body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1 value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
c6d27716acbb01408df34c92b94ff96eb05e5b3d4676fb8ea6d39424baa4fa42 | def load_ckpt(network, pretrain_ckpt_path, trainable=True):
'\n incremental_learning or not\n '
param_dict = load_checkpoint(pretrain_ckpt_path)
load_param_into_net(network, param_dict)
if (not trainable):
for param in network.get_parameters():
param.requires_grad = False | incremental_learning or not | model_zoo/research/nlp/dscnn/src/models.py | load_ckpt | limberc/mindspore | 77 | python | def load_ckpt(network, pretrain_ckpt_path, trainable=True):
'\n \n '
param_dict = load_checkpoint(pretrain_ckpt_path)
load_param_into_net(network, param_dict)
if (not trainable):
for param in network.get_parameters():
param.requires_grad = False | def load_ckpt(network, pretrain_ckpt_path, trainable=True):
'\n \n '
param_dict = load_checkpoint(pretrain_ckpt_path)
load_param_into_net(network, param_dict)
if (not trainable):
for param in network.get_parameters():
param.requires_grad = False<|docstring|>incremental_learning or not<|endoftext|> |
9051c5ad184a2662774907ce7a13e35aa5a1729bb038ad87f3b53c2a459c49de | @classmethod
def __getImgServiceByConfig(cls) -> ImgService:
'ๆ นๆฎๅฝๅ็ณป็ป้
็ฝฎ่ฟๅๅ้็ๅพ็ๆๅก'
sysConfig = Config.getInstance()
imgService = sysConfig.getConfigParam(Config.PARAM_IMG_SERVICE)
return cls.getImgServiceByFlag(imgService) | ๆ นๆฎๅฝๅ็ณป็ป้
็ฝฎ่ฟๅๅ้็ๅพ็ๆๅก | src/markdown_img/img_service_manager.py | __getImgServiceByConfig | icexmoon/markdown-img | 24 | python | @classmethod
def __getImgServiceByConfig(cls) -> ImgService:
sysConfig = Config.getInstance()
imgService = sysConfig.getConfigParam(Config.PARAM_IMG_SERVICE)
return cls.getImgServiceByFlag(imgService) | @classmethod
def __getImgServiceByConfig(cls) -> ImgService:
sysConfig = Config.getInstance()
imgService = sysConfig.getConfigParam(Config.PARAM_IMG_SERVICE)
return cls.getImgServiceByFlag(imgService)<|docstring|>ๆ นๆฎๅฝๅ็ณป็ป้
็ฝฎ่ฟๅๅ้็ๅพ็ๆๅก<|endoftext|> |
ff407919ce46b9fd31ace584429c12b80810def1e77ca5708d0619cdd22c8582 | @classmethod
def getImgServiceByFlag(cls, flag: str) -> ImgService:
'ๆ นๆฎๅพ็ๆๅกๆ ่ฏ่ทๅ็ธๅบ็ๅพ็ๆๅก\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
webImage: ImgService
imgService = flag
if (imgService == Config.IMG_SERVICE_ALI):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_ALI2):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_RRUU):
webImage = NoneImgService()
elif (imgService == Config.IMG_SERVICE_VIMCN):
webImage = VimcnImgService()
elif (imgService == Config.IMG_SERVICE_YUJIAN):
webImage = YujianImgService()
elif (imgService == Config.IMG_SERVICE_QCLOUD):
webImage = QcloudImgService()
elif (imgService == Config.IMG_SERVICE_QINIU):
webImage = QiniuImgService()
elif (imgService == Config.IMG_SERVICE_BILIBILI):
webImage = YujianImgService(YujianImgService.API_TYPE_BILIBILI)
elif (imgService == Config.IMG_SERVICE_360):
webImage = YujianImgService(YujianImgService.API_TYPE_QIHOO)
elif (imgService == Config.IMG_SERVICE_AI58):
webImage = YujianImgService(YujianImgService.API_TYPE_AI58)
elif (imgService == Config.IMG_SERVICE_SOUGOU):
webImage = YujianImgService(YujianImgService.API_TYPE_SOUGOU)
elif (imgService == Config.IMG_SERVICE_HULUXIA):
webImage = YujianImgService(YujianImgService.API_TYPE_HULUXIA)
elif (imgService == Config.IMG_SERVICE_CATBOX):
webImage = YujianImgService(YujianImgService.API_TYPE_CATBOX)
elif (imgService == Config.IMG_SERVICE_POSTIMAGES):
webImage = YujianImgService(YujianImgService.API_TYPE_POSTIMAGES)
elif (imgService == Config.IMG_SERVICE_GTIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_GTIMG)
elif (imgService == Config.IMG_SERVICE_BKIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_BKIMG)
elif (imgService == Config.IMG_SERVICE_MUKE):
webImage = YujianImgService(YujianImgService.API_TYPE_MUKE)
elif (imgService == Config.IMG_SERVICE_UPYUN):
webImage = UpyunImgService()
else:
webImage = SmmsImgService()
return webImage | ๆ นๆฎๅพ็ๆๅกๆ ่ฏ่ทๅ็ธๅบ็ๅพ็ๆๅก
flag: ๅพ็ๆๅกๆ ่ฏ | src/markdown_img/img_service_manager.py | getImgServiceByFlag | icexmoon/markdown-img | 24 | python | @classmethod
def getImgServiceByFlag(cls, flag: str) -> ImgService:
'ๆ นๆฎๅพ็ๆๅกๆ ่ฏ่ทๅ็ธๅบ็ๅพ็ๆๅก\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
webImage: ImgService
imgService = flag
if (imgService == Config.IMG_SERVICE_ALI):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_ALI2):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_RRUU):
webImage = NoneImgService()
elif (imgService == Config.IMG_SERVICE_VIMCN):
webImage = VimcnImgService()
elif (imgService == Config.IMG_SERVICE_YUJIAN):
webImage = YujianImgService()
elif (imgService == Config.IMG_SERVICE_QCLOUD):
webImage = QcloudImgService()
elif (imgService == Config.IMG_SERVICE_QINIU):
webImage = QiniuImgService()
elif (imgService == Config.IMG_SERVICE_BILIBILI):
webImage = YujianImgService(YujianImgService.API_TYPE_BILIBILI)
elif (imgService == Config.IMG_SERVICE_360):
webImage = YujianImgService(YujianImgService.API_TYPE_QIHOO)
elif (imgService == Config.IMG_SERVICE_AI58):
webImage = YujianImgService(YujianImgService.API_TYPE_AI58)
elif (imgService == Config.IMG_SERVICE_SOUGOU):
webImage = YujianImgService(YujianImgService.API_TYPE_SOUGOU)
elif (imgService == Config.IMG_SERVICE_HULUXIA):
webImage = YujianImgService(YujianImgService.API_TYPE_HULUXIA)
elif (imgService == Config.IMG_SERVICE_CATBOX):
webImage = YujianImgService(YujianImgService.API_TYPE_CATBOX)
elif (imgService == Config.IMG_SERVICE_POSTIMAGES):
webImage = YujianImgService(YujianImgService.API_TYPE_POSTIMAGES)
elif (imgService == Config.IMG_SERVICE_GTIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_GTIMG)
elif (imgService == Config.IMG_SERVICE_BKIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_BKIMG)
elif (imgService == Config.IMG_SERVICE_MUKE):
webImage = YujianImgService(YujianImgService.API_TYPE_MUKE)
elif (imgService == Config.IMG_SERVICE_UPYUN):
webImage = UpyunImgService()
else:
webImage = SmmsImgService()
return webImage | @classmethod
def getImgServiceByFlag(cls, flag: str) -> ImgService:
'ๆ นๆฎๅพ็ๆๅกๆ ่ฏ่ทๅ็ธๅบ็ๅพ็ๆๅก\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
webImage: ImgService
imgService = flag
if (imgService == Config.IMG_SERVICE_ALI):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_ALI2):
webImage = YujianImgService(YujianImgService.API_TYPE_ALI)
elif (imgService == Config.IMG_SERVICE_RRUU):
webImage = NoneImgService()
elif (imgService == Config.IMG_SERVICE_VIMCN):
webImage = VimcnImgService()
elif (imgService == Config.IMG_SERVICE_YUJIAN):
webImage = YujianImgService()
elif (imgService == Config.IMG_SERVICE_QCLOUD):
webImage = QcloudImgService()
elif (imgService == Config.IMG_SERVICE_QINIU):
webImage = QiniuImgService()
elif (imgService == Config.IMG_SERVICE_BILIBILI):
webImage = YujianImgService(YujianImgService.API_TYPE_BILIBILI)
elif (imgService == Config.IMG_SERVICE_360):
webImage = YujianImgService(YujianImgService.API_TYPE_QIHOO)
elif (imgService == Config.IMG_SERVICE_AI58):
webImage = YujianImgService(YujianImgService.API_TYPE_AI58)
elif (imgService == Config.IMG_SERVICE_SOUGOU):
webImage = YujianImgService(YujianImgService.API_TYPE_SOUGOU)
elif (imgService == Config.IMG_SERVICE_HULUXIA):
webImage = YujianImgService(YujianImgService.API_TYPE_HULUXIA)
elif (imgService == Config.IMG_SERVICE_CATBOX):
webImage = YujianImgService(YujianImgService.API_TYPE_CATBOX)
elif (imgService == Config.IMG_SERVICE_POSTIMAGES):
webImage = YujianImgService(YujianImgService.API_TYPE_POSTIMAGES)
elif (imgService == Config.IMG_SERVICE_GTIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_GTIMG)
elif (imgService == Config.IMG_SERVICE_BKIMG):
webImage = YujianImgService(YujianImgService.API_TYPE_BKIMG)
elif (imgService == Config.IMG_SERVICE_MUKE):
webImage = YujianImgService(YujianImgService.API_TYPE_MUKE)
elif (imgService == Config.IMG_SERVICE_UPYUN):
webImage = UpyunImgService()
else:
webImage = SmmsImgService()
return webImage<|docstring|>ๆ นๆฎๅพ็ๆๅกๆ ่ฏ่ทๅ็ธๅบ็ๅพ็ๆๅก
flag: ๅพ็ๆๅกๆ ่ฏ<|endoftext|> |
3d0684f0cf4e8f60f28abad76f8d423d33e99da00d9f3c87e14eca7d67ccfc1c | @classmethod
def isValidImgServiceFlag(cls, flag: str) -> bool:
'ๆฏๅฆไธบๅๆณ็ๅพ็ๆๅกๆ ่ฏ\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
supportedService = {Config.IMG_SERVICE_SMMS, Config.IMG_SERVICE_ALI, Config.IMG_SERVICE_RRUU, Config.IMG_SERVICE_VIMCN, Config.IMG_SERVICE_YUJIAN, Config.IMG_SERVICE_ALI2, Config.IMG_SERVICE_QCLOUD, Config.IMG_SERVICE_QINIU, Config.IMG_SERVICE_BILIBILI, Config.IMG_SERVICE_SOUGOU, Config.IMG_SERVICE_HULUXIA, Config.IMG_SERVICE_CATBOX, Config.IMG_SERVICE_360, Config.IMG_SERVICE_POSTIMAGES, Config.IMG_SERVICE_AI58, Config.IMG_SERVICE_GTIMG, Config.IMG_SERVICE_BKIMG, Config.IMG_SERVICE_MUKE, Config.IMG_SERVICE_UPYUN}
if (flag in supportedService):
return True
return False | ๆฏๅฆไธบๅๆณ็ๅพ็ๆๅกๆ ่ฏ
flag: ๅพ็ๆๅกๆ ่ฏ | src/markdown_img/img_service_manager.py | isValidImgServiceFlag | icexmoon/markdown-img | 24 | python | @classmethod
def isValidImgServiceFlag(cls, flag: str) -> bool:
'ๆฏๅฆไธบๅๆณ็ๅพ็ๆๅกๆ ่ฏ\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
supportedService = {Config.IMG_SERVICE_SMMS, Config.IMG_SERVICE_ALI, Config.IMG_SERVICE_RRUU, Config.IMG_SERVICE_VIMCN, Config.IMG_SERVICE_YUJIAN, Config.IMG_SERVICE_ALI2, Config.IMG_SERVICE_QCLOUD, Config.IMG_SERVICE_QINIU, Config.IMG_SERVICE_BILIBILI, Config.IMG_SERVICE_SOUGOU, Config.IMG_SERVICE_HULUXIA, Config.IMG_SERVICE_CATBOX, Config.IMG_SERVICE_360, Config.IMG_SERVICE_POSTIMAGES, Config.IMG_SERVICE_AI58, Config.IMG_SERVICE_GTIMG, Config.IMG_SERVICE_BKIMG, Config.IMG_SERVICE_MUKE, Config.IMG_SERVICE_UPYUN}
if (flag in supportedService):
return True
return False | @classmethod
def isValidImgServiceFlag(cls, flag: str) -> bool:
'ๆฏๅฆไธบๅๆณ็ๅพ็ๆๅกๆ ่ฏ\n flag: ๅพ็ๆๅกๆ ่ฏ\n '
supportedService = {Config.IMG_SERVICE_SMMS, Config.IMG_SERVICE_ALI, Config.IMG_SERVICE_RRUU, Config.IMG_SERVICE_VIMCN, Config.IMG_SERVICE_YUJIAN, Config.IMG_SERVICE_ALI2, Config.IMG_SERVICE_QCLOUD, Config.IMG_SERVICE_QINIU, Config.IMG_SERVICE_BILIBILI, Config.IMG_SERVICE_SOUGOU, Config.IMG_SERVICE_HULUXIA, Config.IMG_SERVICE_CATBOX, Config.IMG_SERVICE_360, Config.IMG_SERVICE_POSTIMAGES, Config.IMG_SERVICE_AI58, Config.IMG_SERVICE_GTIMG, Config.IMG_SERVICE_BKIMG, Config.IMG_SERVICE_MUKE, Config.IMG_SERVICE_UPYUN}
if (flag in supportedService):
return True
return False<|docstring|>ๆฏๅฆไธบๅๆณ็ๅพ็ๆๅกๆ ่ฏ
flag: ๅพ็ๆๅกๆ ่ฏ<|endoftext|> |
e0996eea3ca0d7a838b58db13e6952f59ce6b9b671f885ad0c4bb4496d5085da | def glInitFramebufferMultisampleBlitScaledEXT():
'Return boolean indicating whether this extension is available'
from OpenGL import extensions
return extensions.hasGLExtension(_EXTENSION_NAME) | Return boolean indicating whether this extension is available | OpenGL/GL/EXT/framebuffer_multisample_blit_scaled.py | glInitFramebufferMultisampleBlitScaledEXT | keunhong/pyopengl | 210 | python | def glInitFramebufferMultisampleBlitScaledEXT():
from OpenGL import extensions
return extensions.hasGLExtension(_EXTENSION_NAME) | def glInitFramebufferMultisampleBlitScaledEXT():
from OpenGL import extensions
return extensions.hasGLExtension(_EXTENSION_NAME)<|docstring|>Return boolean indicating whether this extension is available<|endoftext|> |
25f0c0ea1355985c9c33444873c8c6cc32e976dd4c3c17f9f02dba7eedddd805 | def on_timeout(self, user_data):
'\n Update value on the progress bar\n '
if self.activity_mode:
self.progressbar.pulse()
else:
new_value = (self.progressbar.get_fraction() + 0.01)
if (new_value > 1):
new_value = 0
self.progressbar.set_fraction(new_value)
return True | Update value on the progress bar | gym_pcgrl/gym_pcgrl/conditional_window.py | on_timeout | JiangZehua/control-pcgrl3D | 15 | python | def on_timeout(self, user_data):
'\n \n '
if self.activity_mode:
self.progressbar.pulse()
else:
new_value = (self.progressbar.get_fraction() + 0.01)
if (new_value > 1):
new_value = 0
self.progressbar.set_fraction(new_value)
return True | def on_timeout(self, user_data):
'\n \n '
if self.activity_mode:
self.progressbar.pulse()
else:
new_value = (self.progressbar.get_fraction() + 0.01)
if (new_value > 1):
new_value = 0
self.progressbar.set_fraction(new_value)
return True<|docstring|>Update value on the progress bar<|endoftext|> |
34d8efa607b3b51b7943b7744b8e005312c8a6417025bb612b08dbff9e9c3da0 | def parse_darts_log(log_path, key_point='ea_acc'):
'\n report vaild\n '
collect = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
collect = []
if (key_point in l):
metirc = float(l.split(key_point)[(- 1)])
print(metirc)
collect.append(metirc)
print(collect) | report vaild | Model_speed/FLOPs.py | parse_darts_log | Yanjun-Chen/Python-Tools | 1 | python | def parse_darts_log(log_path, key_point='ea_acc'):
'\n \n '
collect = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
collect = []
if (key_point in l):
metirc = float(l.split(key_point)[(- 1)])
print(metirc)
collect.append(metirc)
print(collect) | def parse_darts_log(log_path, key_point='ea_acc'):
'\n \n '
collect = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
collect = []
if (key_point in l):
metirc = float(l.split(key_point)[(- 1)])
print(metirc)
collect.append(metirc)
print(collect)<|docstring|>report vaild<|endoftext|> |
3196c93d357e21b267d381af0f8813cc4ee38c1e3a7810a9cfdd4abb13306b19 | def parse_vs(log_path):
'\n report vaild\n '
previous = []
current = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
previous = []
current = []
if ('previous_vs_current' in l):
import pdb
pdb.set_trace()
p = float(l.split('previous_vs_current')[0].split(' ')[(- 1)])
c = float(l.split('previous_vs_current')[(- 1)].split(' ')[0])
print(metirc)
collect.append(metirc)
print(collect) | report vaild | Model_speed/FLOPs.py | parse_vs | Yanjun-Chen/Python-Tools | 1 | python | def parse_vs(log_path):
'\n \n '
previous = []
current = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
previous = []
current = []
if ('previous_vs_current' in l):
import pdb
pdb.set_trace()
p = float(l.split('previous_vs_current')[0].split(' ')[(- 1)])
c = float(l.split('previous_vs_current')[(- 1)].split(' ')[0])
print(metirc)
collect.append(metirc)
print(collect) | def parse_vs(log_path):
'\n \n '
previous = []
current = []
for l in open(log_path).readlines():
l = l.strip('/n')
if ('args = Namespace' in l):
previous = []
current = []
if ('previous_vs_current' in l):
import pdb
pdb.set_trace()
p = float(l.split('previous_vs_current')[0].split(' ')[(- 1)])
c = float(l.split('previous_vs_current')[(- 1)].split(' ')[0])
print(metirc)
collect.append(metirc)
print(collect)<|docstring|>report vaild<|endoftext|> |
f85cd45012a2a2862327ddb6fc817c19495668c25385e43dc83e871ea610f569 | def get_lantacy(arch=None, l_limit=8000, h_limit=15000):
'\n only support sfn1 oneshot\n '
if (arch is None):
arch = tuple((np.random.randint(4) for i in range(16)))
assert (len(arch) == 16)
lantacy_map = [[581.0, 741.0, 832.0, 1373.0], [450.0, 549.0, 781.0, 877.0], [402.0, 499.0, 515.0, 742.0], [473.0, 673.0, 647.0, 772.0], [550.0, 553.0, 739.0, 821.0], [450.0, 428.0, 551.0, 472.0], [271.0, 408.0, 405.0, 519.0], [342.0, 388.0, 472.0, 437.0], [347.0, 429.0, 483.0, 446.0], [309.0, 365.0, 481.0, 451.0], [425.0, 461.0, 495.0, 502.0], [276.0, 377.0, 434.0, 452.0], [391.0, 415.0, 413.0, 594.0], [197.0, 289.0, 274.0, 363.0], [148.0, 149.0, 301.0, 350.0], [238.0, 272.0, 221.0, 457.0]]
stem = 4282
classifer = 408
limit = 12000
arch_lantacy = (stem + classifer)
for (layer_id, ops_id) in enumerate(arch):
arch_lantacy += lantacy_map[layer_id][ops_id]
return (arch_lantacy, ((arch_lantacy < h_limit) and (arch_lantacy > l_limit))) | only support sfn1 oneshot | Model_speed/FLOPs.py | get_lantacy | Yanjun-Chen/Python-Tools | 1 | python | def get_lantacy(arch=None, l_limit=8000, h_limit=15000):
'\n \n '
if (arch is None):
arch = tuple((np.random.randint(4) for i in range(16)))
assert (len(arch) == 16)
lantacy_map = [[581.0, 741.0, 832.0, 1373.0], [450.0, 549.0, 781.0, 877.0], [402.0, 499.0, 515.0, 742.0], [473.0, 673.0, 647.0, 772.0], [550.0, 553.0, 739.0, 821.0], [450.0, 428.0, 551.0, 472.0], [271.0, 408.0, 405.0, 519.0], [342.0, 388.0, 472.0, 437.0], [347.0, 429.0, 483.0, 446.0], [309.0, 365.0, 481.0, 451.0], [425.0, 461.0, 495.0, 502.0], [276.0, 377.0, 434.0, 452.0], [391.0, 415.0, 413.0, 594.0], [197.0, 289.0, 274.0, 363.0], [148.0, 149.0, 301.0, 350.0], [238.0, 272.0, 221.0, 457.0]]
stem = 4282
classifer = 408
limit = 12000
arch_lantacy = (stem + classifer)
for (layer_id, ops_id) in enumerate(arch):
arch_lantacy += lantacy_map[layer_id][ops_id]
return (arch_lantacy, ((arch_lantacy < h_limit) and (arch_lantacy > l_limit))) | def get_lantacy(arch=None, l_limit=8000, h_limit=15000):
'\n \n '
if (arch is None):
arch = tuple((np.random.randint(4) for i in range(16)))
assert (len(arch) == 16)
lantacy_map = [[581.0, 741.0, 832.0, 1373.0], [450.0, 549.0, 781.0, 877.0], [402.0, 499.0, 515.0, 742.0], [473.0, 673.0, 647.0, 772.0], [550.0, 553.0, 739.0, 821.0], [450.0, 428.0, 551.0, 472.0], [271.0, 408.0, 405.0, 519.0], [342.0, 388.0, 472.0, 437.0], [347.0, 429.0, 483.0, 446.0], [309.0, 365.0, 481.0, 451.0], [425.0, 461.0, 495.0, 502.0], [276.0, 377.0, 434.0, 452.0], [391.0, 415.0, 413.0, 594.0], [197.0, 289.0, 274.0, 363.0], [148.0, 149.0, 301.0, 350.0], [238.0, 272.0, 221.0, 457.0]]
stem = 4282
classifer = 408
limit = 12000
arch_lantacy = (stem + classifer)
for (layer_id, ops_id) in enumerate(arch):
arch_lantacy += lantacy_map[layer_id][ops_id]
return (arch_lantacy, ((arch_lantacy < h_limit) and (arch_lantacy > l_limit)))<|docstring|>only support sfn1 oneshot<|endoftext|> |
453606b32e291856ac04ecdf7429ae4dd7b8d12607698116fd85325c3c98cc25 | def __init__(self):
'\n Main execution path\n '
self.inventory = dict()
self.hosts = dict()
self.parse_cli_args()
self.read_settings()
if (self.args.refresh_cache or (not self.is_cache_valid())):
self.update_cache()
else:
self.load_inventory_from_cache()
self.load_hosts_from_cache()
data_to_print = ''
if self.args.host:
if self.args.debug:
print(('Fetching host [%s]' % self.args.host))
data_to_print += self.get_host_info(self.args.host)
else:
self.inventory['_meta'] = {'hostvars': {}}
for hostname in self.hosts:
self.inventory['_meta']['hostvars'][hostname] = {'cloudforms': self.hosts[hostname]}
if ('ansible_ssh_host' in self.hosts[hostname]):
self.inventory['_meta']['hostvars'][hostname]['ansible_ssh_host'] = self.hosts[hostname]['ansible_ssh_host']
data_to_print += self.json_format_dict(self.inventory, self.args.pretty)
print(data_to_print) | Main execution path | awx/plugins/inventory/cloudforms.py | __init__ | jmferrer/awx | 37 | python | def __init__(self):
'\n \n '
self.inventory = dict()
self.hosts = dict()
self.parse_cli_args()
self.read_settings()
if (self.args.refresh_cache or (not self.is_cache_valid())):
self.update_cache()
else:
self.load_inventory_from_cache()
self.load_hosts_from_cache()
data_to_print =
if self.args.host:
if self.args.debug:
print(('Fetching host [%s]' % self.args.host))
data_to_print += self.get_host_info(self.args.host)
else:
self.inventory['_meta'] = {'hostvars': {}}
for hostname in self.hosts:
self.inventory['_meta']['hostvars'][hostname] = {'cloudforms': self.hosts[hostname]}
if ('ansible_ssh_host' in self.hosts[hostname]):
self.inventory['_meta']['hostvars'][hostname]['ansible_ssh_host'] = self.hosts[hostname]['ansible_ssh_host']
data_to_print += self.json_format_dict(self.inventory, self.args.pretty)
print(data_to_print) | def __init__(self):
'\n \n '
self.inventory = dict()
self.hosts = dict()
self.parse_cli_args()
self.read_settings()
if (self.args.refresh_cache or (not self.is_cache_valid())):
self.update_cache()
else:
self.load_inventory_from_cache()
self.load_hosts_from_cache()
data_to_print =
if self.args.host:
if self.args.debug:
print(('Fetching host [%s]' % self.args.host))
data_to_print += self.get_host_info(self.args.host)
else:
self.inventory['_meta'] = {'hostvars': {}}
for hostname in self.hosts:
self.inventory['_meta']['hostvars'][hostname] = {'cloudforms': self.hosts[hostname]}
if ('ansible_ssh_host' in self.hosts[hostname]):
self.inventory['_meta']['hostvars'][hostname]['ansible_ssh_host'] = self.hosts[hostname]['ansible_ssh_host']
data_to_print += self.json_format_dict(self.inventory, self.args.pretty)
print(data_to_print)<|docstring|>Main execution path<|endoftext|> |
a3be07e799d90c6cbb7eedffb12ca5d1b399bd68426aa7319da09cc77d6254e2 | def is_cache_valid(self):
'\n Determines if the cache files have expired, or if it is still valid\n '
if self.args.debug:
print(('Determining if cache [%s] is still valid (< %s seconds old)' % (self.cache_path_hosts, self.cache_max_age)))
if os.path.isfile(self.cache_path_hosts):
mod_time = os.path.getmtime(self.cache_path_hosts)
current_time = time()
if ((mod_time + self.cache_max_age) > current_time):
if os.path.isfile(self.cache_path_inventory):
if self.args.debug:
print('Cache is still valid!')
return True
if self.args.debug:
print('Cache is stale or does not exist.')
return False | Determines if the cache files have expired, or if it is still valid | awx/plugins/inventory/cloudforms.py | is_cache_valid | jmferrer/awx | 37 | python | def is_cache_valid(self):
'\n \n '
if self.args.debug:
print(('Determining if cache [%s] is still valid (< %s seconds old)' % (self.cache_path_hosts, self.cache_max_age)))
if os.path.isfile(self.cache_path_hosts):
mod_time = os.path.getmtime(self.cache_path_hosts)
current_time = time()
if ((mod_time + self.cache_max_age) > current_time):
if os.path.isfile(self.cache_path_inventory):
if self.args.debug:
print('Cache is still valid!')
return True
if self.args.debug:
print('Cache is stale or does not exist.')
return False | def is_cache_valid(self):
'\n \n '
if self.args.debug:
print(('Determining if cache [%s] is still valid (< %s seconds old)' % (self.cache_path_hosts, self.cache_max_age)))
if os.path.isfile(self.cache_path_hosts):
mod_time = os.path.getmtime(self.cache_path_hosts)
current_time = time()
if ((mod_time + self.cache_max_age) > current_time):
if os.path.isfile(self.cache_path_inventory):
if self.args.debug:
print('Cache is still valid!')
return True
if self.args.debug:
print('Cache is stale or does not exist.')
return False<|docstring|>Determines if the cache files have expired, or if it is still valid<|endoftext|> |
1b3af32709674921911ce128378fbe69cac6ed1efbad7d53633a538dae58fd7d | def read_settings(self):
'\n Reads the settings from the cloudforms.ini file\n '
config = ConfigParser.SafeConfigParser()
config_paths = [(os.path.dirname(os.path.realpath(__file__)) + '/cloudforms.ini'), '/etc/ansible/cloudforms.ini']
env_value = os.environ.get('CLOUDFORMS_INI_PATH')
if (env_value is not None):
config_paths.append(os.path.expanduser(os.path.expandvars(env_value)))
if self.args.debug:
for config_path in config_paths:
print(('Reading from configuration file [%s]' % config_path))
config.read(config_paths)
if config.has_option('cloudforms', 'url'):
self.cloudforms_url = config.get('cloudforms', 'url')
else:
self.cloudforms_url = None
if (not self.cloudforms_url):
warnings.warn("No url specified, expected something like 'https://cfme.example.com'")
if config.has_option('cloudforms', 'username'):
self.cloudforms_username = config.get('cloudforms', 'username')
else:
self.cloudforms_username = None
if (not self.cloudforms_username):
warnings.warn('No username specified, you need to specify a CloudForms username.')
if config.has_option('cloudforms', 'password'):
self.cloudforms_pw = config.get('cloudforms', 'password', raw=True)
else:
self.cloudforms_pw = None
if (not self.cloudforms_pw):
warnings.warn('No password specified, you need to specify a password for the CloudForms user.')
if config.has_option('cloudforms', 'ssl_verify'):
self.cloudforms_ssl_verify = config.getboolean('cloudforms', 'ssl_verify')
else:
self.cloudforms_ssl_verify = True
if config.has_option('cloudforms', 'version'):
self.cloudforms_version = config.get('cloudforms', 'version')
else:
self.cloudforms_version = None
if config.has_option('cloudforms', 'limit'):
self.cloudforms_limit = config.getint('cloudforms', 'limit')
else:
self.cloudforms_limit = 100
if config.has_option('cloudforms', 'purge_actions'):
self.cloudforms_purge_actions = config.getboolean('cloudforms', 'purge_actions')
else:
self.cloudforms_purge_actions = True
if config.has_option('cloudforms', 'clean_group_keys'):
self.cloudforms_clean_group_keys = config.getboolean('cloudforms', 'clean_group_keys')
else:
self.cloudforms_clean_group_keys = True
if config.has_option('cloudforms', 'nest_tags'):
self.cloudforms_nest_tags = config.getboolean('cloudforms', 'nest_tags')
else:
self.cloudforms_nest_tags = False
if config.has_option('cloudforms', 'suffix'):
self.cloudforms_suffix = config.get('cloudforms', 'suffix')
if (self.cloudforms_suffix[0] != '.'):
raise AnsibleError('Leading fullstop is required for Cloudforms suffix')
else:
self.cloudforms_suffix = None
if config.has_option('cloudforms', 'prefer_ipv4'):
self.cloudforms_prefer_ipv4 = config.getboolean('cloudforms', 'prefer_ipv4')
else:
self.cloudforms_prefer_ipv4 = False
try:
group_patterns = config.get('ansible', 'group_patterns')
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
group_patterns = '[]'
self.group_patterns = eval(group_patterns)
try:
cache_path = os.path.expanduser(config.get('cache', 'path'))
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
cache_path = '.'
(script, ext) = os.path.splitext(os.path.basename(__file__))
self.cache_path_hosts = (cache_path + ('/%s.hosts' % script))
self.cache_path_inventory = (cache_path + ('/%s.inventory' % script))
self.cache_max_age = config.getint('cache', 'max_age')
if self.args.debug:
print('CloudForms settings:')
print(('cloudforms_url = %s' % self.cloudforms_url))
print(('cloudforms_username = %s' % self.cloudforms_username))
print(('cloudforms_pw = %s' % self.cloudforms_pw))
print(('cloudforms_ssl_verify = %s' % self.cloudforms_ssl_verify))
print(('cloudforms_version = %s' % self.cloudforms_version))
print(('cloudforms_limit = %s' % self.cloudforms_limit))
print(('cloudforms_purge_actions = %s' % self.cloudforms_purge_actions))
print('Cache settings:')
print(('cache_max_age = %s' % self.cache_max_age))
print(('cache_path_hosts = %s' % self.cache_path_hosts))
print(('cache_path_inventory = %s' % self.cache_path_inventory)) | Reads the settings from the cloudforms.ini file | awx/plugins/inventory/cloudforms.py | read_settings | jmferrer/awx | 37 | python | def read_settings(self):
'\n \n '
config = ConfigParser.SafeConfigParser()
config_paths = [(os.path.dirname(os.path.realpath(__file__)) + '/cloudforms.ini'), '/etc/ansible/cloudforms.ini']
env_value = os.environ.get('CLOUDFORMS_INI_PATH')
if (env_value is not None):
config_paths.append(os.path.expanduser(os.path.expandvars(env_value)))
if self.args.debug:
for config_path in config_paths:
print(('Reading from configuration file [%s]' % config_path))
config.read(config_paths)
if config.has_option('cloudforms', 'url'):
self.cloudforms_url = config.get('cloudforms', 'url')
else:
self.cloudforms_url = None
if (not self.cloudforms_url):
warnings.warn("No url specified, expected something like 'https://cfme.example.com'")
if config.has_option('cloudforms', 'username'):
self.cloudforms_username = config.get('cloudforms', 'username')
else:
self.cloudforms_username = None
if (not self.cloudforms_username):
warnings.warn('No username specified, you need to specify a CloudForms username.')
if config.has_option('cloudforms', 'password'):
self.cloudforms_pw = config.get('cloudforms', 'password', raw=True)
else:
self.cloudforms_pw = None
if (not self.cloudforms_pw):
warnings.warn('No password specified, you need to specify a password for the CloudForms user.')
if config.has_option('cloudforms', 'ssl_verify'):
self.cloudforms_ssl_verify = config.getboolean('cloudforms', 'ssl_verify')
else:
self.cloudforms_ssl_verify = True
if config.has_option('cloudforms', 'version'):
self.cloudforms_version = config.get('cloudforms', 'version')
else:
self.cloudforms_version = None
if config.has_option('cloudforms', 'limit'):
self.cloudforms_limit = config.getint('cloudforms', 'limit')
else:
self.cloudforms_limit = 100
if config.has_option('cloudforms', 'purge_actions'):
self.cloudforms_purge_actions = config.getboolean('cloudforms', 'purge_actions')
else:
self.cloudforms_purge_actions = True
if config.has_option('cloudforms', 'clean_group_keys'):
self.cloudforms_clean_group_keys = config.getboolean('cloudforms', 'clean_group_keys')
else:
self.cloudforms_clean_group_keys = True
if config.has_option('cloudforms', 'nest_tags'):
self.cloudforms_nest_tags = config.getboolean('cloudforms', 'nest_tags')
else:
self.cloudforms_nest_tags = False
if config.has_option('cloudforms', 'suffix'):
self.cloudforms_suffix = config.get('cloudforms', 'suffix')
if (self.cloudforms_suffix[0] != '.'):
raise AnsibleError('Leading fullstop is required for Cloudforms suffix')
else:
self.cloudforms_suffix = None
if config.has_option('cloudforms', 'prefer_ipv4'):
self.cloudforms_prefer_ipv4 = config.getboolean('cloudforms', 'prefer_ipv4')
else:
self.cloudforms_prefer_ipv4 = False
try:
group_patterns = config.get('ansible', 'group_patterns')
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
group_patterns = '[]'
self.group_patterns = eval(group_patterns)
try:
cache_path = os.path.expanduser(config.get('cache', 'path'))
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
cache_path = '.'
(script, ext) = os.path.splitext(os.path.basename(__file__))
self.cache_path_hosts = (cache_path + ('/%s.hosts' % script))
self.cache_path_inventory = (cache_path + ('/%s.inventory' % script))
self.cache_max_age = config.getint('cache', 'max_age')
if self.args.debug:
print('CloudForms settings:')
print(('cloudforms_url = %s' % self.cloudforms_url))
print(('cloudforms_username = %s' % self.cloudforms_username))
print(('cloudforms_pw = %s' % self.cloudforms_pw))
print(('cloudforms_ssl_verify = %s' % self.cloudforms_ssl_verify))
print(('cloudforms_version = %s' % self.cloudforms_version))
print(('cloudforms_limit = %s' % self.cloudforms_limit))
print(('cloudforms_purge_actions = %s' % self.cloudforms_purge_actions))
print('Cache settings:')
print(('cache_max_age = %s' % self.cache_max_age))
print(('cache_path_hosts = %s' % self.cache_path_hosts))
print(('cache_path_inventory = %s' % self.cache_path_inventory)) | def read_settings(self):
'\n \n '
config = ConfigParser.SafeConfigParser()
config_paths = [(os.path.dirname(os.path.realpath(__file__)) + '/cloudforms.ini'), '/etc/ansible/cloudforms.ini']
env_value = os.environ.get('CLOUDFORMS_INI_PATH')
if (env_value is not None):
config_paths.append(os.path.expanduser(os.path.expandvars(env_value)))
if self.args.debug:
for config_path in config_paths:
print(('Reading from configuration file [%s]' % config_path))
config.read(config_paths)
if config.has_option('cloudforms', 'url'):
self.cloudforms_url = config.get('cloudforms', 'url')
else:
self.cloudforms_url = None
if (not self.cloudforms_url):
warnings.warn("No url specified, expected something like 'https://cfme.example.com'")
if config.has_option('cloudforms', 'username'):
self.cloudforms_username = config.get('cloudforms', 'username')
else:
self.cloudforms_username = None
if (not self.cloudforms_username):
warnings.warn('No username specified, you need to specify a CloudForms username.')
if config.has_option('cloudforms', 'password'):
self.cloudforms_pw = config.get('cloudforms', 'password', raw=True)
else:
self.cloudforms_pw = None
if (not self.cloudforms_pw):
warnings.warn('No password specified, you need to specify a password for the CloudForms user.')
if config.has_option('cloudforms', 'ssl_verify'):
self.cloudforms_ssl_verify = config.getboolean('cloudforms', 'ssl_verify')
else:
self.cloudforms_ssl_verify = True
if config.has_option('cloudforms', 'version'):
self.cloudforms_version = config.get('cloudforms', 'version')
else:
self.cloudforms_version = None
if config.has_option('cloudforms', 'limit'):
self.cloudforms_limit = config.getint('cloudforms', 'limit')
else:
self.cloudforms_limit = 100
if config.has_option('cloudforms', 'purge_actions'):
self.cloudforms_purge_actions = config.getboolean('cloudforms', 'purge_actions')
else:
self.cloudforms_purge_actions = True
if config.has_option('cloudforms', 'clean_group_keys'):
self.cloudforms_clean_group_keys = config.getboolean('cloudforms', 'clean_group_keys')
else:
self.cloudforms_clean_group_keys = True
if config.has_option('cloudforms', 'nest_tags'):
self.cloudforms_nest_tags = config.getboolean('cloudforms', 'nest_tags')
else:
self.cloudforms_nest_tags = False
if config.has_option('cloudforms', 'suffix'):
self.cloudforms_suffix = config.get('cloudforms', 'suffix')
if (self.cloudforms_suffix[0] != '.'):
raise AnsibleError('Leading fullstop is required for Cloudforms suffix')
else:
self.cloudforms_suffix = None
if config.has_option('cloudforms', 'prefer_ipv4'):
self.cloudforms_prefer_ipv4 = config.getboolean('cloudforms', 'prefer_ipv4')
else:
self.cloudforms_prefer_ipv4 = False
try:
group_patterns = config.get('ansible', 'group_patterns')
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
group_patterns = '[]'
self.group_patterns = eval(group_patterns)
try:
cache_path = os.path.expanduser(config.get('cache', 'path'))
except (ConfigParser.NoOptionError, ConfigParser.NoSectionError):
cache_path = '.'
(script, ext) = os.path.splitext(os.path.basename(__file__))
self.cache_path_hosts = (cache_path + ('/%s.hosts' % script))
self.cache_path_inventory = (cache_path + ('/%s.inventory' % script))
self.cache_max_age = config.getint('cache', 'max_age')
if self.args.debug:
print('CloudForms settings:')
print(('cloudforms_url = %s' % self.cloudforms_url))
print(('cloudforms_username = %s' % self.cloudforms_username))
print(('cloudforms_pw = %s' % self.cloudforms_pw))
print(('cloudforms_ssl_verify = %s' % self.cloudforms_ssl_verify))
print(('cloudforms_version = %s' % self.cloudforms_version))
print(('cloudforms_limit = %s' % self.cloudforms_limit))
print(('cloudforms_purge_actions = %s' % self.cloudforms_purge_actions))
print('Cache settings:')
print(('cache_max_age = %s' % self.cache_max_age))
print(('cache_path_hosts = %s' % self.cache_path_hosts))
print(('cache_path_inventory = %s' % self.cache_path_inventory))<|docstring|>Reads the settings from the cloudforms.ini file<|endoftext|> |
6f9dbc295c10f20eea70ae5b25c5efc61c1c1b5fb20948f09b483992e42853ec | def parse_cli_args(self):
'\n Command line argument processing\n '
parser = argparse.ArgumentParser(description='Produce an Ansible Inventory file based on CloudForms managed VMs')
parser.add_argument('--list', action='store_true', default=True, help='List instances (default: True)')
parser.add_argument('--host', action='store', help='Get all the variables about a specific instance')
parser.add_argument('--pretty', action='store_true', default=False, help='Pretty print JSON output (default: False)')
parser.add_argument('--refresh-cache', action='store_true', default=False, help='Force refresh of cache by making API requests to CloudForms (default: False - use cache files)')
parser.add_argument('--debug', action='store_true', default=False, help='Show debug output while running (default: False)')
self.args = parser.parse_args() | Command line argument processing | awx/plugins/inventory/cloudforms.py | parse_cli_args | jmferrer/awx | 37 | python | def parse_cli_args(self):
'\n \n '
parser = argparse.ArgumentParser(description='Produce an Ansible Inventory file based on CloudForms managed VMs')
parser.add_argument('--list', action='store_true', default=True, help='List instances (default: True)')
parser.add_argument('--host', action='store', help='Get all the variables about a specific instance')
parser.add_argument('--pretty', action='store_true', default=False, help='Pretty print JSON output (default: False)')
parser.add_argument('--refresh-cache', action='store_true', default=False, help='Force refresh of cache by making API requests to CloudForms (default: False - use cache files)')
parser.add_argument('--debug', action='store_true', default=False, help='Show debug output while running (default: False)')
self.args = parser.parse_args() | def parse_cli_args(self):
'\n \n '
parser = argparse.ArgumentParser(description='Produce an Ansible Inventory file based on CloudForms managed VMs')
parser.add_argument('--list', action='store_true', default=True, help='List instances (default: True)')
parser.add_argument('--host', action='store', help='Get all the variables about a specific instance')
parser.add_argument('--pretty', action='store_true', default=False, help='Pretty print JSON output (default: False)')
parser.add_argument('--refresh-cache', action='store_true', default=False, help='Force refresh of cache by making API requests to CloudForms (default: False - use cache files)')
parser.add_argument('--debug', action='store_true', default=False, help='Show debug output while running (default: False)')
self.args = parser.parse_args()<|docstring|>Command line argument processing<|endoftext|> |
488437670c9e79d4ca336f59ca055bb9aed9b7543e6435bba86f61ebb5ab1fa1 | def _get_json(self, url):
'\n Make a request and return the JSON\n '
results = []
ret = requests.get(url, auth=HTTPBasicAuth(self.cloudforms_username, self.cloudforms_pw), verify=self.cloudforms_ssl_verify)
ret.raise_for_status()
try:
results = json.loads(ret.text)
except ValueError:
warnings.warn('Unexpected response from {0} ({1}): {2}'.format(self.cloudforms_url, ret.status_code, ret.reason))
results = {}
if self.args.debug:
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
print(ret.text)
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
return results | Make a request and return the JSON | awx/plugins/inventory/cloudforms.py | _get_json | jmferrer/awx | 37 | python | def _get_json(self, url):
'\n \n '
results = []
ret = requests.get(url, auth=HTTPBasicAuth(self.cloudforms_username, self.cloudforms_pw), verify=self.cloudforms_ssl_verify)
ret.raise_for_status()
try:
results = json.loads(ret.text)
except ValueError:
warnings.warn('Unexpected response from {0} ({1}): {2}'.format(self.cloudforms_url, ret.status_code, ret.reason))
results = {}
if self.args.debug:
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
print(ret.text)
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
return results | def _get_json(self, url):
'\n \n '
results = []
ret = requests.get(url, auth=HTTPBasicAuth(self.cloudforms_username, self.cloudforms_pw), verify=self.cloudforms_ssl_verify)
ret.raise_for_status()
try:
results = json.loads(ret.text)
except ValueError:
warnings.warn('Unexpected response from {0} ({1}): {2}'.format(self.cloudforms_url, ret.status_code, ret.reason))
results = {}
if self.args.debug:
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
print(ret.text)
print('=======================================================================')
print('=======================================================================')
print('=======================================================================')
return results<|docstring|>Make a request and return the JSON<|endoftext|> |
290f7292e9bc6e4197b6b14a4c189b47a9263da9cdb7340f25db1cbc03a13113 | def _get_hosts(self):
'\n Get all hosts by paging through the results\n '
limit = self.cloudforms_limit
page = 0
last_page = False
results = []
while (not last_page):
offset = (page * limit)
ret = self._get_json(('%s/api/vms?offset=%s&limit=%s&expand=resources,tags,hosts,&attributes=ipaddresses' % (self.cloudforms_url, offset, limit)))
results += ret['resources']
if (ret['subcount'] < limit):
last_page = True
page += 1
return results | Get all hosts by paging through the results | awx/plugins/inventory/cloudforms.py | _get_hosts | jmferrer/awx | 37 | python | def _get_hosts(self):
'\n \n '
limit = self.cloudforms_limit
page = 0
last_page = False
results = []
while (not last_page):
offset = (page * limit)
ret = self._get_json(('%s/api/vms?offset=%s&limit=%s&expand=resources,tags,hosts,&attributes=ipaddresses' % (self.cloudforms_url, offset, limit)))
results += ret['resources']
if (ret['subcount'] < limit):
last_page = True
page += 1
return results | def _get_hosts(self):
'\n \n '
limit = self.cloudforms_limit
page = 0
last_page = False
results = []
while (not last_page):
offset = (page * limit)
ret = self._get_json(('%s/api/vms?offset=%s&limit=%s&expand=resources,tags,hosts,&attributes=ipaddresses' % (self.cloudforms_url, offset, limit)))
results += ret['resources']
if (ret['subcount'] < limit):
last_page = True
page += 1
return results<|docstring|>Get all hosts by paging through the results<|endoftext|> |
fc173281a3141600572b1b2f7ebb19b610486d59872e63e1a6346834849ad4a2 | def update_cache(self):
'\n Make calls to cloudforms and save the output in a cache\n '
self.groups = dict()
self.hosts = dict()
if self.args.debug:
print('Updating cache...')
for host in self._get_hosts():
if ((self.cloudforms_suffix is not None) and (not host['name'].endswith(self.cloudforms_suffix))):
host['name'] = (host['name'] + self.cloudforms_suffix)
if (host['power_state'] != 'on'):
if self.args.debug:
print(('Skipping %s because power_state = %s' % (host['name'], host['power_state'])))
continue
if (self.cloudforms_purge_actions and ('actions' in host)):
del host['actions']
if ('tags' in host):
if ('tags' not in self.inventory):
self.inventory['tags'] = dict(children=[], vars={}, hosts=[])
if (not self.cloudforms_nest_tags):
for group in host['tags']:
safe_key = self.to_safe(group['name'])
if safe_key:
if self.args.debug:
print(("Adding sub-group '%s' to parent 'tags'" % safe_key))
if (safe_key not in self.inventory['tags']['children']):
self.push(self.inventory['tags'], 'children', safe_key)
self.push(self.inventory, safe_key, host['name'])
if self.args.debug:
print(('Found tag [%s] for host which will be mapped to [%s]' % (group['name'], safe_key)))
else:
safe_parent_tag_name = 'tags'
for tag in host['tags']:
tag_hierarchy = tag['name'][1:].split('/')
if self.args.debug:
print(('Working on list %s' % tag_hierarchy))
for tag_name in tag_hierarchy:
if self.args.debug:
print(('Working on tag_name = %s' % tag_name))
safe_tag_name = self.to_safe(tag_name)
if self.args.debug:
print(('Using sanitized name %s' % safe_tag_name))
if (safe_tag_name not in self.inventory):
self.inventory[safe_tag_name] = dict(children=[], vars={}, hosts=[])
if safe_parent_tag_name:
if self.args.debug:
print(("Adding sub-group '%s' to parent '%s'" % (safe_tag_name, safe_parent_tag_name)))
if (safe_tag_name not in self.inventory[safe_parent_tag_name]['children']):
self.push(self.inventory[safe_parent_tag_name], 'children', safe_tag_name)
safe_parent_tag_name = safe_tag_name
self.push(self.inventory[safe_parent_tag_name], 'hosts', host['name'])
if (('ipaddresses' in host) and host['ipaddresses'] and isinstance(host['ipaddresses'], list)):
if (not self.cloudforms_prefer_ipv4):
host['ansible_ssh_host'] = host['ipaddresses'][0]
else:
host['ansible_ssh_host'] = host['ipaddresses'][0]
for currenthost in host['ipaddresses']:
if ('.' in currenthost):
host['ansible_ssh_host'] = currenthost
for key in ('location', 'type', 'vendor'):
safe_key = self.to_safe(host[key])
if (key not in self.inventory):
self.inventory[key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory):
self.inventory[safe_key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory[key]['children']):
self.push(self.inventory[key], 'children', safe_key)
if (key in host):
self.push(self.inventory[safe_key], 'hosts', host['name'])
self.hosts[host['name']] = host
self.push(self.inventory, 'all', host['name'])
if self.args.debug:
print('Saving cached data')
self.write_to_cache(self.hosts, self.cache_path_hosts)
self.write_to_cache(self.inventory, self.cache_path_inventory) | Make calls to cloudforms and save the output in a cache | awx/plugins/inventory/cloudforms.py | update_cache | jmferrer/awx | 37 | python | def update_cache(self):
'\n \n '
self.groups = dict()
self.hosts = dict()
if self.args.debug:
print('Updating cache...')
for host in self._get_hosts():
if ((self.cloudforms_suffix is not None) and (not host['name'].endswith(self.cloudforms_suffix))):
host['name'] = (host['name'] + self.cloudforms_suffix)
if (host['power_state'] != 'on'):
if self.args.debug:
print(('Skipping %s because power_state = %s' % (host['name'], host['power_state'])))
continue
if (self.cloudforms_purge_actions and ('actions' in host)):
del host['actions']
if ('tags' in host):
if ('tags' not in self.inventory):
self.inventory['tags'] = dict(children=[], vars={}, hosts=[])
if (not self.cloudforms_nest_tags):
for group in host['tags']:
safe_key = self.to_safe(group['name'])
if safe_key:
if self.args.debug:
print(("Adding sub-group '%s' to parent 'tags'" % safe_key))
if (safe_key not in self.inventory['tags']['children']):
self.push(self.inventory['tags'], 'children', safe_key)
self.push(self.inventory, safe_key, host['name'])
if self.args.debug:
print(('Found tag [%s] for host which will be mapped to [%s]' % (group['name'], safe_key)))
else:
safe_parent_tag_name = 'tags'
for tag in host['tags']:
tag_hierarchy = tag['name'][1:].split('/')
if self.args.debug:
print(('Working on list %s' % tag_hierarchy))
for tag_name in tag_hierarchy:
if self.args.debug:
print(('Working on tag_name = %s' % tag_name))
safe_tag_name = self.to_safe(tag_name)
if self.args.debug:
print(('Using sanitized name %s' % safe_tag_name))
if (safe_tag_name not in self.inventory):
self.inventory[safe_tag_name] = dict(children=[], vars={}, hosts=[])
if safe_parent_tag_name:
if self.args.debug:
print(("Adding sub-group '%s' to parent '%s'" % (safe_tag_name, safe_parent_tag_name)))
if (safe_tag_name not in self.inventory[safe_parent_tag_name]['children']):
self.push(self.inventory[safe_parent_tag_name], 'children', safe_tag_name)
safe_parent_tag_name = safe_tag_name
self.push(self.inventory[safe_parent_tag_name], 'hosts', host['name'])
if (('ipaddresses' in host) and host['ipaddresses'] and isinstance(host['ipaddresses'], list)):
if (not self.cloudforms_prefer_ipv4):
host['ansible_ssh_host'] = host['ipaddresses'][0]
else:
host['ansible_ssh_host'] = host['ipaddresses'][0]
for currenthost in host['ipaddresses']:
if ('.' in currenthost):
host['ansible_ssh_host'] = currenthost
for key in ('location', 'type', 'vendor'):
safe_key = self.to_safe(host[key])
if (key not in self.inventory):
self.inventory[key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory):
self.inventory[safe_key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory[key]['children']):
self.push(self.inventory[key], 'children', safe_key)
if (key in host):
self.push(self.inventory[safe_key], 'hosts', host['name'])
self.hosts[host['name']] = host
self.push(self.inventory, 'all', host['name'])
if self.args.debug:
print('Saving cached data')
self.write_to_cache(self.hosts, self.cache_path_hosts)
self.write_to_cache(self.inventory, self.cache_path_inventory) | def update_cache(self):
'\n \n '
self.groups = dict()
self.hosts = dict()
if self.args.debug:
print('Updating cache...')
for host in self._get_hosts():
if ((self.cloudforms_suffix is not None) and (not host['name'].endswith(self.cloudforms_suffix))):
host['name'] = (host['name'] + self.cloudforms_suffix)
if (host['power_state'] != 'on'):
if self.args.debug:
print(('Skipping %s because power_state = %s' % (host['name'], host['power_state'])))
continue
if (self.cloudforms_purge_actions and ('actions' in host)):
del host['actions']
if ('tags' in host):
if ('tags' not in self.inventory):
self.inventory['tags'] = dict(children=[], vars={}, hosts=[])
if (not self.cloudforms_nest_tags):
for group in host['tags']:
safe_key = self.to_safe(group['name'])
if safe_key:
if self.args.debug:
print(("Adding sub-group '%s' to parent 'tags'" % safe_key))
if (safe_key not in self.inventory['tags']['children']):
self.push(self.inventory['tags'], 'children', safe_key)
self.push(self.inventory, safe_key, host['name'])
if self.args.debug:
print(('Found tag [%s] for host which will be mapped to [%s]' % (group['name'], safe_key)))
else:
safe_parent_tag_name = 'tags'
for tag in host['tags']:
tag_hierarchy = tag['name'][1:].split('/')
if self.args.debug:
print(('Working on list %s' % tag_hierarchy))
for tag_name in tag_hierarchy:
if self.args.debug:
print(('Working on tag_name = %s' % tag_name))
safe_tag_name = self.to_safe(tag_name)
if self.args.debug:
print(('Using sanitized name %s' % safe_tag_name))
if (safe_tag_name not in self.inventory):
self.inventory[safe_tag_name] = dict(children=[], vars={}, hosts=[])
if safe_parent_tag_name:
if self.args.debug:
print(("Adding sub-group '%s' to parent '%s'" % (safe_tag_name, safe_parent_tag_name)))
if (safe_tag_name not in self.inventory[safe_parent_tag_name]['children']):
self.push(self.inventory[safe_parent_tag_name], 'children', safe_tag_name)
safe_parent_tag_name = safe_tag_name
self.push(self.inventory[safe_parent_tag_name], 'hosts', host['name'])
if (('ipaddresses' in host) and host['ipaddresses'] and isinstance(host['ipaddresses'], list)):
if (not self.cloudforms_prefer_ipv4):
host['ansible_ssh_host'] = host['ipaddresses'][0]
else:
host['ansible_ssh_host'] = host['ipaddresses'][0]
for currenthost in host['ipaddresses']:
if ('.' in currenthost):
host['ansible_ssh_host'] = currenthost
for key in ('location', 'type', 'vendor'):
safe_key = self.to_safe(host[key])
if (key not in self.inventory):
self.inventory[key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory):
self.inventory[safe_key] = dict(children=[], vars={}, hosts=[])
if (safe_key not in self.inventory[key]['children']):
self.push(self.inventory[key], 'children', safe_key)
if (key in host):
self.push(self.inventory[safe_key], 'hosts', host['name'])
self.hosts[host['name']] = host
self.push(self.inventory, 'all', host['name'])
if self.args.debug:
print('Saving cached data')
self.write_to_cache(self.hosts, self.cache_path_hosts)
self.write_to_cache(self.inventory, self.cache_path_inventory)<|docstring|>Make calls to cloudforms and save the output in a cache<|endoftext|> |
5d9582b09b0cb9ce3955bd070fbe4d9c77fe2670ac7f5e5623037434782eae36 | def get_host_info(self, host):
'\n Get variables about a specific host\n '
if ((not self.hosts) or (len(self.hosts) == 0)):
self.load_hosts_from_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] not found in cache.' % host))
self.update_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] does not exist after cache update.' % host))
return self.json_format_dict({}, self.args.pretty)
return self.json_format_dict(self.hosts[host], self.args.pretty) | Get variables about a specific host | awx/plugins/inventory/cloudforms.py | get_host_info | jmferrer/awx | 37 | python | def get_host_info(self, host):
'\n \n '
if ((not self.hosts) or (len(self.hosts) == 0)):
self.load_hosts_from_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] not found in cache.' % host))
self.update_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] does not exist after cache update.' % host))
return self.json_format_dict({}, self.args.pretty)
return self.json_format_dict(self.hosts[host], self.args.pretty) | def get_host_info(self, host):
'\n \n '
if ((not self.hosts) or (len(self.hosts) == 0)):
self.load_hosts_from_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] not found in cache.' % host))
self.update_cache()
if (host not in self.hosts):
if self.args.debug:
print(('[%s] does not exist after cache update.' % host))
return self.json_format_dict({}, self.args.pretty)
return self.json_format_dict(self.hosts[host], self.args.pretty)<|docstring|>Get variables about a specific host<|endoftext|> |
5963e61974b6e961bb1fc1e67518b9f8aadc79f9658e2484f77a76cf005e8aff | def push(self, d, k, v):
'\n Safely puts a new entry onto an array.\n '
if (k in d):
d[k].append(v)
else:
d[k] = [v] | Safely puts a new entry onto an array. | awx/plugins/inventory/cloudforms.py | push | jmferrer/awx | 37 | python | def push(self, d, k, v):
'\n \n '
if (k in d):
d[k].append(v)
else:
d[k] = [v] | def push(self, d, k, v):
'\n \n '
if (k in d):
d[k].append(v)
else:
d[k] = [v]<|docstring|>Safely puts a new entry onto an array.<|endoftext|> |
c043f774dc6fd880cd6703e4014f6515d1d4c038c2a4ac1aad28d2f9345e02bf | def load_inventory_from_cache(self):
'\n Reads the inventory from the cache file sets self.inventory\n '
cache = open(self.cache_path_inventory, 'r')
json_inventory = cache.read()
self.inventory = json.loads(json_inventory) | Reads the inventory from the cache file sets self.inventory | awx/plugins/inventory/cloudforms.py | load_inventory_from_cache | jmferrer/awx | 37 | python | def load_inventory_from_cache(self):
'\n \n '
cache = open(self.cache_path_inventory, 'r')
json_inventory = cache.read()
self.inventory = json.loads(json_inventory) | def load_inventory_from_cache(self):
'\n \n '
cache = open(self.cache_path_inventory, 'r')
json_inventory = cache.read()
self.inventory = json.loads(json_inventory)<|docstring|>Reads the inventory from the cache file sets self.inventory<|endoftext|> |
491cf45641d319ea3b7eaeda18bf3ddc16712f490b70965e6e89562d4a325865 | def load_hosts_from_cache(self):
'\n Reads the cache from the cache file sets self.hosts\n '
cache = open(self.cache_path_hosts, 'r')
json_cache = cache.read()
self.hosts = json.loads(json_cache) | Reads the cache from the cache file sets self.hosts | awx/plugins/inventory/cloudforms.py | load_hosts_from_cache | jmferrer/awx | 37 | python | def load_hosts_from_cache(self):
'\n \n '
cache = open(self.cache_path_hosts, 'r')
json_cache = cache.read()
self.hosts = json.loads(json_cache) | def load_hosts_from_cache(self):
'\n \n '
cache = open(self.cache_path_hosts, 'r')
json_cache = cache.read()
self.hosts = json.loads(json_cache)<|docstring|>Reads the cache from the cache file sets self.hosts<|endoftext|> |
09362cae59fa466fc4e061ac0e1b5dde1a7d3b7deb81ee03b5fc5e21b0b1c3ce | def write_to_cache(self, data, filename):
'\n Writes data in JSON format to a file\n '
json_data = self.json_format_dict(data, True)
cache = open(filename, 'w')
cache.write(json_data)
cache.close() | Writes data in JSON format to a file | awx/plugins/inventory/cloudforms.py | write_to_cache | jmferrer/awx | 37 | python | def write_to_cache(self, data, filename):
'\n \n '
json_data = self.json_format_dict(data, True)
cache = open(filename, 'w')
cache.write(json_data)
cache.close() | def write_to_cache(self, data, filename):
'\n \n '
json_data = self.json_format_dict(data, True)
cache = open(filename, 'w')
cache.write(json_data)
cache.close()<|docstring|>Writes data in JSON format to a file<|endoftext|> |
1599cebb70584db2e88015cb21c222efa53adeca57348707c7e5b9cc0c76efd1 | def to_safe(self, word):
"\n Converts 'bad' characters in a string to underscores so they can be used as Ansible groups\n "
if self.cloudforms_clean_group_keys:
regex = '[^A-Za-z0-9\\_]'
return re.sub(regex, '_', word.replace(' ', ''))
else:
return word | Converts 'bad' characters in a string to underscores so they can be used as Ansible groups | awx/plugins/inventory/cloudforms.py | to_safe | jmferrer/awx | 37 | python | def to_safe(self, word):
"\n \n "
if self.cloudforms_clean_group_keys:
regex = '[^A-Za-z0-9\\_]'
return re.sub(regex, '_', word.replace(' ', ))
else:
return word | def to_safe(self, word):
"\n \n "
if self.cloudforms_clean_group_keys:
regex = '[^A-Za-z0-9\\_]'
return re.sub(regex, '_', word.replace(' ', ))
else:
return word<|docstring|>Converts 'bad' characters in a string to underscores so they can be used as Ansible groups<|endoftext|> |
bb849067831f9ed90e32e322a516e7c8a6a9805f896bc638400ac51a2acbe7f3 | def json_format_dict(self, data, pretty=False):
'\n Converts a dict to a JSON object and dumps it as a formatted string\n '
if pretty:
return json.dumps(data, sort_keys=True, indent=2)
else:
return json.dumps(data) | Converts a dict to a JSON object and dumps it as a formatted string | awx/plugins/inventory/cloudforms.py | json_format_dict | jmferrer/awx | 37 | python | def json_format_dict(self, data, pretty=False):
'\n \n '
if pretty:
return json.dumps(data, sort_keys=True, indent=2)
else:
return json.dumps(data) | def json_format_dict(self, data, pretty=False):
'\n \n '
if pretty:
return json.dumps(data, sort_keys=True, indent=2)
else:
return json.dumps(data)<|docstring|>Converts a dict to a JSON object and dumps it as a formatted string<|endoftext|> |
ce0629d889753c2bcfa20ae0d4f5bb613942b0d4f4e921db826d349864b2fa9a | def gnome_sort(arr: list[int]):
'\n ## Complexities:\n ```py\n Worst Case Time Complexity == O(n * n)\n Average Case Time Complexity == O(n * n)\n Best Case Time Complexity == O(n)\n Space Complexity == O(1) Auxiliary\n ```\n '
for p in range(1, len(arr)):
position: int = p
while ((position > 0) and (arr[(position - 1)] > arr[position])):
(arr[(position - 1)], arr[position]) = (arr[position], arr[(position - 1)])
position -= 1
plot(p, arr, other_highlights=[position]) | ## Complexities:
```py
Worst Case Time Complexity == O(n * n)
Average Case Time Complexity == O(n * n)
Best Case Time Complexity == O(n)
Space Complexity == O(1) Auxiliary
``` | src/algorithms/gnome_sort.py | gnome_sort | c1m50c/visual-sorting-algorithms | 0 | python | def gnome_sort(arr: list[int]):
'\n ## Complexities:\n ```py\n Worst Case Time Complexity == O(n * n)\n Average Case Time Complexity == O(n * n)\n Best Case Time Complexity == O(n)\n Space Complexity == O(1) Auxiliary\n ```\n '
for p in range(1, len(arr)):
position: int = p
while ((position > 0) and (arr[(position - 1)] > arr[position])):
(arr[(position - 1)], arr[position]) = (arr[position], arr[(position - 1)])
position -= 1
plot(p, arr, other_highlights=[position]) | def gnome_sort(arr: list[int]):
'\n ## Complexities:\n ```py\n Worst Case Time Complexity == O(n * n)\n Average Case Time Complexity == O(n * n)\n Best Case Time Complexity == O(n)\n Space Complexity == O(1) Auxiliary\n ```\n '
for p in range(1, len(arr)):
position: int = p
while ((position > 0) and (arr[(position - 1)] > arr[position])):
(arr[(position - 1)], arr[position]) = (arr[position], arr[(position - 1)])
position -= 1
plot(p, arr, other_highlights=[position])<|docstring|>## Complexities:
```py
Worst Case Time Complexity == O(n * n)
Average Case Time Complexity == O(n * n)
Best Case Time Complexity == O(n)
Space Complexity == O(1) Auxiliary
```<|endoftext|> |
2700a7969b1a90d76a0dda76f124627b57654ad5828bece95edcfdd070b9d5c7 | def onLoad(self):
'\n Load the parser.\n '
self.parse = self.core.findPlugin('NMDC Parser')
self.googleLimit = 2 | Load the parser. | src/plugins/dc/Search/main.py | onLoad | nsk89/nodeforge | 0 | python | def onLoad(self):
'\n \n '
self.parse = self.core.findPlugin('NMDC Parser')
self.googleLimit = 2 | def onLoad(self):
'\n \n '
self.parse = self.core.findPlugin('NMDC Parser')
self.googleLimit = 2<|docstring|>Load the parser.<|endoftext|> |
4c4e692f2e8d1b7ee9503f0da22543738d0f47425bdd549f0e2c10fb682c9b56 | def __init__(self, remote: str=None, username: str=None, password: str=None, cache: str=None, signoff: Optional[bool]=None, exists: bool=True, log_level: int=logging.INFO):
"\n Initialize a new instance of :class:`GitIndex`.\n\n :param remote: Remote repository's address where the index is maintained.\n :param username: Username for credentials if protocol is not ssh.\n :param password: Password for credentials if protocol is not ssh.\n :param cache: Path to the folder where the repo will be cached, defaults to `~/.cache`.\n :param signoff: Whether to add a DCO to the commit message.\n :param exists: Whether the Git remote exists or not. If it doesn't, we are initializing (allows to catch some errors).\n :param log_level: The logging level of this instance.\n :raise ValueError: If missing credential, incorrect url, incorrect credentials or index JSON file is not found/unreadable.\n "
self._log = logging.getLogger(type(self).__name__)
self._log.setLevel(log_level)
if (remote is None):
remote = config.INDEX_REPO
if (cache is None):
cache = config.vendor_cache_dir()
if (not signoff):
signoff = config.ALWAYS_SIGNOFF
self.signoff = signoff
parsed_url = urlparse(remote)
errmsg = ('Invalid index URL: "%s"' % remote)
if ((not parsed_url.scheme) or (parsed_url.scheme not in ('git', 'git+ssh', 'ssh', 'http', 'https'))):
self._log.critical('Parsed URL does not contain a valid protocol')
raise ValueError(errmsg)
if (not parsed_url.netloc):
self._log.critical('Parsed URL does not contain a valid domain')
raise ValueError(errmsg)
if (not parsed_url.path):
self._log.critical('Parsed URL does not contain a valid repository path')
raise ValueError(errmsg)
self.repo = parsed_url.path
if self.repo.startswith('/'):
self.repo = self.repo[1:]
if self.repo.endswith('.git'):
self.repo = self.repo[:(- 4)]
self.cached_repo = os.path.join(cache, self.repo)
if (username and password):
auth = (((username + ':') + password) + '@')
self.remote_url = (self.REMOTE_URL % (parsed_url.scheme, auth, parsed_url.netloc, self.repo))
elif ((username is None) != (password is None)):
msg = ('Both username and password must be supplied to access "%s"' % remote)
self._log.critical(msg)
raise ValueError(msg)
else:
self.remote_url = remote
self.contents = {}
try:
self.fetch()
except NotGitRepository as e:
self._log.critical(('Repository does not exist: %s' % e))
raise ValueError from e
except HangupException as e:
self._log.critical(('Check SSH is configured, or connection is stable: %s' % e))
raise ValueError from e
except GitProtocolError as e:
self._log.critical(('%s: %s\nCheck your Git credentials' % (type(e), e)))
raise ValueError from e
except (FileNotFoundError, ValueError) as e:
if exists:
self._log.critical('%s does not exist or is unreadable, please run `init` command', self.INDEX_FILE)
raise ValueError from e
self.models = self.contents.get('models', {})
self.meta = self.contents.get('meta', {}) | Initialize a new instance of :class:`GitIndex`.
:param remote: Remote repository's address where the index is maintained.
:param username: Username for credentials if protocol is not ssh.
:param password: Password for credentials if protocol is not ssh.
:param cache: Path to the folder where the repo will be cached, defaults to `~/.cache`.
:param signoff: Whether to add a DCO to the commit message.
:param exists: Whether the Git remote exists or not. If it doesn't, we are initializing (allows to catch some errors).
:param log_level: The logging level of this instance.
:raise ValueError: If missing credential, incorrect url, incorrect credentials or index JSON file is not found/unreadable. | modelforge/index.py | __init__ | src-d/modelforge | 19 | python | def __init__(self, remote: str=None, username: str=None, password: str=None, cache: str=None, signoff: Optional[bool]=None, exists: bool=True, log_level: int=logging.INFO):
"\n Initialize a new instance of :class:`GitIndex`.\n\n :param remote: Remote repository's address where the index is maintained.\n :param username: Username for credentials if protocol is not ssh.\n :param password: Password for credentials if protocol is not ssh.\n :param cache: Path to the folder where the repo will be cached, defaults to `~/.cache`.\n :param signoff: Whether to add a DCO to the commit message.\n :param exists: Whether the Git remote exists or not. If it doesn't, we are initializing (allows to catch some errors).\n :param log_level: The logging level of this instance.\n :raise ValueError: If missing credential, incorrect url, incorrect credentials or index JSON file is not found/unreadable.\n "
self._log = logging.getLogger(type(self).__name__)
self._log.setLevel(log_level)
if (remote is None):
remote = config.INDEX_REPO
if (cache is None):
cache = config.vendor_cache_dir()
if (not signoff):
signoff = config.ALWAYS_SIGNOFF
self.signoff = signoff
parsed_url = urlparse(remote)
errmsg = ('Invalid index URL: "%s"' % remote)
if ((not parsed_url.scheme) or (parsed_url.scheme not in ('git', 'git+ssh', 'ssh', 'http', 'https'))):
self._log.critical('Parsed URL does not contain a valid protocol')
raise ValueError(errmsg)
if (not parsed_url.netloc):
self._log.critical('Parsed URL does not contain a valid domain')
raise ValueError(errmsg)
if (not parsed_url.path):
self._log.critical('Parsed URL does not contain a valid repository path')
raise ValueError(errmsg)
self.repo = parsed_url.path
if self.repo.startswith('/'):
self.repo = self.repo[1:]
if self.repo.endswith('.git'):
self.repo = self.repo[:(- 4)]
self.cached_repo = os.path.join(cache, self.repo)
if (username and password):
auth = (((username + ':') + password) + '@')
self.remote_url = (self.REMOTE_URL % (parsed_url.scheme, auth, parsed_url.netloc, self.repo))
elif ((username is None) != (password is None)):
msg = ('Both username and password must be supplied to access "%s"' % remote)
self._log.critical(msg)
raise ValueError(msg)
else:
self.remote_url = remote
self.contents = {}
try:
self.fetch()
except NotGitRepository as e:
self._log.critical(('Repository does not exist: %s' % e))
raise ValueError from e
except HangupException as e:
self._log.critical(('Check SSH is configured, or connection is stable: %s' % e))
raise ValueError from e
except GitProtocolError as e:
self._log.critical(('%s: %s\nCheck your Git credentials' % (type(e), e)))
raise ValueError from e
except (FileNotFoundError, ValueError) as e:
if exists:
self._log.critical('%s does not exist or is unreadable, please run `init` command', self.INDEX_FILE)
raise ValueError from e
self.models = self.contents.get('models', {})
self.meta = self.contents.get('meta', {}) | def __init__(self, remote: str=None, username: str=None, password: str=None, cache: str=None, signoff: Optional[bool]=None, exists: bool=True, log_level: int=logging.INFO):
"\n Initialize a new instance of :class:`GitIndex`.\n\n :param remote: Remote repository's address where the index is maintained.\n :param username: Username for credentials if protocol is not ssh.\n :param password: Password for credentials if protocol is not ssh.\n :param cache: Path to the folder where the repo will be cached, defaults to `~/.cache`.\n :param signoff: Whether to add a DCO to the commit message.\n :param exists: Whether the Git remote exists or not. If it doesn't, we are initializing (allows to catch some errors).\n :param log_level: The logging level of this instance.\n :raise ValueError: If missing credential, incorrect url, incorrect credentials or index JSON file is not found/unreadable.\n "
self._log = logging.getLogger(type(self).__name__)
self._log.setLevel(log_level)
if (remote is None):
remote = config.INDEX_REPO
if (cache is None):
cache = config.vendor_cache_dir()
if (not signoff):
signoff = config.ALWAYS_SIGNOFF
self.signoff = signoff
parsed_url = urlparse(remote)
errmsg = ('Invalid index URL: "%s"' % remote)
if ((not parsed_url.scheme) or (parsed_url.scheme not in ('git', 'git+ssh', 'ssh', 'http', 'https'))):
self._log.critical('Parsed URL does not contain a valid protocol')
raise ValueError(errmsg)
if (not parsed_url.netloc):
self._log.critical('Parsed URL does not contain a valid domain')
raise ValueError(errmsg)
if (not parsed_url.path):
self._log.critical('Parsed URL does not contain a valid repository path')
raise ValueError(errmsg)
self.repo = parsed_url.path
if self.repo.startswith('/'):
self.repo = self.repo[1:]
if self.repo.endswith('.git'):
self.repo = self.repo[:(- 4)]
self.cached_repo = os.path.join(cache, self.repo)
if (username and password):
auth = (((username + ':') + password) + '@')
self.remote_url = (self.REMOTE_URL % (parsed_url.scheme, auth, parsed_url.netloc, self.repo))
elif ((username is None) != (password is None)):
msg = ('Both username and password must be supplied to access "%s"' % remote)
self._log.critical(msg)
raise ValueError(msg)
else:
self.remote_url = remote
self.contents = {}
try:
self.fetch()
except NotGitRepository as e:
self._log.critical(('Repository does not exist: %s' % e))
raise ValueError from e
except HangupException as e:
self._log.critical(('Check SSH is configured, or connection is stable: %s' % e))
raise ValueError from e
except GitProtocolError as e:
self._log.critical(('%s: %s\nCheck your Git credentials' % (type(e), e)))
raise ValueError from e
except (FileNotFoundError, ValueError) as e:
if exists:
self._log.critical('%s does not exist or is unreadable, please run `init` command', self.INDEX_FILE)
raise ValueError from e
self.models = self.contents.get('models', {})
self.meta = self.contents.get('meta', {})<|docstring|>Initialize a new instance of :class:`GitIndex`.
:param remote: Remote repository's address where the index is maintained.
:param username: Username for credentials if protocol is not ssh.
:param password: Password for credentials if protocol is not ssh.
:param cache: Path to the folder where the repo will be cached, defaults to `~/.cache`.
:param signoff: Whether to add a DCO to the commit message.
:param exists: Whether the Git remote exists or not. If it doesn't, we are initializing (allows to catch some errors).
:param log_level: The logging level of this instance.
:raise ValueError: If missing credential, incorrect url, incorrect credentials or index JSON file is not found/unreadable.<|endoftext|> |
5fba859c208e29badeb472b93ecba6ab9578fc979f25c3b23e6ebcb81ef239a4 | def fetch(self):
'Load from the associated Git repository.'
os.makedirs(os.path.dirname(self.cached_repo), exist_ok=True)
if (not os.path.exists(self.cached_repo)):
self._log.warning('Index not found, caching %s in %s', self.repo, self.cached_repo)
git.clone(self.remote_url, self.cached_repo, checkout=True)
else:
self._log.debug('Index is cached in %s', self.cached_repo)
try:
diff = self._are_local_and_remote_heads_different()
except Exception as e:
self._log.warning('There was a problem with reading the cached index so cloning from scratch: %s: %s', type(e).__name__, e)
shutil.rmtree(self.cached_repo)
self.fetch()
return
if diff:
self._log.info('Cached index is not up to date, pulling %s', self.repo)
git.pull(self.cached_repo, self.remote_url)
with open(os.path.join(self.cached_repo, self.INDEX_FILE), encoding='utf-8') as _in:
self.contents = json.load(_in) | Load from the associated Git repository. | modelforge/index.py | fetch | src-d/modelforge | 19 | python | def fetch(self):
os.makedirs(os.path.dirname(self.cached_repo), exist_ok=True)
if (not os.path.exists(self.cached_repo)):
self._log.warning('Index not found, caching %s in %s', self.repo, self.cached_repo)
git.clone(self.remote_url, self.cached_repo, checkout=True)
else:
self._log.debug('Index is cached in %s', self.cached_repo)
try:
diff = self._are_local_and_remote_heads_different()
except Exception as e:
self._log.warning('There was a problem with reading the cached index so cloning from scratch: %s: %s', type(e).__name__, e)
shutil.rmtree(self.cached_repo)
self.fetch()
return
if diff:
self._log.info('Cached index is not up to date, pulling %s', self.repo)
git.pull(self.cached_repo, self.remote_url)
with open(os.path.join(self.cached_repo, self.INDEX_FILE), encoding='utf-8') as _in:
self.contents = json.load(_in) | def fetch(self):
os.makedirs(os.path.dirname(self.cached_repo), exist_ok=True)
if (not os.path.exists(self.cached_repo)):
self._log.warning('Index not found, caching %s in %s', self.repo, self.cached_repo)
git.clone(self.remote_url, self.cached_repo, checkout=True)
else:
self._log.debug('Index is cached in %s', self.cached_repo)
try:
diff = self._are_local_and_remote_heads_different()
except Exception as e:
self._log.warning('There was a problem with reading the cached index so cloning from scratch: %s: %s', type(e).__name__, e)
shutil.rmtree(self.cached_repo)
self.fetch()
return
if diff:
self._log.info('Cached index is not up to date, pulling %s', self.repo)
git.pull(self.cached_repo, self.remote_url)
with open(os.path.join(self.cached_repo, self.INDEX_FILE), encoding='utf-8') as _in:
self.contents = json.load(_in)<|docstring|>Load from the associated Git repository.<|endoftext|> |
8e4b22695eec2da3d1b6446a581c38f6ff3314a04c52a6eb80566790b110bc81 | def remove_model(self, model_uuid: str) -> dict:
'Delete the model from the registry. Call `upload()` to update the remote side.'
model_type = None
for (key, val) in self.models.items():
if (model_uuid in val):
self._log.info('Found %s among %s models', model_uuid, key)
model_type = key
break
if (model_type is None):
self._log.error('Model not found, aborted')
raise ValueError
model_directory = os.path.join(self.cached_repo, model_type)
model_node = self.models[model_type]
meta_node = self.meta[model_type]
if (len(model_node) == 1):
self.models.pop(model_type)
self.meta.pop(model_type)
paths = [os.path.join(model_directory, model) for model in os.listdir(model_directory)]
else:
if (meta_node['default'] == model_uuid):
self._log.info('Model is set as default, removing from index ...')
meta_node['default'] = ''
model_node.pop(model_uuid)
paths = [os.path.join(model_directory, (model_uuid + '.md'))]
git.remove(self.cached_repo, paths)
return {'model': model_type, 'uuid': model_uuid} | Delete the model from the registry. Call `upload()` to update the remote side. | modelforge/index.py | remove_model | src-d/modelforge | 19 | python | def remove_model(self, model_uuid: str) -> dict:
model_type = None
for (key, val) in self.models.items():
if (model_uuid in val):
self._log.info('Found %s among %s models', model_uuid, key)
model_type = key
break
if (model_type is None):
self._log.error('Model not found, aborted')
raise ValueError
model_directory = os.path.join(self.cached_repo, model_type)
model_node = self.models[model_type]
meta_node = self.meta[model_type]
if (len(model_node) == 1):
self.models.pop(model_type)
self.meta.pop(model_type)
paths = [os.path.join(model_directory, model) for model in os.listdir(model_directory)]
else:
if (meta_node['default'] == model_uuid):
self._log.info('Model is set as default, removing from index ...')
meta_node['default'] =
model_node.pop(model_uuid)
paths = [os.path.join(model_directory, (model_uuid + '.md'))]
git.remove(self.cached_repo, paths)
return {'model': model_type, 'uuid': model_uuid} | def remove_model(self, model_uuid: str) -> dict:
model_type = None
for (key, val) in self.models.items():
if (model_uuid in val):
self._log.info('Found %s among %s models', model_uuid, key)
model_type = key
break
if (model_type is None):
self._log.error('Model not found, aborted')
raise ValueError
model_directory = os.path.join(self.cached_repo, model_type)
model_node = self.models[model_type]
meta_node = self.meta[model_type]
if (len(model_node) == 1):
self.models.pop(model_type)
self.meta.pop(model_type)
paths = [os.path.join(model_directory, model) for model in os.listdir(model_directory)]
else:
if (meta_node['default'] == model_uuid):
self._log.info('Model is set as default, removing from index ...')
meta_node['default'] =
model_node.pop(model_uuid)
paths = [os.path.join(model_directory, (model_uuid + '.md'))]
git.remove(self.cached_repo, paths)
return {'model': model_type, 'uuid': model_uuid}<|docstring|>Delete the model from the registry. Call `upload()` to update the remote side.<|endoftext|> |
60bd8053d1b2181626233afb508bb4370fe1c8f2b7b9d6ad12f5f50975898310 | def add_model(self, model_type: str, model_uuid: str, meta: dict, template_model: Template, update_default: bool=False):
'Add a new model to the registry. Call `upload()` to update the remote side.'
if (update_default or (model_type not in self.meta)):
self.meta[model_type] = meta['default']
model_meta = meta['model']
self.models.setdefault(model_type, {})[model_uuid] = model_meta
model_directory = os.path.join(self.cached_repo, model_type)
os.makedirs(model_directory, exist_ok=True)
model = os.path.join(model_directory, (model_uuid + '.md'))
if os.path.exists(model):
os.remove(model)
links = {}
for (m_type, items) in self.models.items():
for uuid in items:
if (uuid in model_meta['dependencies']):
links[uuid] = os.path.join('/', m_type, ('%s.md' % uuid))
with open(model, 'w') as fout:
fout.write(template_model.render(model_type=model_type, model_uuid=model_uuid, meta=model_meta, links=links, spdx=LICENSES))
git.add(self.cached_repo, [model])
self._log.info('Added %s', model) | Add a new model to the registry. Call `upload()` to update the remote side. | modelforge/index.py | add_model | src-d/modelforge | 19 | python | def add_model(self, model_type: str, model_uuid: str, meta: dict, template_model: Template, update_default: bool=False):
if (update_default or (model_type not in self.meta)):
self.meta[model_type] = meta['default']
model_meta = meta['model']
self.models.setdefault(model_type, {})[model_uuid] = model_meta
model_directory = os.path.join(self.cached_repo, model_type)
os.makedirs(model_directory, exist_ok=True)
model = os.path.join(model_directory, (model_uuid + '.md'))
if os.path.exists(model):
os.remove(model)
links = {}
for (m_type, items) in self.models.items():
for uuid in items:
if (uuid in model_meta['dependencies']):
links[uuid] = os.path.join('/', m_type, ('%s.md' % uuid))
with open(model, 'w') as fout:
fout.write(template_model.render(model_type=model_type, model_uuid=model_uuid, meta=model_meta, links=links, spdx=LICENSES))
git.add(self.cached_repo, [model])
self._log.info('Added %s', model) | def add_model(self, model_type: str, model_uuid: str, meta: dict, template_model: Template, update_default: bool=False):
if (update_default or (model_type not in self.meta)):
self.meta[model_type] = meta['default']
model_meta = meta['model']
self.models.setdefault(model_type, {})[model_uuid] = model_meta
model_directory = os.path.join(self.cached_repo, model_type)
os.makedirs(model_directory, exist_ok=True)
model = os.path.join(model_directory, (model_uuid + '.md'))
if os.path.exists(model):
os.remove(model)
links = {}
for (m_type, items) in self.models.items():
for uuid in items:
if (uuid in model_meta['dependencies']):
links[uuid] = os.path.join('/', m_type, ('%s.md' % uuid))
with open(model, 'w') as fout:
fout.write(template_model.render(model_type=model_type, model_uuid=model_uuid, meta=model_meta, links=links, spdx=LICENSES))
git.add(self.cached_repo, [model])
self._log.info('Added %s', model)<|docstring|>Add a new model to the registry. Call `upload()` to update the remote side.<|endoftext|> |
6ed5bf3c11518cf2aca5582773a335d5d30405679447dbd12f40bd398fcd6c31 | def update_readme(self, template_readme: Template):
'Generate the new README file locally.'
readme = os.path.join(self.cached_repo, 'README.md')
if os.path.exists(readme):
os.remove(readme)
links = {model_type: {} for model_type in self.models.keys()}
for (model_type, model_uuids) in self.models.items():
for model_uuid in model_uuids:
links[model_type][model_uuid] = os.path.join('/', model_type, ('%s.md' % model_uuid))
with open(readme, 'w') as fout:
fout.write(template_readme.render(models=self.models, meta=self.meta, links=links))
git.add(self.cached_repo, [readme])
self._log.info('Updated %s', readme) | Generate the new README file locally. | modelforge/index.py | update_readme | src-d/modelforge | 19 | python | def update_readme(self, template_readme: Template):
readme = os.path.join(self.cached_repo, 'README.md')
if os.path.exists(readme):
os.remove(readme)
links = {model_type: {} for model_type in self.models.keys()}
for (model_type, model_uuids) in self.models.items():
for model_uuid in model_uuids:
links[model_type][model_uuid] = os.path.join('/', model_type, ('%s.md' % model_uuid))
with open(readme, 'w') as fout:
fout.write(template_readme.render(models=self.models, meta=self.meta, links=links))
git.add(self.cached_repo, [readme])
self._log.info('Updated %s', readme) | def update_readme(self, template_readme: Template):
readme = os.path.join(self.cached_repo, 'README.md')
if os.path.exists(readme):
os.remove(readme)
links = {model_type: {} for model_type in self.models.keys()}
for (model_type, model_uuids) in self.models.items():
for model_uuid in model_uuids:
links[model_type][model_uuid] = os.path.join('/', model_type, ('%s.md' % model_uuid))
with open(readme, 'w') as fout:
fout.write(template_readme.render(models=self.models, meta=self.meta, links=links))
git.add(self.cached_repo, [readme])
self._log.info('Updated %s', readme)<|docstring|>Generate the new README file locally.<|endoftext|> |
11ccd5df706ab99c91eba5f010ec692c996191f874da1b8c7ca89db0b2eb06ac | def reset(self):
'Initialize the remote Git repository.'
paths = []
for filename in os.listdir(self.cached_repo):
if filename.startswith('.git'):
continue
path = os.path.join(self.cached_repo, filename)
if os.path.isfile(path):
paths.append(path)
elif os.path.isdir(path):
for model in os.listdir(path):
paths.append(os.path.join(path, model))
git.remove(self.cached_repo, paths)
self.contents = {'models': {}, 'meta': {}} | Initialize the remote Git repository. | modelforge/index.py | reset | src-d/modelforge | 19 | python | def reset(self):
paths = []
for filename in os.listdir(self.cached_repo):
if filename.startswith('.git'):
continue
path = os.path.join(self.cached_repo, filename)
if os.path.isfile(path):
paths.append(path)
elif os.path.isdir(path):
for model in os.listdir(path):
paths.append(os.path.join(path, model))
git.remove(self.cached_repo, paths)
self.contents = {'models': {}, 'meta': {}} | def reset(self):
paths = []
for filename in os.listdir(self.cached_repo):
if filename.startswith('.git'):
continue
path = os.path.join(self.cached_repo, filename)
if os.path.isfile(path):
paths.append(path)
elif os.path.isdir(path):
for model in os.listdir(path):
paths.append(os.path.join(path, model))
git.remove(self.cached_repo, paths)
self.contents = {'models': {}, 'meta': {}}<|docstring|>Initialize the remote Git repository.<|endoftext|> |
574083ae4593f550fbd5a488d4b69e7c132fc9fc63a6da48dd56addcd63958bd | def upload(self, cmd: str, meta: dict):
'Push the current state of the registry to Git.'
index = os.path.join(self.cached_repo, self.INDEX_FILE)
if os.path.exists(index):
os.remove(index)
self._log.info('Writing the new index.json ...')
with open(index, 'w') as _out:
json.dump(self.contents, _out, sort_keys=True, indent=4)
git.add(self.cached_repo, [index])
message = self.COMMIT_MESSAGES[cmd].format(**meta)
if self.signoff:
global_conf_path = os.path.expanduser('~/.gitconfig')
if os.path.exists(global_conf_path):
with open(global_conf_path, 'br') as _in:
conf = ConfigFile.from_file(_in)
try:
name = conf.get(b'user', b'name').decode()
email = conf.get(b'user', b'email').decode()
message += self.DCO_MESSAGE.format(name=name, email=email)
except KeyError:
self._log.warning('Did not find name or email in %s, committing without DCO', global_conf_path)
else:
self._log.warning('Global git configuration file %s does not exist, committing without DCO', global_conf_path)
else:
self._log.info('Committing the index without DCO')
git.commit(self.cached_repo, message=message)
self._log.info('Pushing the updated index ...')
git.push(self.cached_repo, self.remote_url, b'master')
if self._are_local_and_remote_heads_different():
self._log.error('Push has failed')
raise ValueError('Push has failed') | Push the current state of the registry to Git. | modelforge/index.py | upload | src-d/modelforge | 19 | python | def upload(self, cmd: str, meta: dict):
index = os.path.join(self.cached_repo, self.INDEX_FILE)
if os.path.exists(index):
os.remove(index)
self._log.info('Writing the new index.json ...')
with open(index, 'w') as _out:
json.dump(self.contents, _out, sort_keys=True, indent=4)
git.add(self.cached_repo, [index])
message = self.COMMIT_MESSAGES[cmd].format(**meta)
if self.signoff:
global_conf_path = os.path.expanduser('~/.gitconfig')
if os.path.exists(global_conf_path):
with open(global_conf_path, 'br') as _in:
conf = ConfigFile.from_file(_in)
try:
name = conf.get(b'user', b'name').decode()
email = conf.get(b'user', b'email').decode()
message += self.DCO_MESSAGE.format(name=name, email=email)
except KeyError:
self._log.warning('Did not find name or email in %s, committing without DCO', global_conf_path)
else:
self._log.warning('Global git configuration file %s does not exist, committing without DCO', global_conf_path)
else:
self._log.info('Committing the index without DCO')
git.commit(self.cached_repo, message=message)
self._log.info('Pushing the updated index ...')
git.push(self.cached_repo, self.remote_url, b'master')
if self._are_local_and_remote_heads_different():
self._log.error('Push has failed')
raise ValueError('Push has failed') | def upload(self, cmd: str, meta: dict):
index = os.path.join(self.cached_repo, self.INDEX_FILE)
if os.path.exists(index):
os.remove(index)
self._log.info('Writing the new index.json ...')
with open(index, 'w') as _out:
json.dump(self.contents, _out, sort_keys=True, indent=4)
git.add(self.cached_repo, [index])
message = self.COMMIT_MESSAGES[cmd].format(**meta)
if self.signoff:
global_conf_path = os.path.expanduser('~/.gitconfig')
if os.path.exists(global_conf_path):
with open(global_conf_path, 'br') as _in:
conf = ConfigFile.from_file(_in)
try:
name = conf.get(b'user', b'name').decode()
email = conf.get(b'user', b'email').decode()
message += self.DCO_MESSAGE.format(name=name, email=email)
except KeyError:
self._log.warning('Did not find name or email in %s, committing without DCO', global_conf_path)
else:
self._log.warning('Global git configuration file %s does not exist, committing without DCO', global_conf_path)
else:
self._log.info('Committing the index without DCO')
git.commit(self.cached_repo, message=message)
self._log.info('Pushing the updated index ...')
git.push(self.cached_repo, self.remote_url, b'master')
if self._are_local_and_remote_heads_different():
self._log.error('Push has failed')
raise ValueError('Push has failed')<|docstring|>Push the current state of the registry to Git.<|endoftext|> |
c1e31a2dc2717ddbe26dd521f1bc7cee5db54c8bc89ffcc1398c201ca99ee67c | def load_template(self, template: str) -> Template:
'Load a Jinja2 template from the source directory.'
env = dict(trim_blocks=True, lstrip_blocks=True, keep_trailing_newline=False)
jinja2_ext = '.jinja2'
if (not template.endswith(jinja2_ext)):
self._log.error(('Template file name must end with %s' % jinja2_ext))
raise ValueError
if (not template[:(- len(jinja2_ext))].endswith('.md')):
self._log.error('Template file should be a Markdown file')
raise ValueError
if (not os.path.isabs(template)):
template = os.path.join(os.path.dirname(__file__), template)
with open(template, encoding='utf-8') as fin:
template_obj = Template(fin.read(), **env)
template_obj.filename = template
self._log.info('Loaded %s', template)
return template_obj | Load a Jinja2 template from the source directory. | modelforge/index.py | load_template | src-d/modelforge | 19 | python | def load_template(self, template: str) -> Template:
env = dict(trim_blocks=True, lstrip_blocks=True, keep_trailing_newline=False)
jinja2_ext = '.jinja2'
if (not template.endswith(jinja2_ext)):
self._log.error(('Template file name must end with %s' % jinja2_ext))
raise ValueError
if (not template[:(- len(jinja2_ext))].endswith('.md')):
self._log.error('Template file should be a Markdown file')
raise ValueError
if (not os.path.isabs(template)):
template = os.path.join(os.path.dirname(__file__), template)
with open(template, encoding='utf-8') as fin:
template_obj = Template(fin.read(), **env)
template_obj.filename = template
self._log.info('Loaded %s', template)
return template_obj | def load_template(self, template: str) -> Template:
env = dict(trim_blocks=True, lstrip_blocks=True, keep_trailing_newline=False)
jinja2_ext = '.jinja2'
if (not template.endswith(jinja2_ext)):
self._log.error(('Template file name must end with %s' % jinja2_ext))
raise ValueError
if (not template[:(- len(jinja2_ext))].endswith('.md')):
self._log.error('Template file should be a Markdown file')
raise ValueError
if (not os.path.isabs(template)):
template = os.path.join(os.path.dirname(__file__), template)
with open(template, encoding='utf-8') as fin:
template_obj = Template(fin.read(), **env)
template_obj.filename = template
self._log.info('Loaded %s', template)
return template_obj<|docstring|>Load a Jinja2 template from the source directory.<|endoftext|> |
14b997842c93abcf6db655594fda8411ce5583e158d0a2f2c46157412139870f | def makeId(timestamp=0, machine=0, flow=0):
'\n using unix style timestamp, not python timestamp\n '
timestamp -= _base
return (((timestamp << 13) | (machine << 8)) | flow) | using unix style timestamp, not python timestamp | backend/app/snowflake.py | makeId | GJCav/thywy | 8 | python | def makeId(timestamp=0, machine=0, flow=0):
'\n \n '
timestamp -= _base
return (((timestamp << 13) | (machine << 8)) | flow) | def makeId(timestamp=0, machine=0, flow=0):
'\n \n '
timestamp -= _base
return (((timestamp << 13) | (machine << 8)) | flow)<|docstring|>using unix style timestamp, not python timestamp<|endoftext|> |
88628d1185b0e200ee33c33a6be3c478dba7d523bc1e75f76234fed38b1b3195 | def _preprocess():
'\n Before starting the jobs, first create the image files required for\n determining the chunk starting frequencies (i.e., "_tinyimg.sumwt"). If\n this file already exists it will move on.\n '
_get_config() | Before starting the jobs, first create the image files required for
determining the chunk starting frequencies (i.e., "_tinyimg.sumwt"). If
this file already exists it will move on. | pipe_scripts/run_pipe_cb68_cs.py | _preprocess | autocorr/faust_line_imaging | 1 | python | def _preprocess():
'\n Before starting the jobs, first create the image files required for\n determining the chunk starting frequencies (i.e., "_tinyimg.sumwt"). If\n this file already exists it will move on.\n '
_get_config() | def _preprocess():
'\n Before starting the jobs, first create the image files required for\n determining the chunk starting frequencies (i.e., "_tinyimg.sumwt"). If\n this file already exists it will move on.\n '
_get_config()<|docstring|>Before starting the jobs, first create the image files required for
determining the chunk starting frequencies (i.e., "_tinyimg.sumwt"). If
this file already exists it will move on.<|endoftext|> |
ff041ba556cf36c348c435ee2f2aebb32674fe31b4e1b0542708ad80a83c3626 | def _run_subset(batch_ix):
'\n Run the pipeline for a subset of chunks. Chunks are processed in stride,\n e.g.: 0, 10, 20... or 1, 11, 21...\n\n Parameters\n ----------\n batch_ix : int\n Batch index number. For 100 chunks and 10 batches, ``batch_ix=0``\n would process chunks 0, 10, ..., 90.\n '
nbatches = _NBATCHES
batch_ix = int(batch_ix)
assert (batch_ix < nbatches)
log_post(':: Running batch index: {0}'.format(batch_ix))
log_post('-- Batch: {0} / {1}'.format((batch_ix + 1), nbatches))
(full_config, chunked_configs) = _get_config()
for config in chunked_configs[batch_ix::nbatches]:
config.run_pipeline(ext=_RUN_EXT) | Run the pipeline for a subset of chunks. Chunks are processed in stride,
e.g.: 0, 10, 20... or 1, 11, 21...
Parameters
----------
batch_ix : int
Batch index number. For 100 chunks and 10 batches, ``batch_ix=0``
would process chunks 0, 10, ..., 90. | pipe_scripts/run_pipe_cb68_cs.py | _run_subset | autocorr/faust_line_imaging | 1 | python | def _run_subset(batch_ix):
'\n Run the pipeline for a subset of chunks. Chunks are processed in stride,\n e.g.: 0, 10, 20... or 1, 11, 21...\n\n Parameters\n ----------\n batch_ix : int\n Batch index number. For 100 chunks and 10 batches, ``batch_ix=0``\n would process chunks 0, 10, ..., 90.\n '
nbatches = _NBATCHES
batch_ix = int(batch_ix)
assert (batch_ix < nbatches)
log_post(':: Running batch index: {0}'.format(batch_ix))
log_post('-- Batch: {0} / {1}'.format((batch_ix + 1), nbatches))
(full_config, chunked_configs) = _get_config()
for config in chunked_configs[batch_ix::nbatches]:
config.run_pipeline(ext=_RUN_EXT) | def _run_subset(batch_ix):
'\n Run the pipeline for a subset of chunks. Chunks are processed in stride,\n e.g.: 0, 10, 20... or 1, 11, 21...\n\n Parameters\n ----------\n batch_ix : int\n Batch index number. For 100 chunks and 10 batches, ``batch_ix=0``\n would process chunks 0, 10, ..., 90.\n '
nbatches = _NBATCHES
batch_ix = int(batch_ix)
assert (batch_ix < nbatches)
log_post(':: Running batch index: {0}'.format(batch_ix))
log_post('-- Batch: {0} / {1}'.format((batch_ix + 1), nbatches))
(full_config, chunked_configs) = _get_config()
for config in chunked_configs[batch_ix::nbatches]:
config.run_pipeline(ext=_RUN_EXT)<|docstring|>Run the pipeline for a subset of chunks. Chunks are processed in stride,
e.g.: 0, 10, 20... or 1, 11, 21...
Parameters
----------
batch_ix : int
Batch index number. For 100 chunks and 10 batches, ``batch_ix=0``
would process chunks 0, 10, ..., 90.<|endoftext|> |
aeced38063a2cb92e260b39da1c1b00f02ea6488ecafb8ccf6656fe09805ac3a | @property
def template_url(self):
"Template url for the stack resource.\n\n When stack resource is a TemplateResource, it's the template\n location. For group resources like ResourceGroup where the\n template is constructed dynamically, it's just a placeholder.\n "
return 'nested_stack' | Template url for the stack resource.
When stack resource is a TemplateResource, it's the template
location. For group resources like ResourceGroup where the
template is constructed dynamically, it's just a placeholder. | heat/engine/resources/stack_resource.py | template_url | coreycb/heat | 1 | python | @property
def template_url(self):
"Template url for the stack resource.\n\n When stack resource is a TemplateResource, it's the template\n location. For group resources like ResourceGroup where the\n template is constructed dynamically, it's just a placeholder.\n "
return 'nested_stack' | @property
def template_url(self):
"Template url for the stack resource.\n\n When stack resource is a TemplateResource, it's the template\n location. For group resources like ResourceGroup where the\n template is constructed dynamically, it's just a placeholder.\n "
return 'nested_stack'<|docstring|>Template url for the stack resource.
When stack resource is a TemplateResource, it's the template
location. For group resources like ResourceGroup where the
template is constructed dynamically, it's just a placeholder.<|endoftext|> |
9dfb63efc41610ec0b102e1d57dec02eed1d3891e007cd0bf01b1d6cbebfc6c5 | def has_nested(self):
'Return True if the resource has an existing nested stack.'
return ((self.resource_id is not None) or (self._nested is not None)) | Return True if the resource has an existing nested stack. | heat/engine/resources/stack_resource.py | has_nested | coreycb/heat | 1 | python | def has_nested(self):
return ((self.resource_id is not None) or (self._nested is not None)) | def has_nested(self):
return ((self.resource_id is not None) or (self._nested is not None))<|docstring|>Return True if the resource has an existing nested stack.<|endoftext|> |
0b7d38aac587524f21bb32e5f3ec07392b2be0907199d44a1b89246d29c3e7e3 | def nested(self):
'Return a Stack object representing the nested (child) stack.\n\n If we catch NotFound exception when loading, return None.\n '
if ((self._nested is None) and (self.resource_id is not None)):
try:
self._nested = parser.Stack.load(self.context, self.resource_id)
except exception.NotFound:
return None
return self._nested | Return a Stack object representing the nested (child) stack.
If we catch NotFound exception when loading, return None. | heat/engine/resources/stack_resource.py | nested | coreycb/heat | 1 | python | def nested(self):
'Return a Stack object representing the nested (child) stack.\n\n If we catch NotFound exception when loading, return None.\n '
if ((self._nested is None) and (self.resource_id is not None)):
try:
self._nested = parser.Stack.load(self.context, self.resource_id)
except exception.NotFound:
return None
return self._nested | def nested(self):
'Return a Stack object representing the nested (child) stack.\n\n If we catch NotFound exception when loading, return None.\n '
if ((self._nested is None) and (self.resource_id is not None)):
try:
self._nested = parser.Stack.load(self.context, self.resource_id)
except exception.NotFound:
return None
return self._nested<|docstring|>Return a Stack object representing the nested (child) stack.
If we catch NotFound exception when loading, return None.<|endoftext|> |
22bb2fba51818072343877d2c369947f35404831d4185c16fc949226331cc7ec | def child_template(self):
'Default implementation to get the child template.\n\n Resources that inherit from StackResource should override this method\n with specific details about the template used by them.\n '
raise NotImplementedError() | Default implementation to get the child template.
Resources that inherit from StackResource should override this method
with specific details about the template used by them. | heat/engine/resources/stack_resource.py | child_template | coreycb/heat | 1 | python | def child_template(self):
'Default implementation to get the child template.\n\n Resources that inherit from StackResource should override this method\n with specific details about the template used by them.\n '
raise NotImplementedError() | def child_template(self):
'Default implementation to get the child template.\n\n Resources that inherit from StackResource should override this method\n with specific details about the template used by them.\n '
raise NotImplementedError()<|docstring|>Default implementation to get the child template.
Resources that inherit from StackResource should override this method
with specific details about the template used by them.<|endoftext|> |
7d23ec61561129d1356f2e0eb2ec9b9ed0f1c21009abc15ca2aefc15ed4188f0 | def child_params(self):
'Default implementation to get the child params.\n\n Resources that inherit from StackResource should override this method\n with specific details about the parameters used by them.\n '
raise NotImplementedError() | Default implementation to get the child params.
Resources that inherit from StackResource should override this method
with specific details about the parameters used by them. | heat/engine/resources/stack_resource.py | child_params | coreycb/heat | 1 | python | def child_params(self):
'Default implementation to get the child params.\n\n Resources that inherit from StackResource should override this method\n with specific details about the parameters used by them.\n '
raise NotImplementedError() | def child_params(self):
'Default implementation to get the child params.\n\n Resources that inherit from StackResource should override this method\n with specific details about the parameters used by them.\n '
raise NotImplementedError()<|docstring|>Default implementation to get the child params.
Resources that inherit from StackResource should override this method
with specific details about the parameters used by them.<|endoftext|> |
b71404ae2ffb5f9e3d095971518b0abf06b42d89b172564b23814699410dd46a | def preview(self):
'Preview a StackResource as resources within a Stack.\n\n This method overrides the original Resource.preview to return a preview\n of all the resources contained in this Stack. For this to be possible,\n the specific resources need to override both ``child_template`` and\n ``child_params`` with specific information to allow the stack to be\n parsed correctly. If any of these methods is missing, the entire\n StackResource will be returned as if it were a regular Resource.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Preview of '%s' not yet implemented", class_name)
return self
name = ('%s-%s' % (self.stack.name, self.name))
self._nested = self._parse_nested_stack(name, child_template, params)
return self.nested().preview_resources() | Preview a StackResource as resources within a Stack.
This method overrides the original Resource.preview to return a preview
of all the resources contained in this Stack. For this to be possible,
the specific resources need to override both ``child_template`` and
``child_params`` with specific information to allow the stack to be
parsed correctly. If any of these methods is missing, the entire
StackResource will be returned as if it were a regular Resource. | heat/engine/resources/stack_resource.py | preview | coreycb/heat | 1 | python | def preview(self):
'Preview a StackResource as resources within a Stack.\n\n This method overrides the original Resource.preview to return a preview\n of all the resources contained in this Stack. For this to be possible,\n the specific resources need to override both ``child_template`` and\n ``child_params`` with specific information to allow the stack to be\n parsed correctly. If any of these methods is missing, the entire\n StackResource will be returned as if it were a regular Resource.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Preview of '%s' not yet implemented", class_name)
return self
name = ('%s-%s' % (self.stack.name, self.name))
self._nested = self._parse_nested_stack(name, child_template, params)
return self.nested().preview_resources() | def preview(self):
'Preview a StackResource as resources within a Stack.\n\n This method overrides the original Resource.preview to return a preview\n of all the resources contained in this Stack. For this to be possible,\n the specific resources need to override both ``child_template`` and\n ``child_params`` with specific information to allow the stack to be\n parsed correctly. If any of these methods is missing, the entire\n StackResource will be returned as if it were a regular Resource.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Preview of '%s' not yet implemented", class_name)
return self
name = ('%s-%s' % (self.stack.name, self.name))
self._nested = self._parse_nested_stack(name, child_template, params)
return self.nested().preview_resources()<|docstring|>Preview a StackResource as resources within a Stack.
This method overrides the original Resource.preview to return a preview
of all the resources contained in this Stack. For this to be possible,
the specific resources need to override both ``child_template`` and
``child_params`` with specific information to allow the stack to be
parsed correctly. If any of these methods is missing, the entire
StackResource will be returned as if it were a regular Resource.<|endoftext|> |
c8c7f6512a78d1da077281442b84b609688c274ebff0b3148d6e1081892d21a5 | def get_nested_parameters_stack(self):
'Return a stack for schema validation.\n\n This returns a stack to be introspected for building parameters schema.\n It can be customized by subclass to return a restricted version of what\n will be running.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Nested parameters of '%s' not yet implemented", class_name)
return
name = ('%s-%s' % (self.stack.name, self.name))
return self._parse_nested_stack(name, child_template, params) | Return a stack for schema validation.
This returns a stack to be introspected for building parameters schema.
It can be customized by subclass to return a restricted version of what
will be running. | heat/engine/resources/stack_resource.py | get_nested_parameters_stack | coreycb/heat | 1 | python | def get_nested_parameters_stack(self):
'Return a stack for schema validation.\n\n This returns a stack to be introspected for building parameters schema.\n It can be customized by subclass to return a restricted version of what\n will be running.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Nested parameters of '%s' not yet implemented", class_name)
return
name = ('%s-%s' % (self.stack.name, self.name))
return self._parse_nested_stack(name, child_template, params) | def get_nested_parameters_stack(self):
'Return a stack for schema validation.\n\n This returns a stack to be introspected for building parameters schema.\n It can be customized by subclass to return a restricted version of what\n will be running.\n '
try:
child_template = self.child_template()
params = self.child_params()
except NotImplementedError:
class_name = reflection.get_class_name(self, fully_qualified=False)
LOG.warning("Nested parameters of '%s' not yet implemented", class_name)
return
name = ('%s-%s' % (self.stack.name, self.name))
return self._parse_nested_stack(name, child_template, params)<|docstring|>Return a stack for schema validation.
This returns a stack to be introspected for building parameters schema.
It can be customized by subclass to return a restricted version of what
will be running.<|endoftext|> |
a9efad6367bb2f59b87a273912534a583ec49107ecf5a2c1e7b7de1c98de7101 | def child_template_files(self, child_env):
'Default implementation to get the files map for child template.'
return self.stack.t.files | Default implementation to get the files map for child template. | heat/engine/resources/stack_resource.py | child_template_files | coreycb/heat | 1 | python | def child_template_files(self, child_env):
return self.stack.t.files | def child_template_files(self, child_env):
return self.stack.t.files<|docstring|>Default implementation to get the files map for child template.<|endoftext|> |
a8811583217060a51c324d60b129d71661bb1bcac0339a3b7c5769dafaaa6bd6 | def create_with_template(self, child_template, user_params=None, timeout_mins=None, adopt_data=None):
'Create the nested stack with the given template.'
name = self.physical_resource_name()
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
stack_user_project_id = self.stack.stack_user_project_id
kwargs = self._stack_kwargs(user_params, child_template, adopt_data)
adopt_data_str = None
if (adopt_data is not None):
if ('environment' not in adopt_data):
adopt_data['environment'] = kwargs['params']
if ('template' not in adopt_data):
if isinstance(child_template, template.Template):
adopt_data['template'] = child_template.t
else:
adopt_data['template'] = child_template
adopt_data_str = json.dumps(adopt_data)
args = {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_DISABLE_ROLLBACK: True, rpc_api.PARAM_ADOPT_STACK_DATA: adopt_data_str}
kwargs.update({'stack_name': name, 'args': args, 'environment_files': None, 'owner_id': self.stack.id, 'user_creds_id': self.stack.user_creds_id, 'stack_user_project_id': stack_user_project_id, 'nested_depth': self._child_nested_depth(), 'parent_resource_name': self.name})
with self.translate_remote_exceptions:
try:
result = self.rpc_client()._create_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
if (adopt_data is None):
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
self.resource_id_set(result['stack_id']) | Create the nested stack with the given template. | heat/engine/resources/stack_resource.py | create_with_template | coreycb/heat | 1 | python | def create_with_template(self, child_template, user_params=None, timeout_mins=None, adopt_data=None):
name = self.physical_resource_name()
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
stack_user_project_id = self.stack.stack_user_project_id
kwargs = self._stack_kwargs(user_params, child_template, adopt_data)
adopt_data_str = None
if (adopt_data is not None):
if ('environment' not in adopt_data):
adopt_data['environment'] = kwargs['params']
if ('template' not in adopt_data):
if isinstance(child_template, template.Template):
adopt_data['template'] = child_template.t
else:
adopt_data['template'] = child_template
adopt_data_str = json.dumps(adopt_data)
args = {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_DISABLE_ROLLBACK: True, rpc_api.PARAM_ADOPT_STACK_DATA: adopt_data_str}
kwargs.update({'stack_name': name, 'args': args, 'environment_files': None, 'owner_id': self.stack.id, 'user_creds_id': self.stack.user_creds_id, 'stack_user_project_id': stack_user_project_id, 'nested_depth': self._child_nested_depth(), 'parent_resource_name': self.name})
with self.translate_remote_exceptions:
try:
result = self.rpc_client()._create_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
if (adopt_data is None):
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
self.resource_id_set(result['stack_id']) | def create_with_template(self, child_template, user_params=None, timeout_mins=None, adopt_data=None):
name = self.physical_resource_name()
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
stack_user_project_id = self.stack.stack_user_project_id
kwargs = self._stack_kwargs(user_params, child_template, adopt_data)
adopt_data_str = None
if (adopt_data is not None):
if ('environment' not in adopt_data):
adopt_data['environment'] = kwargs['params']
if ('template' not in adopt_data):
if isinstance(child_template, template.Template):
adopt_data['template'] = child_template.t
else:
adopt_data['template'] = child_template
adopt_data_str = json.dumps(adopt_data)
args = {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_DISABLE_ROLLBACK: True, rpc_api.PARAM_ADOPT_STACK_DATA: adopt_data_str}
kwargs.update({'stack_name': name, 'args': args, 'environment_files': None, 'owner_id': self.stack.id, 'user_creds_id': self.stack.user_creds_id, 'stack_user_project_id': stack_user_project_id, 'nested_depth': self._child_nested_depth(), 'parent_resource_name': self.name})
with self.translate_remote_exceptions:
try:
result = self.rpc_client()._create_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
if (adopt_data is None):
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
self.resource_id_set(result['stack_id'])<|docstring|>Create the nested stack with the given template.<|endoftext|> |
774b0b0bd109f97a82be53d5742367223dffd3aad95312ffdac62fdca4c0423b | def update_with_template(self, child_template, user_params=None, timeout_mins=None):
'Update the nested stack with the new template.'
if (self.id is None):
self.store()
if (self.stack.action == self.stack.ROLLBACK):
if self._try_rollback():
LOG.info('Triggered nested stack %s rollback', self.physical_resource_name())
return {'target_action': self.stack.ROLLBACK}
if (self.resource_id is None):
def _check_for_completion():
while (not self.check_create_complete()):
(yield)
empty_temp = template_format.parse("heat_template_version: '2013-05-23'")
self.create_with_template(empty_temp, {})
checker = scheduler.TaskRunner(_check_for_completion)
checker(timeout=self.stack.timeout_secs())
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
try:
status_data = stack_object.Stack.get_status(self.context, self.resource_id)
except exception.NotFound:
raise resource.UpdateReplace(self)
(action, status, status_reason, updated_time) = status_data
kwargs = self._stack_kwargs(user_params, child_template)
cookie = {'previous': {'updated_at': updated_time, 'state': (action, status)}}
kwargs.update({'stack_identity': dict(self.nested_identifier()), 'args': {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_CONVERGE: self.converge}})
with self.translate_remote_exceptions:
try:
self.rpc_client()._update_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
return cookie | Update the nested stack with the new template. | heat/engine/resources/stack_resource.py | update_with_template | coreycb/heat | 1 | python | def update_with_template(self, child_template, user_params=None, timeout_mins=None):
if (self.id is None):
self.store()
if (self.stack.action == self.stack.ROLLBACK):
if self._try_rollback():
LOG.info('Triggered nested stack %s rollback', self.physical_resource_name())
return {'target_action': self.stack.ROLLBACK}
if (self.resource_id is None):
def _check_for_completion():
while (not self.check_create_complete()):
(yield)
empty_temp = template_format.parse("heat_template_version: '2013-05-23'")
self.create_with_template(empty_temp, {})
checker = scheduler.TaskRunner(_check_for_completion)
checker(timeout=self.stack.timeout_secs())
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
try:
status_data = stack_object.Stack.get_status(self.context, self.resource_id)
except exception.NotFound:
raise resource.UpdateReplace(self)
(action, status, status_reason, updated_time) = status_data
kwargs = self._stack_kwargs(user_params, child_template)
cookie = {'previous': {'updated_at': updated_time, 'state': (action, status)}}
kwargs.update({'stack_identity': dict(self.nested_identifier()), 'args': {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_CONVERGE: self.converge}})
with self.translate_remote_exceptions:
try:
self.rpc_client()._update_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
return cookie | def update_with_template(self, child_template, user_params=None, timeout_mins=None):
if (self.id is None):
self.store()
if (self.stack.action == self.stack.ROLLBACK):
if self._try_rollback():
LOG.info('Triggered nested stack %s rollback', self.physical_resource_name())
return {'target_action': self.stack.ROLLBACK}
if (self.resource_id is None):
def _check_for_completion():
while (not self.check_create_complete()):
(yield)
empty_temp = template_format.parse("heat_template_version: '2013-05-23'")
self.create_with_template(empty_temp, {})
checker = scheduler.TaskRunner(_check_for_completion)
checker(timeout=self.stack.timeout_secs())
if (timeout_mins is None):
timeout_mins = self.stack.timeout_mins
try:
status_data = stack_object.Stack.get_status(self.context, self.resource_id)
except exception.NotFound:
raise resource.UpdateReplace(self)
(action, status, status_reason, updated_time) = status_data
kwargs = self._stack_kwargs(user_params, child_template)
cookie = {'previous': {'updated_at': updated_time, 'state': (action, status)}}
kwargs.update({'stack_identity': dict(self.nested_identifier()), 'args': {rpc_api.PARAM_TIMEOUT: timeout_mins, rpc_api.PARAM_CONVERGE: self.converge}})
with self.translate_remote_exceptions:
try:
self.rpc_client()._update_stack(self.context, **kwargs)
except exception.HeatException:
with excutils.save_and_reraise_exception():
raw_template.RawTemplate.delete(self.context, kwargs['template_id'])
return cookie<|docstring|>Update the nested stack with the new template.<|endoftext|> |
86538e0634f5d35cc1467198b04ec80a92eab948cb0a5766571fdc3ab6c37e29 | def delete_nested(self):
'Delete the nested stack.'
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
with self.rpc_client().ignore_error_by_name('EntityNotFound'):
if self.abandon_in_progress:
self.rpc_client().abandon_stack(self.context, stack_identity)
else:
self.rpc_client().delete_stack(self.context, stack_identity, cast=False) | Delete the nested stack. | heat/engine/resources/stack_resource.py | delete_nested | coreycb/heat | 1 | python | def delete_nested(self):
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
with self.rpc_client().ignore_error_by_name('EntityNotFound'):
if self.abandon_in_progress:
self.rpc_client().abandon_stack(self.context, stack_identity)
else:
self.rpc_client().delete_stack(self.context, stack_identity, cast=False) | def delete_nested(self):
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
with self.rpc_client().ignore_error_by_name('EntityNotFound'):
if self.abandon_in_progress:
self.rpc_client().abandon_stack(self.context, stack_identity)
else:
self.rpc_client().delete_stack(self.context, stack_identity, cast=False)<|docstring|>Delete the nested stack.<|endoftext|> |
a831ce64e4be732cde89438498dfddc79bdf516dc09e1db90552e00a2a2e5927 | def get_output(self, op):
'Return the specified Output value from the nested stack.\n\n If the output key does not exist, raise a NotFound exception.\n '
if ((self._outputs is None) or ((op in self._outputs) and (rpc_api.OUTPUT_ERROR not in self._outputs[op]) and (self._outputs[op].get(rpc_api.OUTPUT_VALUE) is None))):
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
stack = self.rpc_client().show_stack(self.context, dict(stack_identity))
if (not stack):
return
outputs = (stack[0].get(rpc_api.STACK_OUTPUTS) or {})
self._outputs = {o[rpc_api.OUTPUT_KEY]: o for o in outputs}
if (op not in self._outputs):
raise exception.NotFound((_('Specified output key %s not found.') % op))
output_data = self._outputs[op]
if (rpc_api.OUTPUT_ERROR in output_data):
raise exception.TemplateOutputError(resource=self.name, attribute=op, message=output_data[rpc_api.OUTPUT_ERROR])
return output_data[rpc_api.OUTPUT_VALUE] | Return the specified Output value from the nested stack.
If the output key does not exist, raise a NotFound exception. | heat/engine/resources/stack_resource.py | get_output | coreycb/heat | 1 | python | def get_output(self, op):
'Return the specified Output value from the nested stack.\n\n If the output key does not exist, raise a NotFound exception.\n '
if ((self._outputs is None) or ((op in self._outputs) and (rpc_api.OUTPUT_ERROR not in self._outputs[op]) and (self._outputs[op].get(rpc_api.OUTPUT_VALUE) is None))):
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
stack = self.rpc_client().show_stack(self.context, dict(stack_identity))
if (not stack):
return
outputs = (stack[0].get(rpc_api.STACK_OUTPUTS) or {})
self._outputs = {o[rpc_api.OUTPUT_KEY]: o for o in outputs}
if (op not in self._outputs):
raise exception.NotFound((_('Specified output key %s not found.') % op))
output_data = self._outputs[op]
if (rpc_api.OUTPUT_ERROR in output_data):
raise exception.TemplateOutputError(resource=self.name, attribute=op, message=output_data[rpc_api.OUTPUT_ERROR])
return output_data[rpc_api.OUTPUT_VALUE] | def get_output(self, op):
'Return the specified Output value from the nested stack.\n\n If the output key does not exist, raise a NotFound exception.\n '
if ((self._outputs is None) or ((op in self._outputs) and (rpc_api.OUTPUT_ERROR not in self._outputs[op]) and (self._outputs[op].get(rpc_api.OUTPUT_VALUE) is None))):
stack_identity = self.nested_identifier()
if (stack_identity is None):
return
stack = self.rpc_client().show_stack(self.context, dict(stack_identity))
if (not stack):
return
outputs = (stack[0].get(rpc_api.STACK_OUTPUTS) or {})
self._outputs = {o[rpc_api.OUTPUT_KEY]: o for o in outputs}
if (op not in self._outputs):
raise exception.NotFound((_('Specified output key %s not found.') % op))
output_data = self._outputs[op]
if (rpc_api.OUTPUT_ERROR in output_data):
raise exception.TemplateOutputError(resource=self.name, attribute=op, message=output_data[rpc_api.OUTPUT_ERROR])
return output_data[rpc_api.OUTPUT_VALUE]<|docstring|>Return the specified Output value from the nested stack.
If the output key does not exist, raise a NotFound exception.<|endoftext|> |
7c5b4f047c0d737663146976c350af35d6813bf3ee16c7293dde4b0a1f0850f5 | def slow_tqdm(*args, **kwargs):
' Return a tqdm progress bar with infrequent updates. '
return tqdm.tqdm(*args, mininterval=10, **kwargs) | Return a tqdm progress bar with infrequent updates. | bioslds/run_hyper_snippets.py | slow_tqdm | ttesileanu/bio-time-series | 0 | python | def slow_tqdm(*args, **kwargs):
' '
return tqdm.tqdm(*args, mininterval=10, **kwargs) | def slow_tqdm(*args, **kwargs):
' '
return tqdm.tqdm(*args, mininterval=10, **kwargs)<|docstring|>Return a tqdm progress bar with infrequent updates.<|endoftext|> |
13b023ed342f57aac69aa9b9a05d5b2846a61fc61d35e7955da0fb6dc411f42b | def make_bio_wta_with_stable_initial(*args, **kwargs) -> BioWTARegressor:
' Call the BioWTARegressor constructor, ensuring that the initial coefficients are\n chosen to correspond to stable AR processes.\n '
weights = [make_random_arma(kwargs['n_features'], 0, rng=kwargs['rng']).a for _ in range(kwargs['n_models'])]
return BioWTARegressor(*args, weights=weights, **kwargs) | Call the BioWTARegressor constructor, ensuring that the initial coefficients are
chosen to correspond to stable AR processes. | bioslds/run_hyper_snippets.py | make_bio_wta_with_stable_initial | ttesileanu/bio-time-series | 0 | python | def make_bio_wta_with_stable_initial(*args, **kwargs) -> BioWTARegressor:
' Call the BioWTARegressor constructor, ensuring that the initial coefficients are\n chosen to correspond to stable AR processes.\n '
weights = [make_random_arma(kwargs['n_features'], 0, rng=kwargs['rng']).a for _ in range(kwargs['n_models'])]
return BioWTARegressor(*args, weights=weights, **kwargs) | def make_bio_wta_with_stable_initial(*args, **kwargs) -> BioWTARegressor:
' Call the BioWTARegressor constructor, ensuring that the initial coefficients are\n chosen to correspond to stable AR processes.\n '
weights = [make_random_arma(kwargs['n_features'], 0, rng=kwargs['rng']).a for _ in range(kwargs['n_models'])]
return BioWTARegressor(*args, weights=weights, **kwargs)<|docstring|>Call the BioWTARegressor constructor, ensuring that the initial coefficients are
chosen to correspond to stable AR processes.<|endoftext|> |
15744881e855beb7a67a404fd2ddf33199afec0703fea5c08df2c6c1f1030cb9 | def get_metadata(metapath):
' Returns the metadata as a pandas dataframe, translating strings\n to simpler boolean flags.\n '
meta = pd.read_csv(metapath, index_col='docid', dtype='object')
return meta | Returns the metadata as a pandas dataframe, translating strings
to simpler boolean flags. | code/implementpagemodel.py | get_metadata | tedunderwood/hathimetadata | 4 | python | def get_metadata(metapath):
' Returns the metadata as a pandas dataframe, translating strings\n to simpler boolean flags.\n '
meta = pd.read_csv(metapath, index_col='docid', dtype='object')
return meta | def get_metadata(metapath):
' Returns the metadata as a pandas dataframe, translating strings\n to simpler boolean flags.\n '
meta = pd.read_csv(metapath, index_col='docid', dtype='object')
return meta<|docstring|>Returns the metadata as a pandas dataframe, translating strings
to simpler boolean flags.<|endoftext|> |
bdd18c834c4e12351ba4695952eaef70a039c85d6a7f516bf8a39343ced13256 | def get_counts_4pages(path, docid):
' Gets a dictionary of wordcounts.\n\n Adjusted to handle page instances.\n Same logic used in trainapagemodel, but\n simplified for one volume.\n '
volume = parser.PagelistFromJson(path, docid)
pagecounts = volume.get_feature_list()
error = 'success'
counts = dict()
pageids = []
for (idx, page) in enumerate(pagecounts):
pageid = ((docid + '||') + str(idx))
pageids.append(pageid)
counts[pageid] = page
return (counts, pageids, error) | Gets a dictionary of wordcounts.
Adjusted to handle page instances.
Same logic used in trainapagemodel, but
simplified for one volume. | code/implementpagemodel.py | get_counts_4pages | tedunderwood/hathimetadata | 4 | python | def get_counts_4pages(path, docid):
' Gets a dictionary of wordcounts.\n\n Adjusted to handle page instances.\n Same logic used in trainapagemodel, but\n simplified for one volume.\n '
volume = parser.PagelistFromJson(path, docid)
pagecounts = volume.get_feature_list()
error = 'success'
counts = dict()
pageids = []
for (idx, page) in enumerate(pagecounts):
pageid = ((docid + '||') + str(idx))
pageids.append(pageid)
counts[pageid] = page
return (counts, pageids, error) | def get_counts_4pages(path, docid):
' Gets a dictionary of wordcounts.\n\n Adjusted to handle page instances.\n Same logic used in trainapagemodel, but\n simplified for one volume.\n '
volume = parser.PagelistFromJson(path, docid)
pagecounts = volume.get_feature_list()
error = 'success'
counts = dict()
pageids = []
for (idx, page) in enumerate(pagecounts):
pageid = ((docid + '||') + str(idx))
pageids.append(pageid)
counts[pageid] = page
return (counts, pageids, error)<|docstring|>Gets a dictionary of wordcounts.
Adjusted to handle page instances.
Same logic used in trainapagemodel, but
simplified for one volume.<|endoftext|> |
e01a676ab2c28274d2af93e759c07383de6ecebceafcc325618506a93d36275b | def predict_volume(model, allpageIDs, counts, docid):
' what it says on the label; returns a dictionary\n with page-level predictions for the volume; this will\n eventually be written out in json format\n '
vocabulary = model['vocabulary']
df = pages2frame(vocabulary, allpageIDs, counts)
pagepredictions = prediction_for_pages(model, df)
(firstpage, lastpage) = trimends(meansmooth(pagepredictions))
jsonobject = dict()
jsonobject['docid'] = docid
jsonobject['numpages'] = len(pagepredictions)
jsonobject['pagepredictions'] = pagepredictions
jsonobject['firstpage'] = firstpage
jsonobject['lastpage'] = lastpage
return jsonobject | what it says on the label; returns a dictionary
with page-level predictions for the volume; this will
eventually be written out in json format | code/implementpagemodel.py | predict_volume | tedunderwood/hathimetadata | 4 | python | def predict_volume(model, allpageIDs, counts, docid):
' what it says on the label; returns a dictionary\n with page-level predictions for the volume; this will\n eventually be written out in json format\n '
vocabulary = model['vocabulary']
df = pages2frame(vocabulary, allpageIDs, counts)
pagepredictions = prediction_for_pages(model, df)
(firstpage, lastpage) = trimends(meansmooth(pagepredictions))
jsonobject = dict()
jsonobject['docid'] = docid
jsonobject['numpages'] = len(pagepredictions)
jsonobject['pagepredictions'] = pagepredictions
jsonobject['firstpage'] = firstpage
jsonobject['lastpage'] = lastpage
return jsonobject | def predict_volume(model, allpageIDs, counts, docid):
' what it says on the label; returns a dictionary\n with page-level predictions for the volume; this will\n eventually be written out in json format\n '
vocabulary = model['vocabulary']
df = pages2frame(vocabulary, allpageIDs, counts)
pagepredictions = prediction_for_pages(model, df)
(firstpage, lastpage) = trimends(meansmooth(pagepredictions))
jsonobject = dict()
jsonobject['docid'] = docid
jsonobject['numpages'] = len(pagepredictions)
jsonobject['pagepredictions'] = pagepredictions
jsonobject['firstpage'] = firstpage
jsonobject['lastpage'] = lastpage
return jsonobject<|docstring|>what it says on the label; returns a dictionary
with page-level predictions for the volume; this will
eventually be written out in json format<|endoftext|> |
49132e789cdf3a47593e4023c30f2aadca44761784fa190a85768e9ee6dc8cfa | def pages2frame(vocabulary, allpageIDs, counts):
' Returns a pandas dataframe with feature counts for all the volumes\n to be used in this model. The dataframe is going to have an extra column\n that is used to group items for crossvalidation. E.g., if instances are pages,\n they might be grouped by volume ID for crossvalidating to avoid leaking info.\n If these are volumes, that might be the author ID.\n\n We expect positive and negative IDs to be the actual IDs of instances.\n\n Returns an unscaled data frame. Scaling is a separate step.\n '
df = dict()
vocabset = set(vocabulary)
for v in vocabulary:
df[v] = pd.Series(np.zeros(len(allpageIDs)), index=allpageIDs)
for pageid in allpageIDs:
for (feature, count) in counts[pageid].items():
if (feature in vocabset):
df[feature].loc[pageid] = count
df = pd.DataFrame(df, index=allpageIDs)
df = df[vocabulary]
return df | Returns a pandas dataframe with feature counts for all the volumes
to be used in this model. The dataframe is going to have an extra column
that is used to group items for crossvalidation. E.g., if instances are pages,
they might be grouped by volume ID for crossvalidating to avoid leaking info.
If these are volumes, that might be the author ID.
We expect positive and negative IDs to be the actual IDs of instances.
Returns an unscaled data frame. Scaling is a separate step. | code/implementpagemodel.py | pages2frame | tedunderwood/hathimetadata | 4 | python | def pages2frame(vocabulary, allpageIDs, counts):
' Returns a pandas dataframe with feature counts for all the volumes\n to be used in this model. The dataframe is going to have an extra column\n that is used to group items for crossvalidation. E.g., if instances are pages,\n they might be grouped by volume ID for crossvalidating to avoid leaking info.\n If these are volumes, that might be the author ID.\n\n We expect positive and negative IDs to be the actual IDs of instances.\n\n Returns an unscaled data frame. Scaling is a separate step.\n '
df = dict()
vocabset = set(vocabulary)
for v in vocabulary:
df[v] = pd.Series(np.zeros(len(allpageIDs)), index=allpageIDs)
for pageid in allpageIDs:
for (feature, count) in counts[pageid].items():
if (feature in vocabset):
df[feature].loc[pageid] = count
df = pd.DataFrame(df, index=allpageIDs)
df = df[vocabulary]
return df | def pages2frame(vocabulary, allpageIDs, counts):
' Returns a pandas dataframe with feature counts for all the volumes\n to be used in this model. The dataframe is going to have an extra column\n that is used to group items for crossvalidation. E.g., if instances are pages,\n they might be grouped by volume ID for crossvalidating to avoid leaking info.\n If these are volumes, that might be the author ID.\n\n We expect positive and negative IDs to be the actual IDs of instances.\n\n Returns an unscaled data frame. Scaling is a separate step.\n '
df = dict()
vocabset = set(vocabulary)
for v in vocabulary:
df[v] = pd.Series(np.zeros(len(allpageIDs)), index=allpageIDs)
for pageid in allpageIDs:
for (feature, count) in counts[pageid].items():
if (feature in vocabset):
df[feature].loc[pageid] = count
df = pd.DataFrame(df, index=allpageIDs)
df = df[vocabulary]
return df<|docstring|>Returns a pandas dataframe with feature counts for all the volumes
to be used in this model. The dataframe is going to have an extra column
that is used to group items for crossvalidation. E.g., if instances are pages,
they might be grouped by volume ID for crossvalidating to avoid leaking info.
If these are volumes, that might be the author ID.
We expect positive and negative IDs to be the actual IDs of instances.
Returns an unscaled data frame. Scaling is a separate step.<|endoftext|> |
8663c16488686101b3f527a013f957462dc6f3aa0fa57266afe0c74391f004c3 | def trimends(inputseries):
'\n Returns the first page and last page considered\n to belong to the specified genre. Note that this\n is normal world "first" and "last," not the fracked-up\n programming-world definition of ranges where "last"\n is the place you stop, aka last+1.\n '
binsequence = list()
for element in inputseries:
if (float(element) > 0.5):
binsequence.append(1)
else:
binsequence.append(0)
assert (len(binsequence) == len(inputseries))
if (len(binsequence) < 5):
return (0, (len(binsequence) - 1))
newseq = ([1] * len(binsequence))
newseq[0] = binsequence[0]
newseq[(- 1)] = binsequence[(- 1)]
firstpage = 0
lastpage = (len(binsequence) - 1)
if (binsequence[0] != 1):
for i in range(1, (len(binsequence) - 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
firstpage = i
break
else:
firstpage = 0
if (binsequence[(len(binsequence) - 1)] != 1):
for i in range((len(binsequence) - 2), (- 1), (- 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
lastpage = i
break
else:
lastpage = (len(binsequence) - 1)
return (firstpage, lastpage) | Returns the first page and last page considered
to belong to the specified genre. Note that this
is normal world "first" and "last," not the fracked-up
programming-world definition of ranges where "last"
is the place you stop, aka last+1. | code/implementpagemodel.py | trimends | tedunderwood/hathimetadata | 4 | python | def trimends(inputseries):
'\n Returns the first page and last page considered\n to belong to the specified genre. Note that this\n is normal world "first" and "last," not the fracked-up\n programming-world definition of ranges where "last"\n is the place you stop, aka last+1.\n '
binsequence = list()
for element in inputseries:
if (float(element) > 0.5):
binsequence.append(1)
else:
binsequence.append(0)
assert (len(binsequence) == len(inputseries))
if (len(binsequence) < 5):
return (0, (len(binsequence) - 1))
newseq = ([1] * len(binsequence))
newseq[0] = binsequence[0]
newseq[(- 1)] = binsequence[(- 1)]
firstpage = 0
lastpage = (len(binsequence) - 1)
if (binsequence[0] != 1):
for i in range(1, (len(binsequence) - 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
firstpage = i
break
else:
firstpage = 0
if (binsequence[(len(binsequence) - 1)] != 1):
for i in range((len(binsequence) - 2), (- 1), (- 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
lastpage = i
break
else:
lastpage = (len(binsequence) - 1)
return (firstpage, lastpage) | def trimends(inputseries):
'\n Returns the first page and last page considered\n to belong to the specified genre. Note that this\n is normal world "first" and "last," not the fracked-up\n programming-world definition of ranges where "last"\n is the place you stop, aka last+1.\n '
binsequence = list()
for element in inputseries:
if (float(element) > 0.5):
binsequence.append(1)
else:
binsequence.append(0)
assert (len(binsequence) == len(inputseries))
if (len(binsequence) < 5):
return (0, (len(binsequence) - 1))
newseq = ([1] * len(binsequence))
newseq[0] = binsequence[0]
newseq[(- 1)] = binsequence[(- 1)]
firstpage = 0
lastpage = (len(binsequence) - 1)
if (binsequence[0] != 1):
for i in range(1, (len(binsequence) - 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
firstpage = i
break
else:
firstpage = 0
if (binsequence[(len(binsequence) - 1)] != 1):
for i in range((len(binsequence) - 2), (- 1), (- 1)):
total = sum(binsequence[(i - 1):(i + 2)])
if (total < 2):
newseq[i] = 0
else:
newseq[i] = 1
lastpage = i
break
else:
lastpage = (len(binsequence) - 1)
return (firstpage, lastpage)<|docstring|>Returns the first page and last page considered
to belong to the specified genre. Note that this
is normal world "first" and "last," not the fracked-up
programming-world definition of ranges where "last"
is the place you stop, aka last+1.<|endoftext|> |
246316bb078f9c4fef6b88b07889104e98136890f6c8ea5c0acbda934062b63f | def main(sourcedirs, metapath, modeldir, outpath, pairtree=False):
'\n This function can be called from outside the module; it accepts\n path information and then iterates through all the files it\n finds in the metadata at "metapath."\n\n If the pairtree flag is True, we assume sourcedir is the root\n of a pairtree structure. Otherwise we assume it\'s a flat list.\n '
models = []
modelpaths = glob.glob((modeldir + '*.p'))
assert (len(modelpaths) == 1)
model = loadamodel(modelpaths[0])
metadata = get_metadata(metapath)
notfound = dict()
c = 0
path = ''
for docid in metadata.index:
print(c)
c += 1
if pairtree:
found = False
for sourcedir in sourcedirs:
path = get_pairtree(sourcedir, docid)
if os.path.isfile(path):
found = True
chosenpath = path
if (not found):
print(path)
print('file not found')
error = 'file not found'
wordcount = 0
else:
(pagecounts, pageids, error) = get_counts_4pages(chosenpath, docid)
else:
path = os.path.join(sourcedir, (utils.clean_pairtree(docid) + '.csv'))
(pagecounts, pageids, error) = pagecounts4file(path)
if (error == 'success'):
volumejson = predict_volume(model, pageids, pagecounts, docid)
volumestring = json.dumps(volumejson)
with open(outpath, mode='a', encoding='utf-8') as f:
f.write((volumestring + '\n'))
print(docid)
else:
notfound[docid] = error
print(docid, error)
with open('fictionpagesnotfound.txt', mode='a', encoding='utf-8') as f:
for (vol, reason) in notfound.items():
f.write((((vol + '\t') + reason) + '\n')) | This function can be called from outside the module; it accepts
path information and then iterates through all the files it
finds in the metadata at "metapath."
If the pairtree flag is True, we assume sourcedir is the root
of a pairtree structure. Otherwise we assume it's a flat list. | code/implementpagemodel.py | main | tedunderwood/hathimetadata | 4 | python | def main(sourcedirs, metapath, modeldir, outpath, pairtree=False):
'\n This function can be called from outside the module; it accepts\n path information and then iterates through all the files it\n finds in the metadata at "metapath."\n\n If the pairtree flag is True, we assume sourcedir is the root\n of a pairtree structure. Otherwise we assume it\'s a flat list.\n '
models = []
modelpaths = glob.glob((modeldir + '*.p'))
assert (len(modelpaths) == 1)
model = loadamodel(modelpaths[0])
metadata = get_metadata(metapath)
notfound = dict()
c = 0
path =
for docid in metadata.index:
print(c)
c += 1
if pairtree:
found = False
for sourcedir in sourcedirs:
path = get_pairtree(sourcedir, docid)
if os.path.isfile(path):
found = True
chosenpath = path
if (not found):
print(path)
print('file not found')
error = 'file not found'
wordcount = 0
else:
(pagecounts, pageids, error) = get_counts_4pages(chosenpath, docid)
else:
path = os.path.join(sourcedir, (utils.clean_pairtree(docid) + '.csv'))
(pagecounts, pageids, error) = pagecounts4file(path)
if (error == 'success'):
volumejson = predict_volume(model, pageids, pagecounts, docid)
volumestring = json.dumps(volumejson)
with open(outpath, mode='a', encoding='utf-8') as f:
f.write((volumestring + '\n'))
print(docid)
else:
notfound[docid] = error
print(docid, error)
with open('fictionpagesnotfound.txt', mode='a', encoding='utf-8') as f:
for (vol, reason) in notfound.items():
f.write((((vol + '\t') + reason) + '\n')) | def main(sourcedirs, metapath, modeldir, outpath, pairtree=False):
'\n This function can be called from outside the module; it accepts\n path information and then iterates through all the files it\n finds in the metadata at "metapath."\n\n If the pairtree flag is True, we assume sourcedir is the root\n of a pairtree structure. Otherwise we assume it\'s a flat list.\n '
models = []
modelpaths = glob.glob((modeldir + '*.p'))
assert (len(modelpaths) == 1)
model = loadamodel(modelpaths[0])
metadata = get_metadata(metapath)
notfound = dict()
c = 0
path =
for docid in metadata.index:
print(c)
c += 1
if pairtree:
found = False
for sourcedir in sourcedirs:
path = get_pairtree(sourcedir, docid)
if os.path.isfile(path):
found = True
chosenpath = path
if (not found):
print(path)
print('file not found')
error = 'file not found'
wordcount = 0
else:
(pagecounts, pageids, error) = get_counts_4pages(chosenpath, docid)
else:
path = os.path.join(sourcedir, (utils.clean_pairtree(docid) + '.csv'))
(pagecounts, pageids, error) = pagecounts4file(path)
if (error == 'success'):
volumejson = predict_volume(model, pageids, pagecounts, docid)
volumestring = json.dumps(volumejson)
with open(outpath, mode='a', encoding='utf-8') as f:
f.write((volumestring + '\n'))
print(docid)
else:
notfound[docid] = error
print(docid, error)
with open('fictionpagesnotfound.txt', mode='a', encoding='utf-8') as f:
for (vol, reason) in notfound.items():
f.write((((vol + '\t') + reason) + '\n'))<|docstring|>This function can be called from outside the module; it accepts
path information and then iterates through all the files it
finds in the metadata at "metapath."
If the pairtree flag is True, we assume sourcedir is the root
of a pairtree structure. Otherwise we assume it's a flat list.<|endoftext|> |
fdcb7e24c5578079743450e71033f72fca24b0ecf665a8cc717f7e80bdf4b7ba | def measure_velocities_from_timetraces(dataset_name, save, noshow=False):
'\n maximise Sum_i(Envelope(TimeTrace[tof_backwall_i]))\n '
conf = arim.io.load_conf(dataset_name)
root_dir = conf['root_dir']
result_dir = conf['result_dir']
frame = common.load_frame(conf, apply_filter=True, expand=True, warn_if_fallback_vel=False)
frame.scanlines = np.abs(frame.scanlines)
base_l_vel = ((conf['block_material']['longitudinal_vel'] // 10) * 10)
l_vel_range_1 = np.arange((base_l_vel - 100), (base_l_vel + 100.1), 10.0)
intensities_1 = _measure_l_vel(conf, frame, l_vel_range_1)
l_vel_1_idx = intensities_1.values.argmax()
if ((l_vel_1_idx == 0) or (l_vel_1_idx == (len(l_vel_range_1) - 1))):
raise IndefiniteVelocityError
l_vel_range_2 = np.arange((l_vel_range_1[(l_vel_1_idx - 1)] + 1), l_vel_range_1[(l_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_l_vel(conf, frame, l_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
l_vel_opt = intensities.idxmax()
logger.info(f'Optimal L velocitiy: {l_vel_opt} m/s')
conf['block_material']['longitudinal_vel'] = l_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('L velocitiy (m/s)')
plt.ylabel('Backwall LL intensity')
plt.title(f'Optimum: {l_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_L'))
base_t_vel = ((conf['block_material']['transverse_vel'] // 10) * 10)
t_vel_range_1 = np.arange((base_t_vel - 100), (base_t_vel + 100.1), 10.0)
intensities_1 = _measure_t_vel(conf, frame, t_vel_range_1)
t_vel_1_idx = intensities_1.values.argmax()
if ((t_vel_1_idx == 0) or (t_vel_1_idx == (len(t_vel_range_1) - 1))):
raise IndefiniteVelocityError
t_vel_range_2 = np.arange((t_vel_range_1[(t_vel_1_idx - 1)] + 1), t_vel_range_1[(t_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_t_vel(conf, frame, t_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
t_vel_opt = intensities.idxmax()
logger.info(f'Optimal T velocitiy: {t_vel_opt} m/s')
conf['block_material']['transverse_vel'] = t_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('T velocitiy (m/s)')
plt.ylabel('Backwall LT intensity')
plt.title(f'Optimum: {t_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_T'))
if save:
block_conf = dict(longitudinal_vel=float(l_vel_opt), transverse_vel=float(t_vel_opt), metadata=dict(source='Velocities measured from TFM', is_fallback=False))
block_conf2 = dict(block_material=block_conf)
with (root_dir / 'conf.d/30_block_velocities.yaml').open('w') as f:
f.write('# generated by measure_velocities_from_timetraces.py\n')
yaml.dump(block_conf2, f, default_flow_style=False)
if noshow:
plt.close('all')
else:
plt.show()
return (l_vel_opt, t_vel_opt) | maximise Sum_i(Envelope(TimeTrace[tof_backwall_i])) | arimtoolkit/measure_velocities_from_timetraces.py | measure_velocities_from_timetraces | nbud/arimtoolkit | 0 | python | def measure_velocities_from_timetraces(dataset_name, save, noshow=False):
'\n \n '
conf = arim.io.load_conf(dataset_name)
root_dir = conf['root_dir']
result_dir = conf['result_dir']
frame = common.load_frame(conf, apply_filter=True, expand=True, warn_if_fallback_vel=False)
frame.scanlines = np.abs(frame.scanlines)
base_l_vel = ((conf['block_material']['longitudinal_vel'] // 10) * 10)
l_vel_range_1 = np.arange((base_l_vel - 100), (base_l_vel + 100.1), 10.0)
intensities_1 = _measure_l_vel(conf, frame, l_vel_range_1)
l_vel_1_idx = intensities_1.values.argmax()
if ((l_vel_1_idx == 0) or (l_vel_1_idx == (len(l_vel_range_1) - 1))):
raise IndefiniteVelocityError
l_vel_range_2 = np.arange((l_vel_range_1[(l_vel_1_idx - 1)] + 1), l_vel_range_1[(l_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_l_vel(conf, frame, l_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
l_vel_opt = intensities.idxmax()
logger.info(f'Optimal L velocitiy: {l_vel_opt} m/s')
conf['block_material']['longitudinal_vel'] = l_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('L velocitiy (m/s)')
plt.ylabel('Backwall LL intensity')
plt.title(f'Optimum: {l_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_L'))
base_t_vel = ((conf['block_material']['transverse_vel'] // 10) * 10)
t_vel_range_1 = np.arange((base_t_vel - 100), (base_t_vel + 100.1), 10.0)
intensities_1 = _measure_t_vel(conf, frame, t_vel_range_1)
t_vel_1_idx = intensities_1.values.argmax()
if ((t_vel_1_idx == 0) or (t_vel_1_idx == (len(t_vel_range_1) - 1))):
raise IndefiniteVelocityError
t_vel_range_2 = np.arange((t_vel_range_1[(t_vel_1_idx - 1)] + 1), t_vel_range_1[(t_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_t_vel(conf, frame, t_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
t_vel_opt = intensities.idxmax()
logger.info(f'Optimal T velocitiy: {t_vel_opt} m/s')
conf['block_material']['transverse_vel'] = t_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('T velocitiy (m/s)')
plt.ylabel('Backwall LT intensity')
plt.title(f'Optimum: {t_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_T'))
if save:
block_conf = dict(longitudinal_vel=float(l_vel_opt), transverse_vel=float(t_vel_opt), metadata=dict(source='Velocities measured from TFM', is_fallback=False))
block_conf2 = dict(block_material=block_conf)
with (root_dir / 'conf.d/30_block_velocities.yaml').open('w') as f:
f.write('# generated by measure_velocities_from_timetraces.py\n')
yaml.dump(block_conf2, f, default_flow_style=False)
if noshow:
plt.close('all')
else:
plt.show()
return (l_vel_opt, t_vel_opt) | def measure_velocities_from_timetraces(dataset_name, save, noshow=False):
'\n \n '
conf = arim.io.load_conf(dataset_name)
root_dir = conf['root_dir']
result_dir = conf['result_dir']
frame = common.load_frame(conf, apply_filter=True, expand=True, warn_if_fallback_vel=False)
frame.scanlines = np.abs(frame.scanlines)
base_l_vel = ((conf['block_material']['longitudinal_vel'] // 10) * 10)
l_vel_range_1 = np.arange((base_l_vel - 100), (base_l_vel + 100.1), 10.0)
intensities_1 = _measure_l_vel(conf, frame, l_vel_range_1)
l_vel_1_idx = intensities_1.values.argmax()
if ((l_vel_1_idx == 0) or (l_vel_1_idx == (len(l_vel_range_1) - 1))):
raise IndefiniteVelocityError
l_vel_range_2 = np.arange((l_vel_range_1[(l_vel_1_idx - 1)] + 1), l_vel_range_1[(l_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_l_vel(conf, frame, l_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
l_vel_opt = intensities.idxmax()
logger.info(f'Optimal L velocitiy: {l_vel_opt} m/s')
conf['block_material']['longitudinal_vel'] = l_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('L velocitiy (m/s)')
plt.ylabel('Backwall LL intensity')
plt.title(f'Optimum: {l_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_L'))
base_t_vel = ((conf['block_material']['transverse_vel'] // 10) * 10)
t_vel_range_1 = np.arange((base_t_vel - 100), (base_t_vel + 100.1), 10.0)
intensities_1 = _measure_t_vel(conf, frame, t_vel_range_1)
t_vel_1_idx = intensities_1.values.argmax()
if ((t_vel_1_idx == 0) or (t_vel_1_idx == (len(t_vel_range_1) - 1))):
raise IndefiniteVelocityError
t_vel_range_2 = np.arange((t_vel_range_1[(t_vel_1_idx - 1)] + 1), t_vel_range_1[(t_vel_1_idx + 1)], 1.0)
intensities_2 = _measure_t_vel(conf, frame, t_vel_range_2)
intensities = pd.concat([intensities_1, intensities_2]).sort_index()
t_vel_opt = intensities.idxmax()
logger.info(f'Optimal T velocitiy: {t_vel_opt} m/s')
conf['block_material']['transverse_vel'] = t_vel_opt
plt.figure()
plt.plot(intensities.index, intensities, '.-')
plt.xlabel('T velocitiy (m/s)')
plt.ylabel('Backwall LT intensity')
plt.title(f'Optimum: {t_vel_opt}')
if save:
plt.savefig((result_dir / 'velocity_T'))
if save:
block_conf = dict(longitudinal_vel=float(l_vel_opt), transverse_vel=float(t_vel_opt), metadata=dict(source='Velocities measured from TFM', is_fallback=False))
block_conf2 = dict(block_material=block_conf)
with (root_dir / 'conf.d/30_block_velocities.yaml').open('w') as f:
f.write('# generated by measure_velocities_from_timetraces.py\n')
yaml.dump(block_conf2, f, default_flow_style=False)
if noshow:
plt.close('all')
else:
plt.show()
return (l_vel_opt, t_vel_opt)<|docstring|>maximise Sum_i(Envelope(TimeTrace[tof_backwall_i]))<|endoftext|> |
23282078951d659bf1c1e93b5f46b9eb51ad76ae1b614620dd5c256a4dce74b9 | def add_node_to_graph(self, graph, nodename, nodelabel=None, shape='box', color=None, url=None, tooltip=None):
'\n Create a node item for this factory, adds it to the graph.\n\n Node name can vary from label but must always be same for the same node label\n '
if ((nodename is None) or (nodename == '')):
raise ValueError('Empty Node name')
if (nodelabel is None):
nodelabel = nodename
node = pydot.Node(self.escape_name(nodename))
node.set_shape(shape)
node.set_label(self.escape_label(nodelabel))
if (tooltip is not None):
node.set_tooltip(tooltip)
elif (url is not None):
node.set_tooltip(url)
if (url is not None):
node.set_URL(self.escape_name(url))
if (color is not None):
node.set_color(color)
graph.add_node(node) | Create a node item for this factory, adds it to the graph.
Node name can vary from label but must always be same for the same node label | melodic/src/qt_gui_core/qt_dotgraph/src/qt_dotgraph/pydotfactory.py | add_node_to_graph | disorn-inc/ROS-melodic-python3-Opencv-4.1.1-CUDA | 2 | python | def add_node_to_graph(self, graph, nodename, nodelabel=None, shape='box', color=None, url=None, tooltip=None):
'\n Create a node item for this factory, adds it to the graph.\n\n Node name can vary from label but must always be same for the same node label\n '
if ((nodename is None) or (nodename == )):
raise ValueError('Empty Node name')
if (nodelabel is None):
nodelabel = nodename
node = pydot.Node(self.escape_name(nodename))
node.set_shape(shape)
node.set_label(self.escape_label(nodelabel))
if (tooltip is not None):
node.set_tooltip(tooltip)
elif (url is not None):
node.set_tooltip(url)
if (url is not None):
node.set_URL(self.escape_name(url))
if (color is not None):
node.set_color(color)
graph.add_node(node) | def add_node_to_graph(self, graph, nodename, nodelabel=None, shape='box', color=None, url=None, tooltip=None):
'\n Create a node item for this factory, adds it to the graph.\n\n Node name can vary from label but must always be same for the same node label\n '
if ((nodename is None) or (nodename == )):
raise ValueError('Empty Node name')
if (nodelabel is None):
nodelabel = nodename
node = pydot.Node(self.escape_name(nodename))
node.set_shape(shape)
node.set_label(self.escape_label(nodelabel))
if (tooltip is not None):
node.set_tooltip(tooltip)
elif (url is not None):
node.set_tooltip(url)
if (url is not None):
node.set_URL(self.escape_name(url))
if (color is not None):
node.set_color(color)
graph.add_node(node)<|docstring|>Create a node item for this factory, adds it to the graph.
Node name can vary from label but must always be same for the same node label<|endoftext|> |
24290a22af54be60e086c2db09a3bd90a25f2e7c5da45500fa43ab4cf664a3c7 | def add_subgraph_to_graph(self, graph, subgraphname, rank='same', simplify=True, rankdir='TB', ranksep=0.2, compound=True, color=None, shape='box', style='bold', subgraphlabel=None):
'\n Create a cluster subgraph item for this factory, adds it to the graph.\n\n cluster name can vary from label but must always be same for the same node label.\n Most layouters require cluster names to start with cluster.\n '
if ((subgraphname is None) or (subgraphname == '')):
raise ValueError('Empty subgraph name')
g = pydot.Cluster(self.escape_name(subgraphname), rank=rank, rankdir=rankdir, simplify=simplify)
if ('set_style' in g.__dict__):
g.set_style(style)
if ('set_shape' in g.__dict__):
g.set_shape(shape)
if (LooseVersion(pydot.__version__) > LooseVersion('1.0.10')):
g.set_compound(compound)
g.set_ranksep(ranksep)
subgraphlabel = (subgraphname if (subgraphlabel is None) else subgraphlabel)
subgraphlabel = self.escape_label(subgraphlabel)
if subgraphlabel:
g.set_label(subgraphlabel)
if ('set_color' in g.__dict__):
if (color is not None):
g.set_color(color)
graph.add_subgraph(g)
return g | Create a cluster subgraph item for this factory, adds it to the graph.
cluster name can vary from label but must always be same for the same node label.
Most layouters require cluster names to start with cluster. | melodic/src/qt_gui_core/qt_dotgraph/src/qt_dotgraph/pydotfactory.py | add_subgraph_to_graph | disorn-inc/ROS-melodic-python3-Opencv-4.1.1-CUDA | 2 | python | def add_subgraph_to_graph(self, graph, subgraphname, rank='same', simplify=True, rankdir='TB', ranksep=0.2, compound=True, color=None, shape='box', style='bold', subgraphlabel=None):
'\n Create a cluster subgraph item for this factory, adds it to the graph.\n\n cluster name can vary from label but must always be same for the same node label.\n Most layouters require cluster names to start with cluster.\n '
if ((subgraphname is None) or (subgraphname == )):
raise ValueError('Empty subgraph name')
g = pydot.Cluster(self.escape_name(subgraphname), rank=rank, rankdir=rankdir, simplify=simplify)
if ('set_style' in g.__dict__):
g.set_style(style)
if ('set_shape' in g.__dict__):
g.set_shape(shape)
if (LooseVersion(pydot.__version__) > LooseVersion('1.0.10')):
g.set_compound(compound)
g.set_ranksep(ranksep)
subgraphlabel = (subgraphname if (subgraphlabel is None) else subgraphlabel)
subgraphlabel = self.escape_label(subgraphlabel)
if subgraphlabel:
g.set_label(subgraphlabel)
if ('set_color' in g.__dict__):
if (color is not None):
g.set_color(color)
graph.add_subgraph(g)
return g | def add_subgraph_to_graph(self, graph, subgraphname, rank='same', simplify=True, rankdir='TB', ranksep=0.2, compound=True, color=None, shape='box', style='bold', subgraphlabel=None):
'\n Create a cluster subgraph item for this factory, adds it to the graph.\n\n cluster name can vary from label but must always be same for the same node label.\n Most layouters require cluster names to start with cluster.\n '
if ((subgraphname is None) or (subgraphname == )):
raise ValueError('Empty subgraph name')
g = pydot.Cluster(self.escape_name(subgraphname), rank=rank, rankdir=rankdir, simplify=simplify)
if ('set_style' in g.__dict__):
g.set_style(style)
if ('set_shape' in g.__dict__):
g.set_shape(shape)
if (LooseVersion(pydot.__version__) > LooseVersion('1.0.10')):
g.set_compound(compound)
g.set_ranksep(ranksep)
subgraphlabel = (subgraphname if (subgraphlabel is None) else subgraphlabel)
subgraphlabel = self.escape_label(subgraphlabel)
if subgraphlabel:
g.set_label(subgraphlabel)
if ('set_color' in g.__dict__):
if (color is not None):
g.set_color(color)
graph.add_subgraph(g)
return g<|docstring|>Create a cluster subgraph item for this factory, adds it to the graph.
cluster name can vary from label but must always be same for the same node label.
Most layouters require cluster names to start with cluster.<|endoftext|> |
bc685d0b9e508e45698278c64b81162b2d81d725db15674281e0f98a6b970ed3 | def alter_field(self, model, old_field, new_field, strict=False):
'\n Vertica do not allow alter column type if it is used in constraints such as UNIQUE.\n In order to all work, the constraint is dropped, column altered, constraint recreated.\n '
curr = self.connection.cursor()
result = curr.execute(("\n select cc.constraint_name\n from constraint_columns cc\n where 1=1\n and cc.table_name = '%s'\n and cc.constraint_type = 'u'\n and cc.column_name = '%s'" % (model._meta.db_table, new_field.column))).fetchone()
if result:
constraint_name = result[0]
drop_statement = self._delete_constraint_sql(self.sql_delete_unique, model, constraint_name)
self.execute(drop_statement)
super().alter_field(model, old_field, new_field, strict)
create_statement = self._create_unique_sql(model, [new_field.column], constraint_name)
self.execute(create_statement)
else:
super().alter_field(model, old_field, new_field, strict) | Vertica do not allow alter column type if it is used in constraints such as UNIQUE.
In order to all work, the constraint is dropped, column altered, constraint recreated. | vertica/schema.py | alter_field | emushell/django_vertica_backend | 0 | python | def alter_field(self, model, old_field, new_field, strict=False):
'\n Vertica do not allow alter column type if it is used in constraints such as UNIQUE.\n In order to all work, the constraint is dropped, column altered, constraint recreated.\n '
curr = self.connection.cursor()
result = curr.execute(("\n select cc.constraint_name\n from constraint_columns cc\n where 1=1\n and cc.table_name = '%s'\n and cc.constraint_type = 'u'\n and cc.column_name = '%s'" % (model._meta.db_table, new_field.column))).fetchone()
if result:
constraint_name = result[0]
drop_statement = self._delete_constraint_sql(self.sql_delete_unique, model, constraint_name)
self.execute(drop_statement)
super().alter_field(model, old_field, new_field, strict)
create_statement = self._create_unique_sql(model, [new_field.column], constraint_name)
self.execute(create_statement)
else:
super().alter_field(model, old_field, new_field, strict) | def alter_field(self, model, old_field, new_field, strict=False):
'\n Vertica do not allow alter column type if it is used in constraints such as UNIQUE.\n In order to all work, the constraint is dropped, column altered, constraint recreated.\n '
curr = self.connection.cursor()
result = curr.execute(("\n select cc.constraint_name\n from constraint_columns cc\n where 1=1\n and cc.table_name = '%s'\n and cc.constraint_type = 'u'\n and cc.column_name = '%s'" % (model._meta.db_table, new_field.column))).fetchone()
if result:
constraint_name = result[0]
drop_statement = self._delete_constraint_sql(self.sql_delete_unique, model, constraint_name)
self.execute(drop_statement)
super().alter_field(model, old_field, new_field, strict)
create_statement = self._create_unique_sql(model, [new_field.column], constraint_name)
self.execute(create_statement)
else:
super().alter_field(model, old_field, new_field, strict)<|docstring|>Vertica do not allow alter column type if it is used in constraints such as UNIQUE.
In order to all work, the constraint is dropped, column altered, constraint recreated.<|endoftext|> |
f62340220d3dacd7a22c7d528794233fe7f6890e839d7022352545c54d5e7859 | def column_sql(self, model, field, include_default=False):
'\n Take a field and return its column definition.\n The field must already have had set_attributes_from_name() called.\n '
db_params = field.db_parameters(connection=self.connection)
sql = db_params['type']
params = []
if (sql is None):
return (None, None)
null = field.null
include_default = (include_default and (not self.skip_default(field)))
if include_default:
default_value = self.effective_default(field)
if (default_value is not None):
if self.connection.features.requires_literal_defaults:
sql += (' DEFAULT %s' % self.prepare_default(default_value))
else:
sql += ' DEFAULT %s'
params += [default_value]
if (field.empty_strings_allowed and (not field.primary_key) and self.connection.features.interprets_empty_strings_as_nulls):
null = True
if (null and (not self.connection.features.implied_column_null)):
sql += self.custom_sql_column_null
elif (not null):
sql += self.custom_sql_column_not_null
if field.primary_key:
sql += self.custom_sql_column_pk
elif field.unique:
sql += self.custom_sql_column_unique
return (sql, params) | Take a field and return its column definition.
The field must already have had set_attributes_from_name() called. | vertica/schema.py | column_sql | emushell/django_vertica_backend | 0 | python | def column_sql(self, model, field, include_default=False):
'\n Take a field and return its column definition.\n The field must already have had set_attributes_from_name() called.\n '
db_params = field.db_parameters(connection=self.connection)
sql = db_params['type']
params = []
if (sql is None):
return (None, None)
null = field.null
include_default = (include_default and (not self.skip_default(field)))
if include_default:
default_value = self.effective_default(field)
if (default_value is not None):
if self.connection.features.requires_literal_defaults:
sql += (' DEFAULT %s' % self.prepare_default(default_value))
else:
sql += ' DEFAULT %s'
params += [default_value]
if (field.empty_strings_allowed and (not field.primary_key) and self.connection.features.interprets_empty_strings_as_nulls):
null = True
if (null and (not self.connection.features.implied_column_null)):
sql += self.custom_sql_column_null
elif (not null):
sql += self.custom_sql_column_not_null
if field.primary_key:
sql += self.custom_sql_column_pk
elif field.unique:
sql += self.custom_sql_column_unique
return (sql, params) | def column_sql(self, model, field, include_default=False):
'\n Take a field and return its column definition.\n The field must already have had set_attributes_from_name() called.\n '
db_params = field.db_parameters(connection=self.connection)
sql = db_params['type']
params = []
if (sql is None):
return (None, None)
null = field.null
include_default = (include_default and (not self.skip_default(field)))
if include_default:
default_value = self.effective_default(field)
if (default_value is not None):
if self.connection.features.requires_literal_defaults:
sql += (' DEFAULT %s' % self.prepare_default(default_value))
else:
sql += ' DEFAULT %s'
params += [default_value]
if (field.empty_strings_allowed and (not field.primary_key) and self.connection.features.interprets_empty_strings_as_nulls):
null = True
if (null and (not self.connection.features.implied_column_null)):
sql += self.custom_sql_column_null
elif (not null):
sql += self.custom_sql_column_not_null
if field.primary_key:
sql += self.custom_sql_column_pk
elif field.unique:
sql += self.custom_sql_column_unique
return (sql, params)<|docstring|>Take a field and return its column definition.
The field must already have had set_attributes_from_name() called.<|endoftext|> |
3eef918e18994ed3e3971a1018e6404e578b7722492ec0943702c397e7352f0f | def _model_indexes_sql(self, model):
"\n Vertica dose not support INDEX's.\n Skip all statements which are related to index creation or manipulation.\n "
return [] | Vertica dose not support INDEX's.
Skip all statements which are related to index creation or manipulation. | vertica/schema.py | _model_indexes_sql | emushell/django_vertica_backend | 0 | python | def _model_indexes_sql(self, model):
"\n Vertica dose not support INDEX's.\n Skip all statements which are related to index creation or manipulation.\n "
return [] | def _model_indexes_sql(self, model):
"\n Vertica dose not support INDEX's.\n Skip all statements which are related to index creation or manipulation.\n "
return []<|docstring|>Vertica dose not support INDEX's.
Skip all statements which are related to index creation or manipulation.<|endoftext|> |
3e38ac3bc9318b86b285ec1c0161b8916ac801892c55a6fc36a883f91b2a1c9c | def setUp(self):
'\n Setup method that is called at the beginning of each test.\n '
(self.documents, self.users) = (18, 10)
(documents_cnt, users_cnt) = (self.documents, self.users)
self.n_iterations = 15
self.k_folds = 3
self.hyperparameters = {'n_factors': 5, '_lambda': 0.01}
self.options = {'n_iterations': self.n_iterations, 'k_folds': self.k_folds}
self.initializer = ModelInitializer(self.hyperparameters.copy(), self.n_iterations)
self.n_recommendations = 1
def mock_get_ratings_matrix(self=None):
return [[int((not bool(((article + user) % 3)))) for article in range(documents_cnt)] for user in range(users_cnt)]
self.ratings_matrix = numpy.array(mock_get_ratings_matrix())
setattr(DataParser, 'get_ratings_matrix', mock_get_ratings_matrix)
self.evaluator = Evaluator(self.ratings_matrix)
self.cf = CollaborativeFiltering(self.initializer, self.evaluator, self.hyperparameters, self.options, load_matrices=True)
self.cf.train()
self.cf.evaluator.k_folds = self.k_folds
self.test_data = self.cf.test_data
self.predictions = self.cf.get_predictions()
self.rounded_predictions = self.cf.rounded_predictions() | Setup method that is called at the beginning of each test. | tests/evaluator_tests.py | setUp | mostafa-mahmoud/HyPRec | 5 | python | def setUp(self):
'\n \n '
(self.documents, self.users) = (18, 10)
(documents_cnt, users_cnt) = (self.documents, self.users)
self.n_iterations = 15
self.k_folds = 3
self.hyperparameters = {'n_factors': 5, '_lambda': 0.01}
self.options = {'n_iterations': self.n_iterations, 'k_folds': self.k_folds}
self.initializer = ModelInitializer(self.hyperparameters.copy(), self.n_iterations)
self.n_recommendations = 1
def mock_get_ratings_matrix(self=None):
return [[int((not bool(((article + user) % 3)))) for article in range(documents_cnt)] for user in range(users_cnt)]
self.ratings_matrix = numpy.array(mock_get_ratings_matrix())
setattr(DataParser, 'get_ratings_matrix', mock_get_ratings_matrix)
self.evaluator = Evaluator(self.ratings_matrix)
self.cf = CollaborativeFiltering(self.initializer, self.evaluator, self.hyperparameters, self.options, load_matrices=True)
self.cf.train()
self.cf.evaluator.k_folds = self.k_folds
self.test_data = self.cf.test_data
self.predictions = self.cf.get_predictions()
self.rounded_predictions = self.cf.rounded_predictions() | def setUp(self):
'\n \n '
(self.documents, self.users) = (18, 10)
(documents_cnt, users_cnt) = (self.documents, self.users)
self.n_iterations = 15
self.k_folds = 3
self.hyperparameters = {'n_factors': 5, '_lambda': 0.01}
self.options = {'n_iterations': self.n_iterations, 'k_folds': self.k_folds}
self.initializer = ModelInitializer(self.hyperparameters.copy(), self.n_iterations)
self.n_recommendations = 1
def mock_get_ratings_matrix(self=None):
return [[int((not bool(((article + user) % 3)))) for article in range(documents_cnt)] for user in range(users_cnt)]
self.ratings_matrix = numpy.array(mock_get_ratings_matrix())
setattr(DataParser, 'get_ratings_matrix', mock_get_ratings_matrix)
self.evaluator = Evaluator(self.ratings_matrix)
self.cf = CollaborativeFiltering(self.initializer, self.evaluator, self.hyperparameters, self.options, load_matrices=True)
self.cf.train()
self.cf.evaluator.k_folds = self.k_folds
self.test_data = self.cf.test_data
self.predictions = self.cf.get_predictions()
self.rounded_predictions = self.cf.rounded_predictions()<|docstring|>Setup method that is called at the beginning of each test.<|endoftext|> |
fc7e1f47a518a5881efe16bcdea02a2a4a2ac9281444a87052cf7ea5bf131943 | def moon_phase_code_to_name(code, lang='en'):
'Converts moon phase code to name.'
return moon_phase_names[lang][code] | Converts moon phase code to name. | generate.py | moon_phase_code_to_name | PanderMusubi/lunar-phase-calendar | 9 | python | def moon_phase_code_to_name(code, lang='en'):
return moon_phase_names[lang][code] | def moon_phase_code_to_name(code, lang='en'):
return moon_phase_names[lang][code]<|docstring|>Converts moon phase code to name.<|endoftext|> |
1370b37c5ee5ccaa15aa043bcfba47a66c95ad86d69fa88b86a67a83ac3587cc | def moon_phase_code_to_symbol(code):
'Converts moon phase code to symbol.'
return moon_phase_symbols[code] | Converts moon phase code to symbol. | generate.py | moon_phase_code_to_symbol | PanderMusubi/lunar-phase-calendar | 9 | python | def moon_phase_code_to_symbol(code):
return moon_phase_symbols[code] | def moon_phase_code_to_symbol(code):
return moon_phase_symbols[code]<|docstring|>Converts moon phase code to symbol.<|endoftext|> |
5a0e6b366cfc42a45532a6412f9acf0d4b298977cc8d28ac14fef32de08beea2 | def moon_phase_to_inacurate_code(phase):
'Converts moon phase code to inacurate code.'
phase = int(phase)
value = None
if (phase == 0):
value = 0
elif (0 < phase < 7):
value = 1
elif (phase == 7):
value = 2
elif (7 < phase < 14):
value = 3
elif (phase == 14):
value = 4
elif (14 < phase < 21):
value = 5
elif (phase == 21):
value = 6
else:
value = 7
return value | Converts moon phase code to inacurate code. | generate.py | moon_phase_to_inacurate_code | PanderMusubi/lunar-phase-calendar | 9 | python | def moon_phase_to_inacurate_code(phase):
phase = int(phase)
value = None
if (phase == 0):
value = 0
elif (0 < phase < 7):
value = 1
elif (phase == 7):
value = 2
elif (7 < phase < 14):
value = 3
elif (phase == 14):
value = 4
elif (14 < phase < 21):
value = 5
elif (phase == 21):
value = 6
else:
value = 7
return value | def moon_phase_to_inacurate_code(phase):
phase = int(phase)
value = None
if (phase == 0):
value = 0
elif (0 < phase < 7):
value = 1
elif (phase == 7):
value = 2
elif (7 < phase < 14):
value = 3
elif (phase == 14):
value = 4
elif (14 < phase < 21):
value = 5
elif (phase == 21):
value = 6
else:
value = 7
return value<|docstring|>Converts moon phase code to inacurate code.<|endoftext|> |
6173927af6d220edfe877f74949a23fa70fa0d7b8383af53f4b2fb3289d0a0d5 | def day_to_moon_phase_and_accurate_code(day):
'Converts day to moon phase and accurate code.'
phase_today = moon.phase(day)
code_today = moon_phase_to_inacurate_code(phase_today)
if ((code_today % 2) != 0):
return (phase_today, code_today)
phase_yesterday = moon.phase((day - timedelta(days=1)))
code_yesterday = moon_phase_to_inacurate_code(phase_yesterday)
if (code_today == code_yesterday):
return (phase_today, (code_today + 1))
return (phase_today, code_today) | Converts day to moon phase and accurate code. | generate.py | day_to_moon_phase_and_accurate_code | PanderMusubi/lunar-phase-calendar | 9 | python | def day_to_moon_phase_and_accurate_code(day):
phase_today = moon.phase(day)
code_today = moon_phase_to_inacurate_code(phase_today)
if ((code_today % 2) != 0):
return (phase_today, code_today)
phase_yesterday = moon.phase((day - timedelta(days=1)))
code_yesterday = moon_phase_to_inacurate_code(phase_yesterday)
if (code_today == code_yesterday):
return (phase_today, (code_today + 1))
return (phase_today, code_today) | def day_to_moon_phase_and_accurate_code(day):
phase_today = moon.phase(day)
code_today = moon_phase_to_inacurate_code(phase_today)
if ((code_today % 2) != 0):
return (phase_today, code_today)
phase_yesterday = moon.phase((day - timedelta(days=1)))
code_yesterday = moon_phase_to_inacurate_code(phase_yesterday)
if (code_today == code_yesterday):
return (phase_today, (code_today + 1))
return (phase_today, code_today)<|docstring|>Converts day to moon phase and accurate code.<|endoftext|> |
d738f6327a1bd0f3a23f694835449d68346b4dd9ea1792c082e6aab5bdbd071f | def write_files(lang='en'):
'Writes calendar files.'
utcnow = datetime.utcnow()
dtstamp = utcnow.strftime('%Y%m%dT%H%M%SZ')
uid_format = 'UID:%(date)s-%(pid)d-%(seq)04d-%(lang)s@%(domain)s\n'
uid_replace_values = {'date': dtstamp, 'pid': getpid(), 'domain': getfqdn()}
event_seq = 1
tsv = open('moon-phases.tsv', 'w')
tsv_new = open('new-moon.tsv', 'w')
tsv_full = open('full-moon.tsv', 'w')
tsv_all = open('moon-phases-all.tsv', 'w')
mkd = open('moon-phases.md', 'w')
mkd_new = open('new-moon.md', 'w')
mkd_full = open('full-moon.md', 'w')
mkd_all = open('moon-phases-all.md', 'w')
ics = open('moon-phases.ics', 'w', newline='\r\n')
ics_new = open('new-moon.ics', 'w', newline='\r\n')
ics_full = open('full-moon.ics', 'w', newline='\r\n')
tsv_header = '# {}\t# {}\t# {}\t# {}\n'.format(header[lang][0].ljust(10), header[lang][1], header[lang][2], header[lang][3])
tsv_header_short = '# {}\t# {}\n'.format(header[lang][0], header[lang][1])
tsv.write(tsv_header)
tsv_all.write(tsv_header)
tsv_new.write(tsv_header_short)
tsv_full.write(tsv_header_short)
title = header[lang][4]
if (lang in titles):
title = title.title()
mkd_header = '# {}\n\n{} | {} | {} | {}\n-----------|-------:|---|---\n'.format(title, header[lang][0].ljust(10), header[lang][1].ljust(6), header[lang][2], header[lang][3])
title = moon_phase_names[lang][0]
if (lang in titles):
title = title.title()
mkd_header_new = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
title = moon_phase_names[lang][4]
if (lang in titles):
title = title.title()
mkd_header_full = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
mkd.write(mkd_header)
mkd_all.write(mkd_header)
mkd_new.write(mkd_header_new)
mkd_full.write(mkd_header_full)
calendar_header = open('../templates/calendar-header-{}.txt'.format(lang))
for line in calendar_header:
if (lang in titles):
ics.write(line.replace('Lunar Phase', header[lang][4].title()))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0].title()))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4].title()))
else:
ics.write(line.replace('Lunar Phase', header[lang][4]))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0]))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4]))
event_header = ''
for line in open('../templates/event-header.txt'):
event_header += line.replace('DTSTAMP:', 'DTSTAMP:{}'.format(dtstamp))
event_footer = ''
for line in open('../templates/event-footer.txt'):
event_footer += line
today = date.today()
start = (today - timedelta(days=(31 + 1)))
end = (today + timedelta(days=((2 * 366) + (2 * 31))))
for i in range((end - start).days):
day = (start + timedelta(days=i))
(phase, code) = day_to_moon_phase_and_accurate_code(day)
symbol = moon_phase_code_to_symbol(code)
name = moon_phase_code_to_name(code, lang)
tsv_all.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd_all.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
if ((code % 2) == 0):
tsv.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
ics.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', '')))
ics.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', '')))
ics.write(event_footer)
if (code == 0):
tsv_new.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_new.write('{} | {:6.3f}\n'.format(day, phase))
ics_new.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_new.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_new.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', '')))
ics_new.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', '')))
ics_new.write(event_footer)
if (code == 4):
tsv_full.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_full.write('{} | {:6.3f}\n'.format(day, phase))
ics_full.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_full.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_full.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', '')))
ics_full.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', '')))
ics_full.write(event_footer)
calendar_footer = open('../templates/calendar-footer.txt')
for line in calendar_footer:
ics.write(line)
ics_new.write(line)
ics_full.write(line) | Writes calendar files. | generate.py | write_files | PanderMusubi/lunar-phase-calendar | 9 | python | def write_files(lang='en'):
utcnow = datetime.utcnow()
dtstamp = utcnow.strftime('%Y%m%dT%H%M%SZ')
uid_format = 'UID:%(date)s-%(pid)d-%(seq)04d-%(lang)s@%(domain)s\n'
uid_replace_values = {'date': dtstamp, 'pid': getpid(), 'domain': getfqdn()}
event_seq = 1
tsv = open('moon-phases.tsv', 'w')
tsv_new = open('new-moon.tsv', 'w')
tsv_full = open('full-moon.tsv', 'w')
tsv_all = open('moon-phases-all.tsv', 'w')
mkd = open('moon-phases.md', 'w')
mkd_new = open('new-moon.md', 'w')
mkd_full = open('full-moon.md', 'w')
mkd_all = open('moon-phases-all.md', 'w')
ics = open('moon-phases.ics', 'w', newline='\r\n')
ics_new = open('new-moon.ics', 'w', newline='\r\n')
ics_full = open('full-moon.ics', 'w', newline='\r\n')
tsv_header = '# {}\t# {}\t# {}\t# {}\n'.format(header[lang][0].ljust(10), header[lang][1], header[lang][2], header[lang][3])
tsv_header_short = '# {}\t# {}\n'.format(header[lang][0], header[lang][1])
tsv.write(tsv_header)
tsv_all.write(tsv_header)
tsv_new.write(tsv_header_short)
tsv_full.write(tsv_header_short)
title = header[lang][4]
if (lang in titles):
title = title.title()
mkd_header = '# {}\n\n{} | {} | {} | {}\n-----------|-------:|---|---\n'.format(title, header[lang][0].ljust(10), header[lang][1].ljust(6), header[lang][2], header[lang][3])
title = moon_phase_names[lang][0]
if (lang in titles):
title = title.title()
mkd_header_new = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
title = moon_phase_names[lang][4]
if (lang in titles):
title = title.title()
mkd_header_full = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
mkd.write(mkd_header)
mkd_all.write(mkd_header)
mkd_new.write(mkd_header_new)
mkd_full.write(mkd_header_full)
calendar_header = open('../templates/calendar-header-{}.txt'.format(lang))
for line in calendar_header:
if (lang in titles):
ics.write(line.replace('Lunar Phase', header[lang][4].title()))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0].title()))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4].title()))
else:
ics.write(line.replace('Lunar Phase', header[lang][4]))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0]))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4]))
event_header =
for line in open('../templates/event-header.txt'):
event_header += line.replace('DTSTAMP:', 'DTSTAMP:{}'.format(dtstamp))
event_footer =
for line in open('../templates/event-footer.txt'):
event_footer += line
today = date.today()
start = (today - timedelta(days=(31 + 1)))
end = (today + timedelta(days=((2 * 366) + (2 * 31))))
for i in range((end - start).days):
day = (start + timedelta(days=i))
(phase, code) = day_to_moon_phase_and_accurate_code(day)
symbol = moon_phase_code_to_symbol(code)
name = moon_phase_code_to_name(code, lang)
tsv_all.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd_all.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
if ((code % 2) == 0):
tsv.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
ics.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics.write(event_footer)
if (code == 0):
tsv_new.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_new.write('{} | {:6.3f}\n'.format(day, phase))
ics_new.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_new.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_new.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics_new.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics_new.write(event_footer)
if (code == 4):
tsv_full.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_full.write('{} | {:6.3f}\n'.format(day, phase))
ics_full.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_full.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_full.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics_full.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics_full.write(event_footer)
calendar_footer = open('../templates/calendar-footer.txt')
for line in calendar_footer:
ics.write(line)
ics_new.write(line)
ics_full.write(line) | def write_files(lang='en'):
utcnow = datetime.utcnow()
dtstamp = utcnow.strftime('%Y%m%dT%H%M%SZ')
uid_format = 'UID:%(date)s-%(pid)d-%(seq)04d-%(lang)s@%(domain)s\n'
uid_replace_values = {'date': dtstamp, 'pid': getpid(), 'domain': getfqdn()}
event_seq = 1
tsv = open('moon-phases.tsv', 'w')
tsv_new = open('new-moon.tsv', 'w')
tsv_full = open('full-moon.tsv', 'w')
tsv_all = open('moon-phases-all.tsv', 'w')
mkd = open('moon-phases.md', 'w')
mkd_new = open('new-moon.md', 'w')
mkd_full = open('full-moon.md', 'w')
mkd_all = open('moon-phases-all.md', 'w')
ics = open('moon-phases.ics', 'w', newline='\r\n')
ics_new = open('new-moon.ics', 'w', newline='\r\n')
ics_full = open('full-moon.ics', 'w', newline='\r\n')
tsv_header = '# {}\t# {}\t# {}\t# {}\n'.format(header[lang][0].ljust(10), header[lang][1], header[lang][2], header[lang][3])
tsv_header_short = '# {}\t# {}\n'.format(header[lang][0], header[lang][1])
tsv.write(tsv_header)
tsv_all.write(tsv_header)
tsv_new.write(tsv_header_short)
tsv_full.write(tsv_header_short)
title = header[lang][4]
if (lang in titles):
title = title.title()
mkd_header = '# {}\n\n{} | {} | {} | {}\n-----------|-------:|---|---\n'.format(title, header[lang][0].ljust(10), header[lang][1].ljust(6), header[lang][2], header[lang][3])
title = moon_phase_names[lang][0]
if (lang in titles):
title = title.title()
mkd_header_new = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
title = moon_phase_names[lang][4]
if (lang in titles):
title = title.title()
mkd_header_full = '# {}\n\n{} | {}\n-----------|------:\n'.format(title, header[lang][0].ljust(10), header[lang][1])
mkd.write(mkd_header)
mkd_all.write(mkd_header)
mkd_new.write(mkd_header_new)
mkd_full.write(mkd_header_full)
calendar_header = open('../templates/calendar-header-{}.txt'.format(lang))
for line in calendar_header:
if (lang in titles):
ics.write(line.replace('Lunar Phase', header[lang][4].title()))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0].title()))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4].title()))
else:
ics.write(line.replace('Lunar Phase', header[lang][4]))
ics_new.write(line.replace('Lunar Phase', moon_phase_names[lang][0]))
ics_full.write(line.replace('Lunar Phase', moon_phase_names[lang][4]))
event_header =
for line in open('../templates/event-header.txt'):
event_header += line.replace('DTSTAMP:', 'DTSTAMP:{}'.format(dtstamp))
event_footer =
for line in open('../templates/event-footer.txt'):
event_footer += line
today = date.today()
start = (today - timedelta(days=(31 + 1)))
end = (today + timedelta(days=((2 * 366) + (2 * 31))))
for i in range((end - start).days):
day = (start + timedelta(days=i))
(phase, code) = day_to_moon_phase_and_accurate_code(day)
symbol = moon_phase_code_to_symbol(code)
name = moon_phase_code_to_name(code, lang)
tsv_all.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd_all.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
if ((code % 2) == 0):
tsv.write('{}\t{:6.3f}\t{}\t{}\n'.format(day, phase, symbol, name))
mkd.write('{} | {:6.3f} | {} | {}\n'.format(day, phase, symbol, name))
ics.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics.write(event_footer)
if (code == 0):
tsv_new.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_new.write('{} | {:6.3f}\n'.format(day, phase))
ics_new.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_new.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_new.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics_new.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics_new.write(event_footer)
if (code == 4):
tsv_full.write('{}\t{:6.3f}\n'.format(day, phase))
mkd_full.write('{} | {:6.3f}\n'.format(day, phase))
ics_full.write('{}{} {}\n'.format(event_header.strip(), symbol, name))
ics_full.write((uid_format % dict((list(uid_replace_values.items()) + list({'lang': 'nl', 'seq': event_seq}.items())))))
event_seq += 1
ics_start = '{}'.format(day)
ics_end = '{}'.format((day + timedelta(days=1)))
ics_full.write('DTSTART;VALUE=DATE:{}\n'.format(ics_start.replace('-', )))
ics_full.write('DTEND;VALUE=DATE:{}\n'.format(ics_end.replace('-', )))
ics_full.write(event_footer)
calendar_footer = open('../templates/calendar-footer.txt')
for line in calendar_footer:
ics.write(line)
ics_new.write(line)
ics_full.write(line)<|docstring|>Writes calendar files.<|endoftext|> |
0f3a7e68f74c27d41c970f24b6b0d8bc34923155940d5042a213f7866408ed1d | def connect(self) -> None:
'Connect events.'
self.parent_frame.pushButton_load_visualizarion.clicked.connect(self.add_subwindow)
self.parent_frame.pushButton_visualizations_remove_all.clicked.connect(self.remove_all)
self.parent_frame.pushButton_visualizations_reload_all.clicked.connect(self.reload_all)
self.parent_frame.tableWidget_anlaysis.itemChanged.connect(self.analisys_status_update)
self.parent_frame.pushButton_visualizations_stop_all.clicked.connect(self.stop_all_scripts)
self.parent_frame.pushButton_visualizations_restart_all.clicked.connect(self.restart_running_scripts) | Connect events. | bci_framework/framework/environments/visualization.py | connect | UN-GCPDS/bci-framework | 2 | python | def connect(self) -> None:
self.parent_frame.pushButton_load_visualizarion.clicked.connect(self.add_subwindow)
self.parent_frame.pushButton_visualizations_remove_all.clicked.connect(self.remove_all)
self.parent_frame.pushButton_visualizations_reload_all.clicked.connect(self.reload_all)
self.parent_frame.tableWidget_anlaysis.itemChanged.connect(self.analisys_status_update)
self.parent_frame.pushButton_visualizations_stop_all.clicked.connect(self.stop_all_scripts)
self.parent_frame.pushButton_visualizations_restart_all.clicked.connect(self.restart_running_scripts) | def connect(self) -> None:
self.parent_frame.pushButton_load_visualizarion.clicked.connect(self.add_subwindow)
self.parent_frame.pushButton_visualizations_remove_all.clicked.connect(self.remove_all)
self.parent_frame.pushButton_visualizations_reload_all.clicked.connect(self.reload_all)
self.parent_frame.tableWidget_anlaysis.itemChanged.connect(self.analisys_status_update)
self.parent_frame.pushButton_visualizations_stop_all.clicked.connect(self.stop_all_scripts)
self.parent_frame.pushButton_visualizations_restart_all.clicked.connect(self.restart_running_scripts)<|docstring|>Connect events.<|endoftext|> |
fe46b822d7dee87673fefe0456e94a0795329c6284a511562cff50e40d9ff1ec | def on_focus(self) -> None:
'Update mdiAreas.'
self.parent_frame.mdiArea.tileSubWindows()
self.visualizations_list = []
for i in range(self.parent_frame.listWidget_projects_visualizations.count()):
item = self.parent_frame.listWidget_projects_visualizations.item(i)
if item.text().startswith('_'):
continue
if item.text().startswith('Tutorial :'):
continue
self.visualizations_list.append([item.text(), item.path])
self.build_analysis() | Update mdiAreas. | bci_framework/framework/environments/visualization.py | on_focus | UN-GCPDS/bci-framework | 2 | python | def on_focus(self) -> None:
self.parent_frame.mdiArea.tileSubWindows()
self.visualizations_list = []
for i in range(self.parent_frame.listWidget_projects_visualizations.count()):
item = self.parent_frame.listWidget_projects_visualizations.item(i)
if item.text().startswith('_'):
continue
if item.text().startswith('Tutorial :'):
continue
self.visualizations_list.append([item.text(), item.path])
self.build_analysis() | def on_focus(self) -> None:
self.parent_frame.mdiArea.tileSubWindows()
self.visualizations_list = []
for i in range(self.parent_frame.listWidget_projects_visualizations.count()):
item = self.parent_frame.listWidget_projects_visualizations.item(i)
if item.text().startswith('_'):
continue
if item.text().startswith('Tutorial :'):
continue
self.visualizations_list.append([item.text(), item.path])
self.build_analysis()<|docstring|>Update mdiAreas.<|endoftext|> |
5b46b227d50bc46f4d90a030a6921cf2f2a1993ddc8a6e2b2fb68a5c7dbe8880 | def reload_all(self) -> None:
'Reload all patitions.'
for sub in self.parent_frame.mdiArea.subWindowList():
sub.reload() | Reload all patitions. | bci_framework/framework/environments/visualization.py | reload_all | UN-GCPDS/bci-framework | 2 | python | def reload_all(self) -> None:
for sub in self.parent_frame.mdiArea.subWindowList():
sub.reload() | def reload_all(self) -> None:
for sub in self.parent_frame.mdiArea.subWindowList():
sub.reload()<|docstring|>Reload all patitions.<|endoftext|> |
674a245a48689eba189e411c9864c5514ffc5194d2e7ef50b5f2fe4c41664fba | def remove_all(self) -> None:
'Remove all patitions.'
for sub in self.parent_frame.mdiArea.subWindowList():
sub.remove()
QTimer().singleShot(100, self.widgets_set_enabled) | Remove all patitions. | bci_framework/framework/environments/visualization.py | remove_all | UN-GCPDS/bci-framework | 2 | python | def remove_all(self) -> None:
for sub in self.parent_frame.mdiArea.subWindowList():
sub.remove()
QTimer().singleShot(100, self.widgets_set_enabled) | def remove_all(self) -> None:
for sub in self.parent_frame.mdiArea.subWindowList():
sub.remove()
QTimer().singleShot(100, self.widgets_set_enabled)<|docstring|>Remove all patitions.<|endoftext|> |
53546d814d91afe16c07309a5a3c89f332f70614bbaad4af5f5ef1e2aa71b7d4 | def add_subwindow(self) -> None:
'Add new patition.'
sub = ExtensionWidget(self.parent_frame.mdiArea, mode='visualization', extensions_list=self.visualizations_list)
self.parent_frame.mdiArea.addSubWindow(sub)
sub.show()
self.parent_frame.mdiArea.tileSubWindows()
sub.update_menu_bar()
sub.loaded = self.widgets_set_enabled
sub.destroyed.connect(self.widgets_set_enabled)
self.widgets_set_enabled() | Add new patition. | bci_framework/framework/environments/visualization.py | add_subwindow | UN-GCPDS/bci-framework | 2 | python | def add_subwindow(self) -> None:
sub = ExtensionWidget(self.parent_frame.mdiArea, mode='visualization', extensions_list=self.visualizations_list)
self.parent_frame.mdiArea.addSubWindow(sub)
sub.show()
self.parent_frame.mdiArea.tileSubWindows()
sub.update_menu_bar()
sub.loaded = self.widgets_set_enabled
sub.destroyed.connect(self.widgets_set_enabled)
self.widgets_set_enabled() | def add_subwindow(self) -> None:
sub = ExtensionWidget(self.parent_frame.mdiArea, mode='visualization', extensions_list=self.visualizations_list)
self.parent_frame.mdiArea.addSubWindow(sub)
sub.show()
self.parent_frame.mdiArea.tileSubWindows()
sub.update_menu_bar()
sub.loaded = self.widgets_set_enabled
sub.destroyed.connect(self.widgets_set_enabled)
self.widgets_set_enabled()<|docstring|>Add new patition.<|endoftext|> |
875bd64baab66571a50636f9be0e652867a4453362355ce9e4266191ee931b9d | def widgets_set_enabled(self) -> None:
'Update action buttons.'
subwindows = (len(self.parent_frame.mdiArea.subWindowList()) != 0)
self.parent_frame.pushButton_visualizations_remove_all.setEnabled(subwindows)
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(False)
for sub in self.parent_frame.mdiArea.subWindowList():
if getattr(sub, 'stream_subprocess', False):
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(True)
break | Update action buttons. | bci_framework/framework/environments/visualization.py | widgets_set_enabled | UN-GCPDS/bci-framework | 2 | python | def widgets_set_enabled(self) -> None:
subwindows = (len(self.parent_frame.mdiArea.subWindowList()) != 0)
self.parent_frame.pushButton_visualizations_remove_all.setEnabled(subwindows)
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(False)
for sub in self.parent_frame.mdiArea.subWindowList():
if getattr(sub, 'stream_subprocess', False):
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(True)
break | def widgets_set_enabled(self) -> None:
subwindows = (len(self.parent_frame.mdiArea.subWindowList()) != 0)
self.parent_frame.pushButton_visualizations_remove_all.setEnabled(subwindows)
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(False)
for sub in self.parent_frame.mdiArea.subWindowList():
if getattr(sub, 'stream_subprocess', False):
self.parent_frame.pushButton_visualizations_reload_all.setEnabled(True)
break<|docstring|>Update action buttons.<|endoftext|> |
0000e3c5e1f7b4f770135241b1513d239c17d74d6389076cf79889d618a891a3 | def has_repeat_digits(grid: list[list[str]]) -> bool:
'Returns if given 2d grid has repeating digit strings'
digit_strings = {str(i) for i in range(1, 10)}
for row in grid:
for digit in row:
if (digit == '.'):
continue
if (digit not in digit_strings):
return True
digit_strings.remove(digit)
return False | Returns if given 2d grid has repeating digit strings | valid_sudoku.py | has_repeat_digits | tusharsadhwani/leetcode | 6 | python | def has_repeat_digits(grid: list[list[str]]) -> bool:
digit_strings = {str(i) for i in range(1, 10)}
for row in grid:
for digit in row:
if (digit == '.'):
continue
if (digit not in digit_strings):
return True
digit_strings.remove(digit)
return False | def has_repeat_digits(grid: list[list[str]]) -> bool:
digit_strings = {str(i) for i in range(1, 10)}
for row in grid:
for digit in row:
if (digit == '.'):
continue
if (digit not in digit_strings):
return True
digit_strings.remove(digit)
return False<|docstring|>Returns if given 2d grid has repeating digit strings<|endoftext|> |
6576d2b91e1820a7d04d28da94281ca01d0e4d32716362130fc705ee94570a85 | def check_attribute_conflict(label_batch, attr, attrs):
' Based on https://github.com/LynnHo/AttGAN-Tensorflow'
def _set(label, value, attr):
if (attr in attrs):
label[attrs.index(attr)] = value
attr_id = attrs.index(attr)
for label in label_batch:
if ((attr in ['Bald', 'Receding_Hairline']) and (attrs[attr_id] != 0)):
_set(label, 0, 'Bangs')
elif ((attr == 'Bangs') and (attrs[attr_id] != 0)):
_set(label, 0, 'Bald')
_set(label, 0, 'Receding_Hairline')
elif ((attr in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']) and (attrs[attr_id] != 0)):
for a in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']:
if (a != attr):
_set(label, 0, a)
elif ((attr in ['Straight_Hair', 'Wavy_Hair']) and (attrs[attr_id] != 0)):
for a in ['Straight_Hair', 'Wavy_Hair']:
if (a != attr):
_set(label, 0, a)
return label_batch | Based on https://github.com/LynnHo/AttGAN-Tensorflow | PaddleCV/PaddleGAN/util/utility.py | check_attribute_conflict | liuzengzhen1/models | 3 | python | def check_attribute_conflict(label_batch, attr, attrs):
' '
def _set(label, value, attr):
if (attr in attrs):
label[attrs.index(attr)] = value
attr_id = attrs.index(attr)
for label in label_batch:
if ((attr in ['Bald', 'Receding_Hairline']) and (attrs[attr_id] != 0)):
_set(label, 0, 'Bangs')
elif ((attr == 'Bangs') and (attrs[attr_id] != 0)):
_set(label, 0, 'Bald')
_set(label, 0, 'Receding_Hairline')
elif ((attr in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']) and (attrs[attr_id] != 0)):
for a in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']:
if (a != attr):
_set(label, 0, a)
elif ((attr in ['Straight_Hair', 'Wavy_Hair']) and (attrs[attr_id] != 0)):
for a in ['Straight_Hair', 'Wavy_Hair']:
if (a != attr):
_set(label, 0, a)
return label_batch | def check_attribute_conflict(label_batch, attr, attrs):
' '
def _set(label, value, attr):
if (attr in attrs):
label[attrs.index(attr)] = value
attr_id = attrs.index(attr)
for label in label_batch:
if ((attr in ['Bald', 'Receding_Hairline']) and (attrs[attr_id] != 0)):
_set(label, 0, 'Bangs')
elif ((attr == 'Bangs') and (attrs[attr_id] != 0)):
_set(label, 0, 'Bald')
_set(label, 0, 'Receding_Hairline')
elif ((attr in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']) and (attrs[attr_id] != 0)):
for a in ['Black_Hair', 'Blond_Hair', 'Brown_Hair', 'Gray_Hair']:
if (a != attr):
_set(label, 0, a)
elif ((attr in ['Straight_Hair', 'Wavy_Hair']) and (attrs[attr_id] != 0)):
for a in ['Straight_Hair', 'Wavy_Hair']:
if (a != attr):
_set(label, 0, a)
return label_batch<|docstring|>Based on https://github.com/LynnHo/AttGAN-Tensorflow<|endoftext|> |
9d79e42de93e120b8f0912b2c568eba9636c451a3ec5f0743b74042672cb5ad0 | def check_gpu(use_gpu):
'\n Log error and exit when set use_gpu=true in paddlepaddle\n cpu version.\n '
err = 'Config use_gpu cannot be set as true while you are using paddlepaddle cpu version ! \nPlease try: \n\t1. Install paddlepaddle-gpu to run model on GPU \n\t2. Set use_gpu as false in config file to run model on CPU'
try:
if (use_gpu and (not fluid.is_compiled_with_cuda())):
print(err)
sys.exit(1)
except Exception as e:
pass | Log error and exit when set use_gpu=true in paddlepaddle
cpu version. | PaddleCV/PaddleGAN/util/utility.py | check_gpu | liuzengzhen1/models | 3 | python | def check_gpu(use_gpu):
'\n Log error and exit when set use_gpu=true in paddlepaddle\n cpu version.\n '
err = 'Config use_gpu cannot be set as true while you are using paddlepaddle cpu version ! \nPlease try: \n\t1. Install paddlepaddle-gpu to run model on GPU \n\t2. Set use_gpu as false in config file to run model on CPU'
try:
if (use_gpu and (not fluid.is_compiled_with_cuda())):
print(err)
sys.exit(1)
except Exception as e:
pass | def check_gpu(use_gpu):
'\n Log error and exit when set use_gpu=true in paddlepaddle\n cpu version.\n '
err = 'Config use_gpu cannot be set as true while you are using paddlepaddle cpu version ! \nPlease try: \n\t1. Install paddlepaddle-gpu to run model on GPU \n\t2. Set use_gpu as false in config file to run model on CPU'
try:
if (use_gpu and (not fluid.is_compiled_with_cuda())):
print(err)
sys.exit(1)
except Exception as e:
pass<|docstring|>Log error and exit when set use_gpu=true in paddlepaddle
cpu version.<|endoftext|> |
6198b17435b578946f25a72071091b12c1b5278b1a6761ab736c8211378acb18 | def phonemes_to_mels(self, phoneme_ids: np.ndarray, settings: typing.Optional[SettingsType]=None) -> ARRAY_OR_TENSOR:
'Convert phoneme ids to mel spectrograms'
pass | Convert phoneme ids to mel spectrograms | larynx/constants.py | phonemes_to_mels | mbarnig/larynx | 540 | python | def phonemes_to_mels(self, phoneme_ids: np.ndarray, settings: typing.Optional[SettingsType]=None) -> ARRAY_OR_TENSOR:
pass | def phonemes_to_mels(self, phoneme_ids: np.ndarray, settings: typing.Optional[SettingsType]=None) -> ARRAY_OR_TENSOR:
pass<|docstring|>Convert phoneme ids to mel spectrograms<|endoftext|> |
e0f0b21f47be10e0bd0976a2883247fbfb0b6e596edb487be3b7b32a0446529a | def mels_to_audio(self, mels: ARRAY_OR_TENSOR, settings: typing.Optional[SettingsType]=None) -> np.ndarray:
'Convert mel spectrograms to WAV audio'
pass | Convert mel spectrograms to WAV audio | larynx/constants.py | mels_to_audio | mbarnig/larynx | 540 | python | def mels_to_audio(self, mels: ARRAY_OR_TENSOR, settings: typing.Optional[SettingsType]=None) -> np.ndarray:
pass | def mels_to_audio(self, mels: ARRAY_OR_TENSOR, settings: typing.Optional[SettingsType]=None) -> np.ndarray:
pass<|docstring|>Convert mel spectrograms to WAV audio<|endoftext|> |
2817f1ac857ad78be1d45629e5326880d71542d465bd2d1d1f4a561355f78d0f | def __init__(self, *args, **kwargs):
'\n Create the request client instance.\n :param kwargs: The option of request connection.\n api_key: The public key applied from Huobi.\n secret_key: The private key applied from Huobi.\n url: The URL name like "https://api.huobi.pro".\n init_log: to init logger\n '
self.__kwargs = kwargs
self.rest_api_sync_client = RestApiSyncClient(*args, **kwargs)
self.web_socket_req_client = WebSocketReqClient(*args, **kwargs)
self.sub_socket_req_client = SubscribeClient(*args, **kwargs) | Create the request client instance.
:param kwargs: The option of request connection.
api_key: The public key applied from Huobi.
secret_key: The private key applied from Huobi.
url: The URL name like "https://api.huobi.pro".
init_log: to init logger | notecoin/huobi/client/generic.py | __init__ | notechats/notecoin | 0 | python | def __init__(self, *args, **kwargs):
'\n Create the request client instance.\n :param kwargs: The option of request connection.\n api_key: The public key applied from Huobi.\n secret_key: The private key applied from Huobi.\n url: The URL name like "https://api.huobi.pro".\n init_log: to init logger\n '
self.__kwargs = kwargs
self.rest_api_sync_client = RestApiSyncClient(*args, **kwargs)
self.web_socket_req_client = WebSocketReqClient(*args, **kwargs)
self.sub_socket_req_client = SubscribeClient(*args, **kwargs) | def __init__(self, *args, **kwargs):
'\n Create the request client instance.\n :param kwargs: The option of request connection.\n api_key: The public key applied from Huobi.\n secret_key: The private key applied from Huobi.\n url: The URL name like "https://api.huobi.pro".\n init_log: to init logger\n '
self.__kwargs = kwargs
self.rest_api_sync_client = RestApiSyncClient(*args, **kwargs)
self.web_socket_req_client = WebSocketReqClient(*args, **kwargs)
self.sub_socket_req_client = SubscribeClient(*args, **kwargs)<|docstring|>Create the request client instance.
:param kwargs: The option of request connection.
api_key: The public key applied from Huobi.
secret_key: The private key applied from Huobi.
url: The URL name like "https://api.huobi.pro".
init_log: to init logger<|endoftext|> |
ba0733611bcf045fc97229ebf63dae9bdb24e3d17a2757639e6487c20488a607 | def get_exchange_timestamp(self) -> int:
'\n Get the timestamp from Huobi server. The timestamp is the Unix timestamp in millisecond.\n The count shows how many milliseconds passed from Jan 1st 1970, 00:00:00.000 at UTC.\n e.g. 1546300800000 is Thu, 1st Jan 2019 00:00:00.000 UTC.\n\n :return: The timestamp in UTC\n '
channel = '/v1/common/timestamp'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | Get the timestamp from Huobi server. The timestamp is the Unix timestamp in millisecond.
The count shows how many milliseconds passed from Jan 1st 1970, 00:00:00.000 at UTC.
e.g. 1546300800000 is Thu, 1st Jan 2019 00:00:00.000 UTC.
:return: The timestamp in UTC | notecoin/huobi/client/generic.py | get_exchange_timestamp | notechats/notecoin | 0 | python | def get_exchange_timestamp(self) -> int:
'\n Get the timestamp from Huobi server. The timestamp is the Unix timestamp in millisecond.\n The count shows how many milliseconds passed from Jan 1st 1970, 00:00:00.000 at UTC.\n e.g. 1546300800000 is Thu, 1st Jan 2019 00:00:00.000 UTC.\n\n :return: The timestamp in UTC\n '
channel = '/v1/common/timestamp'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | def get_exchange_timestamp(self) -> int:
'\n Get the timestamp from Huobi server. The timestamp is the Unix timestamp in millisecond.\n The count shows how many milliseconds passed from Jan 1st 1970, 00:00:00.000 at UTC.\n e.g. 1546300800000 is Thu, 1st Jan 2019 00:00:00.000 UTC.\n\n :return: The timestamp in UTC\n '
channel = '/v1/common/timestamp'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params)<|docstring|>Get the timestamp from Huobi server. The timestamp is the Unix timestamp in millisecond.
The count shows how many milliseconds passed from Jan 1st 1970, 00:00:00.000 at UTC.
e.g. 1546300800000 is Thu, 1st Jan 2019 00:00:00.000 UTC.
:return: The timestamp in UTC<|endoftext|> |
76c146e5aafa06b6b23feba32b8d4ed0a646b19e3a0bff1fd5cb816e3fa5ee34 | def get_exchange_currencies(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading currencies.\n '
channel = '/v1/common/currencys'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:return: The information of trading currencies. | notecoin/huobi/client/generic.py | get_exchange_currencies | notechats/notecoin | 0 | python | def get_exchange_currencies(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading currencies.\n '
channel = '/v1/common/currencys'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | def get_exchange_currencies(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading currencies.\n '
channel = '/v1/common/currencys'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params)<|docstring|>Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:return: The information of trading currencies.<|endoftext|> |
e72f21633f13f027ee2557008328b6057b1512b232dc31038a395cf674caea10 | def get_exchange_symbols(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument etc.\n\n :return: The information of trading instrument.\n '
channel = '/v1/common/symbols'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | Get all the trading assets and currencies supported in huobi.
The information of trading instrument etc.
:return: The information of trading instrument. | notecoin/huobi/client/generic.py | get_exchange_symbols | notechats/notecoin | 0 | python | def get_exchange_symbols(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument etc.\n\n :return: The information of trading instrument.\n '
channel = '/v1/common/symbols'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | def get_exchange_symbols(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument etc.\n\n :return: The information of trading instrument.\n '
channel = '/v1/common/symbols'
params = {}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params)<|docstring|>Get all the trading assets and currencies supported in huobi.
The information of trading instrument etc.
:return: The information of trading instrument.<|endoftext|> |
de79906dda3e5b1f05f2c572d31dce8da38c8930eec5ceaba26df1aba009e0d2 | def get_exchange_info(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading instrument and currencies.\n '
ret = {'symbol_list': self.get_exchange_symbols(), 'currencies': self.get_exchange_currencies()}
return ret | Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:return: The information of trading instrument and currencies. | notecoin/huobi/client/generic.py | get_exchange_info | notechats/notecoin | 0 | python | def get_exchange_info(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading instrument and currencies.\n '
ret = {'symbol_list': self.get_exchange_symbols(), 'currencies': self.get_exchange_currencies()}
return ret | def get_exchange_info(self):
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :return: The information of trading instrument and currencies.\n '
ret = {'symbol_list': self.get_exchange_symbols(), 'currencies': self.get_exchange_currencies()}
return ret<|docstring|>Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:return: The information of trading instrument and currencies.<|endoftext|> |
8c7342aa32732b79d3ec99cca4809114c4c20aaef36fbbe4f263246b11e50f62 | def get_reference_currencies(self, currency: 'str'=None, is_authorized_user: 'bool'=None) -> list:
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :param currency: btc, ltc, bch, eth, etc ...(available currencies in Huobi Global)\n :param is_authorized_user: is Authorized user? True or False\n :return: The information of trading instrument and currencies.\n '
channel = '/v2/reference/currencies'
params = {'currency': currency, 'authorizedUser': is_authorized_user}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:param currency: btc, ltc, bch, eth, etc ...(available currencies in Huobi Global)
:param is_authorized_user: is Authorized user? True or False
:return: The information of trading instrument and currencies. | notecoin/huobi/client/generic.py | get_reference_currencies | notechats/notecoin | 0 | python | def get_reference_currencies(self, currency: 'str'=None, is_authorized_user: 'bool'=None) -> list:
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :param currency: btc, ltc, bch, eth, etc ...(available currencies in Huobi Global)\n :param is_authorized_user: is Authorized user? True or False\n :return: The information of trading instrument and currencies.\n '
channel = '/v2/reference/currencies'
params = {'currency': currency, 'authorizedUser': is_authorized_user}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params) | def get_reference_currencies(self, currency: 'str'=None, is_authorized_user: 'bool'=None) -> list:
'\n Get all the trading assets and currencies supported in huobi.\n The information of trading instrument, including base currency, quote precision, etc.\n\n :param currency: btc, ltc, bch, eth, etc ...(available currencies in Huobi Global)\n :param is_authorized_user: is Authorized user? True or False\n :return: The information of trading instrument and currencies.\n '
channel = '/v2/reference/currencies'
params = {'currency': currency, 'authorizedUser': is_authorized_user}
return self.rest_api_sync_client.request_process(HttpMethod.GET, channel, params)<|docstring|>Get all the trading assets and currencies supported in huobi.
The information of trading instrument, including base currency, quote precision, etc.
:param currency: btc, ltc, bch, eth, etc ...(available currencies in Huobi Global)
:param is_authorized_user: is Authorized user? True or False
:return: The information of trading instrument and currencies.<|endoftext|> |
9e31e558f40a620afcfa335ec16b566bf1a13a5cbcd9c641224b7b5898af664f | def get_system_status(self) -> str:
'\n get system status\n\n :return: system status.\n '
channel = '/api/v2/summary.json'
temp = self.rest_api_sync_client.__server_url
self.rest_api_sync_client.__server_url = 'https://status.huobigroup.com'
res = self.rest_api_sync_client.request_process(HttpMethod.GET, channel, {})
self.rest_api_sync_client.__server_url = temp
return res | get system status
:return: system status. | notecoin/huobi/client/generic.py | get_system_status | notechats/notecoin | 0 | python | def get_system_status(self) -> str:
'\n get system status\n\n :return: system status.\n '
channel = '/api/v2/summary.json'
temp = self.rest_api_sync_client.__server_url
self.rest_api_sync_client.__server_url = 'https://status.huobigroup.com'
res = self.rest_api_sync_client.request_process(HttpMethod.GET, channel, {})
self.rest_api_sync_client.__server_url = temp
return res | def get_system_status(self) -> str:
'\n get system status\n\n :return: system status.\n '
channel = '/api/v2/summary.json'
temp = self.rest_api_sync_client.__server_url
self.rest_api_sync_client.__server_url = 'https://status.huobigroup.com'
res = self.rest_api_sync_client.request_process(HttpMethod.GET, channel, {})
self.rest_api_sync_client.__server_url = temp
return res<|docstring|>get system status
:return: system status.<|endoftext|> |
414a2249071fac971bcb1cf3d26bad229dff3cf6496c463703d483876a1b6760 | def is_virginica_test(fi, t, reverse, example):
'Apply threshold model to a new example'
test = (example[fi] > t)
if reverse:
test = (not test)
return test | Apply threshold model to a new example | ch02/chapter.py | is_virginica_test | Jonkimi/BuildingMachineLearningSystemsWithPython | 1,490 | python | def is_virginica_test(fi, t, reverse, example):
test = (example[fi] > t)
if reverse:
test = (not test)
return test | def is_virginica_test(fi, t, reverse, example):
test = (example[fi] > t)
if reverse:
test = (not test)
return test<|docstring|>Apply threshold model to a new example<|endoftext|> |
e6c2655a890905eb69fd72841251abe42fe8a236cd00b4764fc906d8cfa72feb | def __init__(self, jwk_endpoint: str, api_logout_url: str, **kwargs):
'Construct a OAuth 2 client session.'
self.jwk_endpoint = jwk_endpoint
self.api_logout_url = api_logout_url
super(OAuth2Session, self).__init__(**kwargs) | Construct a OAuth 2 client session. | src/auth_api/oidc/session.py | __init__ | Energinet-DataHub/po-auth | 1 | python | def __init__(self, jwk_endpoint: str, api_logout_url: str, **kwargs):
self.jwk_endpoint = jwk_endpoint
self.api_logout_url = api_logout_url
super(OAuth2Session, self).__init__(**kwargs) | def __init__(self, jwk_endpoint: str, api_logout_url: str, **kwargs):
self.jwk_endpoint = jwk_endpoint
self.api_logout_url = api_logout_url
super(OAuth2Session, self).__init__(**kwargs)<|docstring|>Construct a OAuth 2 client session.<|endoftext|> |
2e4d5c14a123ddecedd920545e38e75f62b13675c667189cd30c17dbe3533b33 | def get_jwk(self) -> str:
'TODO.'
jwks_response = requests.get(url=self.jwk_endpoint, verify=True)
return jwks_response.content.decode() | TODO. | src/auth_api/oidc/session.py | get_jwk | Energinet-DataHub/po-auth | 1 | python | def get_jwk(self) -> str:
jwks_response = requests.get(url=self.jwk_endpoint, verify=True)
return jwks_response.content.decode() | def get_jwk(self) -> str:
jwks_response = requests.get(url=self.jwk_endpoint, verify=True)
return jwks_response.content.decode()<|docstring|>TODO.<|endoftext|> |
f811eec348ce6a079348c3cd98d825e0f9d6a41cb9d5a6bcc63ffd0a99ad9365 | def logout(self, id_token: str):
'\n Logout the user from used Identity Provider.\n\n Provided an ID-token, this method invokes the back-channel logout\n endpoint on the Identity Provider, which logs the user out on\n their side, forcing the user to login again next time he is\n redirected to the authorization URL.\n '
response = requests.post(url=self.api_logout_url, json={'id_token': id_token})
if (response.status_code != 200):
raise RuntimeError(f'Logout returned status {response.status_code}') | Logout the user from used Identity Provider.
Provided an ID-token, this method invokes the back-channel logout
endpoint on the Identity Provider, which logs the user out on
their side, forcing the user to login again next time he is
redirected to the authorization URL. | src/auth_api/oidc/session.py | logout | Energinet-DataHub/po-auth | 1 | python | def logout(self, id_token: str):
'\n Logout the user from used Identity Provider.\n\n Provided an ID-token, this method invokes the back-channel logout\n endpoint on the Identity Provider, which logs the user out on\n their side, forcing the user to login again next time he is\n redirected to the authorization URL.\n '
response = requests.post(url=self.api_logout_url, json={'id_token': id_token})
if (response.status_code != 200):
raise RuntimeError(f'Logout returned status {response.status_code}') | def logout(self, id_token: str):
'\n Logout the user from used Identity Provider.\n\n Provided an ID-token, this method invokes the back-channel logout\n endpoint on the Identity Provider, which logs the user out on\n their side, forcing the user to login again next time he is\n redirected to the authorization URL.\n '
response = requests.post(url=self.api_logout_url, json={'id_token': id_token})
if (response.status_code != 200):
raise RuntimeError(f'Logout returned status {response.status_code}')<|docstring|>Logout the user from used Identity Provider.
Provided an ID-token, this method invokes the back-channel logout
endpoint on the Identity Provider, which logs the user out on
their side, forcing the user to login again next time he is
redirected to the authorization URL.<|endoftext|> |
6b59f62375d39308fa1dca942a5dc2ade98d6656118f7e18d740bac51fe42dc2 | def __init__(self, keys: KeysCollection, output_postfixes: Sequence[str], to_onehot: Union[(Sequence[bool], bool)]=False, num_classes: Optional[Union[(Sequence[int], int)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n output_postfixes: the postfixes to construct keys to store split data.\n for example: if the key of input data is `pred` and split 2 classes, the output\n data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])\n to_onehot: whether to convert the data to One-Hot format, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n num_classes: the class number used to convert to One-Hot format\n if `to_onehot` is True. it also can be a sequence of int, each element corresponds\n to a key in ``keys``.\n\n '
super().__init__(keys)
self.output_postfixes = output_postfixes
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.num_classes = ensure_tuple_rep(num_classes, len(self.keys))
self.splitter = SplitChannel() | Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
output_postfixes: the postfixes to construct keys to store split data.
for example: if the key of input data is `pred` and split 2 classes, the output
data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])
to_onehot: whether to convert the data to One-Hot format, default is False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
num_classes: the class number used to convert to One-Hot format
if `to_onehot` is True. it also can be a sequence of int, each element corresponds
to a key in ``keys``. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, output_postfixes: Sequence[str], to_onehot: Union[(Sequence[bool], bool)]=False, num_classes: Optional[Union[(Sequence[int], int)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n output_postfixes: the postfixes to construct keys to store split data.\n for example: if the key of input data is `pred` and split 2 classes, the output\n data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])\n to_onehot: whether to convert the data to One-Hot format, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n num_classes: the class number used to convert to One-Hot format\n if `to_onehot` is True. it also can be a sequence of int, each element corresponds\n to a key in ``keys``.\n\n '
super().__init__(keys)
self.output_postfixes = output_postfixes
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.num_classes = ensure_tuple_rep(num_classes, len(self.keys))
self.splitter = SplitChannel() | def __init__(self, keys: KeysCollection, output_postfixes: Sequence[str], to_onehot: Union[(Sequence[bool], bool)]=False, num_classes: Optional[Union[(Sequence[int], int)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n output_postfixes: the postfixes to construct keys to store split data.\n for example: if the key of input data is `pred` and split 2 classes, the output\n data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])\n to_onehot: whether to convert the data to One-Hot format, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n num_classes: the class number used to convert to One-Hot format\n if `to_onehot` is True. it also can be a sequence of int, each element corresponds\n to a key in ``keys``.\n\n '
super().__init__(keys)
self.output_postfixes = output_postfixes
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.num_classes = ensure_tuple_rep(num_classes, len(self.keys))
self.splitter = SplitChannel()<|docstring|>Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
output_postfixes: the postfixes to construct keys to store split data.
for example: if the key of input data is `pred` and split 2 classes, the output
data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])
to_onehot: whether to convert the data to One-Hot format, default is False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
num_classes: the class number used to convert to One-Hot format
if `to_onehot` is True. it also can be a sequence of int, each element corresponds
to a key in ``keys``.<|endoftext|> |
98480aaea2c74b9f5dcfbcbab1f0a46c21e2b01542f59fc1837009ed3a67faae | def __init__(self, keys: KeysCollection, sigmoid: Union[(Sequence[bool], bool)]=False, softmax: Union[(Sequence[bool], bool)]=False, other: Optional[Union[(Sequence[Callable], Callable)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n sigmoid: whether to execute sigmoid function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n softmax: whether to execute softmax function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n other: callable function to execute other activation layers,\n for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each\n element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.sigmoid = ensure_tuple_rep(sigmoid, len(self.keys))
self.softmax = ensure_tuple_rep(softmax, len(self.keys))
self.other = ensure_tuple_rep(other, len(self.keys))
self.converter = Activations() | Args:
keys: keys of the corresponding items to model output and label.
See also: :py:class:`monai.transforms.compose.MapTransform`
sigmoid: whether to execute sigmoid function on model output before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
softmax: whether to execute softmax function on model output before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
other: callable function to execute other activation layers,
for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each
element corresponds to a key in ``keys``. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, sigmoid: Union[(Sequence[bool], bool)]=False, softmax: Union[(Sequence[bool], bool)]=False, other: Optional[Union[(Sequence[Callable], Callable)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n sigmoid: whether to execute sigmoid function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n softmax: whether to execute softmax function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n other: callable function to execute other activation layers,\n for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each\n element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.sigmoid = ensure_tuple_rep(sigmoid, len(self.keys))
self.softmax = ensure_tuple_rep(softmax, len(self.keys))
self.other = ensure_tuple_rep(other, len(self.keys))
self.converter = Activations() | def __init__(self, keys: KeysCollection, sigmoid: Union[(Sequence[bool], bool)]=False, softmax: Union[(Sequence[bool], bool)]=False, other: Optional[Union[(Sequence[Callable], Callable)]]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n sigmoid: whether to execute sigmoid function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n softmax: whether to execute softmax function on model output before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n other: callable function to execute other activation layers,\n for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each\n element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.sigmoid = ensure_tuple_rep(sigmoid, len(self.keys))
self.softmax = ensure_tuple_rep(softmax, len(self.keys))
self.other = ensure_tuple_rep(other, len(self.keys))
self.converter = Activations()<|docstring|>Args:
keys: keys of the corresponding items to model output and label.
See also: :py:class:`monai.transforms.compose.MapTransform`
sigmoid: whether to execute sigmoid function on model output before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
softmax: whether to execute softmax function on model output before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
other: callable function to execute other activation layers,
for example: `other = lambda x: torch.tanh(x)`. it also can be a sequence of Callable, each
element corresponds to a key in ``keys``.<|endoftext|> |
379fe53e1c9c2c5f05034f008d7e1b9ea61655a21e32f901bacc135b9c301ee1 | def __init__(self, keys: KeysCollection, argmax: Union[(Sequence[bool], bool)]=False, to_onehot: Union[(Sequence[bool], bool)]=False, n_classes: Optional[Union[(Sequence[int], int)]]=None, threshold_values: Union[(Sequence[bool], bool)]=False, logit_thresh: Union[(Sequence[float], float)]=0.5) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n argmax: whether to execute argmax function on input data before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n to_onehot: whether to convert input data into the one-hot format. Defaults to False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n n_classes: the number of classes to convert to One-Hot format. it also can be a\n sequence of int, each element corresponds to a key in ``keys``.\n threshold_values: whether threshold the float value to int number 0 or 1, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n logit_thresh: the threshold value for thresholding operation, default is 0.5.\n it also can be a sequence of float, each element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.argmax = ensure_tuple_rep(argmax, len(self.keys))
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.n_classes = ensure_tuple_rep(n_classes, len(self.keys))
self.threshold_values = ensure_tuple_rep(threshold_values, len(self.keys))
self.logit_thresh = ensure_tuple_rep(logit_thresh, len(self.keys))
self.converter = AsDiscrete() | Args:
keys: keys of the corresponding items to model output and label.
See also: :py:class:`monai.transforms.compose.MapTransform`
argmax: whether to execute argmax function on input data before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
to_onehot: whether to convert input data into the one-hot format. Defaults to False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
n_classes: the number of classes to convert to One-Hot format. it also can be a
sequence of int, each element corresponds to a key in ``keys``.
threshold_values: whether threshold the float value to int number 0 or 1, default is False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
logit_thresh: the threshold value for thresholding operation, default is 0.5.
it also can be a sequence of float, each element corresponds to a key in ``keys``. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, argmax: Union[(Sequence[bool], bool)]=False, to_onehot: Union[(Sequence[bool], bool)]=False, n_classes: Optional[Union[(Sequence[int], int)]]=None, threshold_values: Union[(Sequence[bool], bool)]=False, logit_thresh: Union[(Sequence[float], float)]=0.5) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n argmax: whether to execute argmax function on input data before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n to_onehot: whether to convert input data into the one-hot format. Defaults to False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n n_classes: the number of classes to convert to One-Hot format. it also can be a\n sequence of int, each element corresponds to a key in ``keys``.\n threshold_values: whether threshold the float value to int number 0 or 1, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n logit_thresh: the threshold value for thresholding operation, default is 0.5.\n it also can be a sequence of float, each element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.argmax = ensure_tuple_rep(argmax, len(self.keys))
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.n_classes = ensure_tuple_rep(n_classes, len(self.keys))
self.threshold_values = ensure_tuple_rep(threshold_values, len(self.keys))
self.logit_thresh = ensure_tuple_rep(logit_thresh, len(self.keys))
self.converter = AsDiscrete() | def __init__(self, keys: KeysCollection, argmax: Union[(Sequence[bool], bool)]=False, to_onehot: Union[(Sequence[bool], bool)]=False, n_classes: Optional[Union[(Sequence[int], int)]]=None, threshold_values: Union[(Sequence[bool], bool)]=False, logit_thresh: Union[(Sequence[float], float)]=0.5) -> None:
'\n Args:\n keys: keys of the corresponding items to model output and label.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n argmax: whether to execute argmax function on input data before transform.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n to_onehot: whether to convert input data into the one-hot format. Defaults to False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n n_classes: the number of classes to convert to One-Hot format. it also can be a\n sequence of int, each element corresponds to a key in ``keys``.\n threshold_values: whether threshold the float value to int number 0 or 1, default is False.\n it also can be a sequence of bool, each element corresponds to a key in ``keys``.\n logit_thresh: the threshold value for thresholding operation, default is 0.5.\n it also can be a sequence of float, each element corresponds to a key in ``keys``.\n\n '
super().__init__(keys)
self.argmax = ensure_tuple_rep(argmax, len(self.keys))
self.to_onehot = ensure_tuple_rep(to_onehot, len(self.keys))
self.n_classes = ensure_tuple_rep(n_classes, len(self.keys))
self.threshold_values = ensure_tuple_rep(threshold_values, len(self.keys))
self.logit_thresh = ensure_tuple_rep(logit_thresh, len(self.keys))
self.converter = AsDiscrete()<|docstring|>Args:
keys: keys of the corresponding items to model output and label.
See also: :py:class:`monai.transforms.compose.MapTransform`
argmax: whether to execute argmax function on input data before transform.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
to_onehot: whether to convert input data into the one-hot format. Defaults to False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
n_classes: the number of classes to convert to One-Hot format. it also can be a
sequence of int, each element corresponds to a key in ``keys``.
threshold_values: whether threshold the float value to int number 0 or 1, default is False.
it also can be a sequence of bool, each element corresponds to a key in ``keys``.
logit_thresh: the threshold value for thresholding operation, default is 0.5.
it also can be a sequence of float, each element corresponds to a key in ``keys``.<|endoftext|> |
0a3282145c11e467fee9aaa1c471aecf523064aa06ae658cc4e92c73f248684f | def __init__(self, keys: KeysCollection, applied_labels: Union[(Sequence[int], int)], independent: bool=True, connectivity: Optional[int]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n applied_labels: Labels for applying the connected component on.\n If only one channel. The pixel whose value is not in this list will remain unchanged.\n If the data is in one-hot format, this is the channel indices to apply transform.\n independent: consider several labels as a whole or independent, default is `True`.\n Example use case would be segment label 1 is liver and label 2 is liver tumor, in that case\n you want this "independent" to be specified as False.\n connectivity: Maximum number of orthogonal hops to consider a pixel/voxel as a neighbor.\n Accepted values are ranging from 1 to input.ndim. If ``None``, a full\n connectivity of ``input.ndim`` is used.\n\n '
super().__init__(keys)
self.converter = KeepLargestConnectedComponent(applied_labels, independent, connectivity) | Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
applied_labels: Labels for applying the connected component on.
If only one channel. The pixel whose value is not in this list will remain unchanged.
If the data is in one-hot format, this is the channel indices to apply transform.
independent: consider several labels as a whole or independent, default is `True`.
Example use case would be segment label 1 is liver and label 2 is liver tumor, in that case
you want this "independent" to be specified as False.
connectivity: Maximum number of orthogonal hops to consider a pixel/voxel as a neighbor.
Accepted values are ranging from 1 to input.ndim. If ``None``, a full
connectivity of ``input.ndim`` is used. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, applied_labels: Union[(Sequence[int], int)], independent: bool=True, connectivity: Optional[int]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n applied_labels: Labels for applying the connected component on.\n If only one channel. The pixel whose value is not in this list will remain unchanged.\n If the data is in one-hot format, this is the channel indices to apply transform.\n independent: consider several labels as a whole or independent, default is `True`.\n Example use case would be segment label 1 is liver and label 2 is liver tumor, in that case\n you want this "independent" to be specified as False.\n connectivity: Maximum number of orthogonal hops to consider a pixel/voxel as a neighbor.\n Accepted values are ranging from 1 to input.ndim. If ``None``, a full\n connectivity of ``input.ndim`` is used.\n\n '
super().__init__(keys)
self.converter = KeepLargestConnectedComponent(applied_labels, independent, connectivity) | def __init__(self, keys: KeysCollection, applied_labels: Union[(Sequence[int], int)], independent: bool=True, connectivity: Optional[int]=None) -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n applied_labels: Labels for applying the connected component on.\n If only one channel. The pixel whose value is not in this list will remain unchanged.\n If the data is in one-hot format, this is the channel indices to apply transform.\n independent: consider several labels as a whole or independent, default is `True`.\n Example use case would be segment label 1 is liver and label 2 is liver tumor, in that case\n you want this "independent" to be specified as False.\n connectivity: Maximum number of orthogonal hops to consider a pixel/voxel as a neighbor.\n Accepted values are ranging from 1 to input.ndim. If ``None``, a full\n connectivity of ``input.ndim`` is used.\n\n '
super().__init__(keys)
self.converter = KeepLargestConnectedComponent(applied_labels, independent, connectivity)<|docstring|>Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
applied_labels: Labels for applying the connected component on.
If only one channel. The pixel whose value is not in this list will remain unchanged.
If the data is in one-hot format, this is the channel indices to apply transform.
independent: consider several labels as a whole or independent, default is `True`.
Example use case would be segment label 1 is liver and label 2 is liver tumor, in that case
you want this "independent" to be specified as False.
connectivity: Maximum number of orthogonal hops to consider a pixel/voxel as a neighbor.
Accepted values are ranging from 1 to input.ndim. If ``None``, a full
connectivity of ``input.ndim`` is used.<|endoftext|> |
d18004c4ed890220d65f907a76461efe533d12402bcca9aebb3b08729f72bfda | def __init__(self, keys: KeysCollection, kernel_type: str='Laplace') -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n kernel_type: the method applied to do edge detection, default is "Laplace".\n\n '
super().__init__(keys)
self.converter = LabelToContour(kernel_type=kernel_type) | Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
kernel_type: the method applied to do edge detection, default is "Laplace". | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, kernel_type: str='Laplace') -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n kernel_type: the method applied to do edge detection, default is "Laplace".\n\n '
super().__init__(keys)
self.converter = LabelToContour(kernel_type=kernel_type) | def __init__(self, keys: KeysCollection, kernel_type: str='Laplace') -> None:
'\n Args:\n keys: keys of the corresponding items to be transformed.\n See also: :py:class:`monai.transforms.compose.MapTransform`\n kernel_type: the method applied to do edge detection, default is "Laplace".\n\n '
super().__init__(keys)
self.converter = LabelToContour(kernel_type=kernel_type)<|docstring|>Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
kernel_type: the method applied to do edge detection, default is "Laplace".<|endoftext|> |
9acfd4326097c83c9905e26b04982c3cc0aa1af1d9b2352adf9ae5efbe9cb492 | def __init__(self, keys: KeysCollection, ensemble: Callable[([Union[(Sequence[torch.Tensor], torch.Tensor)]], torch.Tensor)], output_key: Optional[str]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n ensemble: callable method to execute ensemble on specified data.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n\n Raises:\n TypeError: When ``ensemble`` is not ``callable``.\n ValueError: When ``len(keys) > 1`` and ``output_key=None``. Incompatible values.\n\n "
super().__init__(keys)
if (not callable(ensemble)):
raise TypeError(f'ensemble must be callable but is {type(ensemble).__name__}.')
self.ensemble = ensemble
if ((len(self.keys) > 1) and (output_key is None)):
raise ValueError('Incompatible values: len(self.keys) > 1 and output_key=None.')
self.output_key = (output_key if (output_key is not None) else self.keys[0]) | Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
ensemble: callable method to execute ensemble on specified data.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
Raises:
TypeError: When ``ensemble`` is not ``callable``.
ValueError: When ``len(keys) > 1`` and ``output_key=None``. Incompatible values. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, ensemble: Callable[([Union[(Sequence[torch.Tensor], torch.Tensor)]], torch.Tensor)], output_key: Optional[str]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n ensemble: callable method to execute ensemble on specified data.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n\n Raises:\n TypeError: When ``ensemble`` is not ``callable``.\n ValueError: When ``len(keys) > 1`` and ``output_key=None``. Incompatible values.\n\n "
super().__init__(keys)
if (not callable(ensemble)):
raise TypeError(f'ensemble must be callable but is {type(ensemble).__name__}.')
self.ensemble = ensemble
if ((len(self.keys) > 1) and (output_key is None)):
raise ValueError('Incompatible values: len(self.keys) > 1 and output_key=None.')
self.output_key = (output_key if (output_key is not None) else self.keys[0]) | def __init__(self, keys: KeysCollection, ensemble: Callable[([Union[(Sequence[torch.Tensor], torch.Tensor)]], torch.Tensor)], output_key: Optional[str]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n ensemble: callable method to execute ensemble on specified data.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n\n Raises:\n TypeError: When ``ensemble`` is not ``callable``.\n ValueError: When ``len(keys) > 1`` and ``output_key=None``. Incompatible values.\n\n "
super().__init__(keys)
if (not callable(ensemble)):
raise TypeError(f'ensemble must be callable but is {type(ensemble).__name__}.')
self.ensemble = ensemble
if ((len(self.keys) > 1) and (output_key is None)):
raise ValueError('Incompatible values: len(self.keys) > 1 and output_key=None.')
self.output_key = (output_key if (output_key is not None) else self.keys[0])<|docstring|>Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
ensemble: callable method to execute ensemble on specified data.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
Raises:
TypeError: When ``ensemble`` is not ``callable``.
ValueError: When ``len(keys) > 1`` and ``output_key=None``. Incompatible values.<|endoftext|> |
b503f318ec4a29a0a2299eaede623c720a16cc07dc1692c552aaa21b817a5caf | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, weights: Optional[Union[(Sequence[float], torch.Tensor, np.ndarray)]]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n weights: can be a list or tuple of numbers for input data with shape: [E, B, C, H, W[, D]].\n or a Numpy ndarray or a PyTorch Tensor data.\n the `weights` will be added to input data from highest dimension, for example:\n 1. if the `weights` only has 1 dimension, it will be added to the `E` dimension of input data.\n 2. if the `weights` has 3 dimensions, it will be added to `E`, `B` and `C` dimensions.\n it's a typical practice to add weights for different classes:\n to ensemble 3 segmentation model outputs, every output has 4 channels(classes),\n so the input data shape can be: [3, B, 4, H, W, D].\n and add different `weights` for different classes, so the `weights` shape can be: [3, 1, 4].\n for example: `weights = [[[1, 2, 3, 4]], [[4, 3, 2, 1]], [[1, 1, 1, 1]]]`.\n\n "
ensemble = MeanEnsemble(weights=weights)
super().__init__(keys, ensemble, output_key) | Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
weights: can be a list or tuple of numbers for input data with shape: [E, B, C, H, W[, D]].
or a Numpy ndarray or a PyTorch Tensor data.
the `weights` will be added to input data from highest dimension, for example:
1. if the `weights` only has 1 dimension, it will be added to the `E` dimension of input data.
2. if the `weights` has 3 dimensions, it will be added to `E`, `B` and `C` dimensions.
it's a typical practice to add weights for different classes:
to ensemble 3 segmentation model outputs, every output has 4 channels(classes),
so the input data shape can be: [3, B, 4, H, W, D].
and add different `weights` for different classes, so the `weights` shape can be: [3, 1, 4].
for example: `weights = [[[1, 2, 3, 4]], [[4, 3, 2, 1]], [[1, 1, 1, 1]]]`. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, weights: Optional[Union[(Sequence[float], torch.Tensor, np.ndarray)]]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n weights: can be a list or tuple of numbers for input data with shape: [E, B, C, H, W[, D]].\n or a Numpy ndarray or a PyTorch Tensor data.\n the `weights` will be added to input data from highest dimension, for example:\n 1. if the `weights` only has 1 dimension, it will be added to the `E` dimension of input data.\n 2. if the `weights` has 3 dimensions, it will be added to `E`, `B` and `C` dimensions.\n it's a typical practice to add weights for different classes:\n to ensemble 3 segmentation model outputs, every output has 4 channels(classes),\n so the input data shape can be: [3, B, 4, H, W, D].\n and add different `weights` for different classes, so the `weights` shape can be: [3, 1, 4].\n for example: `weights = [[[1, 2, 3, 4]], [[4, 3, 2, 1]], [[1, 1, 1, 1]]]`.\n\n "
ensemble = MeanEnsemble(weights=weights)
super().__init__(keys, ensemble, output_key) | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, weights: Optional[Union[(Sequence[float], torch.Tensor, np.ndarray)]]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n weights: can be a list or tuple of numbers for input data with shape: [E, B, C, H, W[, D]].\n or a Numpy ndarray or a PyTorch Tensor data.\n the `weights` will be added to input data from highest dimension, for example:\n 1. if the `weights` only has 1 dimension, it will be added to the `E` dimension of input data.\n 2. if the `weights` has 3 dimensions, it will be added to `E`, `B` and `C` dimensions.\n it's a typical practice to add weights for different classes:\n to ensemble 3 segmentation model outputs, every output has 4 channels(classes),\n so the input data shape can be: [3, B, 4, H, W, D].\n and add different `weights` for different classes, so the `weights` shape can be: [3, 1, 4].\n for example: `weights = [[[1, 2, 3, 4]], [[4, 3, 2, 1]], [[1, 1, 1, 1]]]`.\n\n "
ensemble = MeanEnsemble(weights=weights)
super().__init__(keys, ensemble, output_key)<|docstring|>Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
weights: can be a list or tuple of numbers for input data with shape: [E, B, C, H, W[, D]].
or a Numpy ndarray or a PyTorch Tensor data.
the `weights` will be added to input data from highest dimension, for example:
1. if the `weights` only has 1 dimension, it will be added to the `E` dimension of input data.
2. if the `weights` has 3 dimensions, it will be added to `E`, `B` and `C` dimensions.
it's a typical practice to add weights for different classes:
to ensemble 3 segmentation model outputs, every output has 4 channels(classes),
so the input data shape can be: [3, B, 4, H, W, D].
and add different `weights` for different classes, so the `weights` shape can be: [3, 1, 4].
for example: `weights = [[[1, 2, 3, 4]], [[4, 3, 2, 1]], [[1, 1, 1, 1]]]`.<|endoftext|> |
d3d3c9e833c635e62f93a5a5ad023bdcf93d2a3001f6d7f62af7f98d9579e129 | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, num_classes: Optional[int]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n num_classes: if the input is single channel data instead of One-Hot, we can't get class number\n from channel, need to explicitly specify the number of classes to vote.\n\n "
ensemble = VoteEnsemble(num_classes=num_classes)
super().__init__(keys, ensemble, output_key) | Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
num_classes: if the input is single channel data instead of One-Hot, we can't get class number
from channel, need to explicitly specify the number of classes to vote. | monai/transforms/post/dictionary.py | __init__ | dzenanz/MONAI | 3 | python | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, num_classes: Optional[int]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n num_classes: if the input is single channel data instead of One-Hot, we can't get class number\n from channel, need to explicitly specify the number of classes to vote.\n\n "
ensemble = VoteEnsemble(num_classes=num_classes)
super().__init__(keys, ensemble, output_key) | def __init__(self, keys: KeysCollection, output_key: Optional[str]=None, num_classes: Optional[int]=None) -> None:
"\n Args:\n keys: keys of the corresponding items to be stack and execute ensemble.\n if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.\n output_key: the key to store ensemble result in the dictionary.\n if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.\n num_classes: if the input is single channel data instead of One-Hot, we can't get class number\n from channel, need to explicitly specify the number of classes to vote.\n\n "
ensemble = VoteEnsemble(num_classes=num_classes)
super().__init__(keys, ensemble, output_key)<|docstring|>Args:
keys: keys of the corresponding items to be stack and execute ensemble.
if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
output_key: the key to store ensemble result in the dictionary.
if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
num_classes: if the input is single channel data instead of One-Hot, we can't get class number
from channel, need to explicitly specify the number of classes to vote.<|endoftext|> |
df321a4d212b18579bd4574d45e45d316934807a98356de69fa977c13ddc7bb7 | async def fetch_worker(queue: asyncio.Queue, engine):
"\n The worker task performing items added to the Engine's Queue\n\n Args:\n queue (asyncio.Queue): The Queue \n engine (BaseFetchingEngine): The engine itself\n "
engine: BaseFetchingEngine
register: FetcherRegister = engine.register
while True:
event: FetchEvent
callback: Coroutine
(event, callback) = (await queue.get())
try:
fetcher = register.get_fetcher_for_event(event)
async with fetcher:
res = (await fetcher.fetch())
data = (await fetcher.process(res))
try:
(await callback(data))
except Exception as err:
logger.exception(f'Fetcher callback - {callback} failed')
(await engine._on_failure(err, event))
except Exception as err:
logger.exception('Failed to process fetch event')
(await engine._on_failure(err, event))
finally:
queue.task_done() | The worker task performing items added to the Engine's Queue
Args:
queue (asyncio.Queue): The Queue
engine (BaseFetchingEngine): The engine itself | opal_common/fetcher/engine/fetch_worker.py | fetch_worker | pujan14/opal | 367 | python | async def fetch_worker(queue: asyncio.Queue, engine):
"\n The worker task performing items added to the Engine's Queue\n\n Args:\n queue (asyncio.Queue): The Queue \n engine (BaseFetchingEngine): The engine itself\n "
engine: BaseFetchingEngine
register: FetcherRegister = engine.register
while True:
event: FetchEvent
callback: Coroutine
(event, callback) = (await queue.get())
try:
fetcher = register.get_fetcher_for_event(event)
async with fetcher:
res = (await fetcher.fetch())
data = (await fetcher.process(res))
try:
(await callback(data))
except Exception as err:
logger.exception(f'Fetcher callback - {callback} failed')
(await engine._on_failure(err, event))
except Exception as err:
logger.exception('Failed to process fetch event')
(await engine._on_failure(err, event))
finally:
queue.task_done() | async def fetch_worker(queue: asyncio.Queue, engine):
"\n The worker task performing items added to the Engine's Queue\n\n Args:\n queue (asyncio.Queue): The Queue \n engine (BaseFetchingEngine): The engine itself\n "
engine: BaseFetchingEngine
register: FetcherRegister = engine.register
while True:
event: FetchEvent
callback: Coroutine
(event, callback) = (await queue.get())
try:
fetcher = register.get_fetcher_for_event(event)
async with fetcher:
res = (await fetcher.fetch())
data = (await fetcher.process(res))
try:
(await callback(data))
except Exception as err:
logger.exception(f'Fetcher callback - {callback} failed')
(await engine._on_failure(err, event))
except Exception as err:
logger.exception('Failed to process fetch event')
(await engine._on_failure(err, event))
finally:
queue.task_done()<|docstring|>The worker task performing items added to the Engine's Queue
Args:
queue (asyncio.Queue): The Queue
engine (BaseFetchingEngine): The engine itself<|endoftext|> |
1e500ec44d8f21e2a8020df3635795acaa570f6e210edaca5a2e596fdebd92a5 | def object_link(self, obj):
'Returns the admin link to the log entry object if it exists.'
admin_url = (None if obj.is_deletion() else obj.get_admin_url())
if admin_url:
return format_html('<a href="{}">{}</a>', admin_url, obj.object_repr)
else:
return obj.object_repr | Returns the admin link to the log entry object if it exists. | radical_translations/utils/admin.py | object_link | kingsdigitallab/radical_translations | 3 | python | def object_link(self, obj):
admin_url = (None if obj.is_deletion() else obj.get_admin_url())
if admin_url:
return format_html('<a href="{}">{}</a>', admin_url, obj.object_repr)
else:
return obj.object_repr | def object_link(self, obj):
admin_url = (None if obj.is_deletion() else obj.get_admin_url())
if admin_url:
return format_html('<a href="{}">{}</a>', admin_url, obj.object_repr)
else:
return obj.object_repr<|docstring|>Returns the admin link to the log entry object if it exists.<|endoftext|> |
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