibvirtConfigNodeDevicePciCap() pcicap.parse_dom(c) self.pci_capability = pcicap class LibvirtConfigNodeDevicePciCap(LibvirtConfigObject): """Libvirt Node Devices pci capability parser""" def __init__(self, **kwargs): super(LibvirtConfigNodeDevicePciCap, self).__init__( root_name="capability", **kwargs) self.domain = None self.bus = None self.slot = None self.function = None self.product = None self.product_id = None self.vendor = None self.vendor_id = None self.fun_capability = list() def parse_dom(self, xmldoc): super(LibvirtConfigNodeDevicePciCap, self).parse_dom(xmldoc) for c in xmldoc.getchildren(): if c.tag == "domain": self.domain = int(c.text) elif c.tag == "slot": self.slot = int(c.text) elif c.tag == "bus": self.bus = int(c.text) elif c.tag == "function": self.function = int(c.text) elif c.tag == "product": self.product = c.text self.product_id = c.get('id') elif c.tag == "vendor": self.vendor = c.text self.vendor_id = c.get('id') elif c.tag == "capability" and c.get('type') in \ ('virt_functions', 'phys_function'): funcap = LibvirtConfigNodeDevicePciSubFunctionCap() funcap.parse_dom(c) self.fun_capability.append(funcap) class LibvirtConfigNodeDevicePciSubFunctionCap(LibvirtConfigObject): def __init__(self, **kwargs): super(LibvirtConfigNodeDevicePciSubFunctionCap, self).__init__( root_name="capability", **kwargs) self.type = None self.device_addrs = list() # list of tuple (domain,bus,slot,function) def parse_dom(self, xmldoc): super(LibvirtConfigNodeDevicePciSubFunctionCap, self).parse_dom(xmldoc) self.type = xmldoc.get("type") for c in xmldoc.getchildren(): if c.tag == "address": self.device_addrs.append((c.get('domain'), c.get('bus'), c.get('slot'), c.get('function')))
33.43646
79
0.56797
903a0da7895ef46825f1f32f4100e45659bf6738
457
py
Python
EIDEGraphics/EIDEsYSTEM.py
Vicente-Francisco/EIDEGraphics
8e61bf64f4644a2e80df00946271f8cba4b5e65e
[ "Unlicense" ]
2
2022-02-09T08:06:13.000Z
2022-03-18T07:30:19.000Z
EIDEGraphics/EIDEsYSTEM.py
Vicente-Francisco/EIDEGraphics
8e61bf64f4644a2e80df00946271f8cba4b5e65e
[ "Unlicense" ]
null
null
null
EIDEGraphics/EIDEsYSTEM.py
Vicente-Francisco/EIDEGraphics
8e61bf64f4644a2e80df00946271f8cba4b5e65e
[ "Unlicense" ]
null
null
null
# -*- coding: utf-8 -*- """ """ class triad1(object): """ """ validCorners = ['TL', 'TR', 'BR', 'BL'] def __init__(self, deltaX, deltaY, corner): self.deltaX = int(deltaX) self.deltaY = int(deltaY) self.corner = corner def test(self, deltaX, deltaY, corner): """ Further tests to validate object """ if (corner not in validCorners): raise Exception('0020')
17.576923
47
0.512035
52c59b3ecf45b0abb91f1d1c17cf5c8529693b1c
1,051
py
Python
app/core/migrations/0005_recipe.py
redwanc12/Timeline-REST-API
b57ea5c35211238187d2306965f314b18316f2f8
[ "MIT" ]
1
2019-05-04T10:24:18.000Z
2019-05-04T10:24:18.000Z
app/core/migrations/0005_recipe.py
redwanc12/recipe-app-api
b57ea5c35211238187d2306965f314b18316f2f8
[ "MIT" ]
null
null
null
app/core/migrations/0005_recipe.py
redwanc12/recipe-app-api
b57ea5c35211238187d2306965f314b18316f2f8
[ "MIT" ]
null
null
null
# Generated by Django 2.1.7 on 2019-03-09 04:22 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('core', '0004_auto_20190309_0230'), ] operations = [ migrations.CreateModel( name='Recipe', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=255)), ('time_minutes', models.IntegerField()), ('price', models.DecimalField(decimal_places=2, max_digits=5)), ('link', models.CharField(blank=True, max_length=255)), ('ingredients', models.ManyToManyField(to='core.Ingredients')), ('tags', models.ManyToManyField(to='core.Tag')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]
36.241379
118
0.607041
60f756aa1c26fb029f999a31c3d13deb278f487d
35,956
py
Python
common/utils.py
noanabeshima/seed_rl
4bf7a4f7a9a7babfb961169b7484f7694ea6c5aa
[ "Apache-2.0" ]
null
null
null
common/utils.py
noanabeshima/seed_rl
4bf7a4f7a9a7babfb961169b7484f7694ea6c5aa
[ "Apache-2.0" ]
null
null
null
common/utils.py
noanabeshima/seed_rl
4bf7a4f7a9a7babfb961169b7484f7694ea6c5aa
[ "Apache-2.0" ]
null
null
null
# coding=utf-8 # Copyright 2019 The SEED Authors # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Utility functions/classes.""" import atexit import collections import threading import time import timeit from absl import flags from absl import logging import gym import numpy as np import tensorflow as tf import tensorflow_probability as tfp from tensorflow.python.distribute import values as values_lib from tensorflow.python.framework import composite_tensor from tensorflow.python.framework import tensor_conversion_registry FLAGS = flags.FLAGS # `observation` is the observation *after* a transition. When `done` is True, # `observation` will be the observation *after* the reset. EnvOutput = collections.namedtuple( 'EnvOutput', 'reward done observation abandoned episode_step') Settings = collections.namedtuple( 'Settings', 'strategy inference_devices training_strategy encode decode') MultiHostSettings = collections.namedtuple( 'MultiHostSettings', 'strategy hosts training_strategy encode decode') def init_learner_multi_host(num_training_tpus: int): """Performs common learner initialization including multi-host setting. In multi-host setting, this function will enter a loop for slave learners until the master signals end of training. Args: num_training_tpus: Number of training TPUs. Returns: A MultiHostSettings object. """ tpu = '' job_name = None if tf.config.experimental.list_logical_devices('TPU'): resolver = tf.distribute.cluster_resolver.TPUClusterResolver( tpu=tpu, job_name=job_name) topology = tf.tpu.experimental.initialize_tpu_system(resolver) strategy = tf.distribute.experimental.TPUStrategy(resolver) assert num_training_tpus % topology.num_tasks == 0 num_training_tpus_per_task = num_training_tpus // topology.num_tasks hosts = [] training_coordinates = [] for per_host_coordinates in topology.device_coordinates: host = topology.cpu_device_name_at_coordinates( per_host_coordinates[0], job=job_name) task_training_coordinates = ( per_host_coordinates[:num_training_tpus_per_task]) training_coordinates.extend([[c] for c in task_training_coordinates]) inference_coordinates = per_host_coordinates[num_training_tpus_per_task:] hosts.append((host, [ topology.tpu_device_name_at_coordinates(c, job=job_name) for c in inference_coordinates ])) training_da = tf.tpu.experimental.DeviceAssignment(topology, training_coordinates) training_strategy = tf.distribute.experimental.TPUStrategy( resolver, device_assignment=training_da) return MultiHostSettings(strategy, hosts, training_strategy, tpu_encode, tpu_decode) else: tf.device('/cpu').__enter__() any_gpu = tf.config.experimental.list_logical_devices('GPU') device_name = '/device:GPU:0' if any_gpu else '/device:CPU:0' strategy = tf.distribute.OneDeviceStrategy(device=device_name) enc = lambda x: x dec = lambda x, s=None: x if s is None else tf.nest.pack_sequence_as(s, x) return MultiHostSettings( strategy, [(device_name, [device_name])], strategy, enc, dec) def init_learner(num_training_tpus): """Performs common learner initialization.""" settings = init_learner_multi_host(num_training_tpus) if len(settings.hosts) != 1: raise ValueError(f'Invalid number of hosts: {len(settings.hosts)}') return Settings(settings.strategy, settings.hosts[0][1], settings.training_strategy, settings.encode, settings.decode) class UnrollStore(tf.Module): """Utility module for combining individual environment steps into unrolls.""" def __init__(self, num_envs, unroll_length, timestep_specs, num_overlapping_steps=0, name='UnrollStore'): super(UnrollStore, self).__init__(name=name) with self.name_scope: self._full_length = num_overlapping_steps + unroll_length + 1 def create_unroll_variable(spec): z = tf.zeros( [num_envs, self._full_length] + spec.shape.dims, dtype=spec.dtype) return tf.Variable(z, trainable=False, name=spec.name) self._unroll_length = unroll_length self._num_overlapping_steps = num_overlapping_steps self._state = tf.nest.map_structure(create_unroll_variable, timestep_specs) # For each environment, the index into the environment dimension of the # tensors in self._state where we should add the next element. self._index = tf.Variable( tf.fill([num_envs], tf.constant(num_overlapping_steps, tf.int32)), trainable=False, name='index') @property def unroll_specs(self): return tf.nest.map_structure(lambda v: tf.TensorSpec(v.shape[1:], v.dtype), self._state) @tf.function @tf.Module.with_name_scope def append(self, env_ids, values): """Appends values and returns completed unrolls. Args: env_ids: 1D tensor with the list of environment IDs for which we append data. There must not be duplicates. values: Values to add for each environment. This is a structure (in the tf.nest sense) of tensors following "timestep_specs", with a batch front dimension which must be equal to the length of 'env_ids'. Returns: A pair of: - 1D tensor of the environment IDs of the completed unrolls. - Completed unrolls. This is a structure of tensors following 'timestep_specs', with added front dimensions: [num_completed_unrolls, num_overlapping_steps + unroll_length + 1]. """ tf.debugging.assert_equal( tf.shape(env_ids), tf.shape(tf.unique(env_ids)[0]), message='Duplicate environment ids') tf.nest.map_structure( lambda s: tf.debugging.assert_equal( tf.shape(env_ids)[0], tf.shape(s)[0], message='Batch dimension must equal the number of environments.'), values) curr_indices = self._index.sparse_read(env_ids) unroll_indices = tf.stack([env_ids, curr_indices], axis=-1) for s, v in zip(tf.nest.flatten(self._state), tf.nest.flatten(values)): s.scatter_nd_update(unroll_indices, v) # Intentionally not protecting against out-of-bounds to make it possible to # detect completed unrolls. self._index.scatter_add(tf.IndexedSlices(1, env_ids)) return self._complete_unrolls(env_ids) @tf.function @tf.Module.with_name_scope def reset(self, env_ids): """Resets state. Note, this is only intended to be called when environments need to be reset after preemptions. Not at episode boundaries. Args: env_ids: The environments that need to have their state reset. """ self._index.scatter_update( tf.IndexedSlices(self._num_overlapping_steps, env_ids)) # The following code is the equivalent of: # s[env_ids, :j] = 0 j = self._num_overlapping_steps repeated_env_ids = tf.reshape( tf.tile(tf.expand_dims(tf.cast(env_ids, tf.int64), -1), [1, j]), [-1]) repeated_range = tf.tile(tf.range(j, dtype=tf.int64), [tf.shape(env_ids)[0]]) indices = tf.stack([repeated_env_ids, repeated_range], axis=-1) for s in tf.nest.flatten(self._state): z = tf.zeros(tf.concat([tf.shape(repeated_env_ids), s.shape[2:]], axis=0), s.dtype) s.scatter_nd_update(indices, z) def _complete_unrolls(self, env_ids): # Environment with unrolls that are now complete and should be returned. env_indices = self._index.sparse_read(env_ids) env_ids = tf.gather( env_ids, tf.where(tf.equal(env_indices, self._full_length))[:, 0]) env_ids = tf.cast(env_ids, tf.int64) unrolls = tf.nest.map_structure(lambda s: s.sparse_read(env_ids), self._state) # Store last transitions as the first in the next unroll. # The following code is the equivalent of: # s[env_ids, :j] = s[env_ids, -j:] j = self._num_overlapping_steps + 1 repeated_start_range = tf.tile(tf.range(j, dtype=tf.int64), [tf.shape(env_ids)[0]]) repeated_end_range = tf.tile( tf.range(self._full_length - j, self._full_length, dtype=tf.int64), [tf.shape(env_ids)[0]]) repeated_env_ids = tf.reshape( tf.tile(tf.expand_dims(env_ids, -1), [1, j]), [-1]) start_indices = tf.stack([repeated_env_ids, repeated_start_range], -1) end_indices = tf.stack([repeated_env_ids, repeated_end_range], -1) for s in tf.nest.flatten(self._state): s.scatter_nd_update(start_indices, s.gather_nd(end_indices)) self._index.scatter_update( tf.IndexedSlices(1 + self._num_overlapping_steps, env_ids)) return env_ids, unrolls class PrioritizedReplay(tf.Module): """Prioritized Replay Buffer. This buffer is not threadsafe. Make sure you call insert() and sample() from a single thread. """ def __init__(self, size, specs, importance_sampling_exponent, name='PrioritizedReplay'): super(PrioritizedReplay, self).__init__(name=name) self._priorities = tf.Variable(tf.zeros([size]), dtype=tf.float32) self._buffer = tf.nest.map_structure( lambda ts: tf.Variable(tf.zeros([size] + ts.shape, dtype=ts.dtype)), specs) self.num_inserted = tf.Variable(0, dtype=tf.int64) self._importance_sampling_exponent = importance_sampling_exponent @tf.function @tf.Module.with_name_scope def insert(self, values, priorities): """FIFO insertion/removal. Args: values: The batched values to insert. The tensors must be of the same shape and dtype as the `specs` provided in the constructor, except including a batch dimension. priorities: <float32>[batch_size] tensor with the priorities of the elements we insert. Returns: The indices of the inserted values. """ tf.nest.assert_same_structure(values, self._buffer) values = tf.nest.map_structure(tf.convert_to_tensor, values) append_size = tf.nest.flatten(values)[0].shape[0] start_index = self.num_inserted end_index = start_index + append_size # Wrap around insertion. size = self._priorities.shape[0] insert_indices = tf.range(start_index, end_index) % size tf.nest.map_structure( lambda b, v: b.batch_scatter_update( tf.IndexedSlices(v, insert_indices)), self._buffer, values) self.num_inserted.assign_add(append_size) self._priorities.batch_scatter_update( tf.IndexedSlices(priorities, insert_indices)) return insert_indices @tf.function @tf.Module.with_name_scope def sample(self, num_samples, priority_exp): r"""Samples items from the replay buffer, using priorities. Args: num_samples: int, number of replay items to sample. priority_exp: Priority exponent. Every item i in the replay buffer will be sampled with probability: priority[i] ** priority_exp / sum(priority[j] ** priority_exp, j \in [0, num_items)) Set this to 0 in order to get uniform sampling. Returns: Tuple of: - indices: An int64 tensor of shape [num_samples] with the indices in the replay buffer of the sampled items. - weights: A float32 tensor of shape [num_samples] with the normalized weights of the sampled items. - sampled_values: A nested structure following the spec passed in the contructor, where each tensor has an added front batch dimension equal to 'num_samples'. """ tf.debugging.assert_greater_equal( self.num_inserted, tf.constant(0, tf.int64), message='Cannot sample if replay buffer is empty') size = self._priorities.shape[0] limit = tf.minimum(tf.cast(size, tf.int64), self.num_inserted) if priority_exp == 0: indices = tf.random.uniform([num_samples], maxval=limit, dtype=tf.int64) weights = tf.ones_like(indices, dtype=tf.float32) else: prob = self._priorities[:limit]**priority_exp prob /= tf.reduce_sum(prob) indices = tf.random.categorical([tf.math.log(prob)], num_samples)[0] # Importance weights. weights = (((1. / tf.cast(limit, tf.float32)) / tf.gather(prob, indices)) ** self._importance_sampling_exponent) weights /= tf.reduce_max(weights) # Normalize. sampled_values = tf.nest.map_structure( lambda b: b.sparse_read(indices), self._buffer) return indices, weights, sampled_values @tf.function @tf.Module.with_name_scope def update_priorities(self, indices, priorities): """Updates the priorities of the items with the given indices. Args: indices: <int64>[batch_size] tensor with the indices of the items to update. If duplicate indices are provided, the priority that will be set among possible ones is not specified. priorities: <float32>[batch_size] tensor with the new priorities. """ self._priorities.batch_scatter_update(tf.IndexedSlices(priorities, indices)) class HindsightExperienceReplay(PrioritizedReplay): """Replay Buffer with Hindsight Experience Replay. Hindsight goals are sampled uniformly from subsequent steps in the same window (`future` strategy from https://arxiv.org/pdf/1707.01495). They are not guaranteed to come from the same episode. This buffer is not threadsafe. Make sure you call insert() and sample() from a single thread. """ def __init__(self, size, specs, importance_sampling_exponent, compute_reward_fn, unroll_length, substitution_probability, name='HindsightExperienceReplay'): super(HindsightExperienceReplay, self).__init__( size, specs, importance_sampling_exponent, name) self._compute_reward_fn = compute_reward_fn self._unroll_length = unroll_length self._substitution_probability = substitution_probability @tf.Module.with_name_scope def sample(self, num_samples, priority_exp): indices, weights, sampled_values = super( HindsightExperienceReplay, self).sample(num_samples, priority_exp) observation = sampled_values.env_outputs.observation batch_size, time_horizon = observation['achieved_goal'].shape[:2] def compute_goal_reward(): # reward[batch][time] is the reward on transition from timestep time-1 # to time. This function outputs incorrect rewards for the last transition # in each episode but we filter such cases later. goal_reward = self._compute_reward_fn( achieved_goal=observation['achieved_goal'][:, 1:], desired_goal=observation['desired_goal'][:, :-1]) return tf.concat(values=[goal_reward[:, :1] * np.nan, goal_reward], axis=1) # Substitute goals. old_goal_reward = compute_goal_reward() assert old_goal_reward.shape == observation['achieved_goal'].shape[:-1] goal_ind = tf.concat( values=[tf.random.uniform((batch_size, 1), min(t + 1, time_horizon - 1), time_horizon, dtype=tf.int32) for t in range(time_horizon)], axis=1) substituted_goal = tf.gather(observation['achieved_goal'], goal_ind, axis=1, batch_dims=1) mask = tf.cast(tfp.distributions.Bernoulli( probs=self._substitution_probability * tf.ones(goal_ind.shape)).sample(), observation['desired_goal'].dtype) # We don't substitute goals for the last states in each episodes because we # don't store the next states for them. mask *= tf.cast(~sampled_values.env_outputs.done, observation['desired_goal'].dtype) mask = mask[..., tf.newaxis] observation['desired_goal'] = ( mask * substituted_goal + (1 - mask) * observation['desired_goal']) # Substitude reward new_goal_reward = compute_goal_reward() assert new_goal_reward.shape == observation['achieved_goal'].shape[:-1] sampled_values = sampled_values._replace( env_outputs=sampled_values.env_outputs._replace( reward=sampled_values.env_outputs.reward + (new_goal_reward - old_goal_reward) * tf.cast( ~sampled_values.env_outputs.done, tf.float32) )) # Subsample unrolls of length unroll_length + 1. assert time_horizon >= self._unroll_length + 1 unroll_begin_ind = tf.random.uniform( (batch_size,), 0, time_horizon - self._unroll_length, dtype=tf.int32) unroll_inds = unroll_begin_ind[:, tf.newaxis] + tf.math.cumsum( tf.ones((batch_size, self._unroll_length + 1), tf.int32), axis=1, exclusive=True) subsampled_values = tf.nest.map_structure( lambda t: tf.gather(t, unroll_inds, axis=1, batch_dims=1), sampled_values) if hasattr(sampled_values, 'agent_state'): # do not subsample the state subsampled_values = subsampled_values._replace( agent_state=sampled_values.agent_state) return indices, weights, subsampled_values class Aggregator(tf.Module): """Utility module for keeping state for individual environments.""" def __init__(self, num_envs, specs, name='Aggregator'): """Inits an Aggregator. Args: num_envs: int, number of environments. specs: Structure (as defined by tf.nest) of tf.TensorSpecs that will be stored for each environment. name: Name of the scope for the operations. """ super(Aggregator, self).__init__(name=name) def create_variable(spec): z = tf.zeros([num_envs] + spec.shape.dims, dtype=spec.dtype) return tf.Variable(z, trainable=False, name=spec.name) self._state = tf.nest.map_structure(create_variable, specs) @tf.Module.with_name_scope def reset(self, env_ids): """Fills the tensors for the given environments with zeros.""" with tf.name_scope('Aggregator_reset'): for s in tf.nest.flatten(self._state): s.scatter_update(tf.IndexedSlices(0, env_ids)) @tf.Module.with_name_scope def add(self, env_ids, values): """In-place adds values to the state associated to the given environments. Args: env_ids: 1D tensor with the environment IDs we want to add values to. values: A structure of tensors following the input spec, with an added first dimension that must either have the same size as 'env_ids', or should not exist (in which case, the value is broadcasted to all environment ids). """ tf.nest.assert_same_structure(values, self._state) for s, v in zip(tf.nest.flatten(self._state), tf.nest.flatten(values)): s.scatter_add(tf.IndexedSlices(v, env_ids)) @tf.Module.with_name_scope def read(self, env_ids): """Reads the values corresponding to a list of environments. Args: env_ids: 1D tensor with the list of environment IDs we want to read. Returns: A structure of tensors with the same shapes as the input specs. A dimension is added in front of each tensor, with size equal to the number of env_ids provided. """ return tf.nest.map_structure(lambda s: s.sparse_read(env_ids), self._state) @tf.Module.with_name_scope def replace(self, env_ids, values): """Replaces the state associated to the given environments. Args: env_ids: 1D tensor with the list of environment IDs. values: A structure of tensors following the input spec, with an added first dimension that must either have the same size as 'env_ids', or should not exist (in which case, the value is broadcasted to all environment ids). """ tf.debugging.assert_equal( tf.shape(env_ids), tf.shape(tf.unique(env_ids)[0]), message=f'Duplicate environment ids in Aggregator: {self.name}') tf.nest.assert_same_structure(values, self._state) for s, v in zip(tf.nest.flatten(self._state), tf.nest.flatten(values)): s.scatter_update(tf.IndexedSlices(v, env_ids)) class ProgressLogger(object): """Helper class for performing periodic logging of the training progress.""" def __init__(self, summary_writer=None, initial_period=0.01, period_factor=1.01, max_period=10.0, starting_step=0): """Constructs ProgressLogger. Args: summary_writer: Tensorflow summary writer to use. initial_period: Initial logging period in seconds (how often logging happens). period_factor: Factor by which logging period is multiplied after each iteration (exponential back-off). max_period: Maximal logging period in seconds (the end of exponential back-off). starting_step: Step from which to start the summary writer. """ # summary_writer, last_log_{time, step} are set in reset() function. self.summary_writer = None self.last_log_time = None self.last_log_step = 0 self.period = initial_period self.period_factor = period_factor self.max_period = max_period # Array of strings with names of values to be logged. self.log_keys = [] self.log_keys_set = set() self.step_cnt = tf.Variable(-1, dtype=tf.int64) self.ready_values = tf.Variable([-1.0], dtype=tf.float32, shape=tf.TensorShape(None)) self.logger_thread = None self.logging_callback = None self.terminator = None self.reset(summary_writer, starting_step) def reset(self, summary_writer=None, starting_step=0): """Resets the progress logger. Args: summary_writer: Tensorflow summary writer to use. starting_step: Step from which to start the summary writer. """ self.summary_writer = summary_writer self.step_cnt.assign(starting_step - 1) self.ready_values.assign([-1.0]) self.last_log_time = timeit.default_timer() self.last_log_step = starting_step def start(self, logging_callback=None): assert self.logger_thread is None self.logging_callback = logging_callback self.terminator = threading.Event() self.logger_thread = threading.Thread(target=self._logging_loop) self.logger_thread.start() def shutdown(self): assert self.logger_thread self.terminator.set() self.logger_thread.join() self.logger_thread = None def log_session(self): return [] def log(self, session, name, value): # this is a python op so it happens only when this tf.function is compiled if name not in self.log_keys_set: self.log_keys.append(name) self.log_keys_set.add(name) # this is a TF op. session.append(value) def log_session_from_dict(self, dic): session = self.log_session() for key in dic: self.log(session, key, dic[key]) return session def step_end(self, session, strategy=None, step_increment=1): logs = [] for value in session: if strategy: value = tf.reduce_mean(tf.cast( strategy.experimental_local_results(value)[0], tf.float32)) logs.append(value) self.ready_values.assign(logs) self.step_cnt.assign_add(step_increment) def _log(self): """Perform single round of logging.""" logging_time = timeit.default_timer() step_cnt = self.step_cnt.read_value() values = self.ready_values.read_value().numpy() if values[0] == -1: return assert len(values) == len( self.log_keys ), 'Mismatch between number of keys and values to log: %r vs %r' % ( values, self.log_keys) if self.summary_writer: self.summary_writer.set_as_default() tf.summary.experimental.set_step(step_cnt.numpy()) if self.logging_callback: self.logging_callback() for key, value in zip(self.log_keys, values): tf.summary.scalar(key, value) dt = logging_time - self.last_log_time df = tf.cast(step_cnt - self.last_log_step, tf.float32) tf.summary.scalar('speed/steps_per_sec', df / dt) self.last_log_time, self.last_log_step = logging_time, step_cnt def _logging_loop(self): last_log_try = timeit.default_timer() while not self.terminator.isSet(): self._log() now = timeit.default_timer() elapsed = now - last_log_try last_log_try = now self.period = min(self.period_factor * self.period, self.max_period) self.terminator.wait(timeout=max(0, self.period - elapsed)) class StructuredFIFOQueue(tf.queue.FIFOQueue): """A tf.queue.FIFOQueue that supports nests and tf.TensorSpec.""" def __init__(self, capacity, specs, shared_name=None, name='structured_fifo_queue'): self._specs = specs self._flattened_specs = tf.nest.flatten(specs) dtypes = [ts.dtype for ts in self._flattened_specs] shapes = [ts.shape for ts in self._flattened_specs] super(StructuredFIFOQueue, self).__init__(capacity, dtypes, shapes) def dequeue(self, name=None): result = super(StructuredFIFOQueue, self).dequeue(name=name) return tf.nest.pack_sequence_as(self._specs, result) def dequeue_many(self, batch_size, name=None): result = super(StructuredFIFOQueue, self).dequeue_many( batch_size, name=name) return tf.nest.pack_sequence_as(self._specs, result) def enqueue(self, vals, name=None): tf.nest.assert_same_structure(vals, self._specs) return super(StructuredFIFOQueue, self).enqueue( tf.nest.flatten(vals), name=name) def enqueue_many(self, vals, name=None): tf.nest.assert_same_structure(vals, self._specs) return super(StructuredFIFOQueue, self).enqueue_many( tf.nest.flatten(vals), name=name) def batch_apply(fn, inputs): """Folds time into the batch dimension, runs fn() and unfolds the result. Args: fn: Function that takes as input the n tensors of the tf.nest structure, with shape [time*batch, <remaining shape>], and returns a tf.nest structure of batched tensors. inputs: tf.nest structure of n [time, batch, <remaining shape>] tensors. Returns: tf.nest structure of [time, batch, <fn output shape>]. Structure is determined by the output of fn. """ time_to_batch_fn = lambda t: tf.reshape(t, [-1] + t.shape[2:].as_list()) batched = tf.nest.map_structure(time_to_batch_fn, inputs) output = fn(*batched) prefix = [int(tf.nest.flatten(inputs)[0].shape[0]), -1] batch_to_time_fn = lambda t: tf.reshape(t, prefix + t.shape[1:].as_list()) return tf.nest.map_structure(batch_to_time_fn, output) def make_time_major(x): """Transposes the batch and time dimensions of a nest of Tensors. If an input tensor has rank < 2 it returns the original tensor. Retains as much of the static shape information as possible. Args: x: A nest of Tensors. Returns: x transposed along the first two dimensions. """ def transpose(t): t_static_shape = t.shape if t_static_shape.rank is not None and t_static_shape.rank < 2: return t t_rank = tf.rank(t) t_t = tf.transpose(t, tf.concat(([1, 0], tf.range(2, t_rank)), axis=0)) t_t.set_shape( tf.TensorShape([t_static_shape[1], t_static_shape[0]]).concatenate(t_static_shape[2:])) return t_t return tf.nest.map_structure( lambda t: tf.xla.experimental.compile(transpose, [t])[0], x) class TPUEncodedUInt8Spec(tf.TypeSpec): """Type specification for composite tensor TPUEncodedUInt8.""" def __init__(self, encoded_shape, original_shape): self._value_specs = (tf.TensorSpec(encoded_shape, tf.uint32),) self.original_shape = original_shape @property def _component_specs(self): return self._value_specs def _to_components(self, value): return (value.encoded,) def _from_components(self, components): return TPUEncodedUInt8(components[0], self.original_shape) def _serialize(self): return self._value_specs[0].shape, self.original_shape def _to_legacy_output_types(self): return self._value_specs[0].dtype def _to_legacy_output_shapes(self): return self._value_specs[0].shape @property def value_type(self): return TPUEncodedUInt8 class TPUEncodedUInt8(composite_tensor.CompositeTensor): def __init__(self, encoded, shape): self.encoded = encoded self.original_shape = shape self._spec = TPUEncodedUInt8Spec(encoded.shape, tf.TensorShape(shape)) @property def _type_spec(self): return self._spec tensor_conversion_registry.register_tensor_conversion_function( TPUEncodedUInt8, lambda value, *unused_args, **unused_kwargs: value.encoded) class TPUEncodedF32Spec(tf.TypeSpec): """Type specification for composite tensor TPUEncodedF32Spec.""" def __init__(self, encoded_shape, original_shape): self._value_specs = (tf.TensorSpec(encoded_shape, tf.float32),) self.original_shape = original_shape @property def _component_specs(self): return self._value_specs def _to_components(self, value): return (value.encoded,) def _from_components(self, components): return TPUEncodedF32(components[0], self.original_shape) def _serialize(self): return self._value_specs[0].shape, self.original_shape def _to_legacy_output_types(self): return self._value_specs[0].dtype def _to_legacy_output_shapes(self): return self._value_specs[0].shape @property def value_type(self): return TPUEncodedF32 class TPUEncodedF32(composite_tensor.CompositeTensor): def __init__(self, encoded, shape): self.encoded = encoded self.original_shape = shape self._spec = TPUEncodedF32Spec(encoded.shape, tf.TensorShape(shape)) @property def _type_spec(self): return self._spec tensor_conversion_registry.register_tensor_conversion_function( TPUEncodedF32, lambda value, *unused_args, **unused_kwargs: value.encoded) def num_divisible(v, m): return sum([1 for x in v if x % m == 0]) def tpu_encode(ts): """Encodes a nest of Tensors in a suitable way for TPUs. TPUs do not support tf.uint8, tf.uint16 and other data types. Furthermore, the speed of transfer and device reshapes depend on the shape of the data. This function tries to optimize the data encoding for a number of use cases. Should be used on CPU before sending data to TPU and in conjunction with `tpu_decode` after the data is transferred. Args: ts: A tf.nest of Tensors. Returns: A tf.nest of encoded Tensors. """ def visit(t): num_elements = t.shape.num_elements() # We need a multiple of 128 elements: encoding reduces the number of # elements by a factor 4 (packing uint8s into uint32s), and first thing # decode does is to reshape with a 32 minor-most dimension. if (t.dtype == tf.uint8 and num_elements is not None and num_elements % 128 == 0): # For details of these transformations, see b/137182262. x = tf.xla.experimental.compile( lambda x: tf.transpose(x, list(range(1, t.shape.rank)) + [0]), [t])[0] x = tf.reshape(x, [-1, 4]) x = tf.bitcast(x, tf.uint32) x = tf.reshape(x, [-1]) return TPUEncodedUInt8(x, t.shape) elif t.dtype == tf.uint8: logging.warning('Inefficient uint8 transfer with shape: %s', t.shape) return tf.cast(t, tf.bfloat16) elif t.dtype == tf.uint16: return tf.cast(t, tf.int32) elif (t.dtype == tf.float32 and t.shape.rank > 1 and not (num_divisible(t.shape.dims, 128) >= 1 and num_divisible(t.shape.dims, 8) >= 2)): x = tf.reshape(t, [-1]) return TPUEncodedF32(x, t.shape) else: return t return tf.nest.map_structure(visit, ts) def tpu_decode(ts, structure=None): """Decodes a nest of Tensors encoded with tpu_encode. Args: ts: A nest of Tensors or TPUEncodedUInt8 composite tensors. structure: If not None, a nest of Tensors or TPUEncodedUInt8 composite tensors (possibly within PerReplica's) that are only used to recreate the structure of `ts` which then should be a list without composite tensors. Returns: A nest of decoded tensors packed as `structure` if available, otherwise packed as `ts`. """ def visit(t, s): s = s.values[0] if isinstance(s, values_lib.PerReplica) else s if isinstance(s, TPUEncodedUInt8): x = t.encoded if isinstance(t, TPUEncodedUInt8) else t x = tf.reshape(x, [-1, 32, 1]) x = tf.broadcast_to(x, x.shape[:-1] + [4]) x = tf.reshape(x, [-1, 128]) x = tf.bitwise.bitwise_and(x, [0xFF, 0xFF00, 0xFF0000, 0xFF000000] * 32) x = tf.bitwise.right_shift(x, [0, 8, 16, 24] * 32) rank = s.original_shape.rank perm = [rank - 1] + list(range(rank - 1)) inverted_shape = np.array(s.original_shape)[np.argsort(perm)] x = tf.reshape(x, inverted_shape) x = tf.transpose(x, perm) return x elif isinstance(s, TPUEncodedF32): x = t.encoded if isinstance(t, TPUEncodedF32) else t x = tf.reshape(x, s.original_shape) return x else: return t return tf.nest.map_structure(visit, ts, structure or ts) def split_structure(structure, prefix_length, axis=0): """Splits in two a tf.nest structure of tensors along the first axis.""" flattened = tf.nest.flatten(structure) split = [tf.split(x, [prefix_length, tf.shape(x)[axis] - prefix_length], axis=axis) for x in flattened] flattened_prefix = [pair[0] for pair in split] flattened_suffix = [pair[1] for pair in split] return (tf.nest.pack_sequence_as(structure, flattened_prefix), tf.nest.pack_sequence_as(structure, flattened_suffix)) class nullcontext(object): def __init__(self, *args, **kwds): del args # unused del kwds # unused def __enter__(self): return self def __exit__(self, exc_type, exc_value, traceback): pass def tensor_spec_from_gym_space(space, name): """Get a TensorSpec from a gym spec.""" if space.shape is not None: return tf.TensorSpec(space.shape, space.dtype, name) if not isinstance(space, gym.spaces.Tuple): raise ValueError( 'Space \'{}\' is not a tuple: unknown shape.'.format(space)) num_elements = 0 for s in space: if len(s.shape) != 1: raise ValueError( 'Only 1 dimension subspaces are handled for tuple spaces: {}'.format( space)) num_elements += s.shape[0] return tf.TensorSpec((num_elements,), tf.float32, name) def validate_learner_config(config, num_hosts=1): """Shared part of learner config validation.""" assert config.num_envs > 0 assert config.env_batch_size > 0 if config.inference_batch_size == -1: config.inference_batch_size = max(1, config.num_envs // (2 * num_hosts)) assert config.inference_batch_size % config.env_batch_size == 0, ( 'Learner-side batch size (=%d) must be exact multiple of the ' 'actor-side batch size (=%d).' % (config.inference_batch_size, config.env_batch_size)) assert config.num_envs >= config.inference_batch_size * num_hosts, ( 'Inference batch size is bigger than the number of environments.')
36.429585
80
0.686812
aa527cd77c1e0e1b4125145fedc35e41e3118179
2,307
py
Python
data/test/datasets/json_dataset.py
qrsforever/torchcv
e2e17f730497fb838237357a1df4bf6ca278f107
[ "Apache-2.0" ]
171
2019-01-23T12:51:47.000Z
2019-04-15T03:57:09.000Z
data/test/datasets/json_dataset.py
qrsforever/torchcv
e2e17f730497fb838237357a1df4bf6ca278f107
[ "Apache-2.0" ]
6
2019-02-14T11:28:35.000Z
2019-04-15T04:05:47.000Z
data/test/datasets/json_dataset.py
qrsforever/torchcv
e2e17f730497fb838237357a1df4bf6ca278f107
[ "Apache-2.0" ]
36
2019-01-23T12:51:55.000Z
2019-04-11T13:50:48.000Z
#!/usr/bin/env python # -*- coding:utf-8 -*- # Author: Donny You(youansheng@gmail.com) # Single Shot Detector data loader import os import torch.utils.data as data from lib.parallel.data_container import DataContainer from lib.tools.helper.json_helper import JsonHelper from lib.tools.helper.image_helper import ImageHelper from lib.tools.util.logger import Logger as Log class JsonDataset(data.Dataset): def __init__(self, root_dir=None, json_path=None, aug_transform=None, img_transform=None, configer=None): super(JsonDataset, self).__init__() self.configer = configer self.aug_transform=aug_transform self.img_transform = img_transform self.item_list = self.__read_json(root_dir, json_path) def __getitem__(self, index): img = ImageHelper.read_image(self.item_list[index][0], tool=self.configer.get('data', 'image_tool'), mode=self.configer.get('data', 'input_mode')) ori_img_size = ImageHelper.get_size(img) if self.aug_transform is not None: img = self.aug_transform(img) border_hw = ImageHelper.get_size(img)[::-1] if self.img_transform is not None: img = self.img_transform(img) meta = dict( ori_img_size=ori_img_size, border_hw=border_hw, img_path=self.item_list[index][0], filename=self.item_list[index][1] ) return dict( img=DataContainer(img, stack=True, return_dc=True, samples_per_gpu=True), meta=DataContainer(meta, stack=False, cpu_only=True, return_dc=True, samples_per_gpu=True) ) def __len__(self): return len(self.item_list) def __read_json(self, root_dir, json_path): item_list = [] for item in JsonHelper.load_file(json_path): img_path = os.path.join(root_dir, item['image_path']) if not os.path.exists(img_path) or not ImageHelper.is_img(img_path): Log.error('Image Path: {} is Invalid.'.format(img_path)) exit(1) item_list.append((img_path, '.'.join(item['image_path'].split('.')[:-1]))) Log.info('There are {} images..'.format(len(item_list))) return item_list
35.492308
109
0.637625
769f3c97a2e4244dae9f9a05065e3838fb2b889b
843
py
Python
examples/runners/dodo.py
agrantdeakin/surround
bc6f87bb570d93f362ab01647df197af7e549522
[ "BSD-3-Clause" ]
1
2019-11-18T00:12:48.000Z
2019-11-18T00:12:48.000Z
examples/runners/dodo.py
agrantdeakin/surround
bc6f87bb570d93f362ab01647df197af7e549522
[ "BSD-3-Clause" ]
null
null
null
examples/runners/dodo.py
agrantdeakin/surround
bc6f87bb570d93f362ab01647df197af7e549522
[ "BSD-3-Clause" ]
null
null
null
import os from surround import Config CONFIG = Config(os.path.dirname(__file__)) DOIT_CONFIG = {'verbosity':2} IMAGE = "%s/%s:%s" % (CONFIG["company"], CONFIG["image"], CONFIG["version"]) def task_build(): """Build the Docker image for the current project""" return { 'actions': ['docker build --tag=%s .' % IMAGE] } def task_remove(): """Remove the Docker image for the current project""" return { 'actions': ['docker rmi %s -f' % IMAGE] } def task_dev(): """Run the main task for the project""" return { 'actions': ["docker run --volume %s/:/app %s" % (CONFIG["project_root"], IMAGE)] } def task_prod(): """Run the main task inside a Docker container for use in production """ return { 'actions': ["docker run %s" % IMAGE], 'task_dep': ["build"] }
26.34375
88
0.59312
51541b70d45cdb3b4ea7e3ede30c27358bad3705
4,277
py
Python
nilearn/reporting/_plot_matrices.py
jnecus/nilearn
e929256b8b0ad9f92a221499d217506b816ec28e
[ "BSD-2-Clause" ]
null
null
null
nilearn/reporting/_plot_matrices.py
jnecus/nilearn
e929256b8b0ad9f92a221499d217506b816ec28e
[ "BSD-2-Clause" ]
null
null
null
nilearn/reporting/_plot_matrices.py
jnecus/nilearn
e929256b8b0ad9f92a221499d217506b816ec28e
[ "BSD-2-Clause" ]
null
null
null
""" This module implements plotting functions useful to report analysis results. Author: Martin Perez-Guevara, Elvis Dohmatob, 2017 """ import numpy as np import matplotlib.pyplot as plt from nilearn.stats.first_level_model import check_design_matrix from nilearn.stats.contrasts import expression_to_contrast_vector def plot_design_matrix(design_matrix, rescale=True, ax=None, output_file=None): """Plot a design matrix provided as a DataFrame Parameters ---------- design matrix : pandas DataFrame, Describes a design matrix. rescale : bool, optional Rescale columns magnitude for visualization or not. ax : axis handle, optional Handle to axis onto which we will draw design matrix. output_file: string or None, optional, The name of an image file to export the plot to. Valid extensions are .png, .pdf, .svg. If output_file is not None, the plot is saved to a file, and the display is closed. Returns ------- ax: axis handle The axis used for plotting. """ # We import _set_mpl_backend because just the fact that we are # importing it sets the backend # normalize the values per column for better visualization _, X, names = check_design_matrix(design_matrix) if rescale: X = X / np.maximum(1.e-12, np.sqrt( np.sum(X ** 2, 0))) # pylint: disable=no-member if ax is None: plt.figure() ax = plt.subplot(1, 1, 1) ax.imshow(X, interpolation='nearest', aspect='auto') ax.set_label('conditions') ax.set_ylabel('scan number') ax.set_xticks(range(len(names))) ax.set_xticklabels(names, rotation=60, ha='right') plt.tight_layout() if output_file is not None: plt.savefig(output_file) plt.close() ax = None return ax def plot_contrast_matrix(contrast_def, design_matrix, colorbar=False, ax=None, output_file=None): """Creates plot for contrast definition. Parameters ---------- contrast_def : str or array of shape (n_col) or list of (string or array of shape (n_col)) where ``n_col`` is the number of columns of the design matrix, (one array per run). If only one array is provided when there are several runs, it will be assumed that the same contrast is desired for all runs. The string can be a formula compatible with `pandas.DataFrame.eval`. Basically one can use the name of the conditions as they appear in the design matrix of the fitted model combined with operators +- and combined with numbers with operators +-`*`/. design_matrix: pandas DataFrame colorbar: Boolean, optional (default False) Include a colorbar in the contrast matrix plot. ax: matplotlib Axes object, optional (default None) Directory where plotted figures will be stored. output_file: string or None, optional, The name of an image file to export the plot to. Valid extensions are .png, .pdf, .svg. If output_file is not None, the plot is saved to a file, and the display is closed. Returns ------- Plot Axes object """ design_column_names = design_matrix.columns.tolist() if isinstance(contrast_def, str): contrast_def = expression_to_contrast_vector( contrast_def, design_column_names) maxval = np.max(np.abs(contrast_def)) con_matrix = np.asmatrix(contrast_def) if ax is None: plt.figure(figsize=(8, 4)) ax = plt.gca() mat = ax.matshow(con_matrix, aspect='equal', extent=[0, con_matrix.shape[1], 0, con_matrix.shape[0]], cmap='gray', vmin=-maxval, vmax=maxval) ax.set_label('conditions') ax.set_ylabel('') ax.set_yticklabels(['' for x in ax.get_yticklabels()]) # Shift ticks to be at 0.5, 1.5, etc ax.xaxis.set(ticks=np.arange(len(design_column_names))) ax.set_xticklabels(design_column_names, rotation=60, ha='left') if colorbar: plt.colorbar(mat, fraction=0.025, pad=0.04) plt.tight_layout() if output_file is not None: plt.savefig(output_file) plt.close() ax = None return ax
31.448529
79
0.655834
f71fd8ed4a60f1f0cb0713800b0c028bb7bc4489
16,140
py
Python
desktop/core/ext-py/pysaml2-4.4.0/src/saml2/cert.py
kokosing/hue
2307f5379a35aae9be871e836432e6f45138b3d9
[ "Apache-2.0" ]
3
2018-01-29T14:16:02.000Z
2019-02-05T21:33:05.000Z
desktop/core/ext-py/pysaml2-4.4.0/src/saml2/cert.py
zks888/hue
93a8c370713e70b216c428caa2f75185ef809deb
[ "Apache-2.0" ]
4
2021-03-11T04:02:00.000Z
2022-03-27T08:31:56.000Z
desktop/core/ext-py/pysaml2-4.4.0/src/saml2/cert.py
zks888/hue
93a8c370713e70b216c428caa2f75185ef809deb
[ "Apache-2.0" ]
2
2019-06-17T11:51:56.000Z
2020-07-25T08:29:56.000Z
__author__ = 'haho0032' import base64 import datetime import dateutil.parser import pytz import six from OpenSSL import crypto from os.path import join from os import remove from Cryptodome.Util import asn1 class WrongInput(Exception): pass class CertificateError(Exception): pass class PayloadError(Exception): pass class OpenSSLWrapper(object): def __init__(self): pass def create_certificate(self, cert_info, request=False, valid_from=0, valid_to=315360000, sn=1, key_length=1024, hash_alg="sha256", write_to_file=False, cert_dir="", cipher_passphrase=None): """ Can create certificate requests, to be signed later by another certificate with the method create_cert_signed_certificate. If request is True. Can also create self signed root certificates if request is False. This is default behaviour. :param cert_info: Contains information about the certificate. Is a dictionary that must contain the keys: cn = Common name. This part must match the host being authenticated country_code = Two letter description of the country. state = State city = City organization = Organization, can be a company name. organization_unit = A unit at the organization, can be a department. Example: cert_info_ca = { "cn": "company.com", "country_code": "se", "state": "AC", "city": "Dorotea", "organization": "Company", "organization_unit": "Sales" } :param request: True if this is a request for certificate, that should be signed. False if this is a self signed certificate, root certificate. :param valid_from: When the certificate starts to be valid. Amount of seconds from when the certificate is generated. :param valid_to: How long the certificate will be valid from when it is generated. The value is in seconds. Default is 315360000 seconds, a.k.a 10 years. :param sn: Serial number for the certificate. Default is 1. :param key_length: Length of the key to be generated. Defaults to 1024. :param hash_alg: Hash algorithm to use for the key. Default is sha256. :param write_to_file: True if you want to write the certificate to a file. The method will then return a tuple with path to certificate file and path to key file. False if you want to get the result as strings. The method will then return a tuple with the certificate string and the key as string. WILL OVERWRITE ALL EXISTING FILES WITHOUT ASKING! :param cert_dir: Where to save the files if write_to_file is true. :param cipher_passphrase A dictionary with cipher and passphrase. Example:: {"cipher": "blowfish", "passphrase": "qwerty"} :return: string representation of certificate, string representation of private key if write_to_file parameter is False otherwise path to certificate file, path to private key file """ cn = cert_info["cn"] c_f = None k_f = None if write_to_file: cert_file = "%s.crt" % cn key_file = "%s.key" % cn try: remove(cert_file) except: pass try: remove(key_file) except: pass c_f = join(cert_dir, cert_file) k_f = join(cert_dir, key_file) # create a key pair k = crypto.PKey() k.generate_key(crypto.TYPE_RSA, key_length) # create a self-signed cert cert = crypto.X509() if request: cert = crypto.X509Req() if (len(cert_info["country_code"]) != 2): raise WrongInput("Country code must be two letters!") cert.get_subject().C = cert_info["country_code"] cert.get_subject().ST = cert_info["state"] cert.get_subject().L = cert_info["city"] cert.get_subject().O = cert_info["organization"] cert.get_subject().OU = cert_info["organization_unit"] cert.get_subject().CN = cn if not request: cert.set_serial_number(sn) cert.gmtime_adj_notBefore(valid_from) #Valid before present time cert.gmtime_adj_notAfter(valid_to) #3 650 days cert.set_issuer(cert.get_subject()) cert.set_pubkey(k) cert.sign(k, hash_alg) filesCreated = False try: if request: tmp_cert = crypto.dump_certificate_request(crypto.FILETYPE_PEM, cert) else: tmp_cert = crypto.dump_certificate(crypto.FILETYPE_PEM, cert) tmp_key = None if cipher_passphrase is not None: passphrase = cipher_passphrase["passphrase"] if isinstance(cipher_passphrase["passphrase"], six.string_types): passphrase = passphrase.encode('utf-8') tmp_key = crypto.dump_privatekey(crypto.FILETYPE_PEM, k, cipher_passphrase["cipher"], passphrase) else: tmp_key = crypto.dump_privatekey(crypto.FILETYPE_PEM, k) if write_to_file: fc = open(c_f, "wt") fk = open(k_f, "wt") if request: fc.write(tmp_cert.decode('utf-8')) else: fc.write(tmp_cert.decode('utf-8')) fk.write(tmp_key.decode('utf-8')) filesCreated = True try: fc.close() except: pass try: fk.close() except: pass return c_f, k_f return tmp_cert, tmp_key except Exception as ex: raise CertificateError("Certificate cannot be generated.", ex) def write_str_to_file(self, file, str_data): f = open(file, "wt") f.write(str_data) f.close() def read_str_from_file(self, file, type="pem"): f = open(file, 'rt') str_data = f.read() f.close() if type == "pem": return str_data if type in ["der", "cer", "crt"]: return base64.b64encode(str(str_data)) def create_cert_signed_certificate(self, sign_cert_str, sign_key_str, request_cert_str, hash_alg="sha256", valid_from=0, valid_to=315360000, sn=1, passphrase=None): """ Will sign a certificate request with a give certificate. :param sign_cert_str: This certificate will be used to sign with. Must be a string representation of the certificate. If you only have a file use the method read_str_from_file to get a string representation. :param sign_key_str: This is the key for the ca_cert_str represented as a string. If you only have a file use the method read_str_from_file to get a string representation. :param request_cert_str: This is the prepared certificate to be signed. Must be a string representation of the requested certificate. If you only have a file use the method read_str_from_file to get a string representation. :param hash_alg: Hash algorithm to use for the key. Default is sha256. :param valid_from: When the certificate starts to be valid. Amount of seconds from when the certificate is generated. :param valid_to: How long the certificate will be valid from when it is generated. The value is in seconds. Default is 315360000 seconds, a.k.a 10 years. :param sn: Serial number for the certificate. Default is 1. :param passphrase: Password for the private key in sign_key_str. :return: String representation of the signed certificate. """ ca_cert = crypto.load_certificate(crypto.FILETYPE_PEM, sign_cert_str) ca_key = None if passphrase is not None: ca_key = crypto.load_privatekey(crypto.FILETYPE_PEM, sign_key_str, passphrase) else: ca_key = crypto.load_privatekey(crypto.FILETYPE_PEM, sign_key_str) req_cert = crypto.load_certificate_request(crypto.FILETYPE_PEM, request_cert_str) cert = crypto.X509() cert.set_subject(req_cert.get_subject()) cert.set_serial_number(sn) cert.gmtime_adj_notBefore(valid_from) cert.gmtime_adj_notAfter(valid_to) cert.set_issuer(ca_cert.get_subject()) cert.set_pubkey(req_cert.get_pubkey()) cert.sign(ca_key, hash_alg) cert_dump = crypto.dump_certificate(crypto.FILETYPE_PEM, cert) if isinstance(cert_dump, six.string_types): return cert_dump return cert_dump.decode('utf-8') def verify_chain(self, cert_chain_str_list, cert_str): """ :param cert_chain_str_list: Must be a list of certificate strings, where the first certificate to be validate is in the beginning and the root certificate is last. :param cert_str: The certificate to be validated. :return: """ for tmp_cert_str in cert_chain_str_list: valid, message = self.verify(tmp_cert_str, cert_str) if not valid: return False, message else: cert_str = tmp_cert_str return (True, "Signed certificate is valid and correctly signed by CA " "certificate.") def certificate_not_valid_yet(self, cert): starts_to_be_valid = dateutil.parser.parse(cert.get_notBefore()) now = pytz.UTC.localize(datetime.datetime.utcnow()) if starts_to_be_valid < now: return False return True def verify(self, signing_cert_str, cert_str): """ Verifies if a certificate is valid and signed by a given certificate. :param signing_cert_str: This certificate will be used to verify the signature. Must be a string representation of the certificate. If you only have a file use the method read_str_from_file to get a string representation. :param cert_str: This certificate will be verified if it is correct. Must be a string representation of the certificate. If you only have a file use the method read_str_from_file to get a string representation. :return: Valid, Message Valid = True if the certificate is valid, otherwise false. Message = Why the validation failed. """ try: ca_cert = crypto.load_certificate(crypto.FILETYPE_PEM, signing_cert_str) cert = crypto.load_certificate(crypto.FILETYPE_PEM, cert_str) if self.certificate_not_valid_yet(ca_cert): return False, "CA certificate is not valid yet." if ca_cert.has_expired() == 1: return False, "CA certificate is expired." if cert.has_expired() == 1: return False, "The signed certificate is expired." if self.certificate_not_valid_yet(cert): return False, "The signed certificate is not valid yet." if ca_cert.get_subject().CN == cert.get_subject().CN: return False, ("CN may not be equal for CA certificate and the " "signed certificate.") cert_algorithm = cert.get_signature_algorithm() if six.PY3: cert_algorithm = cert_algorithm.decode('ascii') cert_asn1 = crypto.dump_certificate(crypto.FILETYPE_ASN1, cert) der_seq = asn1.DerSequence() der_seq.decode(cert_asn1) cert_certificate = der_seq[0] #cert_signature_algorithm=der_seq[1] cert_signature = der_seq[2] cert_signature_decoded = asn1.DerObject() cert_signature_decoded.decode(cert_signature) signature_payload = cert_signature_decoded.payload sig_pay0 = signature_payload[0] if ((isinstance(sig_pay0, int) and sig_pay0 != 0) or (isinstance(sig_pay0, str) and sig_pay0 != '\x00')): return (False, "The certificate should not contain any unused bits.") signature = signature_payload[1:] try: crypto.verify(ca_cert, signature, cert_certificate, cert_algorithm) return True, "Signed certificate is valid and correctly signed by CA certificate." except crypto.Error as e: return False, "Certificate is incorrectly signed." except Exception as e: return False, "Certificate is not valid for an unknown reason. %s" % str(e)
43.621622
98
0.495291
3b87b2f9148e22e9cba24571e05cf4172e0febab
2,162
py
Python
app/config.py
lvyaoo/api-demo
f45c05c154385510572b5200b74dcbbfdb7e234c
[ "MIT" ]
null
null
null
app/config.py
lvyaoo/api-demo
f45c05c154385510572b5200b74dcbbfdb7e234c
[ "MIT" ]
null
null
null
app/config.py
lvyaoo/api-demo
f45c05c154385510572b5200b74dcbbfdb7e234c
[ "MIT" ]
null
null
null
import logging from logging.handlers import RotatingFileHandler from os import getenv from flask import Flask from .hooks import before_app_request, teardown_app_request from .misc import CustomJSONEncoder from .blueprints.admin_api import bp_admin_api from .blueprints.admin_ext import bp_admin_ext class _Config: """配置""" SERVER_NAME = getenv('SERVER_NAME') # blueprint BP_SUB_DOMAIN = {} BP_URL_PREFIX = { 'admin_api': '/api', 'admin_ext': '/ext' } @classmethod def init_app(cls, app: Flask) -> None: """初始化flask应用对象""" app.before_request(before_app_request) app.teardown_request(teardown_app_request) app.json_encoder = CustomJSONEncoder sub, url = cls.BP_SUB_DOMAIN, cls.BP_URL_PREFIX app.register_blueprint(bp_admin_api, subdomain=sub.get('admin'), url_prefix=url.get('admin_api')) app.register_blueprint(bp_admin_ext, subdomain=sub.get('admin'), url_prefix=url.get('admin_ext')) # 日志 formatter = logging.Formatter('[%(asctime)s] %(pathname)s:%(lineno)d [%(levelname)s] %(message)s') debug_log = RotatingFileHandler('debug.log', maxBytes=1024 * 1024 * 100, backupCount=10, encoding='utf-8') debug_log.setLevel(logging.DEBUG) debug_log.setFormatter(formatter) error_log = RotatingFileHandler('error.log', maxBytes=1024 * 1024 * 100, backupCount=10, encoding='utf-8') error_log.setLevel(logging.ERROR) error_log.setFormatter(formatter) app.logger.setLevel(logging.DEBUG) app.logger.addHandler(debug_log) app.logger.addHandler(error_log) class _DevelopmentConfig(_Config): """开发环境配置""" BP_URL_PREFIX = { 'admin_api': '/api.admin', 'admin_ext': '/ext.admin' } class _TestingConfig(_Config): """测试环境配置""" BP_SUB_DOMAIN = { 'admin': 'demo-admin' } class _ProductionConfig(_Config): """生产环境配置""" BP_SUB_DOMAIN = { 'admin': 'admin' } config = { 'development': _DevelopmentConfig, 'testing': _TestingConfig, 'production': _ProductionConfig, 'default': _DevelopmentConfig }
28.447368
114
0.671138
d675dd878323cd1155c2451d6f3a3c7dc8adcacb
2,810
py
Python
source/aws/services/sts.py
a-j-b-uk/aws-control-tower-customizations
8b75f6408dc9c3a1a26ad5456676cae4185e4d22
[ "Apache-2.0" ]
1
2020-06-24T13:40:44.000Z
2020-06-24T13:40:44.000Z
source/aws/services/sts.py
a-j-b-uk/aws-control-tower-customizations
8b75f6408dc9c3a1a26ad5456676cae4185e4d22
[ "Apache-2.0" ]
null
null
null
source/aws/services/sts.py
a-j-b-uk/aws-control-tower-customizations
8b75f6408dc9c3a1a26ad5456676cae4185e4d22
[ "Apache-2.0" ]
null
null
null
############################################################################### # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # # # Licensed under the Apache License, Version 2.0 (the "License"). # # You may not use this file except in compliance with the License. # A copy of the License is located at # # # # http://www.apache.org/licenses/LICENSE-2.0 # # # # or in the "license" file accompanying this file. This file is distributed # # on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, express # # or implied. See the License for the specific language governing permissions# # and limitations under the License. # ############################################################################### # !/bin/python from os import environ from botocore.exceptions import ClientError from aws.utils.boto3_session import Boto3Session class AssumeRole(object): def __call__(self, logger, account, role_arn, session_name): try: sts = STS(logger) # assume role credentials = sts.assume_role(role_arn, session_name) return credentials except ClientError as e: logger.log_unhandled_exception(e) raise class STS(Boto3Session): def __init__(self, logger, **kwargs): self.logger = logger __service_name = 'sts' kwargs.update({'region': self.get_sts_region}) kwargs.update({'endpoint_url': self.get_sts_endpoint()}) super().__init__(logger, __service_name, **kwargs) self.sts_client = super().get_client() @property def get_sts_region(self): return environ.get('AWS_REGION') @staticmethod def get_sts_endpoint(): return "https://sts.%s.amazonaws.com" % environ.get('AWS_REGION') def assume_role(self, role_arn, session_name, duration=900): try: response = self.sts_client.assume_role( RoleArn=role_arn, RoleSessionName=session_name, DurationSeconds=duration ) return response['Credentials'] except ClientError as e: self.logger.log_unhandled_exception(e) raise def get_caller_identity(self): try: response = self.sts_client.get_caller_identity() return response except ClientError as e: self.logger.log_unhandled_exception(e) raise
39.577465
79
0.529181
3521ce3e541160b7a0738f5f3c1d166d8da4c82d
2,489
py
Python
src/hostedkafka/confluent_compute_statistics.py
wadkars/python_streaming_utils
eef2c43b65feb075c3753d21b96bcac4ab12a1a7
[ "Apache-2.0" ]
null
null
null
src/hostedkafka/confluent_compute_statistics.py
wadkars/python_streaming_utils
eef2c43b65feb075c3753d21b96bcac4ab12a1a7
[ "Apache-2.0" ]
null
null
null
src/hostedkafka/confluent_compute_statistics.py
wadkars/python_streaming_utils
eef2c43b65feb075c3753d21b96bcac4ab12a1a7
[ "Apache-2.0" ]
1
2021-02-04T20:30:47.000Z
2021-02-04T20:30:47.000Z
import sys from json import loads from confluent_kafka import Consumer from confluent_kafka.cimpl import KafkaError, KafkaException from confluent_kafka import TopicPartition import datetime import statistics user = '<USER_NAME>' pwd = '<PWD>' bsts = 'pkc-4kgmg.us-west-2.aws.confluent.cloud:9092' t = <TOPIC_NAME> conf = {'bootstrap.servers': bsts, 'sasl.mechanism': 'PLAIN', 'security.protocol': 'SASL_SSL', 'sasl.username': user, 'sasl.password': pwd, 'ssl.ca.location': '/tmp/cacert.pem', 'group.id': <PROVIDE_A_UNIQUE_VALUE_FOR_EACH_RUN>, 'auto.offset.reset': 'smallest'} running = True def basic_consume_loop(consumer, topics): try: consumer.assign(topics) durs = [] i=0 message = {} while running: msg = consumer.poll(timeout=1.0) if msg is None: continue message = {} if msg.error(): if msg.error().code() == KafkaError._PARTITION_EOF: # End of partition event sys.stderr.write('%% %s [%d] reached end at offset %d\n' % (msg.topic(), msg.partition(), msg.offset())) elif msg.error(): raise KafkaException(msg.error()) else: message = loads(msg.value().decode("utf-8")) #print(message) if not message['dur_evt_inf'] is None: i = i + 1 durs.append(message['dur_evt_inf']) if(i==1000000): break #durs.append(m['dur_evt_inf']) if (i % 1000 == 0): print(message) #now2 = datetime.now() print(i) finally: # Close down consumer to commit final offsets. consumer.close() #print(durs) mean = statistics.mean(durs) median = statistics.median(durs) max1 = max(durs) min2 = min(durs) print('max=' + str(max1)) print('min=' + str(min2)) print('avg=' + str(mean)) print('med=' + str(median)) print('total obs =' + str(len(durs))) def shutdown(): running = False consumer = Consumer(conf) tls = [TopicPartition(t, 0),TopicPartition(t, 1),TopicPartition(t, 2),TopicPartition(t, 3), TopicPartition(t, 4),TopicPartition(t, 5),TopicPartition(t, 6),TopicPartition(t, 7)] basic_consume_loop(consumer,tls)
31.506329
91
0.548011
08432c14c76b56f6947a8c253f076a37c8e28cf3
920
py
Python
california_house.py
KyleXus/Advanced-Programming
f00bb2882f7c39c98b9616de36ed681339cd29ac
[ "Unlicense" ]
null
null
null
california_house.py
KyleXus/Advanced-Programming
f00bb2882f7c39c98b9616de36ed681339cd29ac
[ "Unlicense" ]
null
null
null
california_house.py
KyleXus/Advanced-Programming
f00bb2882f7c39c98b9616de36ed681339cd29ac
[ "Unlicense" ]
null
null
null
import sqlite3 from flask import Flask, render_template app = Flask(__name__) @app.route('/') def index(): return render_template('index.html') @app.route('/test') def test(): # open the connection to the database conn = sqlite3.connect('california_house_data.db') conn.row_factory = sqlite3.Row cur = conn.cursor() # fetch data from the deployments table cur.execute("select * from test") rows_deploy = cur.fetchall() conn.close() return render_template('test.html', rows_deploy=rows_deploy) @app.route('/train') def train(): # open the connection to the database conn = sqlite3.connect('california_house_data.db') conn.row_factory = sqlite3.Row cur = conn.cursor() # fetch data from the status table cur.execute("select * from train") rows_status = cur.fetchall() conn.close() return render_template('train.html', rows_status=rows_status)
28.75
65
0.696739
4364e37969cda11b9d33590505efd86afb32febd
1,831
py
Python
python/exampleForm.py
wbrown-web/wdv495
546592a2dc8ac82296747e31f6406021c03c377c
[ "MIT" ]
null
null
null
python/exampleForm.py
wbrown-web/wdv495
546592a2dc8ac82296747e31f6406021c03c377c
[ "MIT" ]
null
null
null
python/exampleForm.py
wbrown-web/wdv495
546592a2dc8ac82296747e31f6406021c03c377c
[ "MIT" ]
null
null
null
#!/usr/local/python-3.5 # # Import modules for CGI handling # import cgi, cgitb # # Create instance of FieldStorage # form = cgi.FieldStorage() # # Get data from fields # firstname = form.getvalue('firstname') # lastname = form.getvalue('lastname') # school = form.getvalue('school') print("content-type: text/html\n\n" ) #enables the python to be output by the browser print("<html>") print("<head>") print('<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />') print("<title>WDV341 Intro PHP - Form Example</title>") print("</head>") print("<body>") print("<h1>WDV341 Intro PHP</h1>") print("<h2>WDV101 Intro HTML and CSS Chapter 9 - Creating Forms - Code Example</h2>") print("<p><strong>Basic Form Handler</strong> - This process will display the 'name = value' pairs for all the elements of a form. This summary will on any number of form elements regardless of their name attribute value. </p>") print("<p>Use <strong>basicFormExample.php</strong> in the action attribute of your form. </p>") print("<p>Field '<strong>name</strong>' - The value of the name attribute from the HTML form element.</p>") print("<p>Field <strong>'value</strong>' - The value entered in the field. This will vary depending upon the HTML form element.</p>") print('<form id="form1" name="form1" method="post" action="exampleForm.py">') print('<p>First Name: <input type="text" name="firstName" id="firstName" /> </p>') print('<p>Last Name: <input type="text" name="lastName" id="lastName" /></p>') print('<p>School: <input type="text" name="school" id="school" /></p>') print('<p>') print('<input type="submit" name="button" id="button" value="Submit" />') print('<input type="reset" name="button2" id="button2" value="Reset" />') print('</p>') print('</form>') print('</p>&nbsp;</p>') print("</body>") print("</html>")
44.658537
228
0.682141
fa359631c2556091322c9b1ad4d84937ce25b728
7,664
py
Python
core/management/commands/_base.py
klebed/esdc-ce
2c9e4591f344247d345a83880ba86777bb794460
[ "Apache-2.0" ]
97
2016-11-15T14:44:23.000Z
2022-03-13T18:09:15.000Z
core/management/commands/_base.py
klebed/esdc-ce
2c9e4591f344247d345a83880ba86777bb794460
[ "Apache-2.0" ]
334
2016-11-17T19:56:57.000Z
2022-03-18T10:45:53.000Z
core/management/commands/_base.py
klebed/esdc-ce
2c9e4591f344247d345a83880ba86777bb794460
[ "Apache-2.0" ]
33
2017-01-02T16:04:13.000Z
2022-02-07T19:20:24.000Z
from __future__ import absolute_import from __future__ import print_function import os import getpass from optparse import Option from subprocess import Popen, PIPE, STDOUT from contextlib import contextmanager from django.core.management.base import BaseCommand, CommandError from django.core.management import call_command # noinspection PyUnresolvedReferences from django.utils.six.moves import input from django.conf import settings from ._color import no_color, shell_color @contextmanager def lcd(dirpath): """A context manager which changes the working directory to the given path, and then changes it back to its previous value on exit.""" prev_cwd = os.getcwd() dirpath = dirpath.replace(' ', '\ ') # noqa: W605 if not dirpath.startswith('/') and not dirpath.startswith('~'): new_cwd = os.path.join(os.path.abspath(os.getcwd()), dirpath) else: new_cwd = dirpath os.chdir(new_cwd) try: yield finally: os.chdir(prev_cwd) CommandOption = Option # noinspection PyAbstractClass class DanubeCloudCommand(BaseCommand): """ Base class for all Danube Cloud commands. """ settings = settings DEFAULT_BRANCH = 'master' PROJECT_DIR = settings.PROJECT_DIR PROJECT_NAME = 'esdc-ce' CTLSH = os.path.join(PROJECT_DIR, 'bin', 'ctl.sh') cmd_sha = 'git log --pretty=oneline -1 | cut -d " " -f 1' cmd_tag = 'git symbolic-ref -q --short HEAD || git describe --tags --exact-match' default_verbosity = 1 verbose = False strip_newline = False colors = shell_color options = () option_list = BaseCommand.option_list + ( CommandOption('--no-newline', action='store_true', dest='no_newline', default=False, help='Strip newlines from output'), ) _local_username = None def __init__(self, **kwargs): if self.options: self.option_list = self.__class__.option_list + self.options super(DanubeCloudCommand, self).__init__(**kwargs) def get_version(self): """This isn't used anywhere""" from core.version import __version__ return 'Danube Cloud %s' % __version__ def get_git_version(self): with lcd(self.PROJECT_DIR): _tag = self.local(self.cmd_tag, capture=True).strip().split('/')[-1] _sha = self.local(self.cmd_sha, capture=True).strip() return _tag, _sha def execute(self, *args, **options): """Set some default attributes before calling handle()""" self.verbose = int(options.get('verbosity', self.default_verbosity)) >= self.default_verbosity self.strip_newline = options.pop('no_newline', False) if options.get('no_color'): options['no_color'] = True self.colors = no_color return super(DanubeCloudCommand, self).execute(*args, **options) @staticmethod def confirm(question, default='yes'): """ http://stackoverflow.com/questions/3041986/python-command-line-yes-no-input Ask a yes/no question via raw_input() and return their answer. "question" is a string that is presented to the user. "default" is the presumed answer if the user just hits <Enter>. It must be "yes" (the default), "no" or None (meaning an answer is required of the user). The "answer" return value is one of "yes" or "no". """ valid = {"yes": True, "y": True, "no": False, "n": False} if default is None: prompt = " [y/n] " elif default == "yes": prompt = " [Y/n] " elif default == "no": prompt = " [y/N] " else: raise ValueError("invalid default answer: '%s'" % default) while True: print(question + prompt, end='') choice = input().lower() if default is not None and choice == '': return valid[default] elif choice in valid: return valid[choice] else: print("Please respond with 'yes' or 'no' (or 'y' or 'n').") @staticmethod def _path(*args): """Helper method used by lot of commands""" return os.path.join(*args) @staticmethod def _path_exists(basepath, *args): """Helper method used by lot of commands""" return os.path.exists(os.path.join(basepath, *args)) @property def local_username(self): """Used by the command_prompt property""" if self._local_username is None: self._local_username = getpass.getuser() return self._local_username @property def command_prompt(self): """Return command prompt: [user@localhost CWD] """ return '%s%s:%s]' % (self.colors.reset('['), self.colors.cyan('%s@localhost' % self.local_username), self.colors.blue(os.path.realpath(os.getcwd()))) def display(self, text, stderr=False, color=None, ending=None): """Display message on stdout or stderr""" if self.strip_newline: text = text.strip('\n') if color: color_fun = getattr(self.colors, color, None) else: color_fun = None if stderr: self.stderr.write(text, style_func=color_fun, ending=ending) else: self.stdout.write(text, style_func=color_fun, ending=ending) def local(self, command, capture=False, stderr_to_stdout=True, shell=True, echo_command=None, raise_on_error=True): """Run a command on the local system.""" if echo_command is None and self.verbose: echo_command = True if capture: out_stream = PIPE if stderr_to_stdout: err_stream = STDOUT else: err_stream = PIPE else: out_stream = err_stream = None if echo_command: self.display('%s %s' % (self.command_prompt, command), stderr=True) p = Popen(command, shell=shell, stdout=out_stream, stderr=err_stream, close_fds=True, bufsize=-1) stdout, stderr = p.communicate() if raise_on_error and p.returncode != 0: raise CommandError('Command "%s" returned with non-zero exit code (%d)' % (command, p.returncode)) if capture: if stderr_to_stdout: return stdout else: return stdout, stderr return p.returncode def managepy(self, cmd, *args, **kwargs): """Run Django management command. WARNING: the kwargs options have usually different names than the command line parameters - check the source code of the specific django command for more info""" if kwargs.pop('echo_command', self.verbose): params = ' '.join(['--%s=%s' % (k, repr(v)) for k, v in kwargs.items()] + list(args)) self.display('%s manage.py %s %s' % (self.command_prompt, cmd, params), stderr=True) return call_command(cmd, *args, **kwargs) def ctlsh(self, *cmd, **kwargs): """Run the ctl.sh script""" cmd_desc = 'ctl.sh ' + ' '.join(cmd) if kwargs.get('echo_command', self.verbose): self.display('%s %s' % (self.command_prompt, cmd_desc), stderr=True) cmd = (self.CTLSH,) + cmd p = Popen(cmd, shell=False, close_fds=True, bufsize=-1) p.communicate() if kwargs.get('raise_on_error', True) and p.returncode != 0: raise CommandError('Command "%s" returned with non-zero exit code (%d)' % (cmd_desc, p.returncode)) return p.returncode
33.467249
112
0.609603
1b71035800ba386ce48d66fa4055fc9084b8d405
6,194
py
Python
plugin.video.SportsDevil/lib/common.py
akuala/REPO.KUALA
ea9a157025530d2ce8fa0d88431c46c5352e89d4
[ "Apache-2.0" ]
2
2018-11-02T19:55:30.000Z
2020-08-14T02:22:20.000Z
plugin.video.SportsDevil/lib/common.py
akuala/REPO.KUALA
ea9a157025530d2ce8fa0d88431c46c5352e89d4
[ "Apache-2.0" ]
null
null
null
plugin.video.SportsDevil/lib/common.py
akuala/REPO.KUALA
ea9a157025530d2ce8fa0d88431c46c5352e89d4
[ "Apache-2.0" ]
3
2019-12-17T20:47:00.000Z
2021-02-11T19:03:59.000Z
# -*- coding: utf-8 -*- import os, json #------------------------------------------------------------------------------ # xbmc related #------------------------------------------------------------------------------ import xbmc, xbmcaddon __settings__ = xbmcaddon.Addon(id='plugin.video.SportsDevil') __icon__ = xbmcaddon.Addon(id='plugin.video.SportsDevil').getAddonInfo('icon') translate = __settings__.getLocalizedString enable_debug = True language = xbmc.getLanguage xbmcVersion = float(xbmc.getInfoLabel('System.BuildVersion')[0:4]) def log(msg, level=xbmc.LOGDEBUG): plugin = "SportsDevil" msg = msg.encode('utf-8') xbmc.log("[%s] %s" % (plugin, msg.__str__()), level) def json_rpc_request(payload): """Kodi JSON-RPC request. Return the response in a dictionary.""" xbmc.log('jsonrpc payload: {0}'.format(payload)) response = xbmc.executeJSONRPC(json.dumps(payload)) xbmc.log('jsonrpc response: {0}'.format(response)) return json.loads(response) def getSetting(name): return __settings__.getSetting(name) def setSetting(name, value): __settings__.setSetting(id=name, value=value) def showNotification(title, message, timeout=2000, icon=__icon__): def clean(s): return str(s.encode('utf-8', 'ignore')) command = '' if icon: command = 'Notification(%s,%s,%s,%s)' % (clean(title), clean(message), timeout, icon) else: command = 'Notification(%s,%s,%s)' % (clean(title), clean(message), timeout) xbmc.executebuiltin(command) def runPlugin(url): xbmc.executebuiltin('XBMC.RunPlugin(' + url +')') #------------------------------------------------------------------------------ # dialogs #------------------------------------------------------------------------------ from dialogs.dialogQuestion import DialogQuestion from dialogs.dialogBrowser import DialogBrowser from dialogs.dialogInfo import DialogInfo from dialogs.dialogError import DialogError from utils.xbmcUtils import getKeyboard def ask(question): diaQuestion = DialogQuestion() return diaQuestion.ask(question) def showInfo(message): diaInfo = DialogInfo() diaInfo.show(message) def showError(message): diaError = DialogError() diaError.show(message) def browseFolders(head): diaFolder = DialogBrowser() return diaFolder.browseFolders(head) def showOSK(defaultText='', title='', hidden=False): return getKeyboard(defaultText, title, hidden) #------------------------------------------------------------------------------ # web related #------------------------------------------------------------------------------ from utils.regexUtils import parseTextToGroups from utils.webUtils import CachedWebRequest import cookielib def getHTML(url, form_data='', referer='', xml=False, mobile=False, ignoreCache=False, demystify=False): if 'ws://' in url: from utils.webUtils import WSCLient wsc = WSCLient() return wsc.getSS365(url) else: if url == 'http://www.streamlive.to': url = xbmc.translatePath(os.path.join(Paths.imgDir, 'live.xml')) if url == 'http://www.tvone1.tv': url = xbmc.translatePath(os.path.join(Paths.imgDir, 'tvone.xml')) cookiePath = xbmc.translatePath(os.path.join(Paths.cacheDir, 'cookies.lwp')) request = CachedWebRequest(cookiePath, Paths.cacheDir) return request.getSource(url, form_data, referer, xml, mobile, ignoreCache, demystify) def getLocation(url): #get 302 response location if 'tinyurl' in url: cookiePath = xbmc.translatePath(os.path.join(Paths.cacheDir, 'cookies.lwp')) request = CachedWebRequest(cookiePath, Paths.cacheDir) return request.getLocation(url) return url def getCookies(cookieName, domain): cookiePath = xbmc.translatePath(os.path.join(Paths.cacheDir, 'cookies.lwp')) def load_cookies_from_lwp(filename): lwp_cookiejar = cookielib.LWPCookieJar() lwp_cookiejar.load(filename, ignore_discard=True) return lwp_cookiejar for cookie in load_cookies_from_lwp(cookiePath): if domain in cookie.domain or cookie.domain in domain and cookieName in cookie.name: return cookie.value def parseWebsite(source, regex, referer='', variables=[]): def parseWebsiteToGroups(url, regex, referer=''): data = getHTML(url, None, referer) return parseTextToGroups(data, regex) groups = parseWebsiteToGroups(source, regex, referer) if variables == []: if groups: return groups[0] else: return '' else: resultArr = {} i = 0 for v in variables: if groups: resultArr[v] = groups[i] else: resultArr[v] = '' i += 1 return resultArr #------------------------------------------------------------------------------ # classes with constants #------------------------------------------------------------------------------ class Paths: rootDir = xbmc.translatePath(__settings__.getAddonInfo('path')).decode('utf-8') resDir = os.path.join(rootDir, 'resources') imgDir = os.path.join(resDir, 'images') modulesDir = os.path.join(resDir, 'modules') catchersDir = os.path.join(resDir,'catchers') dictsDir = os.path.join(resDir,'dictionaries') pluginFanart = os.path.join(rootDir, 'fanart.jpg') defaultVideoIcon = os.path.join(imgDir, 'video.png') defaultCategoryIcon = os.path.join(imgDir, 'folder.png') pluginDataDir = xbmc.translatePath(__settings__.getAddonInfo('profile')).decode('utf-8') cacheDir = os.path.join(pluginDataDir, 'cache') favouritesFolder = os.path.join(pluginDataDir, 'favourites') favouritesFile = os.path.join(favouritesFolder, 'favourites.cfg') customModulesDir = os.path.join(pluginDataDir, 'custom') customModulesFile = os.path.join(customModulesDir, 'custom.cfg') catchersRepo = '' modulesRepo = '' customModulesRepo = '' xbmcFavouritesFile = xbmc.translatePath( 'special://profile/favourites.xml' )
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