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 |
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9f89ef537db0ca912ad609f7bb9a1549b709f82c239dc1f1e49af398c4735b49 | def _update_dependent_attributes_(self) -> None:
'\n Atualiza atributos que tem dependências de tempo ou de outros atibutos que podem mudar\n '
print('Atualizando atributos dependentes.')
(self.date, self.time) = get_current_time_and_data()
self.image_name = ((((((((('#' + str(self.training_idx)) + '|') + self.date) + '|') + self.time) + '|') + '|epoch=') + str((self.last_epoch + self.number_of_epochs))) + '.png')
self.sub_dir_0 = 'Relatorios-Dados-etc/Resultados/'
self.sub_dir_1 = (self.dataset_name + '/')
self.sub_dir_2 = (self.model_name.replace('.json', '') + '/')
self.sub_dir_3 = (str(self.training_idx) + '/')
self.data_path = (((self.sub_dir_0 + self.sub_dir_1) + self.sub_dir_2) + self.sub_dir_3)
csv_name: str = (('csv-#' + str(self.training_idx)) + '.log')
self.csv_pathname: str = (self.data_path + csv_name)
self.last_epoch: int = get_last_epoch(self.csv_pathname)
self.model_save_pathname: str = (((self.data_path + '#') + str(self.training_idx)) + '-checkp') | Atualiza atributos que tem dependências de tempo ou de outros atibutos que podem mudar | old/automatic_training.py | _update_dependent_attributes_ | AlanPXD/IC-AutoEncoder | 0 | python | def _update_dependent_attributes_(self) -> None:
'\n \n '
print('Atualizando atributos dependentes.')
(self.date, self.time) = get_current_time_and_data()
self.image_name = ((((((((('#' + str(self.training_idx)) + '|') + self.date) + '|') + self.time) + '|') + '|epoch=') + str((self.last_epoch + self.number_of_epochs))) + '.png')
self.sub_dir_0 = 'Relatorios-Dados-etc/Resultados/'
self.sub_dir_1 = (self.dataset_name + '/')
self.sub_dir_2 = (self.model_name.replace('.json', ) + '/')
self.sub_dir_3 = (str(self.training_idx) + '/')
self.data_path = (((self.sub_dir_0 + self.sub_dir_1) + self.sub_dir_2) + self.sub_dir_3)
csv_name: str = (('csv-#' + str(self.training_idx)) + '.log')
self.csv_pathname: str = (self.data_path + csv_name)
self.last_epoch: int = get_last_epoch(self.csv_pathname)
self.model_save_pathname: str = (((self.data_path + '#') + str(self.training_idx)) + '-checkp') | def _update_dependent_attributes_(self) -> None:
'\n \n '
print('Atualizando atributos dependentes.')
(self.date, self.time) = get_current_time_and_data()
self.image_name = ((((((((('#' + str(self.training_idx)) + '|') + self.date) + '|') + self.time) + '|') + '|epoch=') + str((self.last_epoch + self.number_of_epochs))) + '.png')
self.sub_dir_0 = 'Relatorios-Dados-etc/Resultados/'
self.sub_dir_1 = (self.dataset_name + '/')
self.sub_dir_2 = (self.model_name.replace('.json', ) + '/')
self.sub_dir_3 = (str(self.training_idx) + '/')
self.data_path = (((self.sub_dir_0 + self.sub_dir_1) + self.sub_dir_2) + self.sub_dir_3)
csv_name: str = (('csv-#' + str(self.training_idx)) + '.log')
self.csv_pathname: str = (self.data_path + csv_name)
self.last_epoch: int = get_last_epoch(self.csv_pathname)
self.model_save_pathname: str = (((self.data_path + '#') + str(self.training_idx)) + '-checkp')<|docstring|>Atualiza atributos que tem dependências de tempo ou de outros atibutos que podem mudar<|endoftext|> |
0acfcfdf7bda56b6b7793f0f523118b1cb96e23a8abce36dbaaf1827d3e5a9b5 | def change_attributes(self, kw_att_and_val: dict) -> None:
"\n ## Função:\n\n Muda determinados atributos especificadoes na forma de keyword e valor.\n\n ## Retorna:\n\n Sem retorno\n\n ## Exemplo:\n \n Caso queira mudar o nome do modelo a ser usado e do otimizador escreva:\n\n >>> Kw_att_and_val = {'model_name': 'nome', 'optimizer': optimizer_class}\n # note que 'model_name' e 'optimizer' são atributos de Auto_training\n "
print('Mudando atributos selecionados')
def recursive_update(dictionary: dict, Kw):
for (key, value) in Kw.items():
if (type(value) == dict):
if (key[0] == '*'):
dictionary[key[1:]] = value
else:
recursive_update(dictionary[key], value)
else:
dictionary[key] = value
recursive_update(self.__dict__, kw_att_and_val)
self._update_dependent_attributes_() | ## Função:
Muda determinados atributos especificadoes na forma de keyword e valor.
## Retorna:
Sem retorno
## Exemplo:
Caso queira mudar o nome do modelo a ser usado e do otimizador escreva:
>>> Kw_att_and_val = {'model_name': 'nome', 'optimizer': optimizer_class}
# note que 'model_name' e 'optimizer' são atributos de Auto_training | old/automatic_training.py | change_attributes | AlanPXD/IC-AutoEncoder | 0 | python | def change_attributes(self, kw_att_and_val: dict) -> None:
"\n ## Função:\n\n Muda determinados atributos especificadoes na forma de keyword e valor.\n\n ## Retorna:\n\n Sem retorno\n\n ## Exemplo:\n \n Caso queira mudar o nome do modelo a ser usado e do otimizador escreva:\n\n >>> Kw_att_and_val = {'model_name': 'nome', 'optimizer': optimizer_class}\n # note que 'model_name' e 'optimizer' são atributos de Auto_training\n "
print('Mudando atributos selecionados')
def recursive_update(dictionary: dict, Kw):
for (key, value) in Kw.items():
if (type(value) == dict):
if (key[0] == '*'):
dictionary[key[1:]] = value
else:
recursive_update(dictionary[key], value)
else:
dictionary[key] = value
recursive_update(self.__dict__, kw_att_and_val)
self._update_dependent_attributes_() | def change_attributes(self, kw_att_and_val: dict) -> None:
"\n ## Função:\n\n Muda determinados atributos especificadoes na forma de keyword e valor.\n\n ## Retorna:\n\n Sem retorno\n\n ## Exemplo:\n \n Caso queira mudar o nome do modelo a ser usado e do otimizador escreva:\n\n >>> Kw_att_and_val = {'model_name': 'nome', 'optimizer': optimizer_class}\n # note que 'model_name' e 'optimizer' são atributos de Auto_training\n "
print('Mudando atributos selecionados')
def recursive_update(dictionary: dict, Kw):
for (key, value) in Kw.items():
if (type(value) == dict):
if (key[0] == '*'):
dictionary[key[1:]] = value
else:
recursive_update(dictionary[key], value)
else:
dictionary[key] = value
recursive_update(self.__dict__, kw_att_and_val)
self._update_dependent_attributes_()<|docstring|>## Função:
Muda determinados atributos especificadoes na forma de keyword e valor.
## Retorna:
Sem retorno
## Exemplo:
Caso queira mudar o nome do modelo a ser usado e do otimizador escreva:
>>> Kw_att_and_val = {'model_name': 'nome', 'optimizer': optimizer_class}
# note que 'model_name' e 'optimizer' são atributos de Auto_training<|endoftext|> |
2bd85389fddbf450cf88b4605b1acb830e5e36258c667ab4829aa33ae6eccd60 | def save_state(self) -> None:
'\n ## Função :\n\n Salva o estado atual do objeto.\n '
print('Saving the actual state.')
self._check_if_dirs_exists_()
with open(self.state_pathname, 'wb') as file:
pickle.dump(self.state, file, pickle.HIGHEST_PROTOCOL)
file.close() | ## Função :
Salva o estado atual do objeto. | old/automatic_training.py | save_state | AlanPXD/IC-AutoEncoder | 0 | python | def save_state(self) -> None:
'\n ## Função :\n\n Salva o estado atual do objeto.\n '
print('Saving the actual state.')
self._check_if_dirs_exists_()
with open(self.state_pathname, 'wb') as file:
pickle.dump(self.state, file, pickle.HIGHEST_PROTOCOL)
file.close() | def save_state(self) -> None:
'\n ## Função :\n\n Salva o estado atual do objeto.\n '
print('Saving the actual state.')
self._check_if_dirs_exists_()
with open(self.state_pathname, 'wb') as file:
pickle.dump(self.state, file, pickle.HIGHEST_PROTOCOL)
file.close()<|docstring|>## Função :
Salva o estado atual do objeto.<|endoftext|> |
e676fe766e68473cc911a683d848e987feb8f0fc884ba7e9a60ac67c430c69b0 | def load_state(self) -> None:
'\n ## Função :\n\n Carrega o estado armazenado no arquivo\n '
print('Loading the actual state.')
if file_exists(self.state_pathname):
with open(self.state_pathname, 'rb') as file:
previous_obj: Training_State = pickle.load(file)
self.state = previous_obj
file.close() | ## Função :
Carrega o estado armazenado no arquivo | old/automatic_training.py | load_state | AlanPXD/IC-AutoEncoder | 0 | python | def load_state(self) -> None:
'\n ## Função :\n\n Carrega o estado armazenado no arquivo\n '
print('Loading the actual state.')
if file_exists(self.state_pathname):
with open(self.state_pathname, 'rb') as file:
previous_obj: Training_State = pickle.load(file)
self.state = previous_obj
file.close() | def load_state(self) -> None:
'\n ## Função :\n\n Carrega o estado armazenado no arquivo\n '
print('Loading the actual state.')
if file_exists(self.state_pathname):
with open(self.state_pathname, 'rb') as file:
previous_obj: Training_State = pickle.load(file)
self.state = previous_obj
file.close()<|docstring|>## Função :
Carrega o estado armazenado no arquivo<|endoftext|> |
59c91dc45371c50ff015b3dc9c0f337bf3027dd26a6da60ced6c8ec53ed9e151 | def _check_if_dirs_exists_(self) -> None:
'\n ## Função:\n\n Verifica se todos os diretórios que compoem os diretorios existem.\n E no caso de não existirem, o método cria esses diretórios.\n\n ## Exemplo: \n * `Relatorios-Dados-etc/Imagens de resultados`\n\n São dois diretórios, ambos serão criados caso ja não existam na pasta\n onde o programa é executado.\n '
print('checking if the dirs exists')
if (not isdir(dirname(self.state.csv_pathname))):
makedirs(dirname(self.state.csv_pathname))
if (not isdir(dirname(self.state.data_path))):
makedirs(dirname(self.state.data_path))
if (not isdir(dirname(self.state_pathname))):
makedirs(dirname(self.state_pathname))
if (not isdir(dirname(self.state.dataframe_pathname))):
makedirs(dirname(self.state.dataframe_pathname))
if (not isdir(dirname(self.state.model_save_pathname))):
makedirs(dirname(self.state.model_save_pathname)) | ## Função:
Verifica se todos os diretórios que compoem os diretorios existem.
E no caso de não existirem, o método cria esses diretórios.
## Exemplo:
* `Relatorios-Dados-etc/Imagens de resultados`
São dois diretórios, ambos serão criados caso ja não existam na pasta
onde o programa é executado. | old/automatic_training.py | _check_if_dirs_exists_ | AlanPXD/IC-AutoEncoder | 0 | python | def _check_if_dirs_exists_(self) -> None:
'\n ## Função:\n\n Verifica se todos os diretórios que compoem os diretorios existem.\n E no caso de não existirem, o método cria esses diretórios.\n\n ## Exemplo: \n * `Relatorios-Dados-etc/Imagens de resultados`\n\n São dois diretórios, ambos serão criados caso ja não existam na pasta\n onde o programa é executado.\n '
print('checking if the dirs exists')
if (not isdir(dirname(self.state.csv_pathname))):
makedirs(dirname(self.state.csv_pathname))
if (not isdir(dirname(self.state.data_path))):
makedirs(dirname(self.state.data_path))
if (not isdir(dirname(self.state_pathname))):
makedirs(dirname(self.state_pathname))
if (not isdir(dirname(self.state.dataframe_pathname))):
makedirs(dirname(self.state.dataframe_pathname))
if (not isdir(dirname(self.state.model_save_pathname))):
makedirs(dirname(self.state.model_save_pathname)) | def _check_if_dirs_exists_(self) -> None:
'\n ## Função:\n\n Verifica se todos os diretórios que compoem os diretorios existem.\n E no caso de não existirem, o método cria esses diretórios.\n\n ## Exemplo: \n * `Relatorios-Dados-etc/Imagens de resultados`\n\n São dois diretórios, ambos serão criados caso ja não existam na pasta\n onde o programa é executado.\n '
print('checking if the dirs exists')
if (not isdir(dirname(self.state.csv_pathname))):
makedirs(dirname(self.state.csv_pathname))
if (not isdir(dirname(self.state.data_path))):
makedirs(dirname(self.state.data_path))
if (not isdir(dirname(self.state_pathname))):
makedirs(dirname(self.state_pathname))
if (not isdir(dirname(self.state.dataframe_pathname))):
makedirs(dirname(self.state.dataframe_pathname))
if (not isdir(dirname(self.state.model_save_pathname))):
makedirs(dirname(self.state.model_save_pathname))<|docstring|>## Função:
Verifica se todos os diretórios que compoem os diretorios existem.
E no caso de não existirem, o método cria esses diretórios.
## Exemplo:
* `Relatorios-Dados-etc/Imagens de resultados`
São dois diretórios, ambos serão criados caso ja não existam na pasta
onde o programa é executado.<|endoftext|> |
c7b307dad5a9b1e0a06b15294810bad35bb66cdb878695f1becaab554755fb57 | def _load_model_(self) -> Model:
'\n ## Função:\n\n Carrega o modelo de rede neural definido no atributo `model_name`, \n junto dos pesos armazenados no checkpoint definido no atibuto `checkpoint_name`\n '
print('Trying to load a previous state of training.')
if file_exists(self.state.model_save_pathname):
nNet: Model = load_model(self.state.model_save_pathname, custom_objects={self.state.loss().name: self.state.loss}, compile=True)
print('Previous state loaded.')
return nNet
print('Loading just the model.')
try:
json_file = open((self.state.models_dir + self.state.model_name), 'r')
except FileNotFoundError:
raise Exception(((('Fail attempt to load the model ' + self.state.model_name) + ' at ') + self.state.models_dir))
json_readed = json_file.read()
nNet: Model = model_from_json(json_readed)
json_file.close()
return nNet | ## Função:
Carrega o modelo de rede neural definido no atributo `model_name`,
junto dos pesos armazenados no checkpoint definido no atibuto `checkpoint_name` | old/automatic_training.py | _load_model_ | AlanPXD/IC-AutoEncoder | 0 | python | def _load_model_(self) -> Model:
'\n ## Função:\n\n Carrega o modelo de rede neural definido no atributo `model_name`, \n junto dos pesos armazenados no checkpoint definido no atibuto `checkpoint_name`\n '
print('Trying to load a previous state of training.')
if file_exists(self.state.model_save_pathname):
nNet: Model = load_model(self.state.model_save_pathname, custom_objects={self.state.loss().name: self.state.loss}, compile=True)
print('Previous state loaded.')
return nNet
print('Loading just the model.')
try:
json_file = open((self.state.models_dir + self.state.model_name), 'r')
except FileNotFoundError:
raise Exception(((('Fail attempt to load the model ' + self.state.model_name) + ' at ') + self.state.models_dir))
json_readed = json_file.read()
nNet: Model = model_from_json(json_readed)
json_file.close()
return nNet | def _load_model_(self) -> Model:
'\n ## Função:\n\n Carrega o modelo de rede neural definido no atributo `model_name`, \n junto dos pesos armazenados no checkpoint definido no atibuto `checkpoint_name`\n '
print('Trying to load a previous state of training.')
if file_exists(self.state.model_save_pathname):
nNet: Model = load_model(self.state.model_save_pathname, custom_objects={self.state.loss().name: self.state.loss}, compile=True)
print('Previous state loaded.')
return nNet
print('Loading just the model.')
try:
json_file = open((self.state.models_dir + self.state.model_name), 'r')
except FileNotFoundError:
raise Exception(((('Fail attempt to load the model ' + self.state.model_name) + ' at ') + self.state.models_dir))
json_readed = json_file.read()
nNet: Model = model_from_json(json_readed)
json_file.close()
return nNet<|docstring|>## Função:
Carrega o modelo de rede neural definido no atributo `model_name`,
junto dos pesos armazenados no checkpoint definido no atibuto `checkpoint_name`<|endoftext|> |
c0aee458bb1d69435e2d1bd5499f29f382476225af72bd3abbcb248a4ddb52e7 | def _get_last_epoch_(self) -> int:
'\n ## Função:\n\n Retorna a ultima época treinada de um checkpoint. \n\n obs: retorna -1 quando nenhum treino foi realizado para o treino inciar na época 0.\n '
last_epoch: int
if file_exists(self.state.csv_pathname):
dataframe = self.get_csv_training_history()
if dataframe.empty:
last_epoch = (- 1)
else:
last_epoch = dataframe['epoch'].tolist()[(- 1)]
else:
last_epoch = (- 1)
return last_epoch | ## Função:
Retorna a ultima época treinada de um checkpoint.
obs: retorna -1 quando nenhum treino foi realizado para o treino inciar na época 0. | old/automatic_training.py | _get_last_epoch_ | AlanPXD/IC-AutoEncoder | 0 | python | def _get_last_epoch_(self) -> int:
'\n ## Função:\n\n Retorna a ultima época treinada de um checkpoint. \n\n obs: retorna -1 quando nenhum treino foi realizado para o treino inciar na época 0.\n '
last_epoch: int
if file_exists(self.state.csv_pathname):
dataframe = self.get_csv_training_history()
if dataframe.empty:
last_epoch = (- 1)
else:
last_epoch = dataframe['epoch'].tolist()[(- 1)]
else:
last_epoch = (- 1)
return last_epoch | def _get_last_epoch_(self) -> int:
'\n ## Função:\n\n Retorna a ultima época treinada de um checkpoint. \n\n obs: retorna -1 quando nenhum treino foi realizado para o treino inciar na época 0.\n '
last_epoch: int
if file_exists(self.state.csv_pathname):
dataframe = self.get_csv_training_history()
if dataframe.empty:
last_epoch = (- 1)
else:
last_epoch = dataframe['epoch'].tolist()[(- 1)]
else:
last_epoch = (- 1)
return last_epoch<|docstring|>## Função:
Retorna a ultima época treinada de um checkpoint.
obs: retorna -1 quando nenhum treino foi realizado para o treino inciar na época 0.<|endoftext|> |
3ad2469910f05b158617b0fb64539227b258ce5029e6216ddc732c64e5a39ba2 | def start_training(self) -> None:
'\n ## Function:\n\n Starts the training\n\n ## Receives:\n\n Nothing\n\n ## Returns:\n\n None\n\n ## Examples:\n\n ...\n \n ## Raises:\n\n Nothing.\n '
dataset: DataSet = DataSet()
dataset.load_by_name(self.state.dataset_name)
x_train = dataset.x_train
x_test = dataset.x_test
y_train = dataset.y_train
y_test = dataset.y_test
neural_net: Model = self._load_model_()
neural_net.compile(optimizer=self.state.optimizer(**self.state.optimizer_kwargs), loss=self.state.loss(**self.state.loss_kwargs), **self.state.compile_kwargs)
self._check_if_dirs_exists_()
csv_logger = CSVLogger(filename=self.state.csv_pathname, separator=';', append=True)
standard_callbacks: list = [csv_logger]
neural_net.fit(x=x_train, y=y_train, validation_data=(x_test, y_test), initial_epoch=(self._get_last_epoch_() + 1), callbacks=standard_callbacks, epochs=((self.state.last_epoch + self.state.number_of_epochs) + 1), **self.state.fit_Kwargs)
neural_net.save(filepath=self.state.model_save_pathname)
self.save_data_to_dataframe()
self.state._update_dependent_attributes_()
self.save_state() | ## Function:
Starts the training
## Receives:
Nothing
## Returns:
None
## Examples:
...
## Raises:
Nothing. | old/automatic_training.py | start_training | AlanPXD/IC-AutoEncoder | 0 | python | def start_training(self) -> None:
'\n ## Function:\n\n Starts the training\n\n ## Receives:\n\n Nothing\n\n ## Returns:\n\n None\n\n ## Examples:\n\n ...\n \n ## Raises:\n\n Nothing.\n '
dataset: DataSet = DataSet()
dataset.load_by_name(self.state.dataset_name)
x_train = dataset.x_train
x_test = dataset.x_test
y_train = dataset.y_train
y_test = dataset.y_test
neural_net: Model = self._load_model_()
neural_net.compile(optimizer=self.state.optimizer(**self.state.optimizer_kwargs), loss=self.state.loss(**self.state.loss_kwargs), **self.state.compile_kwargs)
self._check_if_dirs_exists_()
csv_logger = CSVLogger(filename=self.state.csv_pathname, separator=';', append=True)
standard_callbacks: list = [csv_logger]
neural_net.fit(x=x_train, y=y_train, validation_data=(x_test, y_test), initial_epoch=(self._get_last_epoch_() + 1), callbacks=standard_callbacks, epochs=((self.state.last_epoch + self.state.number_of_epochs) + 1), **self.state.fit_Kwargs)
neural_net.save(filepath=self.state.model_save_pathname)
self.save_data_to_dataframe()
self.state._update_dependent_attributes_()
self.save_state() | def start_training(self) -> None:
'\n ## Function:\n\n Starts the training\n\n ## Receives:\n\n Nothing\n\n ## Returns:\n\n None\n\n ## Examples:\n\n ...\n \n ## Raises:\n\n Nothing.\n '
dataset: DataSet = DataSet()
dataset.load_by_name(self.state.dataset_name)
x_train = dataset.x_train
x_test = dataset.x_test
y_train = dataset.y_train
y_test = dataset.y_test
neural_net: Model = self._load_model_()
neural_net.compile(optimizer=self.state.optimizer(**self.state.optimizer_kwargs), loss=self.state.loss(**self.state.loss_kwargs), **self.state.compile_kwargs)
self._check_if_dirs_exists_()
csv_logger = CSVLogger(filename=self.state.csv_pathname, separator=';', append=True)
standard_callbacks: list = [csv_logger]
neural_net.fit(x=x_train, y=y_train, validation_data=(x_test, y_test), initial_epoch=(self._get_last_epoch_() + 1), callbacks=standard_callbacks, epochs=((self.state.last_epoch + self.state.number_of_epochs) + 1), **self.state.fit_Kwargs)
neural_net.save(filepath=self.state.model_save_pathname)
self.save_data_to_dataframe()
self.state._update_dependent_attributes_()
self.save_state()<|docstring|>## Function:
Starts the training
## Receives:
Nothing
## Returns:
None
## Examples:
...
## Raises:
Nothing.<|endoftext|> |
a963c7e2bf8bf3ce570dd12306982f1aee92f7d15ac11cfbfffd4582ff731958 | def set_a_new_training(self, new_parameters: dict) -> None:
'\n ## Function:\n\n Executes a new training after changes in parameters.\n\n ## Receives:\n\n A `dict` where the keys are the parameters to be changed, and the values are new parameters.\n\n ### Possibilities :\n\n \'model_name\' : "AutoEncoder-1.0-64x64.json",\n \'dataset_name\' : "rafael_cifar_10",\n \'number_of_epochs\' : 5,\n \n \'fit_Kwargs\' : {\n \'batch_size\': 10,\n \'verbose\': 1,\n \'validation_split\': 0, \n \'shuffle\': True,\n \'class_weight\': None,\n \'sample_weight\': None,\n \'steps_per_epoch\': None, \n \'validation_steps\': None, \n \'validation_batch_size\': None, \n \'validation_freq\': 1,\n \'max_queue_size\': 10, \n \'workers\': 1, \n \'use_multiprocessing\': False\n },\n \n \'compile_kwargs\' : {\n \'metrics\': None,\n \'loss_weights\': None,\n \'weighted_metrics\': None,\n \'run_eagerly\': None,\n \'steps_per_execution\': None\n },\n \n \'optimizer\' : Adam,\n\n \'optimizer_kwargs\' : {\n \'learning_rate\': 0.001,\n \'beta_1\': 0.9,\n \'beta_2\': 0.999, \n \'epsilon\': 1e-7,\n \'amsgrad\': False\n },\n\n \'loss_class\' : LSSIM,\n \'loss_kwargs\' : { \n \'max_val\':255,\n \'filter_size\':9,\n \'filter_sigma\':1.5,\n \'k1\':0.01,\n \'k2\':0.03\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> self.set_a_new_training ( {"model_name": "model2",\n "dataset": new_dataset} )\n\n ## Raises:\n\n Nothing.\n '
self.state.change_training_idx()
self.state.change_attributes(new_parameters)
self.start_training() | ## Function:
Executes a new training after changes in parameters.
## Receives:
A `dict` where the keys are the parameters to be changed, and the values are new parameters.
### Possibilities :
'model_name' : "AutoEncoder-1.0-64x64.json",
'dataset_name' : "rafael_cifar_10",
'number_of_epochs' : 5,
'fit_Kwargs' : {
'batch_size': 10,
'verbose': 1,
'validation_split': 0,
'shuffle': True,
'class_weight': None,
'sample_weight': None,
'steps_per_epoch': None,
'validation_steps': None,
'validation_batch_size': None,
'validation_freq': 1,
'max_queue_size': 10,
'workers': 1,
'use_multiprocessing': False
},
'compile_kwargs' : {
'metrics': None,
'loss_weights': None,
'weighted_metrics': None,
'run_eagerly': None,
'steps_per_execution': None
},
'optimizer' : Adam,
'optimizer_kwargs' : {
'learning_rate': 0.001,
'beta_1': 0.9,
'beta_2': 0.999,
'epsilon': 1e-7,
'amsgrad': False
},
'loss_class' : LSSIM,
'loss_kwargs' : {
'max_val':255,
'filter_size':9,
'filter_sigma':1.5,
'k1':0.01,
'k2':0.03
## Returns:
None
## Examples:
>>> self.set_a_new_training ( {"model_name": "model2",
"dataset": new_dataset} )
## Raises:
Nothing. | old/automatic_training.py | set_a_new_training | AlanPXD/IC-AutoEncoder | 0 | python | def set_a_new_training(self, new_parameters: dict) -> None:
'\n ## Function:\n\n Executes a new training after changes in parameters.\n\n ## Receives:\n\n A `dict` where the keys are the parameters to be changed, and the values are new parameters.\n\n ### Possibilities :\n\n \'model_name\' : "AutoEncoder-1.0-64x64.json",\n \'dataset_name\' : "rafael_cifar_10",\n \'number_of_epochs\' : 5,\n \n \'fit_Kwargs\' : {\n \'batch_size\': 10,\n \'verbose\': 1,\n \'validation_split\': 0, \n \'shuffle\': True,\n \'class_weight\': None,\n \'sample_weight\': None,\n \'steps_per_epoch\': None, \n \'validation_steps\': None, \n \'validation_batch_size\': None, \n \'validation_freq\': 1,\n \'max_queue_size\': 10, \n \'workers\': 1, \n \'use_multiprocessing\': False\n },\n \n \'compile_kwargs\' : {\n \'metrics\': None,\n \'loss_weights\': None,\n \'weighted_metrics\': None,\n \'run_eagerly\': None,\n \'steps_per_execution\': None\n },\n \n \'optimizer\' : Adam,\n\n \'optimizer_kwargs\' : {\n \'learning_rate\': 0.001,\n \'beta_1\': 0.9,\n \'beta_2\': 0.999, \n \'epsilon\': 1e-7,\n \'amsgrad\': False\n },\n\n \'loss_class\' : LSSIM,\n \'loss_kwargs\' : { \n \'max_val\':255,\n \'filter_size\':9,\n \'filter_sigma\':1.5,\n \'k1\':0.01,\n \'k2\':0.03\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> self.set_a_new_training ( {"model_name": "model2",\n "dataset": new_dataset} )\n\n ## Raises:\n\n Nothing.\n '
self.state.change_training_idx()
self.state.change_attributes(new_parameters)
self.start_training() | def set_a_new_training(self, new_parameters: dict) -> None:
'\n ## Function:\n\n Executes a new training after changes in parameters.\n\n ## Receives:\n\n A `dict` where the keys are the parameters to be changed, and the values are new parameters.\n\n ### Possibilities :\n\n \'model_name\' : "AutoEncoder-1.0-64x64.json",\n \'dataset_name\' : "rafael_cifar_10",\n \'number_of_epochs\' : 5,\n \n \'fit_Kwargs\' : {\n \'batch_size\': 10,\n \'verbose\': 1,\n \'validation_split\': 0, \n \'shuffle\': True,\n \'class_weight\': None,\n \'sample_weight\': None,\n \'steps_per_epoch\': None, \n \'validation_steps\': None, \n \'validation_batch_size\': None, \n \'validation_freq\': 1,\n \'max_queue_size\': 10, \n \'workers\': 1, \n \'use_multiprocessing\': False\n },\n \n \'compile_kwargs\' : {\n \'metrics\': None,\n \'loss_weights\': None,\n \'weighted_metrics\': None,\n \'run_eagerly\': None,\n \'steps_per_execution\': None\n },\n \n \'optimizer\' : Adam,\n\n \'optimizer_kwargs\' : {\n \'learning_rate\': 0.001,\n \'beta_1\': 0.9,\n \'beta_2\': 0.999, \n \'epsilon\': 1e-7,\n \'amsgrad\': False\n },\n\n \'loss_class\' : LSSIM,\n \'loss_kwargs\' : { \n \'max_val\':255,\n \'filter_size\':9,\n \'filter_sigma\':1.5,\n \'k1\':0.01,\n \'k2\':0.03\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> self.set_a_new_training ( {"model_name": "model2",\n "dataset": new_dataset} )\n\n ## Raises:\n\n Nothing.\n '
self.state.change_training_idx()
self.state.change_attributes(new_parameters)
self.start_training()<|docstring|>## Function:
Executes a new training after changes in parameters.
## Receives:
A `dict` where the keys are the parameters to be changed, and the values are new parameters.
### Possibilities :
'model_name' : "AutoEncoder-1.0-64x64.json",
'dataset_name' : "rafael_cifar_10",
'number_of_epochs' : 5,
'fit_Kwargs' : {
'batch_size': 10,
'verbose': 1,
'validation_split': 0,
'shuffle': True,
'class_weight': None,
'sample_weight': None,
'steps_per_epoch': None,
'validation_steps': None,
'validation_batch_size': None,
'validation_freq': 1,
'max_queue_size': 10,
'workers': 1,
'use_multiprocessing': False
},
'compile_kwargs' : {
'metrics': None,
'loss_weights': None,
'weighted_metrics': None,
'run_eagerly': None,
'steps_per_execution': None
},
'optimizer' : Adam,
'optimizer_kwargs' : {
'learning_rate': 0.001,
'beta_1': 0.9,
'beta_2': 0.999,
'epsilon': 1e-7,
'amsgrad': False
},
'loss_class' : LSSIM,
'loss_kwargs' : {
'max_val':255,
'filter_size':9,
'filter_sigma':1.5,
'k1':0.01,
'k2':0.03
## Returns:
None
## Examples:
>>> self.set_a_new_training ( {"model_name": "model2",
"dataset": new_dataset} )
## Raises:
Nothing.<|endoftext|> |
d3fd9701bbfcde968e5187b1934d17cc9f400d2d16a5605c7d4cd07990ee697d | def set_a_sequence_of_trainings(self, list_of_changes: list) -> None:
'\n ## Function:\n\n Executes pieces of training after changes in parameters.\n\n ## Receives:\n\n A `list` where the elements are dicts containing the training changes.\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> change1 = {"model_name": "model2"}\n >>> change2 = {"dataset": new_dataset}\n >>> list_of_changes = [change1, change2]\n >>> self.set_a_new_training ( list_of_changes )\n\n In this example, the first training begins after change1, and the second training is started afterward of change2.\n\n ## Raises:\n\n Nothing.\n '
changes: dict
for changes in list_of_changes:
self.set_a_new_training(changes) | ## Function:
Executes pieces of training after changes in parameters.
## Receives:
A `list` where the elements are dicts containing the training changes.
## Returns:
None
## Examples:
>>> change1 = {"model_name": "model2"}
>>> change2 = {"dataset": new_dataset}
>>> list_of_changes = [change1, change2]
>>> self.set_a_new_training ( list_of_changes )
In this example, the first training begins after change1, and the second training is started afterward of change2.
## Raises:
Nothing. | old/automatic_training.py | set_a_sequence_of_trainings | AlanPXD/IC-AutoEncoder | 0 | python | def set_a_sequence_of_trainings(self, list_of_changes: list) -> None:
'\n ## Function:\n\n Executes pieces of training after changes in parameters.\n\n ## Receives:\n\n A `list` where the elements are dicts containing the training changes.\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> change1 = {"model_name": "model2"}\n >>> change2 = {"dataset": new_dataset}\n >>> list_of_changes = [change1, change2]\n >>> self.set_a_new_training ( list_of_changes )\n\n In this example, the first training begins after change1, and the second training is started afterward of change2.\n\n ## Raises:\n\n Nothing.\n '
changes: dict
for changes in list_of_changes:
self.set_a_new_training(changes) | def set_a_sequence_of_trainings(self, list_of_changes: list) -> None:
'\n ## Function:\n\n Executes pieces of training after changes in parameters.\n\n ## Receives:\n\n A `list` where the elements are dicts containing the training changes.\n\n ## Returns:\n\n None\n\n ## Examples:\n\n >>> change1 = {"model_name": "model2"}\n >>> change2 = {"dataset": new_dataset}\n >>> list_of_changes = [change1, change2]\n >>> self.set_a_new_training ( list_of_changes )\n\n In this example, the first training begins after change1, and the second training is started afterward of change2.\n\n ## Raises:\n\n Nothing.\n '
changes: dict
for changes in list_of_changes:
self.set_a_new_training(changes)<|docstring|>## Function:
Executes pieces of training after changes in parameters.
## Receives:
A `list` where the elements are dicts containing the training changes.
## Returns:
None
## Examples:
>>> change1 = {"model_name": "model2"}
>>> change2 = {"dataset": new_dataset}
>>> list_of_changes = [change1, change2]
>>> self.set_a_new_training ( list_of_changes )
In this example, the first training begins after change1, and the second training is started afterward of change2.
## Raises:
Nothing.<|endoftext|> |
0f4eb81407e4b846471dfe130902876a5278924482e725857606655ca3cec429 | def getenv_bool(name: str, default: bool=False) -> bool:
"Gets a boolean-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : bool, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``False``.\n\n Returns\n -------\n bool\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = (env_value.upper() in ('TRUE', '1'))
return rv | Gets a boolean-valued environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : bool, optional
The default value to use (if the `name` variable doesn't exist),
the default value is ``False``.
Returns
-------
bool
The environment variable `name` value to use. | src/backend/app/core/config.py | getenv_bool | douglasdaly/dougliz-wedding | 5 | python | def getenv_bool(name: str, default: bool=False) -> bool:
"Gets a boolean-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : bool, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``False``.\n\n Returns\n -------\n bool\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = (env_value.upper() in ('TRUE', '1'))
return rv | def getenv_bool(name: str, default: bool=False) -> bool:
"Gets a boolean-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : bool, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``False``.\n\n Returns\n -------\n bool\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = (env_value.upper() in ('TRUE', '1'))
return rv<|docstring|>Gets a boolean-valued environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : bool, optional
The default value to use (if the `name` variable doesn't exist),
the default value is ``False``.
Returns
-------
bool
The environment variable `name` value to use.<|endoftext|> |
7e08d378654df738308c53b7ce0c286e12d8f0d7aae0b407951edb75f058787e | def getenv_int(name: str, default: tp.Optional[int]=None) -> int:
"Gets an integer-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : int, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``None``.\n\n Returns\n -------\n int\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = int(env_value)
return rv | Gets an integer-valued environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : int, optional
The default value to use (if the `name` variable doesn't exist),
the default value is ``None``.
Returns
-------
int
The environment variable `name` value to use. | src/backend/app/core/config.py | getenv_int | douglasdaly/dougliz-wedding | 5 | python | def getenv_int(name: str, default: tp.Optional[int]=None) -> int:
"Gets an integer-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : int, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``None``.\n\n Returns\n -------\n int\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = int(env_value)
return rv | def getenv_int(name: str, default: tp.Optional[int]=None) -> int:
"Gets an integer-valued environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : int, optional\n The default value to use (if the `name` variable doesn't exist),\n the default value is ``None``.\n\n Returns\n -------\n int\n The environment variable `name` value to use.\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
rv = int(env_value)
return rv<|docstring|>Gets an integer-valued environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : int, optional
The default value to use (if the `name` variable doesn't exist),
the default value is ``None``.
Returns
-------
int
The environment variable `name` value to use.<|endoftext|> |
79d797fc96d9c8e530d384c35c00e1eea9a5e57d135b5d95b30ad08472541fbd | def getenv_dict(name: str, default: tp.Optional[tp.Dict[(str, str)]]=None) -> tp.Dict[(str, str)]:
"Gets a dictionary of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n JSON-formatted string representing a dictionary.\n default : Dict[str, str], optional\n The default value to use (if the `name` variable doesn't exist,\n the default value is ``{}``).\n\n Returns\n -------\n Dict[str, str]\n The dictionary from the environment variable `name`'s data.\n\n "
rv = (default or {})
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('\'" ')
rv = json.loads(env_value)
return rv | Gets a dictionary of values from an environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists). Expects a
JSON-formatted string representing a dictionary.
default : Dict[str, str], optional
The default value to use (if the `name` variable doesn't exist,
the default value is ``{}``).
Returns
-------
Dict[str, str]
The dictionary from the environment variable `name`'s data. | src/backend/app/core/config.py | getenv_dict | douglasdaly/dougliz-wedding | 5 | python | def getenv_dict(name: str, default: tp.Optional[tp.Dict[(str, str)]]=None) -> tp.Dict[(str, str)]:
"Gets a dictionary of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n JSON-formatted string representing a dictionary.\n default : Dict[str, str], optional\n The default value to use (if the `name` variable doesn't exist,\n the default value is ``{}``).\n\n Returns\n -------\n Dict[str, str]\n The dictionary from the environment variable `name`'s data.\n\n "
rv = (default or {})
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('\'" ')
rv = json.loads(env_value)
return rv | def getenv_dict(name: str, default: tp.Optional[tp.Dict[(str, str)]]=None) -> tp.Dict[(str, str)]:
"Gets a dictionary of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n JSON-formatted string representing a dictionary.\n default : Dict[str, str], optional\n The default value to use (if the `name` variable doesn't exist,\n the default value is ``{}``).\n\n Returns\n -------\n Dict[str, str]\n The dictionary from the environment variable `name`'s data.\n\n "
rv = (default or {})
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('\'" ')
rv = json.loads(env_value)
return rv<|docstring|>Gets a dictionary of values from an environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists). Expects a
JSON-formatted string representing a dictionary.
default : Dict[str, str], optional
The default value to use (if the `name` variable doesn't exist,
the default value is ``{}``).
Returns
-------
Dict[str, str]
The dictionary from the environment variable `name`'s data.<|endoftext|> |
86b5220053701f50d6219a91eb55073a6322eb8f6106239fe78a91316d732cf1 | def getenv_list(name: str, default: tp.Optional[tp.List[str]]=None, *, seperator: str=',') -> tp.List[str]:
"Gets a list of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n character-seperated string (using `seperator`).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``[]``).\n seperator : str, optional\n The character-seperating string to use (default is a comma).\n\n Returns\n -------\n Sequence[str]\n The sequence from the environment variable `name`'s data.\n\n "
rv = (default or [])
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('"\' ')
rv = [x.strip() for x in env_value.split(seperator)]
return rv | Gets a list of values from an environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists). Expects a
character-seperated string (using `seperator`).
default : Sequence[str], optional
The default value to use (if the `name` environment variable
doesn't exist, the default is ``[]``).
seperator : str, optional
The character-seperating string to use (default is a comma).
Returns
-------
Sequence[str]
The sequence from the environment variable `name`'s data. | src/backend/app/core/config.py | getenv_list | douglasdaly/dougliz-wedding | 5 | python | def getenv_list(name: str, default: tp.Optional[tp.List[str]]=None, *, seperator: str=',') -> tp.List[str]:
"Gets a list of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n character-seperated string (using `seperator`).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``[]``).\n seperator : str, optional\n The character-seperating string to use (default is a comma).\n\n Returns\n -------\n Sequence[str]\n The sequence from the environment variable `name`'s data.\n\n "
rv = (default or [])
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('"\' ')
rv = [x.strip() for x in env_value.split(seperator)]
return rv | def getenv_list(name: str, default: tp.Optional[tp.List[str]]=None, *, seperator: str=',') -> tp.List[str]:
"Gets a list of values from an environment variable.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists). Expects a\n character-seperated string (using `seperator`).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``[]``).\n seperator : str, optional\n The character-seperating string to use (default is a comma).\n\n Returns\n -------\n Sequence[str]\n The sequence from the environment variable `name`'s data.\n\n "
rv = (default or [])
env_value = os.getenv(name)
if (env_value is not None):
env_value = env_value.strip('"\' ')
rv = [x.strip() for x in env_value.split(seperator)]
return rv<|docstring|>Gets a list of values from an environment variable.
Parameters
----------
name : str
The environment variable to get (if it exists). Expects a
character-seperated string (using `seperator`).
default : Sequence[str], optional
The default value to use (if the `name` environment variable
doesn't exist, the default is ``[]``).
seperator : str, optional
The character-seperating string to use (default is a comma).
Returns
-------
Sequence[str]
The sequence from the environment variable `name`'s data.<|endoftext|> |
c7b90e0d42c4d26b981bc7ae0b3f0c9eda0cc155e56301b52cefe46e79e4e53d | def getenv_quotestr(name: str, default: tp.Optional[str]=None) -> tp.Optional[str]:
"Gets a clean environment variable as a (non-quoted) string value.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``None``).\n\n Returns\n -------\n Optional[str]\n The cleaned string version of the environment variable (if it\n exists).\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
if ((env_value[0] == env_value[(- 1)]) and (env_value[0] in ('"', "'"))):
rv = env_value[1:(- 1)]
else:
rv = env_value
return rv | Gets a clean environment variable as a (non-quoted) string value.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : Sequence[str], optional
The default value to use (if the `name` environment variable
doesn't exist, the default is ``None``).
Returns
-------
Optional[str]
The cleaned string version of the environment variable (if it
exists). | src/backend/app/core/config.py | getenv_quotestr | douglasdaly/dougliz-wedding | 5 | python | def getenv_quotestr(name: str, default: tp.Optional[str]=None) -> tp.Optional[str]:
"Gets a clean environment variable as a (non-quoted) string value.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``None``).\n\n Returns\n -------\n Optional[str]\n The cleaned string version of the environment variable (if it\n exists).\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
if ((env_value[0] == env_value[(- 1)]) and (env_value[0] in ('"', "'"))):
rv = env_value[1:(- 1)]
else:
rv = env_value
return rv | def getenv_quotestr(name: str, default: tp.Optional[str]=None) -> tp.Optional[str]:
"Gets a clean environment variable as a (non-quoted) string value.\n\n Parameters\n ----------\n name : str\n The environment variable to get (if it exists).\n default : Sequence[str], optional\n The default value to use (if the `name` environment variable\n doesn't exist, the default is ``None``).\n\n Returns\n -------\n Optional[str]\n The cleaned string version of the environment variable (if it\n exists).\n\n "
rv = default
env_value = os.getenv(name)
if (env_value is not None):
if ((env_value[0] == env_value[(- 1)]) and (env_value[0] in ('"', "'"))):
rv = env_value[1:(- 1)]
else:
rv = env_value
return rv<|docstring|>Gets a clean environment variable as a (non-quoted) string value.
Parameters
----------
name : str
The environment variable to get (if it exists).
default : Sequence[str], optional
The default value to use (if the `name` environment variable
doesn't exist, the default is ``None``).
Returns
-------
Optional[str]
The cleaned string version of the environment variable (if it
exists).<|endoftext|> |
f16e65aaef164a697fdf18f356a4a84523974b48cfbbda8171348be2ab75ba12 | def _get_previous_sim_type(self, sim_type: str):
'\n Works out where to get starting structure from based on the current run and simulation type\n '
if (self.run_type == _PSE.RBFE):
return 'em'
elif (self.run_type == _PSE.ABFE):
if (sim_type in ('em', 'nvt')):
return 'em'
elif (sim_type == 'npt'):
return 'nvt'
elif (sim_type == 'eq'):
return 'npt' | Works out where to get starting structure from based on the current run and simulation type | src/icolos/core/workflow_steps/pmx/prepare_simulations.py | _get_previous_sim_type | jharrymoore/Icolos | 0 | python | def _get_previous_sim_type(self, sim_type: str):
'\n \n '
if (self.run_type == _PSE.RBFE):
return 'em'
elif (self.run_type == _PSE.ABFE):
if (sim_type in ('em', 'nvt')):
return 'em'
elif (sim_type == 'npt'):
return 'nvt'
elif (sim_type == 'eq'):
return 'npt' | def _get_previous_sim_type(self, sim_type: str):
'\n \n '
if (self.run_type == _PSE.RBFE):
return 'em'
elif (self.run_type == _PSE.ABFE):
if (sim_type in ('em', 'nvt')):
return 'em'
elif (sim_type == 'npt'):
return 'nvt'
elif (sim_type == 'eq'):
return 'npt'<|docstring|>Works out where to get starting structure from based on the current run and simulation type<|endoftext|> |
2604825615922bdf72b709d4949f09dfe391722ad016ffb777e6710579cf6502 | def load_voc_instances(dirname: str, split: str):
'\n Load licenseplates VOC detection annotations to Detectron2 format.\n\n Args:\n dirname: Contain "annotations", "images"\n split (str): one of "train", "test"\n '
with PathManager.open(os.path.join(dirname, (split + '.txt'))) as f:
fileids = np.loadtxt(f, dtype=np.str)
dicts = []
for fileid in fileids:
anno_file = os.path.join(dirname, 'annotations', (fileid + '.xml'))
jpeg_file = os.path.join(dirname, 'images', (fileid + '.jpg'))
tree = ET.parse(anno_file)
r = {'file_name': jpeg_file, 'image_id': fileid, 'height': int(tree.findall('./size/height')[0].text), 'width': int(tree.findall('./size/width')[0].text)}
instances = []
for obj in tree.findall('object'):
cls = obj.find('name').text
bbox = obj.find('bndbox')
bbox = [float(bbox.find(x).text) for x in ['xmin', 'ymin', 'xmax', 'ymax']]
instances.append({'category_id': CLASS_NAMES.index(cls), 'bbox': bbox, 'bbox_mode': BoxMode.XYXY_ABS})
r['annotations'] = instances
dicts.append(r)
return dicts | Load licenseplates VOC detection annotations to Detectron2 format.
Args:
dirname: Contain "annotations", "images"
split (str): one of "train", "test" | licenseplates/dataset.py | load_voc_instances | jagin/detectron2-licenseplates | 39 | python | def load_voc_instances(dirname: str, split: str):
'\n Load licenseplates VOC detection annotations to Detectron2 format.\n\n Args:\n dirname: Contain "annotations", "images"\n split (str): one of "train", "test"\n '
with PathManager.open(os.path.join(dirname, (split + '.txt'))) as f:
fileids = np.loadtxt(f, dtype=np.str)
dicts = []
for fileid in fileids:
anno_file = os.path.join(dirname, 'annotations', (fileid + '.xml'))
jpeg_file = os.path.join(dirname, 'images', (fileid + '.jpg'))
tree = ET.parse(anno_file)
r = {'file_name': jpeg_file, 'image_id': fileid, 'height': int(tree.findall('./size/height')[0].text), 'width': int(tree.findall('./size/width')[0].text)}
instances = []
for obj in tree.findall('object'):
cls = obj.find('name').text
bbox = obj.find('bndbox')
bbox = [float(bbox.find(x).text) for x in ['xmin', 'ymin', 'xmax', 'ymax']]
instances.append({'category_id': CLASS_NAMES.index(cls), 'bbox': bbox, 'bbox_mode': BoxMode.XYXY_ABS})
r['annotations'] = instances
dicts.append(r)
return dicts | def load_voc_instances(dirname: str, split: str):
'\n Load licenseplates VOC detection annotations to Detectron2 format.\n\n Args:\n dirname: Contain "annotations", "images"\n split (str): one of "train", "test"\n '
with PathManager.open(os.path.join(dirname, (split + '.txt'))) as f:
fileids = np.loadtxt(f, dtype=np.str)
dicts = []
for fileid in fileids:
anno_file = os.path.join(dirname, 'annotations', (fileid + '.xml'))
jpeg_file = os.path.join(dirname, 'images', (fileid + '.jpg'))
tree = ET.parse(anno_file)
r = {'file_name': jpeg_file, 'image_id': fileid, 'height': int(tree.findall('./size/height')[0].text), 'width': int(tree.findall('./size/width')[0].text)}
instances = []
for obj in tree.findall('object'):
cls = obj.find('name').text
bbox = obj.find('bndbox')
bbox = [float(bbox.find(x).text) for x in ['xmin', 'ymin', 'xmax', 'ymax']]
instances.append({'category_id': CLASS_NAMES.index(cls), 'bbox': bbox, 'bbox_mode': BoxMode.XYXY_ABS})
r['annotations'] = instances
dicts.append(r)
return dicts<|docstring|>Load licenseplates VOC detection annotations to Detectron2 format.
Args:
dirname: Contain "annotations", "images"
split (str): one of "train", "test"<|endoftext|> |
326deedb536703a7e8af53def6791b6f9d8c0ded3a8c319f96705ae3cd5fec2b | def test_parse_exac_line(exac_handle):
'Test to parse a exac line'
header = next(exac_handle).rstrip().split('\t')
first_gene = next(exac_handle)
gene_info = parse_exac_line(header=header, line=first_gene)
assert (gene_info['hgnc_symbol'] == first_gene.split('\t')[1]) | Test to parse a exac line | tests/parse/test_parse_exac_genes.py | test_parse_exac_line | Clinical-Genomics/scout | 111 | python | def test_parse_exac_line(exac_handle):
header = next(exac_handle).rstrip().split('\t')
first_gene = next(exac_handle)
gene_info = parse_exac_line(header=header, line=first_gene)
assert (gene_info['hgnc_symbol'] == first_gene.split('\t')[1]) | def test_parse_exac_line(exac_handle):
header = next(exac_handle).rstrip().split('\t')
first_gene = next(exac_handle)
gene_info = parse_exac_line(header=header, line=first_gene)
assert (gene_info['hgnc_symbol'] == first_gene.split('\t')[1])<|docstring|>Test to parse a exac line<|endoftext|> |
9e371ca67ac3b206d163418ea6e6694e954ea6921b61b14b3b9d328d98bc9a26 | def onTrack(self, callback=None):
'\n Callback that gets called each time a video track is received::\n\n @r.video.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.video.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.video.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback) | Callback that gets called each time a video track is received::
@r.video.onTrack
def onTrack(track):
print(track)
The callback actually works exactly as a subscribe(), so you can do::
subscription = r.video.onTrack()
await subscription.get()
Note that if you have more than one track, you will need to tell rtcbot how
many tracks to prepare to receive::
r.video.offerToReceive(2) | rtcbot/connection.py | onTrack | kimsooyoung/rtcbot | 35 | python | def onTrack(self, callback=None):
'\n Callback that gets called each time a video track is received::\n\n @r.video.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.video.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.video.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback) | def onTrack(self, callback=None):
'\n Callback that gets called each time a video track is received::\n\n @r.video.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.video.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.video.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback)<|docstring|>Callback that gets called each time a video track is received::
@r.video.onTrack
def onTrack(track):
print(track)
The callback actually works exactly as a subscribe(), so you can do::
subscription = r.video.onTrack()
await subscription.get()
Note that if you have more than one track, you will need to tell rtcbot how
many tracks to prepare to receive::
r.video.offerToReceive(2)<|endoftext|> |
8a8ea8c905099060b1ff9b6b794759f850b4acfc35695cd832de22130f3e2b2f | def addTrack(self, frameSubscription=None, fps=None, canSkip=True):
'\n Allows to send multiple video tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single video stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding video track to connection')
s = VideoSender(fps=fps, canSkip=True)
if (frameSubscription is not None):
s.putSubscription(frameSubscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.videoStreamTrack)
self._senders.add(s)
return s | Allows to send multiple video tracks in a single connection.
Each call to putTrack *adds* the track to the connection.
For simple usage, where you only have a single video stream,
just use `putSubscription` - it automatically calls putTrack for you. | rtcbot/connection.py | addTrack | kimsooyoung/rtcbot | 35 | python | def addTrack(self, frameSubscription=None, fps=None, canSkip=True):
'\n Allows to send multiple video tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single video stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding video track to connection')
s = VideoSender(fps=fps, canSkip=True)
if (frameSubscription is not None):
s.putSubscription(frameSubscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.videoStreamTrack)
self._senders.add(s)
return s | def addTrack(self, frameSubscription=None, fps=None, canSkip=True):
'\n Allows to send multiple video tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single video stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding video track to connection')
s = VideoSender(fps=fps, canSkip=True)
if (frameSubscription is not None):
s.putSubscription(frameSubscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.videoStreamTrack)
self._senders.add(s)
return s<|docstring|>Allows to send multiple video tracks in a single connection.
Each call to putTrack *adds* the track to the connection.
For simple usage, where you only have a single video stream,
just use `putSubscription` - it automatically calls putTrack for you.<|endoftext|> |
0031c1632cdfb20207d27f14bdfaf91b4dc5e6bc60fb592d2c36e56c01b2aa53 | def _onTrack(self, track):
'\n Internal raw track receiver\n '
self._log.debug('Received video track from connection')
track = VideoReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track) | Internal raw track receiver | rtcbot/connection.py | _onTrack | kimsooyoung/rtcbot | 35 | python | def _onTrack(self, track):
'\n \n '
self._log.debug('Received video track from connection')
track = VideoReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track) | def _onTrack(self, track):
'\n \n '
self._log.debug('Received video track from connection')
track = VideoReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track)<|docstring|>Internal raw track receiver<|endoftext|> |
3477f4884b4d204ab93b44caf8f8d434eea6e048d586ace9d43c401be2759e48 | def offerToReceive(self, num=1):
'\n Set the number of tracks that you can receive\n '
if (self._offerToReceive < num):
self._offerToReceive = num | Set the number of tracks that you can receive | rtcbot/connection.py | offerToReceive | kimsooyoung/rtcbot | 35 | python | def offerToReceive(self, num=1):
'\n \n '
if (self._offerToReceive < num):
self._offerToReceive = num | def offerToReceive(self, num=1):
'\n \n '
if (self._offerToReceive < num):
self._offerToReceive = num<|docstring|>Set the number of tracks that you can receive<|endoftext|> |
4b850c7792c32556cbc15fc5a2d55ec2588c8ff55f8fd15ed9a42c939450d644 | def onTrack(self, callback=None):
'\n Callback that gets called each time a audio track is received::\n\n @r.audio.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.audio.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.audio.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback) | Callback that gets called each time a audio track is received::
@r.audio.onTrack
def onTrack(track):
print(track)
The callback actually works exactly as a subscribe(), so you can do::
subscription = r.audio.onTrack()
await subscription.get()
Note that if you have more than one track, you will need to tell rtcbot how
many tracks to prepare to receive::
r.audio.offerToReceive(2) | rtcbot/connection.py | onTrack | kimsooyoung/rtcbot | 35 | python | def onTrack(self, callback=None):
'\n Callback that gets called each time a audio track is received::\n\n @r.audio.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.audio.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.audio.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback) | def onTrack(self, callback=None):
'\n Callback that gets called each time a audio track is received::\n\n @r.audio.onTrack\n def onTrack(track):\n print(track)\n\n The callback actually works exactly as a subscribe(), so you can do::\n\n subscription = r.audio.onTrack()\n await subscription.get()\n\n Note that if you have more than one track, you will need to tell rtcbot how\n many tracks to prepare to receive::\n\n r.audio.offerToReceive(2)\n\n '
self.offerToReceive()
return self._trackSubscriber.subscribe(callback)<|docstring|>Callback that gets called each time a audio track is received::
@r.audio.onTrack
def onTrack(track):
print(track)
The callback actually works exactly as a subscribe(), so you can do::
subscription = r.audio.onTrack()
await subscription.get()
Note that if you have more than one track, you will need to tell rtcbot how
many tracks to prepare to receive::
r.audio.offerToReceive(2)<|endoftext|> |
390062e95cd99affb81da3f9b5b1eb9ac0ce8846c5326d240ac881125808212c | def addTrack(self, subscription=None, sampleRate=48000, canSkip=True):
'\n Allows to send multiple audio tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single audio stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding audio track to connection')
s = AudioSender(sampleRate=sampleRate, canSkip=True)
if (subscription is not None):
s.putSubscription(subscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.audioStreamTrack)
self._senders.add(s)
return s | Allows to send multiple audio tracks in a single connection.
Each call to putTrack *adds* the track to the connection.
For simple usage, where you only have a single audio stream,
just use `putSubscription` - it automatically calls putTrack for you. | rtcbot/connection.py | addTrack | kimsooyoung/rtcbot | 35 | python | def addTrack(self, subscription=None, sampleRate=48000, canSkip=True):
'\n Allows to send multiple audio tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single audio stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding audio track to connection')
s = AudioSender(sampleRate=sampleRate, canSkip=True)
if (subscription is not None):
s.putSubscription(subscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.audioStreamTrack)
self._senders.add(s)
return s | def addTrack(self, subscription=None, sampleRate=48000, canSkip=True):
'\n Allows to send multiple audio tracks in a single connection.\n Each call to putTrack *adds* the track to the connection.\n For simple usage, where you only have a single audio stream,\n just use `putSubscription` - it automatically calls putTrack for you.\n '
self._log.debug('Adding audio track to connection')
s = AudioSender(sampleRate=sampleRate, canSkip=True)
if (subscription is not None):
s.putSubscription(subscription)
elif (self._defaultSender is None):
s.putSubscription(self._defaultSenderSubscription)
if (self._defaultSender is None):
self._defaultSender = s
self._defaultSender.onClose(self.close)
self._rtc.addTrack(s.audioStreamTrack)
self._senders.add(s)
return s<|docstring|>Allows to send multiple audio tracks in a single connection.
Each call to putTrack *adds* the track to the connection.
For simple usage, where you only have a single audio stream,
just use `putSubscription` - it automatically calls putTrack for you.<|endoftext|> |
1c1632b167e0e2009e0b3e6a7d4239075813f55a92b17b74bf43c1b2e29bd41e | def _onTrack(self, track):
'\n Internal raw track receiver\n '
self._log.debug('Received audio track from connection')
track = AudioReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track) | Internal raw track receiver | rtcbot/connection.py | _onTrack | kimsooyoung/rtcbot | 35 | python | def _onTrack(self, track):
'\n \n '
self._log.debug('Received audio track from connection')
track = AudioReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track) | def _onTrack(self, track):
'\n \n '
self._log.debug('Received audio track from connection')
track = AudioReceiver(track)
if (self._defaultReceiver is None):
self._defaultReceiver = track
self._defaultReceiver.subscribe(self._put_nowait)
self._defaultReceiver.onClose(self.close)
self._receivers.add(track)
self._trackSubscriber._put_nowait(track)<|docstring|>Internal raw track receiver<|endoftext|> |
3477f4884b4d204ab93b44caf8f8d434eea6e048d586ace9d43c401be2759e48 | def offerToReceive(self, num=1):
'\n Set the number of tracks that you can receive\n '
if (self._offerToReceive < num):
self._offerToReceive = num | Set the number of tracks that you can receive | rtcbot/connection.py | offerToReceive | kimsooyoung/rtcbot | 35 | python | def offerToReceive(self, num=1):
'\n \n '
if (self._offerToReceive < num):
self._offerToReceive = num | def offerToReceive(self, num=1):
'\n \n '
if (self._offerToReceive < num):
self._offerToReceive = num<|docstring|>Set the number of tracks that you can receive<|endoftext|> |
1bdfa10ecc5e08edb528f4cc922a6388b51d7b53d1f536cc2f74bc516c6a599c | async def getLocalDescription(self, description=None):
'\n Gets the description to send on. Creates an initial description\n if no remote description was passed, and creates a response if\n a remote was given,\n '
if (self._hasRemoteDescription or (description is not None)):
if (not self._hasRemoteDescription):
(await self.setRemoteDescription(description))
self._log.debug('Creating response to connection offer')
try:
answer = (await self._rtc.createAnswer())
except AttributeError:
self._log.exception("\n>>> Looks like the offer didn't include the necessary info to set up audio/video. See RTCConnection.video.offerToReceive(). <<<\n\n")
raise
(await self._rtc.setLocalDescription(answer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type}
self._log.debug('Setting up default data channel')
channel = DataChannel(self._rtc.createDataChannel('default', ordered=self._defaultChannelOrdered))
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
self._dataChannels[channel.name] = channel
if (len(self.video._senders) < self.video._offerToReceive):
self._log.debug('Offering to receive video')
for i in range((self.video._offerToReceive - len(self.video._senders))):
self._rtc.addTransceiver('video', 'recvonly')
if (len(self.audio._senders) < self.audio._offerToReceive):
self._log.debug('Offering to receive audio')
for i in range((self.audio._offerToReceive - len(self.audio._senders))):
self._rtc.addTransceiver('audio', 'recvonly')
self._log.debug('Creating new connection offer')
offer = (await self._rtc.createOffer())
(await self._rtc.setLocalDescription(offer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type} | Gets the description to send on. Creates an initial description
if no remote description was passed, and creates a response if
a remote was given, | rtcbot/connection.py | getLocalDescription | kimsooyoung/rtcbot | 35 | python | async def getLocalDescription(self, description=None):
'\n Gets the description to send on. Creates an initial description\n if no remote description was passed, and creates a response if\n a remote was given,\n '
if (self._hasRemoteDescription or (description is not None)):
if (not self._hasRemoteDescription):
(await self.setRemoteDescription(description))
self._log.debug('Creating response to connection offer')
try:
answer = (await self._rtc.createAnswer())
except AttributeError:
self._log.exception("\n>>> Looks like the offer didn't include the necessary info to set up audio/video. See RTCConnection.video.offerToReceive(). <<<\n\n")
raise
(await self._rtc.setLocalDescription(answer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type}
self._log.debug('Setting up default data channel')
channel = DataChannel(self._rtc.createDataChannel('default', ordered=self._defaultChannelOrdered))
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
self._dataChannels[channel.name] = channel
if (len(self.video._senders) < self.video._offerToReceive):
self._log.debug('Offering to receive video')
for i in range((self.video._offerToReceive - len(self.video._senders))):
self._rtc.addTransceiver('video', 'recvonly')
if (len(self.audio._senders) < self.audio._offerToReceive):
self._log.debug('Offering to receive audio')
for i in range((self.audio._offerToReceive - len(self.audio._senders))):
self._rtc.addTransceiver('audio', 'recvonly')
self._log.debug('Creating new connection offer')
offer = (await self._rtc.createOffer())
(await self._rtc.setLocalDescription(offer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type} | async def getLocalDescription(self, description=None):
'\n Gets the description to send on. Creates an initial description\n if no remote description was passed, and creates a response if\n a remote was given,\n '
if (self._hasRemoteDescription or (description is not None)):
if (not self._hasRemoteDescription):
(await self.setRemoteDescription(description))
self._log.debug('Creating response to connection offer')
try:
answer = (await self._rtc.createAnswer())
except AttributeError:
self._log.exception("\n>>> Looks like the offer didn't include the necessary info to set up audio/video. See RTCConnection.video.offerToReceive(). <<<\n\n")
raise
(await self._rtc.setLocalDescription(answer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type}
self._log.debug('Setting up default data channel')
channel = DataChannel(self._rtc.createDataChannel('default', ordered=self._defaultChannelOrdered))
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
self._dataChannels[channel.name] = channel
if (len(self.video._senders) < self.video._offerToReceive):
self._log.debug('Offering to receive video')
for i in range((self.video._offerToReceive - len(self.video._senders))):
self._rtc.addTransceiver('video', 'recvonly')
if (len(self.audio._senders) < self.audio._offerToReceive):
self._log.debug('Offering to receive audio')
for i in range((self.audio._offerToReceive - len(self.audio._senders))):
self._rtc.addTransceiver('audio', 'recvonly')
self._log.debug('Creating new connection offer')
offer = (await self._rtc.createOffer())
(await self._rtc.setLocalDescription(offer))
return {'sdp': self._rtc.localDescription.sdp, 'type': self._rtc.localDescription.type}<|docstring|>Gets the description to send on. Creates an initial description
if no remote description was passed, and creates a response if
a remote was given,<|endoftext|> |
8cd12d465f0f3092084894b6e21c40aa72da9d26e4e7cef4247ad0097db9bc24 | def _onDatachannel(self, channel):
'\n When a data channel comes in, adds it to the data channels, and sets up its messaging and stuff.\n\n '
channel = DataChannel(channel)
self._log.debug('Got channel: %s', channel.name)
if (channel.name == 'default'):
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
else:
self._dataChannelSubscriber.put_nowait(channel)
self._dataChannels[channel.name] = channel | When a data channel comes in, adds it to the data channels, and sets up its messaging and stuff. | rtcbot/connection.py | _onDatachannel | kimsooyoung/rtcbot | 35 | python | def _onDatachannel(self, channel):
'\n \n\n '
channel = DataChannel(channel)
self._log.debug('Got channel: %s', channel.name)
if (channel.name == 'default'):
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
else:
self._dataChannelSubscriber.put_nowait(channel)
self._dataChannels[channel.name] = channel | def _onDatachannel(self, channel):
'\n \n\n '
channel = DataChannel(channel)
self._log.debug('Got channel: %s', channel.name)
if (channel.name == 'default'):
channel.putSubscription(NoClosedSubscription(self._get))
channel.subscribe(self._put_nowait)
channel.onReady((lambda : self._setReady(channel.ready)))
channel.onClose(self.close)
else:
self._dataChannelSubscriber.put_nowait(channel)
self._dataChannels[channel.name] = channel<|docstring|>When a data channel comes in, adds it to the data channels, and sets up its messaging and stuff.<|endoftext|> |
ee943925c6fd6043caa7abcaff4f2b2b1d5b0df3b5ce01aea743861423fb63e8 | def onDataChannel(self, callback=None):
'\n Acts as a subscriber...\n '
return self._dataChannelSubscriber.subscribe(callback) | Acts as a subscriber... | rtcbot/connection.py | onDataChannel | kimsooyoung/rtcbot | 35 | python | def onDataChannel(self, callback=None):
'\n \n '
return self._dataChannelSubscriber.subscribe(callback) | def onDataChannel(self, callback=None):
'\n \n '
return self._dataChannelSubscriber.subscribe(callback)<|docstring|>Acts as a subscriber...<|endoftext|> |
e59c206bfbf31d0ae99f662724d2516fdaa4fc157215826978cf529a28887f90 | def addDataChannel(self, name, ordered=True):
'\n Adds a data channel to the connection. Note that the RTCConnection adds a "default" channel\n automatically, which you can subscribe to directly.\n '
self._log.debug('Adding data channel to connection')
if ((name in self._dataChannels) or (name == 'default')):
raise KeyError('Data channel %s already exists', name)
dc = DataChannel(self._rtc.createDataChannel(name, ordered=ordered))
self._dataChannels[name] = dc
return dc | Adds a data channel to the connection. Note that the RTCConnection adds a "default" channel
automatically, which you can subscribe to directly. | rtcbot/connection.py | addDataChannel | kimsooyoung/rtcbot | 35 | python | def addDataChannel(self, name, ordered=True):
'\n Adds a data channel to the connection. Note that the RTCConnection adds a "default" channel\n automatically, which you can subscribe to directly.\n '
self._log.debug('Adding data channel to connection')
if ((name in self._dataChannels) or (name == 'default')):
raise KeyError('Data channel %s already exists', name)
dc = DataChannel(self._rtc.createDataChannel(name, ordered=ordered))
self._dataChannels[name] = dc
return dc | def addDataChannel(self, name, ordered=True):
'\n Adds a data channel to the connection. Note that the RTCConnection adds a "default" channel\n automatically, which you can subscribe to directly.\n '
self._log.debug('Adding data channel to connection')
if ((name in self._dataChannels) or (name == 'default')):
raise KeyError('Data channel %s already exists', name)
dc = DataChannel(self._rtc.createDataChannel(name, ordered=ordered))
self._dataChannels[name] = dc
return dc<|docstring|>Adds a data channel to the connection. Note that the RTCConnection adds a "default" channel
automatically, which you can subscribe to directly.<|endoftext|> |
bb51950f3a86a834836ce5c63cfb9c210eb497148581511946720c7e9fdc60f8 | def getDataChannel(self, name):
'\n Returns the data channel with the given name. Please note that the "default" channel is considered special,\n and is not returned.\n '
if (name == 'default'):
raise KeyError("Default channel not available for 'get'. Use the RTCConnection's subscribe and put_nowait methods for access to it.")
return self._dataChannels[name] | Returns the data channel with the given name. Please note that the "default" channel is considered special,
and is not returned. | rtcbot/connection.py | getDataChannel | kimsooyoung/rtcbot | 35 | python | def getDataChannel(self, name):
'\n Returns the data channel with the given name. Please note that the "default" channel is considered special,\n and is not returned.\n '
if (name == 'default'):
raise KeyError("Default channel not available for 'get'. Use the RTCConnection's subscribe and put_nowait methods for access to it.")
return self._dataChannels[name] | def getDataChannel(self, name):
'\n Returns the data channel with the given name. Please note that the "default" channel is considered special,\n and is not returned.\n '
if (name == 'default'):
raise KeyError("Default channel not available for 'get'. Use the RTCConnection's subscribe and put_nowait methods for access to it.")
return self._dataChannels[name]<|docstring|>Returns the data channel with the given name. Please note that the "default" channel is considered special,
and is not returned.<|endoftext|> |
edd7900eb0ec6879ea110951f347309eae5abd0dd1d0a88f25e8e04a88f963ae | @property
def video(self):
'\n Convenience function - you can subscribe to it to get video frames once they show up\n '
return self._videoHandler | Convenience function - you can subscribe to it to get video frames once they show up | rtcbot/connection.py | video | kimsooyoung/rtcbot | 35 | python | @property
def video(self):
'\n \n '
return self._videoHandler | @property
def video(self):
'\n \n '
return self._videoHandler<|docstring|>Convenience function - you can subscribe to it to get video frames once they show up<|endoftext|> |
559b3d328f43ce25b4c2df50bfc8118d9d4eebaf5b8247bba3877a082bd9d343 | @property
def audio(self):
'\n Convenience function - you can subscribe to it to get audio once a stream is received\n '
return self._audioHandler | Convenience function - you can subscribe to it to get audio once a stream is received | rtcbot/connection.py | audio | kimsooyoung/rtcbot | 35 | python | @property
def audio(self):
'\n \n '
return self._audioHandler | @property
def audio(self):
'\n \n '
return self._audioHandler<|docstring|>Convenience function - you can subscribe to it to get audio once a stream is received<|endoftext|> |
5c35f11528c5c6bcb2789cfe44c53b3c5664ec6baae26f2a9805c80dbdb85864 | def close(self):
'\n If the loop is running, returns a future that will close the connection. Otherwise, runs\n the loop temporarily to complete closing.\n '
if self.closed:
if self._loop.is_running():
async def donothing():
pass
return asyncio.ensure_future(donothing())
return None
self._log.debug('Closing connection')
super().close()
self.video.close()
self.audio.close()
for dc in self._dataChannels:
self._dataChannels[dc].close()
self._dataChannelSubscriber.close()
if self._loop.is_running():
self._log.debug('Loop is running - close will return a future!')
return asyncio.ensure_future(self._rtc.close())
else:
self._loop.run_until_complete(self._rtc.close())
return None | If the loop is running, returns a future that will close the connection. Otherwise, runs
the loop temporarily to complete closing. | rtcbot/connection.py | close | kimsooyoung/rtcbot | 35 | python | def close(self):
'\n If the loop is running, returns a future that will close the connection. Otherwise, runs\n the loop temporarily to complete closing.\n '
if self.closed:
if self._loop.is_running():
async def donothing():
pass
return asyncio.ensure_future(donothing())
return None
self._log.debug('Closing connection')
super().close()
self.video.close()
self.audio.close()
for dc in self._dataChannels:
self._dataChannels[dc].close()
self._dataChannelSubscriber.close()
if self._loop.is_running():
self._log.debug('Loop is running - close will return a future!')
return asyncio.ensure_future(self._rtc.close())
else:
self._loop.run_until_complete(self._rtc.close())
return None | def close(self):
'\n If the loop is running, returns a future that will close the connection. Otherwise, runs\n the loop temporarily to complete closing.\n '
if self.closed:
if self._loop.is_running():
async def donothing():
pass
return asyncio.ensure_future(donothing())
return None
self._log.debug('Closing connection')
super().close()
self.video.close()
self.audio.close()
for dc in self._dataChannels:
self._dataChannels[dc].close()
self._dataChannelSubscriber.close()
if self._loop.is_running():
self._log.debug('Loop is running - close will return a future!')
return asyncio.ensure_future(self._rtc.close())
else:
self._loop.run_until_complete(self._rtc.close())
return None<|docstring|>If the loop is running, returns a future that will close the connection. Otherwise, runs
the loop temporarily to complete closing.<|endoftext|> |
6dcda9820e27e7ea613b56d7b49a24efd320d59617bd4e4b300d885acc1b5227 | def send(self, msg):
'\n Send is an alias for put_nowait - makes it easier for people new to rtcbot to understand\n what is going on\n '
self.put_nowait(msg) | Send is an alias for put_nowait - makes it easier for people new to rtcbot to understand
what is going on | rtcbot/connection.py | send | kimsooyoung/rtcbot | 35 | python | def send(self, msg):
'\n Send is an alias for put_nowait - makes it easier for people new to rtcbot to understand\n what is going on\n '
self.put_nowait(msg) | def send(self, msg):
'\n Send is an alias for put_nowait - makes it easier for people new to rtcbot to understand\n what is going on\n '
self.put_nowait(msg)<|docstring|>Send is an alias for put_nowait - makes it easier for people new to rtcbot to understand
what is going on<|endoftext|> |
e0b033e254b95e2c72aa0fa7abdd80c092d32cb7079ea548c3220809350ecb17 | @classmethod
async def fetch(cls, id: Union[(str, int)]) -> Optional['File']:
'Fetch a `File` with the given id.'
query = 'SELECT * FROM files WHERE id = $1'
record = (await cls.pool.fetchrow(query, int(id)))
if (record is None):
return None
return cls(**record) | Fetch a `File` with the given id. | cdn/file.py | fetch | Tech-With-Tim/models | 2 | python | @classmethod
async def fetch(cls, id: Union[(str, int)]) -> Optional['File']:
query = 'SELECT * FROM files WHERE id = $1'
record = (await cls.pool.fetchrow(query, int(id)))
if (record is None):
return None
return cls(**record) | @classmethod
async def fetch(cls, id: Union[(str, int)]) -> Optional['File']:
query = 'SELECT * FROM files WHERE id = $1'
record = (await cls.pool.fetchrow(query, int(id)))
if (record is None):
return None
return cls(**record)<|docstring|>Fetch a `File` with the given id.<|endoftext|> |
37f5861e2f7cc4edc0cc0e437759af6d3e8abc679480c7bc588b9beb0f9da0be | @property
def created_at(self) -> 'datetime':
'Returns the objects creation time in UTC.'
return utils.snowflake_time(id=self.id, internal=True) | Returns the objects creation time in UTC. | cdn/file.py | created_at | Tech-With-Tim/models | 2 | python | @property
def created_at(self) -> 'datetime':
return utils.snowflake_time(id=self.id, internal=True) | @property
def created_at(self) -> 'datetime':
return utils.snowflake_time(id=self.id, internal=True)<|docstring|>Returns the objects creation time in UTC.<|endoftext|> |
fac6d18f8cb7b5748d19337bd00518890b0c24e9af2fe86eb9c462ddb13e5321 | @pytest.mark.unit
def test_record_model_create(self, test_record_model):
'Should return a Subcategory record model instance.'
assert isinstance(test_record_model, RAMSTKSubCategoryRecord)
assert (test_record_model.__tablename__ == 'ramstk_subcategory')
assert (test_record_model.category_id == 1)
assert (test_record_model.subcategory_id == 1)
assert (test_record_model.description == 'Linear') | Should return a Subcategory record model instance. | tests/models/commondb/subcategory/subcategory_unit_test.py | test_record_model_create | weibullguy/ramstk | 4 | python | @pytest.mark.unit
def test_record_model_create(self, test_record_model):
assert isinstance(test_record_model, RAMSTKSubCategoryRecord)
assert (test_record_model.__tablename__ == 'ramstk_subcategory')
assert (test_record_model.category_id == 1)
assert (test_record_model.subcategory_id == 1)
assert (test_record_model.description == 'Linear') | @pytest.mark.unit
def test_record_model_create(self, test_record_model):
assert isinstance(test_record_model, RAMSTKSubCategoryRecord)
assert (test_record_model.__tablename__ == 'ramstk_subcategory')
assert (test_record_model.category_id == 1)
assert (test_record_model.subcategory_id == 1)
assert (test_record_model.description == 'Linear')<|docstring|>Should return a Subcategory record model instance.<|endoftext|> |
7ea89b44e28339158734af7714a53cd90f4aea973f3a6be66a099f2e996b88a3 | @pytest.mark.unit
def test_table_model_create(self, unit_test_table_model):
'Should return a Subcategory table model instance.'
assert isinstance(unit_test_table_model, RAMSTKSubCategoryTable)
assert isinstance(unit_test_table_model.tree, Tree)
assert isinstance(unit_test_table_model.dao, MockDAO)
assert (unit_test_table_model._lst_id_columns == ['category_id', 'subcategory_id'])
assert (unit_test_table_model._tag == 'subcategory')
assert (unit_test_table_model._root == 0)
assert pub.isSubscribed(unit_test_table_model.do_get_attributes, 'request_get_subcategory_attributes')
assert pub.isSubscribed(unit_test_table_model.do_get_tree, 'request_get_subcategory_tree') | Should return a Subcategory table model instance. | tests/models/commondb/subcategory/subcategory_unit_test.py | test_table_model_create | weibullguy/ramstk | 4 | python | @pytest.mark.unit
def test_table_model_create(self, unit_test_table_model):
assert isinstance(unit_test_table_model, RAMSTKSubCategoryTable)
assert isinstance(unit_test_table_model.tree, Tree)
assert isinstance(unit_test_table_model.dao, MockDAO)
assert (unit_test_table_model._lst_id_columns == ['category_id', 'subcategory_id'])
assert (unit_test_table_model._tag == 'subcategory')
assert (unit_test_table_model._root == 0)
assert pub.isSubscribed(unit_test_table_model.do_get_attributes, 'request_get_subcategory_attributes')
assert pub.isSubscribed(unit_test_table_model.do_get_tree, 'request_get_subcategory_tree') | @pytest.mark.unit
def test_table_model_create(self, unit_test_table_model):
assert isinstance(unit_test_table_model, RAMSTKSubCategoryTable)
assert isinstance(unit_test_table_model.tree, Tree)
assert isinstance(unit_test_table_model.dao, MockDAO)
assert (unit_test_table_model._lst_id_columns == ['category_id', 'subcategory_id'])
assert (unit_test_table_model._tag == 'subcategory')
assert (unit_test_table_model._root == 0)
assert pub.isSubscribed(unit_test_table_model.do_get_attributes, 'request_get_subcategory_attributes')
assert pub.isSubscribed(unit_test_table_model.do_get_tree, 'request_get_subcategory_tree')<|docstring|>Should return a Subcategory table model instance.<|endoftext|> |
18a3b5c4828dc4e48daf97e86ed80be958575313f8143ae21b8ceefb2245315b | @pytest.mark.unit
def test_get_attributes(self, test_record_model):
'Should return a dict of attribute key:value pairs.\n\n This method must be local because the attributes are different for each\n database record model.\n '
_attributes = test_record_model.get_attributes()
assert (_attributes['category_id'] == 1)
assert (_attributes['subcategory_id'] == 1)
assert (_attributes['description'] == 'Linear') | Should return a dict of attribute key:value pairs.
This method must be local because the attributes are different for each
database record model. | tests/models/commondb/subcategory/subcategory_unit_test.py | test_get_attributes | weibullguy/ramstk | 4 | python | @pytest.mark.unit
def test_get_attributes(self, test_record_model):
'Should return a dict of attribute key:value pairs.\n\n This method must be local because the attributes are different for each\n database record model.\n '
_attributes = test_record_model.get_attributes()
assert (_attributes['category_id'] == 1)
assert (_attributes['subcategory_id'] == 1)
assert (_attributes['description'] == 'Linear') | @pytest.mark.unit
def test_get_attributes(self, test_record_model):
'Should return a dict of attribute key:value pairs.\n\n This method must be local because the attributes are different for each\n database record model.\n '
_attributes = test_record_model.get_attributes()
assert (_attributes['category_id'] == 1)
assert (_attributes['subcategory_id'] == 1)
assert (_attributes['description'] == 'Linear')<|docstring|>Should return a dict of attribute key:value pairs.
This method must be local because the attributes are different for each
database record model.<|endoftext|> |
62f364957a1881df186e9cefc5d6e1573be65b4aa1549c1efff3f4ecae9baf3b | def compute(startdt, enddt, context):
'\n PE\n :param startdt:\n :param enddt:\n :return:\n '
user_log.info('pe compute')
_jyConnStr = 'mysql+pymysql://liangh:huaxun!@#db@172.18.44.5:3306/jydb'
engine = create_engine(_jyConnStr)
_category = [1]
_sectors = [1, 2, 6]
_sql = ("SELECT p.TradingDay,p.PE,a.SecuCode,a.SecuMarket FROM LC_DIndicesForValuation as p inner join secumain as a on a.innerCode=p.innerCode where a.SecuMarket in (83,90) and a.SecuCategory in (%s) and a.ListedSector in (%s) and a.ListedState!=9 and p.TradingDay between '%s' and '%s' order by p.TradingDay asc" % (','.join([str(i) for i in _category]), ','.join([str(i) for i in _sectors]), startdt.strftime('%Y-%m-%d'), enddt.strftime('%Y-%m-%d')))
print(_sql)
_res = pd.read_sql(sql=_sql, con=engine)
market = {90: 'XSHE', 83: 'XSHG'}
_res.SecuCode = ((_res.SecuCode + '.') + _res.SecuMarket.apply((lambda x: market.get(x))))
_res = _res.drop(['SecuMarket'], axis=1).set_index(['TradingDay', 'SecuCode']).unstack(level=(- 1))
_res.columns = _res.columns.droplevel(level=0)
return _res | PE
:param startdt:
:param enddt:
:return: | rqalpha/examples/pe.py | compute | xclxxl414/rqalpha | 0 | python | def compute(startdt, enddt, context):
'\n PE\n :param startdt:\n :param enddt:\n :return:\n '
user_log.info('pe compute')
_jyConnStr = 'mysql+pymysql://liangh:huaxun!@#db@172.18.44.5:3306/jydb'
engine = create_engine(_jyConnStr)
_category = [1]
_sectors = [1, 2, 6]
_sql = ("SELECT p.TradingDay,p.PE,a.SecuCode,a.SecuMarket FROM LC_DIndicesForValuation as p inner join secumain as a on a.innerCode=p.innerCode where a.SecuMarket in (83,90) and a.SecuCategory in (%s) and a.ListedSector in (%s) and a.ListedState!=9 and p.TradingDay between '%s' and '%s' order by p.TradingDay asc" % (','.join([str(i) for i in _category]), ','.join([str(i) for i in _sectors]), startdt.strftime('%Y-%m-%d'), enddt.strftime('%Y-%m-%d')))
print(_sql)
_res = pd.read_sql(sql=_sql, con=engine)
market = {90: 'XSHE', 83: 'XSHG'}
_res.SecuCode = ((_res.SecuCode + '.') + _res.SecuMarket.apply((lambda x: market.get(x))))
_res = _res.drop(['SecuMarket'], axis=1).set_index(['TradingDay', 'SecuCode']).unstack(level=(- 1))
_res.columns = _res.columns.droplevel(level=0)
return _res | def compute(startdt, enddt, context):
'\n PE\n :param startdt:\n :param enddt:\n :return:\n '
user_log.info('pe compute')
_jyConnStr = 'mysql+pymysql://liangh:huaxun!@#db@172.18.44.5:3306/jydb'
engine = create_engine(_jyConnStr)
_category = [1]
_sectors = [1, 2, 6]
_sql = ("SELECT p.TradingDay,p.PE,a.SecuCode,a.SecuMarket FROM LC_DIndicesForValuation as p inner join secumain as a on a.innerCode=p.innerCode where a.SecuMarket in (83,90) and a.SecuCategory in (%s) and a.ListedSector in (%s) and a.ListedState!=9 and p.TradingDay between '%s' and '%s' order by p.TradingDay asc" % (','.join([str(i) for i in _category]), ','.join([str(i) for i in _sectors]), startdt.strftime('%Y-%m-%d'), enddt.strftime('%Y-%m-%d')))
print(_sql)
_res = pd.read_sql(sql=_sql, con=engine)
market = {90: 'XSHE', 83: 'XSHG'}
_res.SecuCode = ((_res.SecuCode + '.') + _res.SecuMarket.apply((lambda x: market.get(x))))
_res = _res.drop(['SecuMarket'], axis=1).set_index(['TradingDay', 'SecuCode']).unstack(level=(- 1))
_res.columns = _res.columns.droplevel(level=0)
return _res<|docstring|>PE
:param startdt:
:param enddt:
:return:<|endoftext|> |
d0b91e365dce05783c7254af7804e8bd0feeea824bb0ed1a0b41e983fe23fc82 | def _onSendMenuButtonClicked(self):
'Executed when the menu button is clicked.'
send_to_3D_print_log = self._hasSlicedModel()
if (not send_to_3D_print_log):
Logger.log('d', 'No file sliced, not sending to 3D Print Log')
self._createDialog('Please slice file before sending to 3D Print Log.', 'File Not Sliced').exec()
return
self._sendTo3DPrintLog() | Executed when the menu button is clicked. | PrintLogUploader.py | _onSendMenuButtonClicked | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _onSendMenuButtonClicked(self):
send_to_3D_print_log = self._hasSlicedModel()
if (not send_to_3D_print_log):
Logger.log('d', 'No file sliced, not sending to 3D Print Log')
self._createDialog('Please slice file before sending to 3D Print Log.', 'File Not Sliced').exec()
return
self._sendTo3DPrintLog() | def _onSendMenuButtonClicked(self):
send_to_3D_print_log = self._hasSlicedModel()
if (not send_to_3D_print_log):
Logger.log('d', 'No file sliced, not sending to 3D Print Log')
self._createDialog('Please slice file before sending to 3D Print Log.', 'File Not Sliced').exec()
return
self._sendTo3DPrintLog()<|docstring|>Executed when the menu button is clicked.<|endoftext|> |
fbcfe858c5fab13bc0fc91e2edf89293b4e8b154b8e599645693f8e35bbcb983 | def _onWriteStarted(self, output_device):
'Send to 3D Print Log when gcode is saved.'
try:
send_to_3D_print_log = self._shouldSendTo3DPrintLog()
if (not send_to_3D_print_log):
Logger.log('d', 'User denied the prompt')
return
self._sendTo3DPrintLog()
except Exception:
Logger.logException('e', 'Exception raised in _onWriteStarted') | Send to 3D Print Log when gcode is saved. | PrintLogUploader.py | _onWriteStarted | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _onWriteStarted(self, output_device):
try:
send_to_3D_print_log = self._shouldSendTo3DPrintLog()
if (not send_to_3D_print_log):
Logger.log('d', 'User denied the prompt')
return
self._sendTo3DPrintLog()
except Exception:
Logger.logException('e', 'Exception raised in _onWriteStarted') | def _onWriteStarted(self, output_device):
try:
send_to_3D_print_log = self._shouldSendTo3DPrintLog()
if (not send_to_3D_print_log):
Logger.log('d', 'User denied the prompt')
return
self._sendTo3DPrintLog()
except Exception:
Logger.logException('e', 'Exception raised in _onWriteStarted')<|docstring|>Send to 3D Print Log when gcode is saved.<|endoftext|> |
35837f9b09807cc741f70e90479fcce93e475efcfa2db2a1727a567c841ba688 | def _sendTo3DPrintLog(self):
'Gets the print settings and send them to 3D Print Log'
try:
Logger.log('i', 'Generating Test Log')
data = dict()
data['curaVersion'] = self._application.getVersion()
data['pluginVersion'] = self.plugin_version
settings = dict()
settings['note'] = self._generateNotes()
settings['print_name'] = self._getPrintName()
settings.update(self._getCuraMetadata())
settings.update(self._getPrintTime())
settings.update(self._getMaterialUsage())
preferences = self._application.getInstance().getPreferences()
include_snapshot = preferences.getValue('3d_print_log/include_snapshot')
if include_snapshot:
snapshot = self._generateSnapshot()
if snapshot:
settings['snapshot'] = snapshot
data['settings'] = settings
self._sendToApi(data)
except Exception:
Logger.logException('e', 'Exception raised while sending print info in _sendTo3DPrintLog.') | Gets the print settings and send them to 3D Print Log | PrintLogUploader.py | _sendTo3DPrintLog | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _sendTo3DPrintLog(self):
try:
Logger.log('i', 'Generating Test Log')
data = dict()
data['curaVersion'] = self._application.getVersion()
data['pluginVersion'] = self.plugin_version
settings = dict()
settings['note'] = self._generateNotes()
settings['print_name'] = self._getPrintName()
settings.update(self._getCuraMetadata())
settings.update(self._getPrintTime())
settings.update(self._getMaterialUsage())
preferences = self._application.getInstance().getPreferences()
include_snapshot = preferences.getValue('3d_print_log/include_snapshot')
if include_snapshot:
snapshot = self._generateSnapshot()
if snapshot:
settings['snapshot'] = snapshot
data['settings'] = settings
self._sendToApi(data)
except Exception:
Logger.logException('e', 'Exception raised while sending print info in _sendTo3DPrintLog.') | def _sendTo3DPrintLog(self):
try:
Logger.log('i', 'Generating Test Log')
data = dict()
data['curaVersion'] = self._application.getVersion()
data['pluginVersion'] = self.plugin_version
settings = dict()
settings['note'] = self._generateNotes()
settings['print_name'] = self._getPrintName()
settings.update(self._getCuraMetadata())
settings.update(self._getPrintTime())
settings.update(self._getMaterialUsage())
preferences = self._application.getInstance().getPreferences()
include_snapshot = preferences.getValue('3d_print_log/include_snapshot')
if include_snapshot:
snapshot = self._generateSnapshot()
if snapshot:
settings['snapshot'] = snapshot
data['settings'] = settings
self._sendToApi(data)
except Exception:
Logger.logException('e', 'Exception raised while sending print info in _sendTo3DPrintLog.')<|docstring|>Gets the print settings and send them to 3D Print Log<|endoftext|> |
34c5520686d3a2c045aa6065615df6edafe72fb42d611db46791acca28879cbd | def _shouldSendTo3DPrintLog(self) -> bool:
'Returns true if this print should be sent.'
hasSliced = self._hasSlicedModel()
if (not hasSliced):
return False
dialog = self._createConfirmationDialog()
returnValue = dialog.exec()
return (returnValue == QMessageBox.Ok) | Returns true if this print should be sent. | PrintLogUploader.py | _shouldSendTo3DPrintLog | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _shouldSendTo3DPrintLog(self) -> bool:
hasSliced = self._hasSlicedModel()
if (not hasSliced):
return False
dialog = self._createConfirmationDialog()
returnValue = dialog.exec()
return (returnValue == QMessageBox.Ok) | def _shouldSendTo3DPrintLog(self) -> bool:
hasSliced = self._hasSlicedModel()
if (not hasSliced):
return False
dialog = self._createConfirmationDialog()
returnValue = dialog.exec()
return (returnValue == QMessageBox.Ok)<|docstring|>Returns true if this print should be sent.<|endoftext|> |
ba9adcd5fc31b429bb56ee267c6130a5a7042e534991e7b97f90f073ee9d0467 | def _hasSlicedModel(self) -> bool:
'Checks to see if the model has been sliced'
scene = self._application.getController().getScene()
if (not hasattr(scene, 'gcode_dict')):
return False
gcode_dict = getattr(scene, 'gcode_dict')
if (not gcode_dict):
return False
return True | Checks to see if the model has been sliced | PrintLogUploader.py | _hasSlicedModel | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _hasSlicedModel(self) -> bool:
scene = self._application.getController().getScene()
if (not hasattr(scene, 'gcode_dict')):
return False
gcode_dict = getattr(scene, 'gcode_dict')
if (not gcode_dict):
return False
return True | def _hasSlicedModel(self) -> bool:
scene = self._application.getController().getScene()
if (not hasattr(scene, 'gcode_dict')):
return False
gcode_dict = getattr(scene, 'gcode_dict')
if (not gcode_dict):
return False
return True<|docstring|>Checks to see if the model has been sliced<|endoftext|> |
e34e98bb4ca3d077818f393f5482b4da4d9a813075e64228a924074bd22b5364 | def _createConfirmationDialog(self):
'Create a message box prompting the user if they want to send this print information.'
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText('Would you like to send to 3Dprintlog.com?')
msgBox.setWindowTitle('Send to 3D Print Log?')
msgBox.setStandardButtons((QMessageBox.Ok | QMessageBox.Cancel))
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox | Create a message box prompting the user if they want to send this print information. | PrintLogUploader.py | _createConfirmationDialog | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _createConfirmationDialog(self):
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText('Would you like to send to 3Dprintlog.com?')
msgBox.setWindowTitle('Send to 3D Print Log?')
msgBox.setStandardButtons((QMessageBox.Ok | QMessageBox.Cancel))
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox | def _createConfirmationDialog(self):
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText('Would you like to send to 3Dprintlog.com?')
msgBox.setWindowTitle('Send to 3D Print Log?')
msgBox.setStandardButtons((QMessageBox.Ok | QMessageBox.Cancel))
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox<|docstring|>Create a message box prompting the user if they want to send this print information.<|endoftext|> |
3e3600a58dc1f519a740fc7716a4e74106ab20d6e5d593395d4e775cbbc905e2 | def _createDialog(self, text, title):
'Create a messsage box with a title and text'
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText(text)
msgBox.setWindowTitle(title)
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox | Create a messsage box with a title and text | PrintLogUploader.py | _createDialog | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _createDialog(self, text, title):
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText(text)
msgBox.setWindowTitle(title)
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox | def _createDialog(self, text, title):
msgBox = QMessageBox()
msgBox.setIcon(QMessageBox.Information)
msgBox.setText(text)
msgBox.setWindowTitle(title)
msgBox.setStandardButtons(QMessageBox.Ok)
msgBox.setDefaultButton(QMessageBox.Ok)
self._add3DPrintLogLogo(msgBox)
return msgBox<|docstring|>Create a messsage box with a title and text<|endoftext|> |
d7a72e3f176552420659a156f0bf976c4df9876a2bd0fb30eba2cdedcf01f8be | def _add3DPrintLogLogo(self, msgBox):
'Adds the 3D Print Log Logo as a message boxes icon.'
p = QPixmap()
plugin_path = PluginRegistry.getInstance().getPluginPath(self.getPluginId())
if (not plugin_path):
Logger.log('e', 'Could not get plugin path!', self.getPluginId())
return None
file_path = os.path.join(plugin_path, '3DPrintLog_logo_64px.jpg')
p.load(file_path)
msgBox.setIconPixmap(p) | Adds the 3D Print Log Logo as a message boxes icon. | PrintLogUploader.py | _add3DPrintLogLogo | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _add3DPrintLogLogo(self, msgBox):
p = QPixmap()
plugin_path = PluginRegistry.getInstance().getPluginPath(self.getPluginId())
if (not plugin_path):
Logger.log('e', 'Could not get plugin path!', self.getPluginId())
return None
file_path = os.path.join(plugin_path, '3DPrintLog_logo_64px.jpg')
p.load(file_path)
msgBox.setIconPixmap(p) | def _add3DPrintLogLogo(self, msgBox):
p = QPixmap()
plugin_path = PluginRegistry.getInstance().getPluginPath(self.getPluginId())
if (not plugin_path):
Logger.log('e', 'Could not get plugin path!', self.getPluginId())
return None
file_path = os.path.join(plugin_path, '3DPrintLog_logo_64px.jpg')
p.load(file_path)
msgBox.setIconPixmap(p)<|docstring|>Adds the 3D Print Log Logo as a message boxes icon.<|endoftext|> |
ea60d21ddded23553fa0df3add649d5190242c8ee8d47975e4a2be6be906e96c | def _sendToApi(self, data):
'Sends the data to the 3D Print Log api.'
binary_data = json.dumps(data).encode('utf-8')
network_manager = self._application.getHttpRequestManager()
network_manager.post(self.api_url, data=binary_data, callback=self._onRequestFinished, error_callback=self._onRequestError) | Sends the data to the 3D Print Log api. | PrintLogUploader.py | _sendToApi | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _sendToApi(self, data):
binary_data = json.dumps(data).encode('utf-8')
network_manager = self._application.getHttpRequestManager()
network_manager.post(self.api_url, data=binary_data, callback=self._onRequestFinished, error_callback=self._onRequestError) | def _sendToApi(self, data):
binary_data = json.dumps(data).encode('utf-8')
network_manager = self._application.getHttpRequestManager()
network_manager.post(self.api_url, data=binary_data, callback=self._onRequestFinished, error_callback=self._onRequestError)<|docstring|>Sends the data to the 3D Print Log api.<|endoftext|> |
feace19c4cac2ce62e22454b22a3c83a46022274f64d45269d761168a7ef389d | def _onRequestFinished(self, reply: 'QNetworkReply') -> None:
'Handle the response from the API after sending the settings.'
status_code = reply.attribute(QNetworkRequest.HttpStatusCodeAttribute)
if (status_code == 200):
results = json.loads(reply.readAll().data().decode('utf-8'))
newGuid = results['newSettingId']
data = dict()
data['cura_version'] = self._application.getVersion()
data['plugin_version'] = self.plugin_version
data['settingId'] = newGuid
self._openBrowser(data)
return
data = reply.readAll().data().decode('utf-8')
Logger.log('e', 'Settings Api request failed, status code %s, data: %s', status_code, data) | Handle the response from the API after sending the settings. | PrintLogUploader.py | _onRequestFinished | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _onRequestFinished(self, reply: 'QNetworkReply') -> None:
status_code = reply.attribute(QNetworkRequest.HttpStatusCodeAttribute)
if (status_code == 200):
results = json.loads(reply.readAll().data().decode('utf-8'))
newGuid = results['newSettingId']
data = dict()
data['cura_version'] = self._application.getVersion()
data['plugin_version'] = self.plugin_version
data['settingId'] = newGuid
self._openBrowser(data)
return
data = reply.readAll().data().decode('utf-8')
Logger.log('e', 'Settings Api request failed, status code %s, data: %s', status_code, data) | def _onRequestFinished(self, reply: 'QNetworkReply') -> None:
status_code = reply.attribute(QNetworkRequest.HttpStatusCodeAttribute)
if (status_code == 200):
results = json.loads(reply.readAll().data().decode('utf-8'))
newGuid = results['newSettingId']
data = dict()
data['cura_version'] = self._application.getVersion()
data['plugin_version'] = self.plugin_version
data['settingId'] = newGuid
self._openBrowser(data)
return
data = reply.readAll().data().decode('utf-8')
Logger.log('e', 'Settings Api request failed, status code %s, data: %s', status_code, data)<|docstring|>Handle the response from the API after sending the settings.<|endoftext|> |
5c98147d70eea3e1dff28741a7edae5c4617d77bfb384fa08b7b8652c746bd97 | def _openBrowser(self, data):
'Opens 3D Print Log website and passes the data as query params.'
import webbrowser
try:
from urllib import urlencode
except ImportError:
from urllib.parse import urlencode
query_params = urlencode(data)
url = ((self.new_print_url + '?') + query_params)
webbrowser.open(url, new=0, autoraise=True) | Opens 3D Print Log website and passes the data as query params. | PrintLogUploader.py | _openBrowser | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _openBrowser(self, data):
import webbrowser
try:
from urllib import urlencode
except ImportError:
from urllib.parse import urlencode
query_params = urlencode(data)
url = ((self.new_print_url + '?') + query_params)
webbrowser.open(url, new=0, autoraise=True) | def _openBrowser(self, data):
import webbrowser
try:
from urllib import urlencode
except ImportError:
from urllib.parse import urlencode
query_params = urlencode(data)
url = ((self.new_print_url + '?') + query_params)
webbrowser.open(url, new=0, autoraise=True)<|docstring|>Opens 3D Print Log website and passes the data as query params.<|endoftext|> |
9b76234d189eaefdfb8604c8c06d8acbfff1149ba65c757b33e14f1e66859760 | def _generateSnapshot(self) -> Optional[str]:
'Grabs the snapshot from the Cura Backend if one exists and returns it as a buffer.'
try:
Logger.log('i', 'Generating Snapshot')
backend = CuraApplication.getInstance().getBackend()
snapshot = (None if (getattr(backend, 'getLatestSnapshot', None) is None) else backend.getLatestSnapshot())
if (snapshot is None):
Logger.log('i', 'No snapshot from backend, generate snapshot ourselves.')
try:
from cura.Snapshot import Snapshot
snapshot = Snapshot.snapshot(width=300, height=300)
except:
Logger.log('e', 'Failed to create snapshot image')
return None
if snapshot:
Logger.log('i', 'Snapshot Found')
thumbnail_buffer = QBuffer()
thumbnail_buffer.open(QBuffer.ReadWrite)
snapshot.save(thumbnail_buffer, 'PNG')
encodedSnapshot = thumbnail_buffer.data().toBase64().data().decode('utf-8')
thumbnail_buffer.close()
return encodedSnapshot
else:
Logger.log('i', 'No Snapshot Found')
return None
except Exception:
Logger.logException('e', 'Exception raised while saving snapshot')
return None | Grabs the snapshot from the Cura Backend if one exists and returns it as a buffer. | PrintLogUploader.py | _generateSnapshot | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _generateSnapshot(self) -> Optional[str]:
try:
Logger.log('i', 'Generating Snapshot')
backend = CuraApplication.getInstance().getBackend()
snapshot = (None if (getattr(backend, 'getLatestSnapshot', None) is None) else backend.getLatestSnapshot())
if (snapshot is None):
Logger.log('i', 'No snapshot from backend, generate snapshot ourselves.')
try:
from cura.Snapshot import Snapshot
snapshot = Snapshot.snapshot(width=300, height=300)
except:
Logger.log('e', 'Failed to create snapshot image')
return None
if snapshot:
Logger.log('i', 'Snapshot Found')
thumbnail_buffer = QBuffer()
thumbnail_buffer.open(QBuffer.ReadWrite)
snapshot.save(thumbnail_buffer, 'PNG')
encodedSnapshot = thumbnail_buffer.data().toBase64().data().decode('utf-8')
thumbnail_buffer.close()
return encodedSnapshot
else:
Logger.log('i', 'No Snapshot Found')
return None
except Exception:
Logger.logException('e', 'Exception raised while saving snapshot')
return None | def _generateSnapshot(self) -> Optional[str]:
try:
Logger.log('i', 'Generating Snapshot')
backend = CuraApplication.getInstance().getBackend()
snapshot = (None if (getattr(backend, 'getLatestSnapshot', None) is None) else backend.getLatestSnapshot())
if (snapshot is None):
Logger.log('i', 'No snapshot from backend, generate snapshot ourselves.')
try:
from cura.Snapshot import Snapshot
snapshot = Snapshot.snapshot(width=300, height=300)
except:
Logger.log('e', 'Failed to create snapshot image')
return None
if snapshot:
Logger.log('i', 'Snapshot Found')
thumbnail_buffer = QBuffer()
thumbnail_buffer.open(QBuffer.ReadWrite)
snapshot.save(thumbnail_buffer, 'PNG')
encodedSnapshot = thumbnail_buffer.data().toBase64().data().decode('utf-8')
thumbnail_buffer.close()
return encodedSnapshot
else:
Logger.log('i', 'No Snapshot Found')
return None
except Exception:
Logger.logException('e', 'Exception raised while saving snapshot')
return None<|docstring|>Grabs the snapshot from the Cura Backend if one exists and returns it as a buffer.<|endoftext|> |
99ec06ee7956cb676b43ccb0b063f0c3ff23408f9e241b646f1e936005dba3f3 | def _getCuraMetadata(self):
'Returns meta data about cura and the plugin itself.'
data = dict()
data['time_stamp'] = time.time()
data['cura_version'] = self._application.getVersion()
data['cura_build_type'] = ApplicationMetadata.CuraBuildType
data['plugin_version'] = self.plugin_version
return data | Returns meta data about cura and the plugin itself. | PrintLogUploader.py | _getCuraMetadata | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _getCuraMetadata(self):
data = dict()
data['time_stamp'] = time.time()
data['cura_version'] = self._application.getVersion()
data['cura_build_type'] = ApplicationMetadata.CuraBuildType
data['plugin_version'] = self.plugin_version
return data | def _getCuraMetadata(self):
data = dict()
data['time_stamp'] = time.time()
data['cura_version'] = self._application.getVersion()
data['cura_build_type'] = ApplicationMetadata.CuraBuildType
data['plugin_version'] = self.plugin_version
return data<|docstring|>Returns meta data about cura and the plugin itself.<|endoftext|> |
a74f8afce30d0504206cd8c11cf719cfce759c3f014ad578dd1576a8ef6f79eb | def _getPrintTime(self):
'Returns the estimated print time in seconds.'
data = dict()
print_information = self._application.getPrintInformation()
data['estimated_print_time_seconds'] = int(print_information.currentPrintTime.getDisplayString(DurationFormat.Format.Seconds))
return data | Returns the estimated print time in seconds. | PrintLogUploader.py | _getPrintTime | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _getPrintTime(self):
data = dict()
print_information = self._application.getPrintInformation()
data['estimated_print_time_seconds'] = int(print_information.currentPrintTime.getDisplayString(DurationFormat.Format.Seconds))
return data | def _getPrintTime(self):
data = dict()
print_information = self._application.getPrintInformation()
data['estimated_print_time_seconds'] = int(print_information.currentPrintTime.getDisplayString(DurationFormat.Format.Seconds))
return data<|docstring|>Returns the estimated print time in seconds.<|endoftext|> |
72ce8eaa72e779c52b10b5647f87917bf2e472f4d3143a89981bf7c686e1a941 | def _getPrintName(self):
'Returns the name of the Print Object.'
for node in DepthFirstIterator(self._application.getController().getScene().getRoot()):
if node.callDecoration('isSliceable'):
return node.getName()
return '' | Returns the name of the Print Object. | PrintLogUploader.py | _getPrintName | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _getPrintName(self):
for node in DepthFirstIterator(self._application.getController().getScene().getRoot()):
if node.callDecoration('isSliceable'):
return node.getName()
return | def _getPrintName(self):
for node in DepthFirstIterator(self._application.getController().getScene().getRoot()):
if node.callDecoration('isSliceable'):
return node.getName()
return <|docstring|>Returns the name of the Print Object.<|endoftext|> |
01595a074ec5c0b4e35c6d26c667bde8fd7ed1414bc3eec871c026ccf1c18e3f | def _getMaterialUsage(self):
'Returns a dictionary containing the material used in milligrams.'
print_information = self._application.getPrintInformation()
data = dict()
material_used_g = sum(print_information.materialWeights)
material_used_mg = round((material_used_g * 1000))
data['material_used_mg'] = material_used_mg
return data | Returns a dictionary containing the material used in milligrams. | PrintLogUploader.py | _getMaterialUsage | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _getMaterialUsage(self):
print_information = self._application.getPrintInformation()
data = dict()
material_used_g = sum(print_information.materialWeights)
material_used_mg = round((material_used_g * 1000))
data['material_used_mg'] = material_used_mg
return data | def _getMaterialUsage(self):
print_information = self._application.getPrintInformation()
data = dict()
material_used_g = sum(print_information.materialWeights)
material_used_mg = round((material_used_g * 1000))
data['material_used_mg'] = material_used_mg
return data<|docstring|>Returns a dictionary containing the material used in milligrams.<|endoftext|> |
cbe09440739b3cf656e9fd227519f957bbd5c057b914c8e0cb684525f67bf779 | def _buildSettingRow(self, setting_name) -> str:
'Builds the string representation of a single setting, \n taking into account if the setting is different between extruders.'
machine_manager = self._application.getMachineManager()
global_stack = machine_manager.activeMachine
extruders = global_stack.extruderList
extruders = sorted(extruders, key=(lambda extruder: extruder.getMetaDataEntry('position')))
settingValues = collections.OrderedDict()
for extruder in extruders:
extruder_position = int(extruder.getMetaDataEntry('position', '0'))
print_information = self._application.getPrintInformation()
if (len(print_information.materialLengths) > extruder_position):
materialUsed = print_information.materialLengths[extruder_position]
if ((materialUsed is None) or (not (materialUsed > 0))):
continue
value = extruder.getProperty(setting_name, 'value')
unit = extruder.getProperty(setting_name, 'unit')
result = str(value)
if (unit and (not str(unit).isspace())):
if (str(unit) in ['°C', '°F', '%']):
result = (result + str(unit))
else:
result = ((result + ' ') + str(unit))
settingValues[('Ex ' + str((extruder_position + 1)))] = result
areAllValuesTheSame = (len(list(set(list(settingValues.values())))) == 1)
if areAllValuesTheSame:
label = global_stack.getProperty(setting_name, 'label')
value = list(settingValues.values())[0]
return ((str(label) + ': ') + str(value))
label = global_stack.getProperty(setting_name, 'label')
result = (str(label) + ': ')
isFirst = True
for setting in settingValues:
if (not isFirst):
result = (result + ', ')
result = ((((result + settingValues[setting]) + ' (') + str(setting)) + ')')
isFirst = False
return result | Builds the string representation of a single setting,
taking into account if the setting is different between extruders. | PrintLogUploader.py | _buildSettingRow | ChristopherHoffman/3d-print-log-cura-plugin | 5 | python | def _buildSettingRow(self, setting_name) -> str:
'Builds the string representation of a single setting, \n taking into account if the setting is different between extruders.'
machine_manager = self._application.getMachineManager()
global_stack = machine_manager.activeMachine
extruders = global_stack.extruderList
extruders = sorted(extruders, key=(lambda extruder: extruder.getMetaDataEntry('position')))
settingValues = collections.OrderedDict()
for extruder in extruders:
extruder_position = int(extruder.getMetaDataEntry('position', '0'))
print_information = self._application.getPrintInformation()
if (len(print_information.materialLengths) > extruder_position):
materialUsed = print_information.materialLengths[extruder_position]
if ((materialUsed is None) or (not (materialUsed > 0))):
continue
value = extruder.getProperty(setting_name, 'value')
unit = extruder.getProperty(setting_name, 'unit')
result = str(value)
if (unit and (not str(unit).isspace())):
if (str(unit) in ['°C', '°F', '%']):
result = (result + str(unit))
else:
result = ((result + ' ') + str(unit))
settingValues[('Ex ' + str((extruder_position + 1)))] = result
areAllValuesTheSame = (len(list(set(list(settingValues.values())))) == 1)
if areAllValuesTheSame:
label = global_stack.getProperty(setting_name, 'label')
value = list(settingValues.values())[0]
return ((str(label) + ': ') + str(value))
label = global_stack.getProperty(setting_name, 'label')
result = (str(label) + ': ')
isFirst = True
for setting in settingValues:
if (not isFirst):
result = (result + ', ')
result = ((((result + settingValues[setting]) + ' (') + str(setting)) + ')')
isFirst = False
return result | def _buildSettingRow(self, setting_name) -> str:
'Builds the string representation of a single setting, \n taking into account if the setting is different between extruders.'
machine_manager = self._application.getMachineManager()
global_stack = machine_manager.activeMachine
extruders = global_stack.extruderList
extruders = sorted(extruders, key=(lambda extruder: extruder.getMetaDataEntry('position')))
settingValues = collections.OrderedDict()
for extruder in extruders:
extruder_position = int(extruder.getMetaDataEntry('position', '0'))
print_information = self._application.getPrintInformation()
if (len(print_information.materialLengths) > extruder_position):
materialUsed = print_information.materialLengths[extruder_position]
if ((materialUsed is None) or (not (materialUsed > 0))):
continue
value = extruder.getProperty(setting_name, 'value')
unit = extruder.getProperty(setting_name, 'unit')
result = str(value)
if (unit and (not str(unit).isspace())):
if (str(unit) in ['°C', '°F', '%']):
result = (result + str(unit))
else:
result = ((result + ' ') + str(unit))
settingValues[('Ex ' + str((extruder_position + 1)))] = result
areAllValuesTheSame = (len(list(set(list(settingValues.values())))) == 1)
if areAllValuesTheSame:
label = global_stack.getProperty(setting_name, 'label')
value = list(settingValues.values())[0]
return ((str(label) + ': ') + str(value))
label = global_stack.getProperty(setting_name, 'label')
result = (str(label) + ': ')
isFirst = True
for setting in settingValues:
if (not isFirst):
result = (result + ', ')
result = ((((result + settingValues[setting]) + ' (') + str(setting)) + ')')
isFirst = False
return result<|docstring|>Builds the string representation of a single setting,
taking into account if the setting is different between extruders.<|endoftext|> |
7ce5a98b746fb2f00fbab878cfb79b952b4f0d861d55438666d9e7dd59e16f05 | def get_image_name(self):
'\n :return: image name\n ' | :return: image name | services/docker_runner.py | get_image_name | eliorav/Population-Genotype-Frequency | 0 | python | def get_image_name(self):
'\n \n ' | def get_image_name(self):
'\n \n '<|docstring|>:return: image name<|endoftext|> |
cf1eddd481c3e655da38dc779e8d7845ef1784e660c20d53ebf8482cf6c07167 | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n '
return None | Get a MIDI message, convert to button (0-7), top row (0-3) to select preset | src/midibox.py | get_button | ytsibizov/midibox | 4 | python | def get_button(self):
' \n '
return None | def get_button(self):
' \n '
return None<|docstring|>Get a MIDI message, convert to button (0-7), top row (0-3) to select preset<|endoftext|> |
d506106fd93906ccec959f61ea4be9243920e7cd486886a867d1bc2292bd4969 | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n DEBUG:root:[144, 91, 0]\n DEBUG:root:[144, 91, 127]\n DEBUG:root:[144, 92, 0]\n DEBUG:root:[144, 92, 127]\n DEBUG:root:[144, 93, 0]\n DEBUG:root:[144, 93, 127]\n DEBUG:root:[144, 94, 0]\n DEBUG:root:[144, 94, 127]\n Bottom row:\n DEBUG:root:[144, 86, 127]\n DEBUG:root:[144, 86, 0]\n DEBUG:root:[144, 95, 127]\n DEBUG:root:[144, 95, 0]\n DEBUG:root:[144, 48, 127]\n DEBUG:root:[144, 48, 0]\n DEBUG:root:[144, 49, 127]\n DEBUG:root:[144, 49, 0]\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 144) and (message[2] == 127)):
button = (message[1] - 91)
if ((button >= 0) and (button <= 3)):
logging.debug('Button {0}'.format(button))
return button
if (message[1] == 86):
button = 4
if (message[1] == 95):
button = 5
if (message[1] == 48):
button = 6
if (message[1] == 49):
button = 7
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None | Get a MIDI message, convert to button (0-7), top row (0-3) to select preset
Top row:
DEBUG:root:[144, 91, 0]
DEBUG:root:[144, 91, 127]
DEBUG:root:[144, 92, 0]
DEBUG:root:[144, 92, 127]
DEBUG:root:[144, 93, 0]
DEBUG:root:[144, 93, 127]
DEBUG:root:[144, 94, 0]
DEBUG:root:[144, 94, 127]
Bottom row:
DEBUG:root:[144, 86, 127]
DEBUG:root:[144, 86, 0]
DEBUG:root:[144, 95, 127]
DEBUG:root:[144, 95, 0]
DEBUG:root:[144, 48, 127]
DEBUG:root:[144, 48, 0]
DEBUG:root:[144, 49, 127]
DEBUG:root:[144, 49, 0] | src/midibox.py | get_button | ytsibizov/midibox | 4 | python | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n DEBUG:root:[144, 91, 0]\n DEBUG:root:[144, 91, 127]\n DEBUG:root:[144, 92, 0]\n DEBUG:root:[144, 92, 127]\n DEBUG:root:[144, 93, 0]\n DEBUG:root:[144, 93, 127]\n DEBUG:root:[144, 94, 0]\n DEBUG:root:[144, 94, 127]\n Bottom row:\n DEBUG:root:[144, 86, 127]\n DEBUG:root:[144, 86, 0]\n DEBUG:root:[144, 95, 127]\n DEBUG:root:[144, 95, 0]\n DEBUG:root:[144, 48, 127]\n DEBUG:root:[144, 48, 0]\n DEBUG:root:[144, 49, 127]\n DEBUG:root:[144, 49, 0]\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 144) and (message[2] == 127)):
button = (message[1] - 91)
if ((button >= 0) and (button <= 3)):
logging.debug('Button {0}'.format(button))
return button
if (message[1] == 86):
button = 4
if (message[1] == 95):
button = 5
if (message[1] == 48):
button = 6
if (message[1] == 49):
button = 7
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n DEBUG:root:[144, 91, 0]\n DEBUG:root:[144, 91, 127]\n DEBUG:root:[144, 92, 0]\n DEBUG:root:[144, 92, 127]\n DEBUG:root:[144, 93, 0]\n DEBUG:root:[144, 93, 127]\n DEBUG:root:[144, 94, 0]\n DEBUG:root:[144, 94, 127]\n Bottom row:\n DEBUG:root:[144, 86, 127]\n DEBUG:root:[144, 86, 0]\n DEBUG:root:[144, 95, 127]\n DEBUG:root:[144, 95, 0]\n DEBUG:root:[144, 48, 127]\n DEBUG:root:[144, 48, 0]\n DEBUG:root:[144, 49, 127]\n DEBUG:root:[144, 49, 0]\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 144) and (message[2] == 127)):
button = (message[1] - 91)
if ((button >= 0) and (button <= 3)):
logging.debug('Button {0}'.format(button))
return button
if (message[1] == 86):
button = 4
if (message[1] == 95):
button = 5
if (message[1] == 48):
button = 6
if (message[1] == 49):
button = 7
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None<|docstring|>Get a MIDI message, convert to button (0-7), top row (0-3) to select preset
Top row:
DEBUG:root:[144, 91, 0]
DEBUG:root:[144, 91, 127]
DEBUG:root:[144, 92, 0]
DEBUG:root:[144, 92, 127]
DEBUG:root:[144, 93, 0]
DEBUG:root:[144, 93, 127]
DEBUG:root:[144, 94, 0]
DEBUG:root:[144, 94, 127]
Bottom row:
DEBUG:root:[144, 86, 127]
DEBUG:root:[144, 86, 0]
DEBUG:root:[144, 95, 127]
DEBUG:root:[144, 95, 0]
DEBUG:root:[144, 48, 127]
DEBUG:root:[144, 48, 0]
DEBUG:root:[144, 49, 127]
DEBUG:root:[144, 49, 0]<|endoftext|> |
7667cfb9f2821d8977b7da712e5e0ac2dd6eafcd03f326ecfceeeedcc59232dc | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 138) and (message[2] == 0)):
button = (message[1] - 8)
if ((button >= 0) and (button <= 8)):
logging.debug('Button {0}'.format(button))
return button
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None | Get a MIDI message, convert to button (0-7), top row (0-3) to select preset
Top row: | src/midibox.py | get_button | ytsibizov/midibox | 4 | python | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 138) and (message[2] == 0)):
button = (message[1] - 8)
if ((button >= 0) and (button <= 8)):
logging.debug('Button {0}'.format(button))
return button
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None | def get_button(self):
' Get a MIDI message, convert to button (0-7), top row (0-3) to select preset\n Top row:\n '
button = None
msg = self.indev.get_message()
if msg:
(message, deltatime) = msg
logging.debug(('MIDI IN: %r' % message))
if ((message[0] == 138) and (message[2] == 0)):
button = (message[1] - 8)
if ((button >= 0) and (button <= 8)):
logging.debug('Button {0}'.format(button))
return button
if (button is not None):
logging.debug('Button {}'.format(button))
return button
return None<|docstring|>Get a MIDI message, convert to button (0-7), top row (0-3) to select preset
Top row:<|endoftext|> |
03ed506a10242aee68e2a615f9b0a79feee902d6327a7c7649b049e92e7fb922 | def load_authors(authors_file: Path) -> Dict[(str, Author)]:
'Load a list of authors from the given file'
with open(authors_file) as f:
authors_list = yaml.load(f, Loader=yaml.SafeLoader)
authors = [Author(**d) for d in authors_list]
return {author.name: author for author in authors} | Load a list of authors from the given file | advent/data.py | load_authors | camphor-/advent | 0 | python | def load_authors(authors_file: Path) -> Dict[(str, Author)]:
with open(authors_file) as f:
authors_list = yaml.load(f, Loader=yaml.SafeLoader)
authors = [Author(**d) for d in authors_list]
return {author.name: author for author in authors} | def load_authors(authors_file: Path) -> Dict[(str, Author)]:
with open(authors_file) as f:
authors_list = yaml.load(f, Loader=yaml.SafeLoader)
authors = [Author(**d) for d in authors_list]
return {author.name: author for author in authors}<|docstring|>Load a list of authors from the given file<|endoftext|> |
ae289fc92fde5e0911df2c27f08f34b024b75322a05be226bb0f9cc3af4c1da8 | def load_entries(entries_file: Path, authors: Mapping[(str, Author)]) -> List[Entry]:
'Load a list of entries from the given file\n\n This method replaces url of entries which are not published yet with None.\n '
today = datetime.now(tz=TIMEZONE).date()
def load_entry(d: Dict[(str, Any)]) -> Entry:
entry = Entry(**d)
if (entry.author is not None):
entry.author_url = authors[entry.author].url
if (entry.date > today):
entry.url = None
return entry
with open(entries_file) as f:
return list(map(load_entry, yaml.load(f, Loader=yaml.SafeLoader))) | Load a list of entries from the given file
This method replaces url of entries which are not published yet with None. | advent/data.py | load_entries | camphor-/advent | 0 | python | def load_entries(entries_file: Path, authors: Mapping[(str, Author)]) -> List[Entry]:
'Load a list of entries from the given file\n\n This method replaces url of entries which are not published yet with None.\n '
today = datetime.now(tz=TIMEZONE).date()
def load_entry(d: Dict[(str, Any)]) -> Entry:
entry = Entry(**d)
if (entry.author is not None):
entry.author_url = authors[entry.author].url
if (entry.date > today):
entry.url = None
return entry
with open(entries_file) as f:
return list(map(load_entry, yaml.load(f, Loader=yaml.SafeLoader))) | def load_entries(entries_file: Path, authors: Mapping[(str, Author)]) -> List[Entry]:
'Load a list of entries from the given file\n\n This method replaces url of entries which are not published yet with None.\n '
today = datetime.now(tz=TIMEZONE).date()
def load_entry(d: Dict[(str, Any)]) -> Entry:
entry = Entry(**d)
if (entry.author is not None):
entry.author_url = authors[entry.author].url
if (entry.date > today):
entry.url = None
return entry
with open(entries_file) as f:
return list(map(load_entry, yaml.load(f, Loader=yaml.SafeLoader)))<|docstring|>Load a list of entries from the given file
This method replaces url of entries which are not published yet with None.<|endoftext|> |
74e119de8f0b89048900682f5cdc24e9da834f5e9da57232daa3f4c83270ed69 | def group_entries_by_year(entries: Iterable[Entry]) -> Dict[(int, List[Entry])]:
'Groups entries by year in descending order'
entries_by_year = {}
years = list({e.date.year for e in entries})
for year in sorted(years, reverse=True):
entries_by_year[year] = [e for e in entries if (e.date.year == year)]
return entries_by_year | Groups entries by year in descending order | advent/data.py | group_entries_by_year | camphor-/advent | 0 | python | def group_entries_by_year(entries: Iterable[Entry]) -> Dict[(int, List[Entry])]:
entries_by_year = {}
years = list({e.date.year for e in entries})
for year in sorted(years, reverse=True):
entries_by_year[year] = [e for e in entries if (e.date.year == year)]
return entries_by_year | def group_entries_by_year(entries: Iterable[Entry]) -> Dict[(int, List[Entry])]:
entries_by_year = {}
years = list({e.date.year for e in entries})
for year in sorted(years, reverse=True):
entries_by_year[year] = [e for e in entries if (e.date.year == year)]
return entries_by_year<|docstring|>Groups entries by year in descending order<|endoftext|> |
7401480d96774f1d78016e13a9613d57cca01bee0a4b0ca2d2783e321282ab12 | def get_last_published_entries(entries: Iterable[Entry], n: int) -> List[Entry]:
'Get last N published entries in descending order'
return sorted(filter((lambda e: e.url), entries), reverse=True, key=attrgetter('date'))[:n] | Get last N published entries in descending order | advent/data.py | get_last_published_entries | camphor-/advent | 0 | python | def get_last_published_entries(entries: Iterable[Entry], n: int) -> List[Entry]:
return sorted(filter((lambda e: e.url), entries), reverse=True, key=attrgetter('date'))[:n] | def get_last_published_entries(entries: Iterable[Entry], n: int) -> List[Entry]:
return sorted(filter((lambda e: e.url), entries), reverse=True, key=attrgetter('date'))[:n]<|docstring|>Get last N published entries in descending order<|endoftext|> |
7aaae41eadabfc88689bb2356f401458b76004ff374c93cb8172b5690894fd30 | def get_entry_for_day(entries: Iterable[Entry], day: date) -> Optional[Entry]:
'Find an entry on the given day if it exists'
for entry in entries:
if (entry.date == day):
return entry
return None | Find an entry on the given day if it exists | advent/data.py | get_entry_for_day | camphor-/advent | 0 | python | def get_entry_for_day(entries: Iterable[Entry], day: date) -> Optional[Entry]:
for entry in entries:
if (entry.date == day):
return entry
return None | def get_entry_for_day(entries: Iterable[Entry], day: date) -> Optional[Entry]:
for entry in entries:
if (entry.date == day):
return entry
return None<|docstring|>Find an entry on the given day if it exists<|endoftext|> |
b3e5206923422703144aba29c462126bad254f28be103b6d55b8d7992d9a640f | def get_sha1(filepath):
'\n calculate the sha1 hash of the content of a given file\n\n Parameters\n ----------\n filepath : path\n the file of which to calculate the hash.\n\n Returns\n -------\n hash: str\n the hash of the content of the file.\n\n '
sha1sum = hashlib.sha1()
with open(filepath, 'rb') as source:
block = source.read((2 ** 16))
while (len(block) != 0):
sha1sum.update(block)
block = source.read((2 ** 16))
return sha1sum.hexdigest() | calculate the sha1 hash of the content of a given file
Parameters
----------
filepath : path
the file of which to calculate the hash.
Returns
-------
hash: str
the hash of the content of the file. | MedicalImageAnonymizer/GUI/_ssh_utils.py | get_sha1 | fiendish/MedicalImageAnonymizer | 2 | python | def get_sha1(filepath):
'\n calculate the sha1 hash of the content of a given file\n\n Parameters\n ----------\n filepath : path\n the file of which to calculate the hash.\n\n Returns\n -------\n hash: str\n the hash of the content of the file.\n\n '
sha1sum = hashlib.sha1()
with open(filepath, 'rb') as source:
block = source.read((2 ** 16))
while (len(block) != 0):
sha1sum.update(block)
block = source.read((2 ** 16))
return sha1sum.hexdigest() | def get_sha1(filepath):
'\n calculate the sha1 hash of the content of a given file\n\n Parameters\n ----------\n filepath : path\n the file of which to calculate the hash.\n\n Returns\n -------\n hash: str\n the hash of the content of the file.\n\n '
sha1sum = hashlib.sha1()
with open(filepath, 'rb') as source:
block = source.read((2 ** 16))
while (len(block) != 0):
sha1sum.update(block)
block = source.read((2 ** 16))
return sha1sum.hexdigest()<|docstring|>calculate the sha1 hash of the content of a given file
Parameters
----------
filepath : path
the file of which to calculate the hash.
Returns
-------
hash: str
the hash of the content of the file.<|endoftext|> |
f1ae289cd390693512bcc503a312a3bb349cc7001d97704500e9513fbffb9bf5 | @contextmanager
def get_destination_local(params, remote_config):
'\n generate a context manager with the remote connection to the server\n\n Parameters\n ----------\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Yields\n ------\n rem : RemoteConnection\n the actul connection to the remote server.\n\n todo : path\n the (remote) directory where to write the files in the pushin.\n\n done : path\n the (remote) directory where to search for the completed results.\n\n '
with ParamikoMachine(missing_host_policy=paramiko.AutoAddPolicy(), **params) as rem:
with rem.cwd(remote_config['base_dir']):
todo = (rem.cwd / remote_config['todo_subdir'])
done = (rem.cwd / remote_config['done_subdir'])
(yield (rem, todo, done)) | generate a context manager with the remote connection to the server
Parameters
----------
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Yields
------
rem : RemoteConnection
the actul connection to the remote server.
todo : path
the (remote) directory where to write the files in the pushin.
done : path
the (remote) directory where to search for the completed results. | MedicalImageAnonymizer/GUI/_ssh_utils.py | get_destination_local | fiendish/MedicalImageAnonymizer | 2 | python | @contextmanager
def get_destination_local(params, remote_config):
'\n generate a context manager with the remote connection to the server\n\n Parameters\n ----------\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Yields\n ------\n rem : RemoteConnection\n the actul connection to the remote server.\n\n todo : path\n the (remote) directory where to write the files in the pushin.\n\n done : path\n the (remote) directory where to search for the completed results.\n\n '
with ParamikoMachine(missing_host_policy=paramiko.AutoAddPolicy(), **params) as rem:
with rem.cwd(remote_config['base_dir']):
todo = (rem.cwd / remote_config['todo_subdir'])
done = (rem.cwd / remote_config['done_subdir'])
(yield (rem, todo, done)) | @contextmanager
def get_destination_local(params, remote_config):
'\n generate a context manager with the remote connection to the server\n\n Parameters\n ----------\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Yields\n ------\n rem : RemoteConnection\n the actul connection to the remote server.\n\n todo : path\n the (remote) directory where to write the files in the pushin.\n\n done : path\n the (remote) directory where to search for the completed results.\n\n '
with ParamikoMachine(missing_host_policy=paramiko.AutoAddPolicy(), **params) as rem:
with rem.cwd(remote_config['base_dir']):
todo = (rem.cwd / remote_config['todo_subdir'])
done = (rem.cwd / remote_config['done_subdir'])
(yield (rem, todo, done))<|docstring|>generate a context manager with the remote connection to the server
Parameters
----------
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Yields
------
rem : RemoteConnection
the actul connection to the remote server.
todo : path
the (remote) directory where to write the files in the pushin.
done : path
the (remote) directory where to search for the completed results.<|endoftext|> |
45661fe82ece77233dc533af38d8f1ebaa4d37d050b0a0d23a7217eee2397281 | def query_single_file(filename, params, remote):
'\n given a filepath, check all the files on the remote server whose\n names contains the hash of the original one.\n\n Parameters\n ----------\n filepath : path\n filepath (with full locatable path) to search for in the server\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n origin_hash : str\n the hash of the original file (calculated on the content)\n\n exists : list of paths\n all the files on the server whose name contains the hash of the\n original file. The list is empty if no files are found\n\n '
with get_destination_local(params, remote) as (rem, todo, done):
origin = filename
origin_hash = get_sha1(origin)
source = (done / origin_hash)
find_hash = (lambda p: (origin_hash in str(p)))
paths = list(done.walk(filter=find_hash))
return (origin_hash, paths) | given a filepath, check all the files on the remote server whose
names contains the hash of the original one.
Parameters
----------
filepath : path
filepath (with full locatable path) to search for in the server
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Returns
-------
origin_hash : str
the hash of the original file (calculated on the content)
exists : list of paths
all the files on the server whose name contains the hash of the
original file. The list is empty if no files are found | MedicalImageAnonymizer/GUI/_ssh_utils.py | query_single_file | fiendish/MedicalImageAnonymizer | 2 | python | def query_single_file(filename, params, remote):
'\n given a filepath, check all the files on the remote server whose\n names contains the hash of the original one.\n\n Parameters\n ----------\n filepath : path\n filepath (with full locatable path) to search for in the server\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n origin_hash : str\n the hash of the original file (calculated on the content)\n\n exists : list of paths\n all the files on the server whose name contains the hash of the\n original file. The list is empty if no files are found\n\n '
with get_destination_local(params, remote) as (rem, todo, done):
origin = filename
origin_hash = get_sha1(origin)
source = (done / origin_hash)
find_hash = (lambda p: (origin_hash in str(p)))
paths = list(done.walk(filter=find_hash))
return (origin_hash, paths) | def query_single_file(filename, params, remote):
'\n given a filepath, check all the files on the remote server whose\n names contains the hash of the original one.\n\n Parameters\n ----------\n filepath : path\n filepath (with full locatable path) to search for in the server\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n origin_hash : str\n the hash of the original file (calculated on the content)\n\n exists : list of paths\n all the files on the server whose name contains the hash of the\n original file. The list is empty if no files are found\n\n '
with get_destination_local(params, remote) as (rem, todo, done):
origin = filename
origin_hash = get_sha1(origin)
source = (done / origin_hash)
find_hash = (lambda p: (origin_hash in str(p)))
paths = list(done.walk(filter=find_hash))
return (origin_hash, paths)<|docstring|>given a filepath, check all the files on the remote server whose
names contains the hash of the original one.
Parameters
----------
filepath : path
filepath (with full locatable path) to search for in the server
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Returns
-------
origin_hash : str
the hash of the original file (calculated on the content)
exists : list of paths
all the files on the server whose name contains the hash of the
original file. The list is empty if no files are found<|endoftext|> |
d838d0d76fe6cd2d674a1bbcc79de37f3372edcc471f2143648d328f179b75a4 | def push_single_file(filepath, params, remote_config):
'\n upload a file to the server while changing its name\n\n Parameters\n ----------\n filepath : path\n the file to upload to the server.\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Raises\n ------\n FileExistsError\n if the file that would be generated already exists.\n\n Returns\n -------\n destination : path\n the location in which it has been copied on the server.\n\n '
with get_destination_local(params, remote_config) as (rem, todo, done):
origin = filepath
origin_hash = get_sha1(origin)
destination = (todo / origin_hash)
destination = destination.with_suffix(os.path.splitext(str(origin))[(- 1)])
destination = Path(destination)
if (not destination.exists()):
rem.upload(origin, destination)
else:
s = '{} has already been pushed'.format(filepath)
raise FileExistsError(s)
if False:
origin.chmod(read_only)
return destination | upload a file to the server while changing its name
Parameters
----------
filepath : path
the file to upload to the server.
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Raises
------
FileExistsError
if the file that would be generated already exists.
Returns
-------
destination : path
the location in which it has been copied on the server. | MedicalImageAnonymizer/GUI/_ssh_utils.py | push_single_file | fiendish/MedicalImageAnonymizer | 2 | python | def push_single_file(filepath, params, remote_config):
'\n upload a file to the server while changing its name\n\n Parameters\n ----------\n filepath : path\n the file to upload to the server.\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Raises\n ------\n FileExistsError\n if the file that would be generated already exists.\n\n Returns\n -------\n destination : path\n the location in which it has been copied on the server.\n\n '
with get_destination_local(params, remote_config) as (rem, todo, done):
origin = filepath
origin_hash = get_sha1(origin)
destination = (todo / origin_hash)
destination = destination.with_suffix(os.path.splitext(str(origin))[(- 1)])
destination = Path(destination)
if (not destination.exists()):
rem.upload(origin, destination)
else:
s = '{} has already been pushed'.format(filepath)
raise FileExistsError(s)
if False:
origin.chmod(read_only)
return destination | def push_single_file(filepath, params, remote_config):
'\n upload a file to the server while changing its name\n\n Parameters\n ----------\n filepath : path\n the file to upload to the server.\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Raises\n ------\n FileExistsError\n if the file that would be generated already exists.\n\n Returns\n -------\n destination : path\n the location in which it has been copied on the server.\n\n '
with get_destination_local(params, remote_config) as (rem, todo, done):
origin = filepath
origin_hash = get_sha1(origin)
destination = (todo / origin_hash)
destination = destination.with_suffix(os.path.splitext(str(origin))[(- 1)])
destination = Path(destination)
if (not destination.exists()):
rem.upload(origin, destination)
else:
s = '{} has already been pushed'.format(filepath)
raise FileExistsError(s)
if False:
origin.chmod(read_only)
return destination<|docstring|>upload a file to the server while changing its name
Parameters
----------
filepath : path
the file to upload to the server.
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Raises
------
FileExistsError
if the file that would be generated already exists.
Returns
-------
destination : path
the location in which it has been copied on the server.<|endoftext|> |
a1c32a80442592d2c3ac7c3557a26f80c500880559810b31c262e63213cdca62 | def pull_single_file(filepath, destination_dir, params, remote_config):
'\n\n Parameters\n ----------\n filepath : plumbum path object\n origin file to pull from the server\n\n destination_dir : plumbum path object\n the directory in which to copy the files\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n pulled_file: List[path]\n the list of filepaths downloaded from the server\n (after name-swapping the hash)\n\n '
pulled_file = []
with get_destination_local(params, remote_config) as (rem, todo, done):
(origin_hash, paths) = query_single_file(filepath, params, remote_config)
for path in paths:
path.remote = rem
dest_name = path.name.replace(origin_hash, filepath.stem)
destination = (destination_dir / dest_name)
rem.download(path, destination)
pulled_file.append(destination)
return pulled_file | Parameters
----------
filepath : plumbum path object
origin file to pull from the server
destination_dir : plumbum path object
the directory in which to copy the files
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Returns
-------
pulled_file: List[path]
the list of filepaths downloaded from the server
(after name-swapping the hash) | MedicalImageAnonymizer/GUI/_ssh_utils.py | pull_single_file | fiendish/MedicalImageAnonymizer | 2 | python | def pull_single_file(filepath, destination_dir, params, remote_config):
'\n\n Parameters\n ----------\n filepath : plumbum path object\n origin file to pull from the server\n\n destination_dir : plumbum path object\n the directory in which to copy the files\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n pulled_file: List[path]\n the list of filepaths downloaded from the server\n (after name-swapping the hash)\n\n '
pulled_file = []
with get_destination_local(params, remote_config) as (rem, todo, done):
(origin_hash, paths) = query_single_file(filepath, params, remote_config)
for path in paths:
path.remote = rem
dest_name = path.name.replace(origin_hash, filepath.stem)
destination = (destination_dir / dest_name)
rem.download(path, destination)
pulled_file.append(destination)
return pulled_file | def pull_single_file(filepath, destination_dir, params, remote_config):
'\n\n Parameters\n ----------\n filepath : plumbum path object\n origin file to pull from the server\n\n destination_dir : plumbum path object\n the directory in which to copy the files\n\n params : dict\n parameters of the connection host\n\n remote_config : dict\n parameters of the remote server\n\n Returns\n -------\n pulled_file: List[path]\n the list of filepaths downloaded from the server\n (after name-swapping the hash)\n\n '
pulled_file = []
with get_destination_local(params, remote_config) as (rem, todo, done):
(origin_hash, paths) = query_single_file(filepath, params, remote_config)
for path in paths:
path.remote = rem
dest_name = path.name.replace(origin_hash, filepath.stem)
destination = (destination_dir / dest_name)
rem.download(path, destination)
pulled_file.append(destination)
return pulled_file<|docstring|>Parameters
----------
filepath : plumbum path object
origin file to pull from the server
destination_dir : plumbum path object
the directory in which to copy the files
params : dict
parameters of the connection host
remote_config : dict
parameters of the remote server
Returns
-------
pulled_file: List[path]
the list of filepaths downloaded from the server
(after name-swapping the hash)<|endoftext|> |
3bbd32bf97bdffd9eb6aae1504d44d9825a34c0d792f6456bd669af1650b3c10 | def test_filerep_sync_ct(self):
'\n @data_provider sync_ct_tests\n '
fault_name = self.test_data[1][0]
fault_type = self.test_data[1][1]
fault_role = self.test_data[1][2]
filerep_state = self.test_data[1][3]
filerep_role = self.test_data[1][4]
tinctest.logger.info('\n ===============================================')
tinctest.logger.info(('\n Starting New Test: %s ' % self.test_data[0][1]))
tinctest.logger.info('\n ===============================================')
self.filerep_sync_ct(fault_name, fault_type, fault_role, filerep_state, filerep_role) | @data_provider sync_ct_tests | src/test/tinc/tincrepo/mpp/gpdb/tests/storage/fts/fts_transitions/test_fts_transitions_01.py | test_filerep_sync_ct | lintzc/GPDB | 1 | python | def test_filerep_sync_ct(self):
'\n \n '
fault_name = self.test_data[1][0]
fault_type = self.test_data[1][1]
fault_role = self.test_data[1][2]
filerep_state = self.test_data[1][3]
filerep_role = self.test_data[1][4]
tinctest.logger.info('\n ===============================================')
tinctest.logger.info(('\n Starting New Test: %s ' % self.test_data[0][1]))
tinctest.logger.info('\n ===============================================')
self.filerep_sync_ct(fault_name, fault_type, fault_role, filerep_state, filerep_role) | def test_filerep_sync_ct(self):
'\n \n '
fault_name = self.test_data[1][0]
fault_type = self.test_data[1][1]
fault_role = self.test_data[1][2]
filerep_state = self.test_data[1][3]
filerep_role = self.test_data[1][4]
tinctest.logger.info('\n ===============================================')
tinctest.logger.info(('\n Starting New Test: %s ' % self.test_data[0][1]))
tinctest.logger.info('\n ===============================================')
self.filerep_sync_ct(fault_name, fault_type, fault_role, filerep_state, filerep_role)<|docstring|>@data_provider sync_ct_tests<|endoftext|> |
4577121bc86ebe38c7750585a9210e12d7e20478b567d25127a6bad38eac047b | def __init__(self, completed_at=None, condition_note=None, container_image=None, cpu=None, created_at=None, created_by=None, data_set=None, display_id=None, entry_point=None, execution_time=None, favorite=None, full_name=None, git_model=None, gpu=None, id=None, key=None, local_data_set=None, log_summary=None, memo=None, memory=None, modified_at=None, modified_by=None, name=None, node=None, node_ports=None, options=None, parent_full_name_list=None, parents=None, partition=None, ports=None, started_at=None, status=None, status_type=None, tags=None, waiting_time=None, zip=None):
'TrainingApiModelsDetailsOutputModel - a model defined in Swagger'
self._completed_at = None
self._condition_note = None
self._container_image = None
self._cpu = None
self._created_at = None
self._created_by = None
self._data_set = None
self._display_id = None
self._entry_point = None
self._execution_time = None
self._favorite = None
self._full_name = None
self._git_model = None
self._gpu = None
self._id = None
self._key = None
self._local_data_set = None
self._log_summary = None
self._memo = None
self._memory = None
self._modified_at = None
self._modified_by = None
self._name = None
self._node = None
self._node_ports = None
self._options = None
self._parent_full_name_list = None
self._parents = None
self._partition = None
self._ports = None
self._started_at = None
self._status = None
self._status_type = None
self._tags = None
self._waiting_time = None
self._zip = None
self.discriminator = None
if (completed_at is not None):
self.completed_at = completed_at
if (condition_note is not None):
self.condition_note = condition_note
if (container_image is not None):
self.container_image = container_image
if (cpu is not None):
self.cpu = cpu
if (created_at is not None):
self.created_at = created_at
if (created_by is not None):
self.created_by = created_by
if (data_set is not None):
self.data_set = data_set
if (display_id is not None):
self.display_id = display_id
if (entry_point is not None):
self.entry_point = entry_point
if (execution_time is not None):
self.execution_time = execution_time
if (favorite is not None):
self.favorite = favorite
if (full_name is not None):
self.full_name = full_name
if (git_model is not None):
self.git_model = git_model
if (gpu is not None):
self.gpu = gpu
if (id is not None):
self.id = id
if (key is not None):
self.key = key
if (local_data_set is not None):
self.local_data_set = local_data_set
if (log_summary is not None):
self.log_summary = log_summary
if (memo is not None):
self.memo = memo
if (memory is not None):
self.memory = memory
if (modified_at is not None):
self.modified_at = modified_at
if (modified_by is not None):
self.modified_by = modified_by
if (name is not None):
self.name = name
if (node is not None):
self.node = node
if (node_ports is not None):
self.node_ports = node_ports
if (options is not None):
self.options = options
if (parent_full_name_list is not None):
self.parent_full_name_list = parent_full_name_list
if (parents is not None):
self.parents = parents
if (partition is not None):
self.partition = partition
if (ports is not None):
self.ports = ports
if (started_at is not None):
self.started_at = started_at
if (status is not None):
self.status = status
if (status_type is not None):
self.status_type = status_type
if (tags is not None):
self.tags = tags
if (waiting_time is not None):
self.waiting_time = waiting_time
if (zip is not None):
self.zip = zip | TrainingApiModelsDetailsOutputModel - a model defined in Swagger | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | __init__ | yonetatuu/kamonohashi | 100 | python | def __init__(self, completed_at=None, condition_note=None, container_image=None, cpu=None, created_at=None, created_by=None, data_set=None, display_id=None, entry_point=None, execution_time=None, favorite=None, full_name=None, git_model=None, gpu=None, id=None, key=None, local_data_set=None, log_summary=None, memo=None, memory=None, modified_at=None, modified_by=None, name=None, node=None, node_ports=None, options=None, parent_full_name_list=None, parents=None, partition=None, ports=None, started_at=None, status=None, status_type=None, tags=None, waiting_time=None, zip=None):
self._completed_at = None
self._condition_note = None
self._container_image = None
self._cpu = None
self._created_at = None
self._created_by = None
self._data_set = None
self._display_id = None
self._entry_point = None
self._execution_time = None
self._favorite = None
self._full_name = None
self._git_model = None
self._gpu = None
self._id = None
self._key = None
self._local_data_set = None
self._log_summary = None
self._memo = None
self._memory = None
self._modified_at = None
self._modified_by = None
self._name = None
self._node = None
self._node_ports = None
self._options = None
self._parent_full_name_list = None
self._parents = None
self._partition = None
self._ports = None
self._started_at = None
self._status = None
self._status_type = None
self._tags = None
self._waiting_time = None
self._zip = None
self.discriminator = None
if (completed_at is not None):
self.completed_at = completed_at
if (condition_note is not None):
self.condition_note = condition_note
if (container_image is not None):
self.container_image = container_image
if (cpu is not None):
self.cpu = cpu
if (created_at is not None):
self.created_at = created_at
if (created_by is not None):
self.created_by = created_by
if (data_set is not None):
self.data_set = data_set
if (display_id is not None):
self.display_id = display_id
if (entry_point is not None):
self.entry_point = entry_point
if (execution_time is not None):
self.execution_time = execution_time
if (favorite is not None):
self.favorite = favorite
if (full_name is not None):
self.full_name = full_name
if (git_model is not None):
self.git_model = git_model
if (gpu is not None):
self.gpu = gpu
if (id is not None):
self.id = id
if (key is not None):
self.key = key
if (local_data_set is not None):
self.local_data_set = local_data_set
if (log_summary is not None):
self.log_summary = log_summary
if (memo is not None):
self.memo = memo
if (memory is not None):
self.memory = memory
if (modified_at is not None):
self.modified_at = modified_at
if (modified_by is not None):
self.modified_by = modified_by
if (name is not None):
self.name = name
if (node is not None):
self.node = node
if (node_ports is not None):
self.node_ports = node_ports
if (options is not None):
self.options = options
if (parent_full_name_list is not None):
self.parent_full_name_list = parent_full_name_list
if (parents is not None):
self.parents = parents
if (partition is not None):
self.partition = partition
if (ports is not None):
self.ports = ports
if (started_at is not None):
self.started_at = started_at
if (status is not None):
self.status = status
if (status_type is not None):
self.status_type = status_type
if (tags is not None):
self.tags = tags
if (waiting_time is not None):
self.waiting_time = waiting_time
if (zip is not None):
self.zip = zip | def __init__(self, completed_at=None, condition_note=None, container_image=None, cpu=None, created_at=None, created_by=None, data_set=None, display_id=None, entry_point=None, execution_time=None, favorite=None, full_name=None, git_model=None, gpu=None, id=None, key=None, local_data_set=None, log_summary=None, memo=None, memory=None, modified_at=None, modified_by=None, name=None, node=None, node_ports=None, options=None, parent_full_name_list=None, parents=None, partition=None, ports=None, started_at=None, status=None, status_type=None, tags=None, waiting_time=None, zip=None):
self._completed_at = None
self._condition_note = None
self._container_image = None
self._cpu = None
self._created_at = None
self._created_by = None
self._data_set = None
self._display_id = None
self._entry_point = None
self._execution_time = None
self._favorite = None
self._full_name = None
self._git_model = None
self._gpu = None
self._id = None
self._key = None
self._local_data_set = None
self._log_summary = None
self._memo = None
self._memory = None
self._modified_at = None
self._modified_by = None
self._name = None
self._node = None
self._node_ports = None
self._options = None
self._parent_full_name_list = None
self._parents = None
self._partition = None
self._ports = None
self._started_at = None
self._status = None
self._status_type = None
self._tags = None
self._waiting_time = None
self._zip = None
self.discriminator = None
if (completed_at is not None):
self.completed_at = completed_at
if (condition_note is not None):
self.condition_note = condition_note
if (container_image is not None):
self.container_image = container_image
if (cpu is not None):
self.cpu = cpu
if (created_at is not None):
self.created_at = created_at
if (created_by is not None):
self.created_by = created_by
if (data_set is not None):
self.data_set = data_set
if (display_id is not None):
self.display_id = display_id
if (entry_point is not None):
self.entry_point = entry_point
if (execution_time is not None):
self.execution_time = execution_time
if (favorite is not None):
self.favorite = favorite
if (full_name is not None):
self.full_name = full_name
if (git_model is not None):
self.git_model = git_model
if (gpu is not None):
self.gpu = gpu
if (id is not None):
self.id = id
if (key is not None):
self.key = key
if (local_data_set is not None):
self.local_data_set = local_data_set
if (log_summary is not None):
self.log_summary = log_summary
if (memo is not None):
self.memo = memo
if (memory is not None):
self.memory = memory
if (modified_at is not None):
self.modified_at = modified_at
if (modified_by is not None):
self.modified_by = modified_by
if (name is not None):
self.name = name
if (node is not None):
self.node = node
if (node_ports is not None):
self.node_ports = node_ports
if (options is not None):
self.options = options
if (parent_full_name_list is not None):
self.parent_full_name_list = parent_full_name_list
if (parents is not None):
self.parents = parents
if (partition is not None):
self.partition = partition
if (ports is not None):
self.ports = ports
if (started_at is not None):
self.started_at = started_at
if (status is not None):
self.status = status
if (status_type is not None):
self.status_type = status_type
if (tags is not None):
self.tags = tags
if (waiting_time is not None):
self.waiting_time = waiting_time
if (zip is not None):
self.zip = zip<|docstring|>TrainingApiModelsDetailsOutputModel - a model defined in Swagger<|endoftext|> |
ba4d92cbe98a7cc91361fd7c74e369542b47dd951bd173a0a00dc519b13943a3 | @property
def completed_at(self):
'Gets the completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._completed_at | Gets the completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | completed_at | yonetatuu/kamonohashi | 100 | python | @property
def completed_at(self):
'Gets the completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._completed_at | @property
def completed_at(self):
'Gets the completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._completed_at<|docstring|>Gets the completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
5a8d10c1059ed05d7b7ebfa5551b1db695704c0ebd83deef2964d8163acb34aa | @completed_at.setter
def completed_at(self, completed_at):
'Sets the completed_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param completed_at: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._completed_at = completed_at | Sets the completed_at of this TrainingApiModelsDetailsOutputModel.
:param completed_at: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | completed_at | yonetatuu/kamonohashi | 100 | python | @completed_at.setter
def completed_at(self, completed_at):
'Sets the completed_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param completed_at: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._completed_at = completed_at | @completed_at.setter
def completed_at(self, completed_at):
'Sets the completed_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param completed_at: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._completed_at = completed_at<|docstring|>Sets the completed_at of this TrainingApiModelsDetailsOutputModel.
:param completed_at: The completed_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
227f61ffc625e5dd131299d9112c1854646a1455d0aeefdf5ed79d02c4cea0e9 | @property
def condition_note(self):
'Gets the condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._condition_note | Gets the condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | condition_note | yonetatuu/kamonohashi | 100 | python | @property
def condition_note(self):
'Gets the condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._condition_note | @property
def condition_note(self):
'Gets the condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._condition_note<|docstring|>Gets the condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
0c5a96b10d33220864298726cceb54577326397fcc74cd49a91d1b2294f9883d | @condition_note.setter
def condition_note(self, condition_note):
'Sets the condition_note of this TrainingApiModelsDetailsOutputModel.\n\n\n :param condition_note: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._condition_note = condition_note | Sets the condition_note of this TrainingApiModelsDetailsOutputModel.
:param condition_note: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | condition_note | yonetatuu/kamonohashi | 100 | python | @condition_note.setter
def condition_note(self, condition_note):
'Sets the condition_note of this TrainingApiModelsDetailsOutputModel.\n\n\n :param condition_note: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._condition_note = condition_note | @condition_note.setter
def condition_note(self, condition_note):
'Sets the condition_note of this TrainingApiModelsDetailsOutputModel.\n\n\n :param condition_note: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._condition_note = condition_note<|docstring|>Sets the condition_note of this TrainingApiModelsDetailsOutputModel.
:param condition_note: The condition_note of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
d27c2e01ac19a54cb23c3e38ff0c3b35fed87721b8e4733d4408354ee27725a4 | @property
def container_image(self):
'Gets the container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsContainerImageOutputModel\n '
return self._container_image | Gets the container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: ComponentsContainerImageOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | container_image | yonetatuu/kamonohashi | 100 | python | @property
def container_image(self):
'Gets the container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsContainerImageOutputModel\n '
return self._container_image | @property
def container_image(self):
'Gets the container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsContainerImageOutputModel\n '
return self._container_image<|docstring|>Gets the container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: ComponentsContainerImageOutputModel<|endoftext|> |
656685ce3deace501bfaf5159497a6ed14d07305bcdb6b7d6cf485c62e56d9d1 | @container_image.setter
def container_image(self, container_image):
'Sets the container_image of this TrainingApiModelsDetailsOutputModel.\n\n\n :param container_image: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsContainerImageOutputModel\n '
self._container_image = container_image | Sets the container_image of this TrainingApiModelsDetailsOutputModel.
:param container_image: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: ComponentsContainerImageOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | container_image | yonetatuu/kamonohashi | 100 | python | @container_image.setter
def container_image(self, container_image):
'Sets the container_image of this TrainingApiModelsDetailsOutputModel.\n\n\n :param container_image: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsContainerImageOutputModel\n '
self._container_image = container_image | @container_image.setter
def container_image(self, container_image):
'Sets the container_image of this TrainingApiModelsDetailsOutputModel.\n\n\n :param container_image: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsContainerImageOutputModel\n '
self._container_image = container_image<|docstring|>Sets the container_image of this TrainingApiModelsDetailsOutputModel.
:param container_image: The container_image of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: ComponentsContainerImageOutputModel<|endoftext|> |
1e353a494a9b596855613b8267b85df2e92216ad5b067e4e3574bb578e19ef3d | @property
def cpu(self):
'Gets the cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._cpu | Gets the cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: int | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | cpu | yonetatuu/kamonohashi | 100 | python | @property
def cpu(self):
'Gets the cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._cpu | @property
def cpu(self):
'Gets the cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._cpu<|docstring|>Gets the cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: int<|endoftext|> |
26ecfcc59373707b30ae9c0ff324499df1127ed8afe929498c508bf582e305a3 | @cpu.setter
def cpu(self, cpu):
'Sets the cpu of this TrainingApiModelsDetailsOutputModel.\n\n\n :param cpu: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._cpu = cpu | Sets the cpu of this TrainingApiModelsDetailsOutputModel.
:param cpu: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: int | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | cpu | yonetatuu/kamonohashi | 100 | python | @cpu.setter
def cpu(self, cpu):
'Sets the cpu of this TrainingApiModelsDetailsOutputModel.\n\n\n :param cpu: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._cpu = cpu | @cpu.setter
def cpu(self, cpu):
'Sets the cpu of this TrainingApiModelsDetailsOutputModel.\n\n\n :param cpu: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._cpu = cpu<|docstring|>Sets the cpu of this TrainingApiModelsDetailsOutputModel.
:param cpu: The cpu of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: int<|endoftext|> |
1fdec5797eafda43d25d3c64c2bb838169c432b6c023c9a3f229040b1117d87e | @property
def created_at(self):
'Gets the created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_at | Gets the created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | created_at | yonetatuu/kamonohashi | 100 | python | @property
def created_at(self):
'Gets the created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_at | @property
def created_at(self):
'Gets the created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_at<|docstring|>Gets the created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
fe2692788282d4358118b5ce9367ad89e248e248fa9ea1367c159299000b31d3 | @created_at.setter
def created_at(self, created_at):
'Sets the created_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_at: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_at = created_at | Sets the created_at of this TrainingApiModelsDetailsOutputModel.
:param created_at: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | created_at | yonetatuu/kamonohashi | 100 | python | @created_at.setter
def created_at(self, created_at):
'Sets the created_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_at: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_at = created_at | @created_at.setter
def created_at(self, created_at):
'Sets the created_at of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_at: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_at = created_at<|docstring|>Sets the created_at of this TrainingApiModelsDetailsOutputModel.
:param created_at: The created_at of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
372b9668a0d45199883fa4246d814069edfd0c00b52d1cd022db57ffd2bd7d82 | @property
def created_by(self):
'Gets the created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_by | Gets the created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | created_by | yonetatuu/kamonohashi | 100 | python | @property
def created_by(self):
'Gets the created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_by | @property
def created_by(self):
'Gets the created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._created_by<|docstring|>Gets the created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
46582b0577da1c2404de2e4aede8f8fa6b4156cd6c6e1ca4322f1f40eedfdb2f | @created_by.setter
def created_by(self, created_by):
'Sets the created_by of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_by: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_by = created_by | Sets the created_by of this TrainingApiModelsDetailsOutputModel.
:param created_by: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | created_by | yonetatuu/kamonohashi | 100 | python | @created_by.setter
def created_by(self, created_by):
'Sets the created_by of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_by: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_by = created_by | @created_by.setter
def created_by(self, created_by):
'Sets the created_by of this TrainingApiModelsDetailsOutputModel.\n\n\n :param created_by: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._created_by = created_by<|docstring|>Sets the created_by of this TrainingApiModelsDetailsOutputModel.
:param created_by: The created_by of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
5355736d623c0d0199b4917efc22c38a32faa4785eab50e3459cfa869d1f6dde | @property
def data_set(self):
'Gets the data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: DataSetApiModelsIndexOutputModel\n '
return self._data_set | Gets the data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: DataSetApiModelsIndexOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | data_set | yonetatuu/kamonohashi | 100 | python | @property
def data_set(self):
'Gets the data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: DataSetApiModelsIndexOutputModel\n '
return self._data_set | @property
def data_set(self):
'Gets the data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: DataSetApiModelsIndexOutputModel\n '
return self._data_set<|docstring|>Gets the data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: DataSetApiModelsIndexOutputModel<|endoftext|> |
10d3baaec7d47087a724f733c98ba8740fb0ce9a4aa7fda57b50eeb50b3238fd | @data_set.setter
def data_set(self, data_set):
'Sets the data_set of this TrainingApiModelsDetailsOutputModel.\n\n\n :param data_set: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: DataSetApiModelsIndexOutputModel\n '
self._data_set = data_set | Sets the data_set of this TrainingApiModelsDetailsOutputModel.
:param data_set: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: DataSetApiModelsIndexOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | data_set | yonetatuu/kamonohashi | 100 | python | @data_set.setter
def data_set(self, data_set):
'Sets the data_set of this TrainingApiModelsDetailsOutputModel.\n\n\n :param data_set: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: DataSetApiModelsIndexOutputModel\n '
self._data_set = data_set | @data_set.setter
def data_set(self, data_set):
'Sets the data_set of this TrainingApiModelsDetailsOutputModel.\n\n\n :param data_set: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: DataSetApiModelsIndexOutputModel\n '
self._data_set = data_set<|docstring|>Sets the data_set of this TrainingApiModelsDetailsOutputModel.
:param data_set: The data_set of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: DataSetApiModelsIndexOutputModel<|endoftext|> |
cecf045bd95ff82d187a36ddde19ebff7b559c49c841dd5892e667c66fb43ff6 | @property
def display_id(self):
'Gets the display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._display_id | Gets the display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: int | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | display_id | yonetatuu/kamonohashi | 100 | python | @property
def display_id(self):
'Gets the display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._display_id | @property
def display_id(self):
'Gets the display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: int\n '
return self._display_id<|docstring|>Gets the display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: int<|endoftext|> |
3707759b66d2b0af324a184aabe894934e64333508cac2fa3a5ee14db678e75a | @display_id.setter
def display_id(self, display_id):
'Sets the display_id of this TrainingApiModelsDetailsOutputModel.\n\n\n :param display_id: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._display_id = display_id | Sets the display_id of this TrainingApiModelsDetailsOutputModel.
:param display_id: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: int | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | display_id | yonetatuu/kamonohashi | 100 | python | @display_id.setter
def display_id(self, display_id):
'Sets the display_id of this TrainingApiModelsDetailsOutputModel.\n\n\n :param display_id: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._display_id = display_id | @display_id.setter
def display_id(self, display_id):
'Sets the display_id of this TrainingApiModelsDetailsOutputModel.\n\n\n :param display_id: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: int\n '
self._display_id = display_id<|docstring|>Sets the display_id of this TrainingApiModelsDetailsOutputModel.
:param display_id: The display_id of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: int<|endoftext|> |
3ecf3c117b0e46509731ee6efc3c2e73e7743e34d979dfc948a80fe65bde41a8 | @property
def entry_point(self):
'Gets the entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._entry_point | Gets the entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | entry_point | yonetatuu/kamonohashi | 100 | python | @property
def entry_point(self):
'Gets the entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._entry_point | @property
def entry_point(self):
'Gets the entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._entry_point<|docstring|>Gets the entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
6d0e3f2da4d2344653f89f203a53e0073a3be08c2f79fbf90aff799755b0a3cb | @entry_point.setter
def entry_point(self, entry_point):
'Sets the entry_point of this TrainingApiModelsDetailsOutputModel.\n\n\n :param entry_point: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._entry_point = entry_point | Sets the entry_point of this TrainingApiModelsDetailsOutputModel.
:param entry_point: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | entry_point | yonetatuu/kamonohashi | 100 | python | @entry_point.setter
def entry_point(self, entry_point):
'Sets the entry_point of this TrainingApiModelsDetailsOutputModel.\n\n\n :param entry_point: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._entry_point = entry_point | @entry_point.setter
def entry_point(self, entry_point):
'Sets the entry_point of this TrainingApiModelsDetailsOutputModel.\n\n\n :param entry_point: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._entry_point = entry_point<|docstring|>Sets the entry_point of this TrainingApiModelsDetailsOutputModel.
:param entry_point: The entry_point of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
3f4a7c654abe6c89ac71f2c942044b9e4a9736d4f780f5e3082ea1158af24a4f | @property
def execution_time(self):
'Gets the execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._execution_time | Gets the execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | execution_time | yonetatuu/kamonohashi | 100 | python | @property
def execution_time(self):
'Gets the execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._execution_time | @property
def execution_time(self):
'Gets the execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._execution_time<|docstring|>Gets the execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
3a0cdc83c779a153f28784dbf9a12a5f79498d6b72d9f6bbccc40bdf896302e0 | @execution_time.setter
def execution_time(self, execution_time):
'Sets the execution_time of this TrainingApiModelsDetailsOutputModel.\n\n\n :param execution_time: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._execution_time = execution_time | Sets the execution_time of this TrainingApiModelsDetailsOutputModel.
:param execution_time: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | execution_time | yonetatuu/kamonohashi | 100 | python | @execution_time.setter
def execution_time(self, execution_time):
'Sets the execution_time of this TrainingApiModelsDetailsOutputModel.\n\n\n :param execution_time: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._execution_time = execution_time | @execution_time.setter
def execution_time(self, execution_time):
'Sets the execution_time of this TrainingApiModelsDetailsOutputModel.\n\n\n :param execution_time: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._execution_time = execution_time<|docstring|>Sets the execution_time of this TrainingApiModelsDetailsOutputModel.
:param execution_time: The execution_time of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
01ae4532589660e347a167c472ef711c29c411eaafd4695923dc9edb2c092d39 | @property
def favorite(self):
'Gets the favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: bool\n '
return self._favorite | Gets the favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: bool | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | favorite | yonetatuu/kamonohashi | 100 | python | @property
def favorite(self):
'Gets the favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: bool\n '
return self._favorite | @property
def favorite(self):
'Gets the favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: bool\n '
return self._favorite<|docstring|>Gets the favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: bool<|endoftext|> |
a58c778df260b944df417e05794460bb682edec781c65d43784f5ec8df88a92b | @favorite.setter
def favorite(self, favorite):
'Sets the favorite of this TrainingApiModelsDetailsOutputModel.\n\n\n :param favorite: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: bool\n '
self._favorite = favorite | Sets the favorite of this TrainingApiModelsDetailsOutputModel.
:param favorite: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: bool | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | favorite | yonetatuu/kamonohashi | 100 | python | @favorite.setter
def favorite(self, favorite):
'Sets the favorite of this TrainingApiModelsDetailsOutputModel.\n\n\n :param favorite: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: bool\n '
self._favorite = favorite | @favorite.setter
def favorite(self, favorite):
'Sets the favorite of this TrainingApiModelsDetailsOutputModel.\n\n\n :param favorite: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: bool\n '
self._favorite = favorite<|docstring|>Sets the favorite of this TrainingApiModelsDetailsOutputModel.
:param favorite: The favorite of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: bool<|endoftext|> |
37d3a8c017332dcc6fe4001c48b15df727f85106b7fbbd056571c70df1345289 | @property
def full_name(self):
'Gets the full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._full_name | Gets the full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | full_name | yonetatuu/kamonohashi | 100 | python | @property
def full_name(self):
'Gets the full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._full_name | @property
def full_name(self):
'Gets the full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: str\n '
return self._full_name<|docstring|>Gets the full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: str<|endoftext|> |
e050e63b096aaee026bb99119adeb125abcf78d6a5633ec3d92160a310c4ed6b | @full_name.setter
def full_name(self, full_name):
'Sets the full_name of this TrainingApiModelsDetailsOutputModel.\n\n\n :param full_name: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._full_name = full_name | Sets the full_name of this TrainingApiModelsDetailsOutputModel.
:param full_name: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | full_name | yonetatuu/kamonohashi | 100 | python | @full_name.setter
def full_name(self, full_name):
'Sets the full_name of this TrainingApiModelsDetailsOutputModel.\n\n\n :param full_name: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._full_name = full_name | @full_name.setter
def full_name(self, full_name):
'Sets the full_name of this TrainingApiModelsDetailsOutputModel.\n\n\n :param full_name: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: str\n '
self._full_name = full_name<|docstring|>Sets the full_name of this TrainingApiModelsDetailsOutputModel.
:param full_name: The full_name of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: str<|endoftext|> |
491b2b9344ffdd9de00e56b4723cfed5fbcd3bfb393a6c601e8ad8f0de5b87f3 | @property
def git_model(self):
'Gets the git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsGitCommitOutputModel\n '
return self._git_model | Gets the git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: ComponentsGitCommitOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | git_model | yonetatuu/kamonohashi | 100 | python | @property
def git_model(self):
'Gets the git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsGitCommitOutputModel\n '
return self._git_model | @property
def git_model(self):
'Gets the git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n\n\n :return: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :rtype: ComponentsGitCommitOutputModel\n '
return self._git_model<|docstring|>Gets the git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:return: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:rtype: ComponentsGitCommitOutputModel<|endoftext|> |
55a5214002695b6f9ec890410f523fa5991edfcda575036eb7d504bfdd5a8b0a | @git_model.setter
def git_model(self, git_model):
'Sets the git_model of this TrainingApiModelsDetailsOutputModel.\n\n\n :param git_model: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsGitCommitOutputModel\n '
self._git_model = git_model | Sets the git_model of this TrainingApiModelsDetailsOutputModel.
:param git_model: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: ComponentsGitCommitOutputModel | sdk/kamonohashi/op/rest/models/training_api_models_details_output_model.py | git_model | yonetatuu/kamonohashi | 100 | python | @git_model.setter
def git_model(self, git_model):
'Sets the git_model of this TrainingApiModelsDetailsOutputModel.\n\n\n :param git_model: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsGitCommitOutputModel\n '
self._git_model = git_model | @git_model.setter
def git_model(self, git_model):
'Sets the git_model of this TrainingApiModelsDetailsOutputModel.\n\n\n :param git_model: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501\n :type: ComponentsGitCommitOutputModel\n '
self._git_model = git_model<|docstring|>Sets the git_model of this TrainingApiModelsDetailsOutputModel.
:param git_model: The git_model of this TrainingApiModelsDetailsOutputModel. # noqa: E501
:type: ComponentsGitCommitOutputModel<|endoftext|> |
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