', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1)","= df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no","homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag","idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem',","from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from","airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import","def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else:","de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator(","PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv')","med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres","* * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl","'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03',","* *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o","from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta","return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag )","{med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >>","pd import random # Default args definition default_args = {","dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem, branch_mulher]","mulheres\", default_args = default_args, schedule_interval='*/20 * * * *' )","/usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m =","def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m,","mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media","= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade","sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag","mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media","else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag","= PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df =","def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean()","def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean()","ou mulheres\", default_args = default_args, schedule_interval='*/20 * * * *'","datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False,","'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional',","1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG(","import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator,","male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem():","DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade media","description=\"Extrai dados do Titanic e calcula idade media para homens","pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos","= df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no","default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11,","bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male',","'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20),","import pandas as pd import random # Default args definition","if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female","= BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df","from airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator","'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } #","DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator","do Titanic e calcula idade media para homens ou mulheres\",","'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email':","print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher =","Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic","= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade","dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex","default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator(","'treino-03', description=\"Extrai dados do Titanic e calcula idade media para","'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True,",") get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag","python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem,","definition dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e","11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry':","False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag","18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries':","task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return","random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def","import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas","# Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past':","df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de","get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag )","df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic:","*' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv',","value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female =","python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med","idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher',","task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med","BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m():","return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF,","Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data","'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag =","PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female","import datetime, timedelta import pandas as pd import random #","'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay':","branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m","calcula idade media para homens ou mulheres\", default_args = default_args,","== 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator(","'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure':","task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value ==","Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def","branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df","MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return","idade media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20","PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value","20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1,","* * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv","False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'],","False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag","df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de","'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context):","= { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29,","https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female'])","'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>',","PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as","python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male':",") def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==","das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher,",") def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m',","default_args = default_args, schedule_interval='*/20 * * * *' ) get_data","== 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}')","e calcula idade media para homens ou mulheres\", default_args =","airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime","'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition","== 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}')","datetime, timedelta import pandas as pd import random # Default","'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def","'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem","datetime import datetime, timedelta import pandas as pd import random","timedelta import pandas as pd import random # Default args","dag = DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula","from datetime import datetime, timedelta import pandas as pd import","BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime,","print(f'Media de idade dos homens no Titanic: {med}') branch_homem =","return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag )","timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\"Extrai","-o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m","BranchPythonOperator from datetime import datetime, timedelta import pandas as pd","BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df =","'<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) }","= default_args, schedule_interval='*/20 * * * *' ) get_data =","args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date':",") def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem'","homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * * *","definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020,","escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m')","dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex","29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False,","df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic:","Titanic e calcula idade media para homens ou mulheres\", default_args","= PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >>","as pd import random # Default args definition default_args =","value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher'","pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das","{ 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18,","no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag )","random # Default args definition default_args = { 'owner': 'Rafael',","task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >>","import random # Default args definition default_args = { 'owner':","mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag","airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import","dados do Titanic e calcula idade media para homens ou","# Dag definition dag = DAG( 'treino-03', description=\"Extrai dados do","no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag )","{med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher():","para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 * *","dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem,","pandas as pd import random # Default args definition default_args","Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False,","media para homens ou mulheres\", default_args = default_args, schedule_interval='*/20 *","schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data',",") def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==","dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return","import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import","= DAG( 'treino-03', description=\"Extrai dados do Titanic e calcula idade","provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =","= PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if"],"string":"[\n \"python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =\",\n \"} # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados\",\n \"med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens\",\n \"de idade dos homens no Titanic: {med}') branch_homem = PythonOperator(\",\n \"task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv')\",\n \"= BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def\",\n \"'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher\",\n \"dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator(\",\n \"['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1)\",\n \"= df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no\",\n \"homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag\",\n \"idade dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem',\",\n \"from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from\",\n \"airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import\",\n \"def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else:\",\n \"de idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator(\",\n \"PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv')\",\n \"med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres\",\n \"* * * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl\",\n \"'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03',\",\n \"* *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o\",\n \"from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta\",\n \"return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag )\",\n \"{med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >>\",\n \"pd import random # Default args definition default_args = {\",\n \"dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem, branch_mulher]\",\n \"mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *' )\",\n \"/usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m =\",\n \"def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m,\",\n \"mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media\",\n \"= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade\",\n \"sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag\",\n \"mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media\",\n \"else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag\",\n \"= PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df =\",\n \"def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean()\",\n \"def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean()\",\n \"ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * * *'\",\n \"datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False,\",\n \"'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional',\",\n \"1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag = DAG(\",\n \"import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator,\",\n \"male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem():\",\n \"DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media\",\n \"description=\\\"Extrai dados do Titanic e calcula idade media para homens\",\n \"pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos\",\n \"= df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no\",\n \"default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11,\",\n \"bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male',\",\n \"'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20),\",\n \"import pandas as pd import random # Default args definition\",\n \"if value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female\",\n \"= BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df\",\n \"from airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator\",\n \"'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } #\",\n \"DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator\",\n \"do Titanic e calcula idade media para homens ou mulheres\\\",\",\n \"'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email':\",\n \"print(f'Media de idade das mulheres no Titanic: {med}') branch_mulher =\",\n \"Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic\",\n \"= pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade\",\n \"dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex\",\n \"default_args, schedule_interval='*/20 * * * *' ) get_data = BashOperator(\",\n \"'treino-03', description=\\\"Extrai dados do Titanic e calcula idade media para\",\n \"'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True,\",\n \") get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag\",\n \"python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >> [branch_homem,\",\n \"definition dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e\",\n \"11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry':\",\n \"False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag\",\n \"18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries':\",\n \"task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return\",\n \"random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def\",\n \"import PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas\",\n \"# Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past':\",\n \"df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de\",\n \"get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag )\",\n \"df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic:\",\n \"*' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv',\",\n \"value == 'male': return 'branch_homem' else: return 'branch_mulher' male_female =\",\n \"python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med\",\n \"idade das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher',\",\n \"task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med\",\n \"BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m():\",\n \"return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF,\",\n \"Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data\",\n \"'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag =\",\n \"PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female\",\n \"import datetime, timedelta import pandas as pd import random #\",\n \"'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay':\",\n \"branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m\",\n \"calcula idade media para homens ou mulheres\\\", default_args = default_args,\",\n \"== 'male': return 'branch_homem' else: return 'branch_mulher' male_female = BranchPythonOperator(\",\n \"'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure':\",\n \"task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value ==\",\n \"Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def\",\n \"branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher(): df\",\n \"MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return\",\n \"idade media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20\",\n \"PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value\",\n \"20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1,\",\n \"* * *' ) get_data = BashOperator( task_id='get-data', bash_command='curl https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv\",\n \"False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'],\",\n \"False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition dag\",\n \"df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de\",\n \"'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context):\",\n \"= { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29,\",\n \"https://raw.githubusercontent.com/A3Data/hermione/master/hermione/file_text/train.csv -o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female'])\",\n \"'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18, 20), 'email': ['<EMAIL>',\",\n \"PythonOperator, BranchPythonOperator from datetime import datetime, timedelta import pandas as\",\n \"python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male':\",\n \") def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==\",\n \"das mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher,\",\n \") def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m',\",\n \"default_args = default_args, schedule_interval='*/20 * * * *' ) get_data\",\n \"== 'female'].Age.mean() print(f'Media de idade das mulheres no Titanic: {med}')\",\n \"e calcula idade media para homens ou mulheres\\\", default_args =\",\n \"airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime\",\n \"'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) } # Dag definition\",\n \"== 'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}')\",\n \"datetime, timedelta import pandas as pd import random # Default\",\n \"'branch_mulher' male_female = BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def\",\n \"'male'].Age.mean() print(f'Media de idade dos homens no Titanic: {med}') branch_homem\",\n \"datetime import datetime, timedelta import pandas as pd import random\",\n \"timedelta import pandas as pd import random # Default args\",\n \"dag = DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula\",\n \"from datetime import datetime, timedelta import pandas as pd import\",\n \"BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import datetime,\",\n \"print(f'Media de idade dos homens no Titanic: {med}') branch_homem =\",\n \"return random.choice(['male', 'female']) escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag )\",\n \"timedelta(minutes=1) } # Dag definition dag = DAG( 'treino-03', description=\\\"Extrai\",\n \"-o /usr/local/airflow/data/train.csv', dag=dag ) def sorteia_h_m(): return random.choice(['male', 'female']) escolhe_h_m\",\n \"BranchPythonOperator from datetime import datetime, timedelta import pandas as pd\",\n \"BranchPythonOperator( task_id='condicional', python_callable=MouF, provide_context=True, dag=dag ) def mean_homem(): df =\",\n \"'<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'Retry_delay': timedelta(minutes=1) }\",\n \"= default_args, schedule_interval='*/20 * * * *' ) get_data =\",\n \"args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date':\",\n \") def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem'\",\n \"homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * * *\",\n \"definition default_args = { 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020,\",\n \"escolhe_h_m = PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m')\",\n \"dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex\",\n \"29, 18, 20), 'email': ['<EMAIL>', '<EMAIL>'], 'email_on_failure': False, 'email_on_retry': False,\",\n \"df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens no Titanic:\",\n \"Titanic e calcula idade media para homens ou mulheres\\\", default_args\",\n \"= PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >>\",\n \"as pd import random # Default args definition default_args =\",\n \"value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return 'branch_homem' else: return 'branch_mulher'\",\n \"pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex == 'female'].Age.mean() print(f'Media de idade das\",\n \"{ 'owner': 'Rafael', 'depends_on_past': False, 'start_date': datetime(2020, 11, 29, 18,\",\n \"no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag )\",\n \"random # Default args definition default_args = { 'owner': 'Rafael',\",\n \"task_id='branch_mulher', python_callable=mean_mulher, dag=dag ) get_data >> escolhe_h_m >> male_female >>\",\n \"import random # Default args definition default_args = { 'owner':\",\n \"mulheres no Titanic: {med}') branch_mulher = PythonOperator( task_id='branch_mulher', python_callable=mean_mulher, dag=dag\",\n \"airflow import DAG from airflow.operators.bash_operator import BashOperator from airflow.operators.python_operator import\",\n \"dados do Titanic e calcula idade media para homens ou\",\n \"# Dag definition dag = DAG( 'treino-03', description=\\\"Extrai dados do\",\n \"no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag )\",\n \"{med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem, dag=dag ) def mean_mulher():\",\n \"para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 * *\",\n \"dos homens no Titanic: {med}') branch_homem = PythonOperator( task_id='branch_homem', python_callable=mean_homem,\",\n \"pandas as pd import random # Default args definition default_args\",\n \"Default args definition default_args = { 'owner': 'Rafael', 'depends_on_past': False,\",\n \"media para homens ou mulheres\\\", default_args = default_args, schedule_interval='*/20 *\",\n \"schedule_interval='*/20 * * * *' ) get_data = BashOperator( task_id='get-data',\",\n \") def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med = df.loc[df.Sex ==\",\n \"dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if value == 'male': return\",\n \"import BashOperator from airflow.operators.python_operator import PythonOperator, BranchPythonOperator from datetime import\",\n \"= DAG( 'treino-03', description=\\\"Extrai dados do Titanic e calcula idade\",\n \"provide_context=True, dag=dag ) def mean_homem(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =\",\n \"= PythonOperator( task_id='escolhe-h-m', python_callable=sorteia_h_m, dag=dag ) def MouF(**context): value=context['task_instance'].xcom_pull(task_ids='escolhe-h-m') if\"\n]","isConversational":false}}},{"rowIdx":99,"cells":{"ngram":{"kind":"list like","value":["variable.\\n\" \"In that case it will list only the system","Dictionary of types from Tcl command, needs to be ordered","collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl","from Tcl command, needs to be ordered , this is","unnamed_args: :return: \"\"\" if 'selection' in args: argument = args['selection']","# # MIT Licence # # ########################################################## from tclCommands.TclCommand import","command to get the list of system variables example: list_sys","to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) #","execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\"","\"Returns the list of the names of system variables.\\n\" \"Without","get the list of system variables example: list_sys \"\"\" #","system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples':","the list with the names of system variables.\") # Dictionary","system parameters. \" \"As an argument use first letter or","import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get",":param args: :param unnamed_args: :return: \"\"\" if 'selection' in args:","types from Tcl command, needs to be ordered , this","args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if","args needs to be ordered help = { 'main': \"Returns","or cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to","def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args: :return:","# ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl","example: list_sys \"\"\" # List of all command aliases, to","with the names of system variables.\") # Dictionary of types","for current Tcl command: required = {'name','outname'} required = []","\"As an argument use first letter or first letters from","use first letter or first letters from the name \"","of all command aliases, to be able use old names","\"Outputs in Tcl Shell the list with the names of","command, args needs to be ordered help = { 'main':","of system variables.\\n\" \"Without an argument it will list all","Date: 8/17/2019 # # MIT Licence # # ########################################################## from","for Manufacturing # # File Author: <NAME> (c) # #","ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of","old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys',","gerber or excellon or geometry or cncjob or global.\\n\" \"Note:","# MIT Licence # # ########################################################## from tclCommands.TclCommand import *","starts with that string.\\n\" \"Main categories start with: gerber or","categories start with: gerber or excellon or geometry or cncjob","\"In that case it will list only the system variables","Tcl Shell the list with the names of system variables.\")","the value and 'set_sys system variable value' to set it.\\n\",","'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\"","class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list","(\"--\", \"Outputs in Tcl Shell the list with the names","or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system","if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return","\"of the system variable.\\n\" \"In that case it will list","command: required = {'name','outname'} required = [] # structured help",", this is for options like -optionname value option_types =","get the value and 'set_sys system variable value' to set","for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description","list of system variables example: list_sys \"\"\" # List of","\" \"As an argument use first letter or first letters","2D Post-processing for Manufacturing # # File Author: <NAME> (c)","Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand):","in Tcl Shell the list with the names of system","= {'name','outname'} required = [] # structured help for current","or first letters from the name \" \"of the system","the system variable.\\n\" \"In that case it will list only","'get_sys system variable' to get the value and 'set_sys system","# # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\"","% (\"--\", \"Outputs in Tcl Shell the list with the","system variables.\") # Dictionary of types from Tcl command, needs","be able use old names for backward compatibility (add_poly, add_polygon)","-optionname value option_types = collections.OrderedDict([ ]) # array of mandatory","8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand","to get the list of system variables example: list_sys \"\"\"","of system variables example: list_sys \"\"\" # List of all","all the system parameters. \" \"As an argument use first","is for options like -optionname value option_types = collections.OrderedDict([ ])","command, needs to be ordered , this is for options","variables example: list_sys \"\"\" # List of all command aliases,","system variables that starts with that string.\\n\" \"Main categories start","str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val =","\" \"of the system variable.\\n\" \"In that case it will","an argument it will list all the system parameters. \"","case it will list only the system variables that starts","of types from Tcl command, needs to be ordered arg_names","the list of system variables example: list_sys \"\"\" # List","args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else:","variables.\\n\" \"Without an argument it will list all the system","the system variables that starts with that string.\\n\" \"Main categories","value and 'set_sys system variable value' to set it.\\n\", 'args':","able use old names for backward compatibility (add_poly, add_polygon) aliases","%s' % (\"--\", \"Outputs in Tcl Shell the list with","of the names of system variables.\\n\" \"Without an argument it","the name \" \"of the system variable.\\n\" \"In that case","ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args):","needs to be ordered , this is for options like","{'name','outname'} required = [] # structured help for current command,","# Dictionary of types from Tcl command, needs to be","if 'selection' in args: argument = args['selection'] return str([k for","Shell the list with the names of system variables.\") #","Manufacturing # # File Author: <NAME> (c) # # Date:","FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME>","value option_types = collections.OrderedDict([ ]) # array of mandatory options","\"Main categories start with: gerber or excellon or geometry or","command aliases, to be able use old names for backward","<filename>tclCommands/TclCommandListSys.py # ########################################################## # FlatCAM: 2D Post-processing for Manufacturing #","tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to","excellon or geometry or cncjob or global.\\n\" \"Note: Use 'get_sys","ordered , this is for options like -optionname value option_types","geometry or cncjob or global.\\n\" \"Note: Use 'get_sys system variable'","\"\"\" if 'selection' in args: argument = args['selection'] return str([k","= args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))])","= collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from","types from Tcl command, needs to be ordered arg_names =","argument it will list all the system parameters. \" \"As","# # File Author: <NAME> (c) # # Date: 8/17/2019","to be ordered , this is for options like -optionname","current command, args needs to be ordered help = {","in args: argument = args['selection'] return str([k for k in","{ 'main': \"Returns the list of the names of system","names of system variables.\") # Dictionary of types from Tcl","ordered help = { 'main': \"Returns the list of the","system variables example: list_sys \"\"\" # List of all command","<NAME> (c) # # Date: 8/17/2019 # # MIT Licence","system variable' to get the value and 'set_sys system variable","or global.\\n\" \"Note: Use 'get_sys system variable' to get the","it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber',","# Date: 8/17/2019 # # MIT Licence # # ##########################################################","required = {'name','outname'} required = [] # structured help for","letters from the name \" \"of the system variable.\\n\" \"In","to get the value and 'set_sys system variable value' to","mandatory options for current Tcl command: required = {'name','outname'} required","\"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection' in","TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the list of","compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s","only the system variables that starts with that string.\\n\" \"Main","the list of the names of system variables.\\n\" \"Without an","name \" \"of the system variable.\\n\" \"In that case it","be ordered help = { 'main': \"Returns the list of","# array of mandatory options for current Tcl command: required","File Author: <NAME> (c) # # Date: 8/17/2019 # #","to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser',","collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj']","k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return","unnamed_args): \"\"\" :param args: :param unnamed_args: :return: \"\"\" if 'selection'","in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val)","or excellon or geometry or cncjob or global.\\n\" \"Note: Use","collections.OrderedDict([ ]) # array of mandatory options for current Tcl","]) # array of mandatory options for current Tcl command:","start with: gerber or excellon or geometry or cncjob or","with that string.\\n\" \"Main categories start with: gerber or excellon","gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param","be ordered , this is for options like -optionname value","Use 'get_sys system variable' to get the value and 'set_sys","argument = args['selection'] return str([k for k in self.app.defaults.keys() if","from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell command","options like -optionname value option_types = collections.OrderedDict([ ]) # array","for options like -optionname value option_types = collections.OrderedDict([ ]) #","# structured help for current command, args needs to be","and 'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([","= collections.OrderedDict([ ]) # array of mandatory options for current","names of system variables.\\n\" \"Without an argument it will list","structured help for current command, args needs to be ordered","command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str),","(add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s'","(c) # # Date: 8/17/2019 # # MIT Licence #","argument use first letter or first letters from the name","from Tcl command, needs to be ordered arg_names = collections.OrderedDict([","help for current command, args needs to be ordered help","'set_sys system variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]),","'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def","aliases = ['list_sys', 'listsys'] description = '%s %s' % (\"--\",","'selection' in args: argument = args['selection'] return str([k for k","the system parameters. \" \"As an argument use first letter","variables.\") # Dictionary of types from Tcl command, needs to","str), ]) # Dictionary of types from Tcl command, needs","list with the names of system variables.\") # Dictionary of","Tcl command: required = {'name','outname'} required = [] # structured","cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args: :param","['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self,","]) # Dictionary of types from Tcl command, needs to","str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return str([*self.app.defaults])","first letters from the name \" \"of the system variable.\\n\"","that case it will list only the system variables that","########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File","of mandatory options for current Tcl command: required = {'name','outname'}","args: :param unnamed_args: :return: \"\"\" if 'selection' in args: argument","letter or first letters from the name \" \"of the","an argument use first letter or first letters from the","for current command, args needs to be ordered help =","aliases, to be able use old names for backward compatibility","return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val","'%s %s' % (\"--\", \"Outputs in Tcl Shell the list","['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs in","system variables.\\n\" \"Without an argument it will list all the","option_types = collections.OrderedDict([ ]) # array of mandatory options for","= [] # structured help for current command, args needs","Author: <NAME> (c) # # Date: 8/17/2019 # # MIT","[] # structured help for current command, args needs to","be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary","= ['list_sys', 'listsys'] description = '%s %s' % (\"--\", \"Outputs","set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys","# ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # #","('selection', str), ]) # Dictionary of types from Tcl command,","\"Note: Use 'get_sys system variable' to get the value and","from the name \" \"of the system variable.\\n\" \"In that","that string.\\n\" \"Main categories start with: gerber or excellon or","current Tcl command: required = {'name','outname'} required = [] #","self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) #",":param unnamed_args: :return: \"\"\" if 'selection' in args: argument =","it will list only the system variables that starts with","= { 'main': \"Returns the list of the names of","arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types","MIT Licence # # ########################################################## from tclCommands.TclCommand import * class","it will list all the system parameters. \" \"As an","of types from Tcl command, needs to be ordered ,","Tcl command, needs to be ordered , this is for","args: argument = args['selection'] return str([k for k in self.app.defaults.keys()","like -optionname value option_types = collections.OrderedDict([ ]) # array of","all command aliases, to be able use old names for","list_sys \"\"\" # List of all command aliases, to be","to be ordered help = { 'main': \"Returns the list","'main': \"Returns the list of the names of system variables.\\n\"","list of the names of system variables.\\n\" \"Without an argument","variable' to get the value and 'set_sys system variable value'","'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args,","names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys']","list only the system variables that starts with that string.\\n\"",":return: \"\"\" if 'selection' in args: argument = args['selection'] return","# List of all command aliases, to be able use","needs to be ordered help = { 'main': \"Returns the","options for current Tcl command: required = {'name','outname'} required =","\"\"\" # List of all command aliases, to be able","variable value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys',","# FlatCAM: 2D Post-processing for Manufacturing # # File Author:","parameters. \" \"As an argument use first letter or first","\"\"\" Tcl shell command to get the list of system","this is for options like -optionname value option_types = collections.OrderedDict([","Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection',","shell command to get the list of system variables example:","'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys","with: gerber or excellon or geometry or cncjob or global.\\n\"","use old names for backward compatibility (add_poly, add_polygon) aliases =","that starts with that string.\\n\" \"Main categories start with: gerber","will list all the system parameters. \" \"As an argument","List of all command aliases, to be able use old","the names of system variables.\\n\" \"Without an argument it will","will list only the system variables that starts with that","value' to set it.\\n\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys","first letter or first letters from the name \" \"of","# # Date: 8/17/2019 # # MIT Licence # #","backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description =","'list_sys cncj'] } def execute(self, args, unnamed_args): \"\"\" :param args:","Tcl shell command to get the list of system variables","} def execute(self, args, unnamed_args): \"\"\" :param args: :param unnamed_args:","add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' %","help = { 'main': \"Returns the list of the names","]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] }","required = [] # structured help for current command, args","string.\\n\" \"Main categories start with: gerber or excellon or geometry","Post-processing for Manufacturing # # File Author: <NAME> (c) #","# File Author: <NAME> (c) # # Date: 8/17/2019 #","needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ])","list all the system parameters. \" \"As an argument use","\"Without an argument it will list all the system parameters.","to be able use old names for backward compatibility (add_poly,","description = '%s %s' % (\"--\", \"Outputs in Tcl Shell","system variable.\\n\" \"In that case it will list only the","for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys())","= '%s %s' % (\"--\", \"Outputs in Tcl Shell the","of system variables.\") # Dictionary of types from Tcl command,","cncjob or global.\\n\" \"Note: Use 'get_sys system variable' to get","'listsys'] description = '%s %s' % (\"--\", \"Outputs in Tcl","########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \"\"\" Tcl shell","* class TclCommandListSys(TclCommand): \"\"\" Tcl shell command to get the","global.\\n\" \"Note: Use 'get_sys system variable' to get the value","array of mandatory options for current Tcl command: required =","the names of system variables.\") # Dictionary of types from","variables that starts with that string.\\n\" \"Main categories start with:"],"string":"[\n \"variable.\\\\n\\\" \\\"In that case it will list only the system\",\n \"Dictionary of types from Tcl command, needs to be ordered\",\n \"collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl\",\n \"from Tcl command, needs to be ordered , this is\",\n \"unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection']\",\n \"# # MIT Licence # # ########################################################## from tclCommands.TclCommand import\",\n \"command to get the list of system variables example: list_sys\",\n \"to be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) #\",\n \"execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\"\",\n \"\\\"Returns the list of the names of system variables.\\\\n\\\" \\\"Without\",\n \"get the list of system variables example: list_sys \\\"\\\"\\\" #\",\n \"system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples':\",\n \"the list with the names of system variables.\\\") # Dictionary\",\n \"system parameters. \\\" \\\"As an argument use first letter or\",\n \"import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get\",\n \":param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args:\",\n \"types from Tcl command, needs to be ordered , this\",\n \"args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if\",\n \"args needs to be ordered help = { 'main': \\\"Returns\",\n \"or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to\",\n \"def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return:\",\n \"# ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl\",\n \"example: list_sys \\\"\\\"\\\" # List of all command aliases, to\",\n \"with the names of system variables.\\\") # Dictionary of types\",\n \"for current Tcl command: required = {'name','outname'} required = []\",\n \"\\\"As an argument use first letter or first letters from\",\n \"use first letter or first letters from the name \\\"\",\n \"of all command aliases, to be able use old names\",\n \"\\\"Outputs in Tcl Shell the list with the names of\",\n \"command, args needs to be ordered help = { 'main':\",\n \"of system variables.\\\\n\\\" \\\"Without an argument it will list all\",\n \"Date: 8/17/2019 # # MIT Licence # # ########################################################## from\",\n \"for Manufacturing # # File Author: <NAME> (c) # #\",\n \"ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of\",\n \"old names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys',\",\n \"gerber or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note:\",\n \"# MIT Licence # # ########################################################## from tclCommands.TclCommand import *\",\n \"starts with that string.\\\\n\\\" \\\"Main categories start with: gerber or\",\n \"categories start with: gerber or excellon or geometry or cncjob\",\n \"\\\"In that case it will list only the system variables\",\n \"Tcl Shell the list with the names of system variables.\\\")\",\n \"the value and 'set_sys system variable value' to set it.\\\\n\\\",\",\n \"'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\"\",\n \"class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list\",\n \"(\\\"--\\\", \\\"Outputs in Tcl Shell the list with the names\",\n \"or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system\",\n \"if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return\",\n \"\\\"of the system variable.\\\\n\\\" \\\"In that case it will list\",\n \"command: required = {'name','outname'} required = [] # structured help\",\n \", this is for options like -optionname value option_types =\",\n \"get the value and 'set_sys system variable value' to set\",\n \"for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description\",\n \"list of system variables example: list_sys \\\"\\\"\\\" # List of\",\n \"\\\" \\\"As an argument use first letter or first letters\",\n \"2D Post-processing for Manufacturing # # File Author: <NAME> (c)\",\n \"Licence # # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand):\",\n \"in Tcl Shell the list with the names of system\",\n \"= {'name','outname'} required = [] # structured help for current\",\n \"or first letters from the name \\\" \\\"of the system\",\n \"the system variable.\\\\n\\\" \\\"In that case it will list only\",\n \"'get_sys system variable' to get the value and 'set_sys system\",\n \"# # ########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\"\",\n \"% (\\\"--\\\", \\\"Outputs in Tcl Shell the list with the\",\n \"system variables.\\\") # Dictionary of types from Tcl command, needs\",\n \"be able use old names for backward compatibility (add_poly, add_polygon)\",\n \"-optionname value option_types = collections.OrderedDict([ ]) # array of mandatory\",\n \"8/17/2019 # # MIT Licence # # ########################################################## from tclCommands.TclCommand\",\n \"to get the list of system variables example: list_sys \\\"\\\"\\\"\",\n \"of system variables example: list_sys \\\"\\\"\\\" # List of all\",\n \"all the system parameters. \\\" \\\"As an argument use first\",\n \"is for options like -optionname value option_types = collections.OrderedDict([ ])\",\n \"command, needs to be ordered , this is for options\",\n \"variables example: list_sys \\\"\\\"\\\" # List of all command aliases,\",\n \"system variables that starts with that string.\\\\n\\\" \\\"Main categories start\",\n \"str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val =\",\n \"\\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it will\",\n \"an argument it will list all the system parameters. \\\"\",\n \"case it will list only the system variables that starts\",\n \"of types from Tcl command, needs to be ordered arg_names\",\n \"the list of system variables example: list_sys \\\"\\\"\\\" # List\",\n \"args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else:\",\n \"variables.\\\\n\\\" \\\"Without an argument it will list all the system\",\n \"the system variables that starts with that string.\\\\n\\\" \\\"Main categories\",\n \"value and 'set_sys system variable value' to set it.\\\\n\\\", 'args':\",\n \"able use old names for backward compatibility (add_poly, add_polygon) aliases\",\n \"%s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list with\",\n \"of the names of system variables.\\\\n\\\" \\\"Without an argument it\",\n \"the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case\",\n \"ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args):\",\n \"needs to be ordered , this is for options like\",\n \"{'name','outname'} required = [] # structured help for current command,\",\n \"# Dictionary of types from Tcl command, needs to be\",\n \"if 'selection' in args: argument = args['selection'] return str([k for\",\n \"Shell the list with the names of system variables.\\\") #\",\n \"Manufacturing # # File Author: <NAME> (c) # # Date:\",\n \"FlatCAM: 2D Post-processing for Manufacturing # # File Author: <NAME>\",\n \"value option_types = collections.OrderedDict([ ]) # array of mandatory options\",\n \"\\\"Main categories start with: gerber or excellon or geometry or\",\n \"command aliases, to be able use old names for backward\",\n \"<filename>tclCommands/TclCommandListSys.py # ########################################################## # FlatCAM: 2D Post-processing for Manufacturing #\",\n \"tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to\",\n \"excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys\",\n \"ordered , this is for options like -optionname value option_types\",\n \"geometry or cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable'\",\n \"\\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return str([k\",\n \"= args['selection'] return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))])\",\n \"= collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from\",\n \"types from Tcl command, needs to be ordered arg_names =\",\n \"argument it will list all the system parameters. \\\" \\\"As\",\n \"# # File Author: <NAME> (c) # # Date: 8/17/2019\",\n \"to be ordered , this is for options like -optionname\",\n \"current command, args needs to be ordered help = {\",\n \"in args: argument = args['selection'] return str([k for k in\",\n \"{ 'main': \\\"Returns the list of the names of system\",\n \"names of system variables.\\\") # Dictionary of types from Tcl\",\n \"ordered help = { 'main': \\\"Returns the list of the\",\n \"system variables example: list_sys \\\"\\\"\\\" # List of all command\",\n \"<NAME> (c) # # Date: 8/17/2019 # # MIT Licence\",\n \"system variable' to get the value and 'set_sys system variable\",\n \"or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the\",\n \"it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber',\",\n \"# Date: 8/17/2019 # # MIT Licence # # ##########################################################\",\n \"required = {'name','outname'} required = [] # structured help for\",\n \"letters from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In\",\n \"to get the value and 'set_sys system variable value' to\",\n \"mandatory options for current Tcl command: required = {'name','outname'} required\",\n \"\\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in\",\n \"TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the list of\",\n \"compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s\",\n \"only the system variables that starts with that string.\\\\n\\\" \\\"Main\",\n \"the list of the names of system variables.\\\\n\\\" \\\"Without an\",\n \"name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that case it\",\n \"be ordered help = { 'main': \\\"Returns the list of\",\n \"# array of mandatory options for current Tcl command: required\",\n \"File Author: <NAME> (c) # # Date: 8/17/2019 # #\",\n \"to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser',\",\n \"collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj']\",\n \"k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return\",\n \"unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection'\",\n \"in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val)\",\n \"or excellon or geometry or cncjob or global.\\\\n\\\" \\\"Note: Use\",\n \"collections.OrderedDict([ ]) # array of mandatory options for current Tcl\",\n \"]) # array of mandatory options for current Tcl command:\",\n \"start with: gerber or excellon or geometry or cncjob or\",\n \"with that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon\",\n \"gerber', 'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param\",\n \"be ordered , this is for options like -optionname value\",\n \"Use 'get_sys system variable' to get the value and 'set_sys\",\n \"argument = args['selection'] return str([k for k in self.app.defaults.keys() if\",\n \"from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command\",\n \"options like -optionname value option_types = collections.OrderedDict([ ]) # array\",\n \"for options like -optionname value option_types = collections.OrderedDict([ ]) #\",\n \"# structured help for current command, args needs to be\",\n \"and 'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([\",\n \"= collections.OrderedDict([ ]) # array of mandatory options for current\",\n \"names of system variables.\\\\n\\\" \\\"Without an argument it will list\",\n \"structured help for current command, args needs to be ordered\",\n \"command, needs to be ordered arg_names = collections.OrderedDict([ ('selection', str),\",\n \"(add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s'\",\n \"(c) # # Date: 8/17/2019 # # MIT Licence #\",\n \"argument use first letter or first letters from the name\",\n \"from Tcl command, needs to be ordered arg_names = collections.OrderedDict([\",\n \"help for current command, args needs to be ordered help\",\n \"'set_sys system variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]),\",\n \"'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def\",\n \"aliases = ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\",\",\n \"'selection' in args: argument = args['selection'] return str([k for k\",\n \"the system parameters. \\\" \\\"As an argument use first letter\",\n \"variables.\\\") # Dictionary of types from Tcl command, needs to\",\n \"str), ]) # Dictionary of types from Tcl command, needs\",\n \"list with the names of system variables.\\\") # Dictionary of\",\n \"Tcl command: required = {'name','outname'} required = [] # structured\",\n \"cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param\",\n \"['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self,\",\n \"]) # Dictionary of types from Tcl command, needs to\",\n \"str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) # return str([*self.app.defaults])\",\n \"first letters from the name \\\" \\\"of the system variable.\\\\n\\\"\",\n \"that case it will list only the system variables that\",\n \"########################################################## # FlatCAM: 2D Post-processing for Manufacturing # # File\",\n \"of mandatory options for current Tcl command: required = {'name','outname'}\",\n \"args: :param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument\",\n \"letter or first letters from the name \\\" \\\"of the\",\n \"an argument use first letter or first letters from the\",\n \"for current command, args needs to be ordered help =\",\n \"aliases, to be able use old names for backward compatibility\",\n \"return str([k for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val\",\n \"'%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the list\",\n \"['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in\",\n \"system variables.\\\\n\\\" \\\"Without an argument it will list all the\",\n \"option_types = collections.OrderedDict([ ]) # array of mandatory options for\",\n \"= [] # structured help for current command, args needs\",\n \"Author: <NAME> (c) # # Date: 8/17/2019 # # MIT\",\n \"[] # structured help for current command, args needs to\",\n \"be ordered arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary\",\n \"= ['list_sys', 'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs\",\n \"set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys\",\n \"# ########################################################## # FlatCAM: 2D Post-processing for Manufacturing # #\",\n \"('selection', str), ]) # Dictionary of types from Tcl command,\",\n \"\\\"Note: Use 'get_sys system variable' to get the value and\",\n \"from the name \\\" \\\"of the system variable.\\\\n\\\" \\\"In that\",\n \"that string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or\",\n \"current Tcl command: required = {'name','outname'} required = [] #\",\n \"self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys()) return str(ret_val) #\",\n \":param unnamed_args: :return: \\\"\\\"\\\" if 'selection' in args: argument =\",\n \"it will list only the system variables that starts with\",\n \"= { 'main': \\\"Returns the list of the names of\",\n \"arg_names = collections.OrderedDict([ ('selection', str), ]) # Dictionary of types\",\n \"MIT Licence # # ########################################################## from tclCommands.TclCommand import * class\",\n \"it will list all the system parameters. \\\" \\\"As an\",\n \"of types from Tcl command, needs to be ordered ,\",\n \"Tcl command, needs to be ordered , this is for\",\n \"args: argument = args['selection'] return str([k for k in self.app.defaults.keys()\",\n \"like -optionname value option_types = collections.OrderedDict([ ]) # array of\",\n \"all command aliases, to be able use old names for\",\n \"list_sys \\\"\\\"\\\" # List of all command aliases, to be\",\n \"to be ordered help = { 'main': \\\"Returns the list\",\n \"'main': \\\"Returns the list of the names of system variables.\\\\n\\\"\",\n \"list of the names of system variables.\\\\n\\\" \\\"Without an argument\",\n \"variable' to get the value and 'set_sys system variable value'\",\n \"'list_sys ser', 'list_sys gerber', 'list_sys cncj'] } def execute(self, args,\",\n \"names for backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys']\",\n \"list only the system variables that starts with that string.\\\\n\\\"\",\n \":return: \\\"\\\"\\\" if 'selection' in args: argument = args['selection'] return\",\n \"# List of all command aliases, to be able use\",\n \"needs to be ordered help = { 'main': \\\"Returns the\",\n \"options for current Tcl command: required = {'name','outname'} required =\",\n \"\\\"\\\"\\\" # List of all command aliases, to be able\",\n \"variable value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys',\",\n \"# FlatCAM: 2D Post-processing for Manufacturing # # File Author:\",\n \"parameters. \\\" \\\"As an argument use first letter or first\",\n \"\\\"\\\"\\\" Tcl shell command to get the list of system\",\n \"this is for options like -optionname value option_types = collections.OrderedDict([\",\n \"Tcl command, needs to be ordered arg_names = collections.OrderedDict([ ('selection',\",\n \"shell command to get the list of system variables example:\",\n \"'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys\",\n \"with: gerber or excellon or geometry or cncjob or global.\\\\n\\\"\",\n \"use old names for backward compatibility (add_poly, add_polygon) aliases =\",\n \"that starts with that string.\\\\n\\\" \\\"Main categories start with: gerber\",\n \"will list all the system parameters. \\\" \\\"As an argument\",\n \"List of all command aliases, to be able use old\",\n \"the names of system variables.\\\\n\\\" \\\"Without an argument it will\",\n \"will list only the system variables that starts with that\",\n \"value' to set it.\\\\n\\\", 'args': collections.OrderedDict([ ]), 'examples': ['list_sys', 'list_sys\",\n \"first letter or first letters from the name \\\" \\\"of\",\n \"# # Date: 8/17/2019 # # MIT Licence # #\",\n \"backward compatibility (add_poly, add_polygon) aliases = ['list_sys', 'listsys'] description =\",\n \"'list_sys cncj'] } def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args:\",\n \"Tcl shell command to get the list of system variables\",\n \"} def execute(self, args, unnamed_args): \\\"\\\"\\\" :param args: :param unnamed_args:\",\n \"add_polygon) aliases = ['list_sys', 'listsys'] description = '%s %s' %\",\n \"help = { 'main': \\\"Returns the list of the names\",\n \"]), 'examples': ['list_sys', 'list_sys ser', 'list_sys gerber', 'list_sys cncj'] }\",\n \"required = [] # structured help for current command, args\",\n \"string.\\\\n\\\" \\\"Main categories start with: gerber or excellon or geometry\",\n \"Post-processing for Manufacturing # # File Author: <NAME> (c) #\",\n \"# File Author: <NAME> (c) # # Date: 8/17/2019 #\",\n \"needs to be ordered arg_names = collections.OrderedDict([ ('selection', str), ])\",\n \"list all the system parameters. \\\" \\\"As an argument use\",\n \"\\\"Without an argument it will list all the system parameters.\",\n \"to be able use old names for backward compatibility (add_poly,\",\n \"description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell\",\n \"system variable.\\\\n\\\" \\\"In that case it will list only the\",\n \"for k in self.app.defaults.keys() if str(k).startswith(str(argument))]) else: ret_val = list(self.app.defaults.keys())\",\n \"= '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl Shell the\",\n \"of system variables.\\\") # Dictionary of types from Tcl command,\",\n \"cncjob or global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get\",\n \"'listsys'] description = '%s %s' % (\\\"--\\\", \\\"Outputs in Tcl\",\n \"########################################################## from tclCommands.TclCommand import * class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell\",\n \"* class TclCommandListSys(TclCommand): \\\"\\\"\\\" Tcl shell command to get the\",\n \"global.\\\\n\\\" \\\"Note: Use 'get_sys system variable' to get the value\",\n \"array of mandatory options for current Tcl command: required =\",\n \"the names of system variables.\\\") # Dictionary of types from\",\n \"variables that starts with that string.\\\\n\\\" \\\"Main categories start with:\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":0,"numItemsPerPage":100,"numTotalItems":12866649,"offset":0,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NDMzMDk4OCwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMCIsImV4cCI6MTc3NDMzNDU4OCwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.0ipVGbaD63Wz85Fqw_rCpHDa-Q1pH2w-1lppPM8r0Z5MU1aeNAg_LUF0D47I3Yp5gyUlxCWxh8P0Y6YV7nNGCw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":126831957853}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 82k |
|---|
[
"class Meta: fields = ( \"id\", \"couverture\", \"usage\", \"millesime\", \"map_color\",",
"( \"nom\", \"code_insee\", \"surface\", ) geo_field = \"mpoly\" model =",
"\"surface\", ) geo_field = \"mpoly\" model = ZonesBaties2018 class CouvertureSolSerializer(serializers.ModelSerializer):",
"GeoJSON serializer.... |
[
"from django.contrib import admin from .models import SearchResult # Register",
"your models here. class SearchResultAdmin(admin.ModelAdmin): fields = [\"query\", \"heading\", \"url\",",
"import admin from .models import SearchResult # Register your models",
"import SearchResult # Register your models here. c... |
[
"nlu_data = await asyncio.gather( file_importer.get_stories(), file_importer.get_nlu_data() ) # if stories.is_empty()",
"output_path: Text = DEFAULT_MODELS_PATH, force_training: bool = False, fixed_model_name: Optional[Text]",
"train_path = stack.enter_context(TempDirectoryPath(tempfile.mkdtemp())) # bf mod fro... |
[
"if prices[j]<=prices[i]: res.append(prices[i]-prices[j]) break if j==len(prices)-1: res.append(prices[i]) res.append(prices[-1]) return res",
"in range(len(prices)): for j in range(i+1,len(prices)): if prices[j]<=prices[i]: res.append(prices[i]-prices[j]) break",
"List[int]: res = [] for i in range(len(prices)... |
[
"self._context['is_redraw'] = False self._is_multi = len(sources) > 1 if not",
"self._vim.command('vertical resize ' + str(winwidth)) if not is_current_buffer: self._vim.call('win_gotoid', restore)",
"= ( 'Normal:' + self._context['highlight_window_background'] ) self._vim.command(('syntax match deniteSelectedL... |
[
"_stdchannel_redirected(stdchannel, dest_filename, mode=\"w\"): \"\"\" A context manager to temporarily redirect",
"= None dest_file = None try: if stdchannel is None:",
"\"RedirectStderr\"] @contextlib.contextmanager def _stdchannel_redirected(stdchannel, dest_filename, mode=\"w\"): \"\"\" A context manager",
... |
[
"\"grey\" app_email = \"<EMAIL>\" app_license = \"MIT\" # Includes in",
": \"public/js/doctype.js\"} # doctype_list_js = {\"doctype\" : \"public/js/doctype_list.js\"} # doctype_tree_js",
": \"public/js/doctype_tree.js\"} # doctype_calendar_js = {\"doctype\" : \"public/js/doctype_calendar.js\"} fixtures =",
"\... |
[
"= Embedding(self._vocab_size, 64)(question) eb_question = Dropout(0.3)(eb_question) conc = concatenate([eb_story, eb_question],",
"KerasModel class SimpleLSTM(KerasModel): \"\"\" Use a simple lstm neural network",
"name='story') question = Input((self._query_maxlen, ), name='question') conc = concatenate([stor... |
[] |
[
"activationName self.bn_name = bnName self.first_output = num_planes self.in_planes = self.first_output",
"from easyai.model.base_block.cls.pnasnet_block import CellA, CellB __all__ = ['pnasnet_A', 'pnasnet_B'] class",
"def downsample(self, planes): down_block = self.block(self.in_planes, planes, stride=2, bn_n... |
[
"def get_access_token(token): resp = None request_count = 0 url =",
"CONUS, 30m resolution \" \"SRTM between 60N and 60S, 30m",
"global coverage of 1000m.\", \"extensions\": [\"watermask\", \"vertexnormals\", \"octvertexnormals\", ], \"format\":",
"{ \"endX\": 1, \"endY\": 0, \"startX\": 0, \"startY\": 0 }",
... |
[
"2017 @author: dhingratul \"\"\" import urllib.request import os from selenium",
"download after the timeout period, an exceptions is thrown, and",
"1 return flag def getDriver(url): driver = webdriver.Chrome() driver.get(url) return",
"return driver def is_valid_pdf(fn): \"\"\"Check is the PDF valid \"\"\"",... |
[
"the most similar trajectory to a given country? Plots similar",
"= len(LINE_STYLES) dist_diff = os.path.join('../exp/results/', 'knn_raw.json') f = open(dist_diff,) dist_diff",
"= other_region.replace('*', '') plt.title(f'Comparing confirmed cases in {region} and {other_region}')",
"for val in regions: df = ... |
[
"context (currently not happening, since unclear, how and why helpful)",
"not happening, since unclear, how and why helpful) # self.device",
"information needs to be passed to # version D self.training",
"* x^{m + 1}|) `C`: Q(x) = (0.1 + |b_0",
"import Rational_base class Rational(Rational_base, HybridBlock... |
[
"+ yy - 2 * torch.matmul(x, y.t()) dist = dist.clamp(min=1e-12).sqrt()",
": https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master/models/triplet_loss.py def euclidean_dist(x, y): \"\"\"Computes Euclidean distance.\"\"\" m, n",
"+ 1e-12 return num / denom # Source : https://github.com/earhian... |
[
"sbahn_munich integration\"\"\" line_dict = { \"name\": \"S3\", \"color\": \"#333333\", \"text_color\":",
"integration\"\"\" line_dict = { \"name\": \"S3\", \"color\": \"#333333\", \"text_color\": \"#444444\",",
"\"\"\"Tests for the sbahn_munich integration\"\"\" line_dict = { \"name\": \"S3\",",
"line_dict =... |
[
"flask import render_template from flask_login import login_required homestack = Blueprint(\"homestack\",",
"python2.7 # -*- coding: latin-1 -*- from flask import Blueprint",
"# -*- coding: latin-1 -*- from flask import Blueprint from",
"coding: latin-1 -*- from flask import Blueprint from flask import",
"f... |
[
"established on :py:class:`StripeModelForm` \"\"\" class Meta: model = Supporter fields",
"urls_enabled' }), 'site_url': forms.TextInput(attrs={ 'data-bind': 'value: site_url, enable: urls_enabled' }),",
"{ 'public': _('Your name and image will be displayed on",
"a receipt'), 'logo_url': _(\"URL of your compa... |
[
"self._get_multi_todict def _get_one(self, name, *args, **kwargs): return(self._get_one_raw(name, 'All', 'json')) def",
"params = { 'q': symbol, 'type': typ, 'output': output, }",
"(result[-1][1] == ','): result.pop() # fix single-quoted strings elif (tokid",
"option\" \"vol\": \"the volume of options traded.... |
[
"embed, rate=1): label_set, len_all = self.preprocess_get_label_set(path) # 获取label转index字典等, 如果label2index存在则不转换了, dev验证集合的时候用",
"keras_textclassification.data_preprocess.text_preprocess import load_json, save_json from keras_textclassification.conf.path_config import path_model_dir path_fast_text_model_vocab2in... |
[
"for documentation. class PixelExpectations(GpuTestExpectations): def SetExpectations(self): # Sample Usage: #",
"LICENSE file. from gpu_tests.gpu_test_expectations import GpuTestExpectations # See the GpuTestExpectations",
"license that can be # found in the LICENSE file.",
"self.Fail('Pixel_CSSFilterEffects... |
[
"name='BudgetItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('year', models.IntegerField()), ('agency',",
"('status_changed_by', models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to=settings.AUTH_USER_MOD... |
[
"based on SMO algorithm', author_email=\"<EMAIL>\", packages=['pysvm'], license='MIT License', long_description=open('README.md', encoding='utf-8').read(),",
"#enables develop setuptools.setup( name='pysvm', version='0.1', description='PySVM : A NumPy implementation",
"description='PySVM : A NumPy implementatio... |
[
"cv2.imread(PATH_TO_IMAGE) image_expanded = np.expand_dims(image, axis=0) # Perform the actual detection",
"boxes and scores around the objects of interest in the",
"[1, None, None, 3] # i.e. a single-column array, where",
"results') vis_util.visualize_boxes_and_labels_on_image_array( image, np.squeeze(boxes)... |
[
"import BaseXpressDemocracyClubCsvImporter class Command(BaseXpressDemocracyClubCsvImporter): council_id = 'E06000027' addresses_name = 'parl.2017-06-08/Version",
"data_collection.management.commands import BaseXpressDemocracyClubCsvImporter class Command(BaseXpressDemocracyClubCsvImporter): council_id = 'E060000... |
[
"rest_framework.views import APIView from rest_framework.response import Response from rest_framework.decorators import",
"category_slug, format= None): category = self.get_object(category_slug) serializer = CategorySerializer(category) return",
"category_slug): try: return Category.objects.get(slug=category_sl... |
[
"other): return (self.id is None or other.id is None or",
"maxsize class Contact: def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None,",
"home self.mobile = mobile self.work = work self.fax = fax",
"is None or self.id == other.id) and self.fname == other.fname",
"email3=None, homepa... |
[
"ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,",
"in the # documentation and/or other materials provided with the",
"\"b\", \"\", 1.0 ), ] ) savePath = os.path.abspath( os.path.join(",
"p = IECore.BasicPreset( testObj, testObj.parameters()[\"b\"] ) self.assertTrue( p.applicableTo( testObj,... |
[
"a parameter. Based on above, total dimensionality of state vector",
"import layout, pacman, game, ghostAgents from .PacmanPackage import graphicsDisplay import",
"# Sleep for 0.1 sec def step(self, a): \"\"\" Applies",
"eaten stuff for graphics (original code assumes # graphics are",
"2]) statespace_limits... |
[
"def get_working_directory(template): \"\"\"Return the collection which is the main working",
"is the main working directory. template: Template which will be",
"\"\"\"Global CMS settings.\"\"\" default_year = zope.schema.Int( title=_(\"Default year\"), min=1900, max=2100)",
"default_volume = zope.schema.Int(... |
[
"N, M = map(int, input().split()) for i in range(1, M",
"j = (i - 2) // 2 print(M + 2",
"range(1, M + 1): if i % 2 == 1:",
"= (i - 1) // 2 print(1 + j, M",
"j) else: j = (i - 2) // 2 print(M",
"print(1 + j, M + 1 - j) else: j",
"in range(1, M + 1): if i % 2 ==",
"% 2 == 1: j = (i - 1) //",
"1): if i... |
[
"API SDK for Python\", long_description=long_description, license='Apache License 2.0', packages=[ \"facebookbot\",",
"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law",
"distributed on an \"AS IS\" BASIS, WITHOUT # WARRANTIES OR",
"fd: m = reg.match(line) if m: __version__... |
[
"2.0 (the \"License\"); # you may not use this file",
"a decoder. Mask values selected in `[0, 1]`: - 1",
"its model (such as downloading or saving, resizing the input",
"else: raise ValueError(\"You have to specify either input_ids or inputs_embeds\")",
"weights after the attention softmax, used to compute... |
[
"from eth2.beacon.validation import ( validate_slot, ) if TYPE_CHECKING: from eth2.beacon.state_machines.base",
"self.get_chaindb_class()(base_db) # # Helpers # @classmethod def get_chaindb_class(cls) -> Type['BaseBeaconChainDB']:",
") state, imported_block = self.get_state_machine(base_block_for_import).import... |
[
"send command to the device device_access.send(\"ter len 0\\nshow run \\n\")",
"FOR SINGLE COMMAND, FOR MULTIPLE COMMANDS CODE BELOW # send",
"client.invoke_shell() for line in f2: device_access.send(line) time.sleep(1) output = device_access.recv(55000).decode('ascii')",
"= input('Provide IP address to conne... |
[
"10 # k = n % 10 # if n",
"返回出去的列表 for i in l1: re_l1.append(i) def jisuan(str_num): he1 =",
"# 返回出去的列表 for i in l1: re_l1.append(i) def jisuan(str_num): he1",
"** 3 + k ** 3: # print(n) # 第一道题(16)",
"# l1 = s1.split(' ') # l2 = [] #",
"re_l1.append(i) def jisuan(str_num): he1 = 0 global out_l1 for i",
... |
[
"need to run early, so they get a high priority",
"long lists, but adds a little complexity and doesn’t really",
"default arguments for the alias Dagoba.addPipetype(newname, function() {}) # because",
"Dagoba.addTransformer(function(program) { return program.map(function(step) { if(step[0] != newname) return ... |
[
"110 POLLING = 120 CALLBACK = 130 SUCCESS = 200",
"300 # 任务重试 FAILURE = 400 # 任务执行失败 REVOKED =",
"# 任务重试 FAILURE = 400 # 任务执行失败 REVOKED = 500",
"2020-12-2 @desc: ... \"\"\" class JobStatus(object): PENDING = 0 #",
"\"\"\" class JobStatus(object): PENDING = 0 # 任务等待执行 STARTED =",
"-*- \"\"\" @auth: cml @da... |
[
"carnê. \"\"\" def __init__(self, file_descr, landscape=False): # Tamanhos em px",
"para modelo de página inteira :param boletoDados: Objeto com os",
"= 27 self.fontSizeValue = 12 self.title = 'Boleto bancário' self.fileDescr",
":type boletoDados2: :class:`pyboleto.data.BoletoData` \"\"\" raise NotImplemented... |
[
"= 0 i = 0 while i < 5: summary",
"0 while i < 5: summary = summary + i",
"5: summary = summary + i print(summary) i = i",
"= summary + i print(summary) i = i + 1",
"= 0 while i < 5: summary = summary +",
"i = 0 while i < 5: summary = summary",
"0 i = 0 while i < 5: summary =",
"while i < 5: summary =... |
[
"imtreat img = imtreat.imageManagerClass.openImageFunction(\"../images/soleil.png\", 0) img = imtreat.definedModesClass.detailEnhanceFunction(img) imtreat.imageManagerClass.saveImageFunction(\"/Téléchargements/\", \"image_1\",",
"img = imtreat.imageManagerClass.openImageFunction(\"../images/soleil.png\", 0) img =... |
[
"RAM implies 512MB of RAM allocated at startup. Possible values:",
"service or its path is in the PATH environment variable",
"path to an ``mkisofs.exe`` installation. \"\"\"), cfg.StrOpt('vswitch_name', help=\"\"\" External virtual",
"a VHD, otherwise the config drive will remain an ISO.",
"provided, the f... |
[
"input(\"Chemin d'écriture ? (words.txt) \") if path == \"\": path",
"x: len(x) > 4, words_list.split('\\n')) path = input(\"Chemin d'écriture ?",
"4, words_list.split('\\n')) path = input(\"Chemin d'écriture ? (words.txt) \") if",
"= input(\"Chemin d'écriture ? (words.txt) \") if path == \"\":",
"len(x) > ... |
[
"gallery_path, 's3://testbucket/path/', '--exclude', '.DS_Store']) # Test upload to bucket without",
"prefix uploader.upload_gallery('testbucket/path/', gallery_path) subprocess_run.assert_called_with( ['aws', 's3', 'sync', gallery_path, 's3://testbucket/path/', '--exclude',",
"# Test upload to bucket without t... |
[
"self.label_add_subject.setText(_translate(\"Dialog_add_subject\", \"ADD SUBJECT\", None)) self.label_year.setText(_translate(\"Dialog_add_subject\", \"YEAR\", None)) self.label_semester.setText(_translate(\"Dialog_add_subject\", \"SEMESTER\", None))",
"file will be lost! from PyQt4 import QtCore, QtGui try:",
... |
[
"test_pre_syncdb_args(self): r = PreSyncdbReceiver() signals.pre_syncdb.connect(r, sender=models) management.call_command('syncdb', database=SYNCDB_DATABASE, verbosity=SYNCDB_VERBOSITY, interactive=SYNCDB_INTERACTIVE,",
"OneTimeReceiver(object): \"\"\" Special receiver for handle the fact that test",
"= 'defaul... |
[
"\"127.0.0.1\" root_node = self.resolve_root_node_address(root_node) os.environ[\"MASTER_ADDR\"] = root_node log.debug(f\"MASTER_ADDR: {os.environ['MASTER_ADDR']}\") return",
"last 4 numbers in the job id as the id",
"if default_port: # use the last 4 numbers in the",
"os.environ.get(\"SLURM_JOB_ID\") if defa... |
[
"python import time import os import math from trackball import",
"xautomation?\") while True: up, down, left, right, switch, state =",
"math.copysign(y**2, y) cmd = 'xte \"mousermove {} {}\"'.format(int(x), int(y)) os.system(cmd)",
"when the switch is pressed. Press Ctrl+C to exit! \"\"\")",
"= 'xte \"mous... |
[
"spec. Return: list[str]: List of key(str) for the network outputs.",
"tfp from garage.experiment import deterministic from garage.tf.models import GaussianMLPModel class",
"function for the weight of output dense layer(s) in the",
"trainable=False) y_std_var = tf.compat.v1.get_variable( name='y_std_var', sha... |
[
"= datasets.ImageFolder(valdir, transform_test) num_classes=1000 testloader = torch.utils.data.DataLoader(testset, batch_size=1000, shuffle=False, pin_memory=True,",
"True, True) pred = pred.t() correct = pred.eq(target.view(1, -1).expand_as(pred)) res",
"test_loss = 0 correct_1 = 0 correct_5 = 0 total",
"len... |
[
"= { 'adadelta': optim.Adadelta, 'adagrad': optim.Adagrad, 'adam': optim.Adam, 'adamax': optim.Adamax,",
"as optim from .search import SamplingSearch, GreedySearch, BeamSearch SEARCH_FACTORY =",
"SamplingSearch, 'greedy': GreedySearch, 'beam': BeamSearch, } OPTIMIZER_FACTORY = { 'adadelta':",
"} OPTIMIZER_FAC... |
[
"= lv._inference_posteriors( [np.random.randn(num_data, 3), np.random.randn(num_data, 2)] ) q_mu = posteriors.parameters[\"loc\"]",
"2.0 (the \"License\"); # you may not use this file",
"expected_loss = [tf.reduce_mean(posteriors.kl_divergence(prior))] np.testing.assert_equal(lv.losses, expected_loss) # also ch... |
[
"PUT /trust/{relationship}}/{actorid} with a json body to change details on",
"to create trust relationship') return self.response.headers.add_header( \"Location\", str(Config.root + myself.id",
"myself.deleteReciprocalTrust(peerid=peerid, deletePeer=True) if not deleted: self.response.set_status(502, 'Not able... |
[
"strategy for 3D lines that go past the camera. Formerly",
"prediction data in python. - Skyborg \"\"\", '1.1.3': \"\"\" -",
"Skyborg - Java bots will now shut down when the",
"to another team in the GUI no longer breaks the",
"in python. - Skyborg - Java bots will now shut",
"the position, velocity, etc ... |
[
"for FullyConnectedHead Args: unique_id: A unique identifier for the head.",
"size for the fully connected layer. \"\"\" super().__init__(unique_id, num_classes) assert",
"typing import Any, Dict import torch.nn as nn from classy_vision.generic.util",
"be attached to a model, and unique_id is used to",
"ide... |
[
"entry in warning_stations: print(entry[0].name,entry[1]) if __name__ == \"__main__\": print(\"*** Task",
"import stations_highest_rel_level def run(): stations = build_station_list() warning_stations = stations_highest_rel_level(stations,10)",
"if __name__ == \"__main__\": print(\"*** Task 2C: CUED Part IA",
... |
[
"`__copy_create__()` method. All variables, that could not be set via",
"objects, that should be copyable. The public method `copy()` first",
"constructor takes parameters. Returns ------- copy A freshly instantiated copy",
"set via the constructor, are then copied via `__copy_fill__()`, starting",
"All var... |
[
"import HomeAssistant from wyzeapy.base_client import Device, AccessTokenError from wyzeapy.client import",
"= latest_event.event_ts else: self._on = False self._last_event = latest_event.event_ts else:",
"-> List[Device]: try: return client.get_cameras() except AccessTokenError as e: _LOGGER.warning(e)",
"la... |
[
"BRDF 16-day Level 3 products, MCD43C1 (0.05 degree horz res),",
"horz res), \"\"\" def __init__ (self,Path,lon,lat,Verb=1): \"\"\" Reads files for",
"'Snow_BRDF_Albedo', 'BRDF_Albedo_Ancillary', ) ) ALIAS = dict ( BRDF_Albedo_Parameter1_Band1 =",
"( LAND = ('BRDF_Albedo_Parameter1_Band1','BRDF_Albedo_Paramet... |
[
"x = Input(shape=(3, 2)) layer = wrappers.TimeDistributed(layers.BatchNormalization()) _ = layer(x)",
"mask_outputs = [model.layers[0].compute_mask(model.input)] mask_outputs += [model.layers[1].compute_mask(model.layers[1].input, mask_outputs[-1])] func = K.function([model.input],",
"need learning_phase to be ... |
[
"from tornado.platform import interface class Waker(interface.Waker): \"\"\"Create an OS independent",
"socket.error as detail: if (not hasattr(errno, 'WSAEADDRINUSE') or detail[0] !=",
"# assigned (host, port) pair try: self.writer.connect(connect_address) break # success",
"first try). See the long thread a... |
[
"pathymetric data. The file current named mapserv.png was obtained using",
"\"--num-leds\", dest=\"num_leds\", help=\"Number of LEDs in strip (ex: 60)\", default=config[\"num_leds\"])",
"if args: print(\"Unknown parameters: \" + args) # grab the",
"strip (ex: 70,-110)\", default=config[\"location\"]) parser.a... |
[
"in data[key].items(): if multi_value: multi_selects.append(multi_key) output[key] = ', '.join(multi_selects) else:",
"for key in data: # flatten list values if isinstance(data[key],",
"numbers and building application number elif phone_appnum_key is not None:",
"output) else: multi_selects = [] for multi_key... |
[
"yield address_info # The code after the yield will run",
"= trainer.fit() # If loading from a state dict, a",
"def test_torch_linear(ray_start_4_cpus, num_workers): def train_func(config): result = linear_train_func(config) assert len(result)",
"= ray.data.range(3) predictions = predict_dataset.map_batches( ... |
[
"LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A",
"**kwargs): # type: (*Any, **Any) -> Union[str, None] \"\"\"Executes the",
"Specifies the rate at which IxNetwork sends learn frames to",
"item in kwargs.items(): payload[item[0]] = item[1] return self._execute('applyITWizardConfiguration', payl... |
[
"rest_framework import serializers from core import models class AssetSerializer(serializers.ModelSerializer): class",
"import models class AssetSerializer(serializers.ModelSerializer): class Meta: model = models.Asset fields",
"import serializers from core import models class AssetSerializer(serializers.ModelS... |
[
"\"\"\" c(2). p(1). a(2). d(2,2,1). okay(X):- c(X), #count{V:a(V),d(V,X,1)} = 1.",
"= 1. ouch(X):- p(X), #count{V:a(V),d(V,X,1)} = 1. \"\"\" output =",
"\"\"\" output = \"\"\" {a(2), c(2), d(2,2,1), okay(2), p(1)} \"\"\"",
"ouch(X):- p(X), #count{V:a(V),d(V,X,1)} = 1. \"\"\" output = \"\"\" {a(2),",
"p(X), ... |
[
"str(salt) + \"&sign=\" + sign ) async with ClientSession() as",
"langdetect import detect, detect_langs from aiohttp import ClientSession from nonebot",
"def _(session: CommandSession): arg = session.current_arg_text.strip() if session.is_first_run: parser =",
"= \"en\" else: session.state[\"to\"] = \"zh\" e... |
[
"function.\" lib.set_add_rowmode(self.lp, 0) const.fill_buffers(self.colbuff, self.rowbuff) ret = lib.set_obj_fnex(self.lp, len(const.vars), cast(self.rowbuff,",
"constraint into the model.\" assert const.optype is not None, \"You",
"vtype): lib.set_binary(self.lp.lp, self.index, (vtype == \"int\")) def __rmul_... |
[
"id=lb.id, provisioning_status=constants.ERROR) self.assertEqual(2, repo.ListenerRepository.update.call_count) repo.ListenerRepository.update.has_calls( [mock.call('TEST', listeners[0].id, provisioning_status=constants.ERROR), mock.call('TEST', listeners[1].id,",
"id=L7RULE_ID) # Test the revert mock_l7rule_repo_... |
[
"'3', 'url': 'recruitment'}, #{'id': '4', 'url': 'software'}, #{'id': '5', 'url':",
"error connection at url : \" + str(e)) finally: print('done')",
"+ \"/\" + city html_search = requests.get(url_search) soup_search = BeautifulSoup(html_search.content,",
"+ str(number_of_pages)) elif int(str(number_of_pages_w... |
[
"dagster.core.errors import DagsterInstanceMigrationRequired from dagster.core.instance import DagsterInstance, InstanceRef from dagster.utils.test",
"runs: instance.all_logs(run.run_id) def test_0_6_6_sqlite_exc(): test_dir = file_relative_path(__file__, 'snapshot_0_6_6/sqlite') with restore_directory(test_dir):... |
[
"= df.groupby(['CATEGORY']).size().to_frame('Crimes') labels = ['Trespassing', 'Vehicle theft', 'General Theft', 'Damage",
"/ len(df) grouped = grouped.drop(columns='Size') grouped.index = grouped.index.astype(int) p =",
"By Year') p.get_legend().remove() plt.savefig('../charts/year.png') def group_by_territory... |
[
"2]), 5) self.assertEqual(monroescore_flowbased(profile, [2, 1, 5]), 4) self.assertEqual(monroescore_matching(profile, [2, 1,",
"3, 4, 5]], \"av\": [[0, 1, 4, 5], [0, 2,",
"2, 4, 5]], \"cc-noilp\": [[0, 1, 2, 3], [0, 1,",
"1, 2], [0, 1, 3], [0, 2, 3]]) # this",
"msg=rule + \" failed with resolute=True\") de... |
[
"# Solve index reading problem, pandas add 2 index to",
"'139807', '139808', '139809', '139810', '139811', '139812' ] # The list",
"me_df.reset_index(drop=True, inplace=True) # Read rahavard 365 data for calculating returns",
"month ME into two groups conditions = [ ( portfo_const_df['market_cap']",
"] port... |
[
"calcurated_checksum = hashlib.sha256(f.read()).hexdigest() if checksum not in calcurated_checksum: print('ERROR: checksum",
"print('ERROR: checksum is different. download is failed') return False with",
"license_key, 'suffix': suffix} data = urllib.parse.urlencode(values) try: urllib.request.urlretrieve( url +... |
[
"Y[j] = yRef[j] MInv = MM.invertMatrix(M) for i in range(size):",
"2.0 (the \"License\"); # you may not use this file",
"'baseline' logging_name = 'isce.mroipac.baseline' parameter_list = (BASELINE_LOCATION,) # Calculate the",
"not (len(xRef) == len(yRef)): print(\"Error. Expecting input vectors of same",
"... |
[
"import Card class Deck: \"\"\" Class representing a deck. The",
"rank in Card.STR_RANKS: for suit, val in Card.CHAR_SUIT_TO_INT_SUIT.items(): Deck._FULL_DECK.append(Card.new(rank +",
"this object and shuffles it. \"\"\" _FULL_DECK = [] def",
"i in range(n): cards.append(self.draw()) return cards def __str__(... |
[
"LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A",
"just remove this token. self._delete_token(self.last_returned_uuid) return None refresh_result = self._refresh_token(self.last_returned_uuid)",
"= urlencode(rquery) authz_url = '%s?%s' % (self._idp_url('Authorization'), query) print('Please visit... |
[
"False), **attrib) def _encode_param_common(prm, title_required=True): \"\"\" Encode common sub-elements of",
"notice shall be included in all # copies of this",
"dtype.encode(range_.minval))) if range_.maxval is not None: elms.append(OWS(\"MaximumValue\", dtype.encode(range_.maxval))) if range_.spacing",
"LI... |
[
"' bucket. ERROR\\n%s' %e) raise return archive_object def build(vp_save={}): '''",
"raise ValueError() archive_file = __archive_key(save_data) + '/' + vp_save_pk +",
"to ' + bucket + ' bucket. ERROR\\n%s' %e) raise",
"for the archive. This value is required. :param str vp_save_pk:",
"return vp_save def arc... |
[
"=========== This example presents the basic usage of brokenaxes \"\"\"",
"Basic usage =========== This example presents the basic usage of",
"brokenaxes import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2))",
"import brokenaxes import numpy as np fig = plt.figure(figsize=(5,2)) bax",
"import... |
[
"all.add(stmt) elif prefix == \"org\": stmt = (subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Organization\"))",
"> 20: continue # ln = obj[\"uri\"].split(\":\")[1] ''' wiki_path =",
"(subject, RDF.type, URIRef(\"https://jpsearch.go.jp/term/type/Time\")) all.add(stmt) elif prefix == \"place\": stm... |
[
"# The first two board answers the ping board_answers =",
"in range(1, 3)] + [None] read_can_datagram.return_value = iter(board_answers) write_command_retry.return_value =",
"@patch('utils.write_command_retry') @patch('utils.write_command') @patch('utils.read_can_datagrams') @patch('builtins.print') def test_ne... |
[
"msg = await diary_embed(username) except LetterboxdError as err: msg =",
"err await send_msg(ctx, msg) async def check_if_two_args(ctx): msg = ctx.message.content.split()",
"except LetterboxdError as err: msg = err await send_msg(ctx, msg)",
"await ctx.send('Sorry, the command crashed. :/') logging.error(ctx... |
[
"= [] for (k, s) in store.list_workflow(): if s ==",
"-> ray.ObjectRef: \"\"\"Resume a workflow asynchronously. See \"api.resume()\" for details.",
"\"\"\" store = get_global_storage() assert ray.is_initialized() if workflow_id is None:",
"= workflow_storage.get_workflow_storage(workflow_id) meta = store.load... |
[
"from .compose import Compose # noqa from .signature import BinarySignature,",
"from .signature import BinarySignature, Signature, MemorySignature # noqa from .username",
"import Compose # noqa from .signature import BinarySignature, Signature, MemorySignature",
"Compose # noqa from .signature import BinarySi... |
[
"x,y,v_x,v_y = u r=np.hypot(x,y) #r= 1.521e+06 #M,G=1.989e+30,6.7e-11 M,G=20,110 f=G*M/r**3 return",
"u+(k1+2*k2+2*k3+k4)/6 def RK4_int(f,y0,tspan): y=np.zeros([len(tspan),len(y0)]) y[0,:] =y0 for k in range",
"0.0, 10, 10]) sol_rk4=RK4_int(orbit,y0,t) x,y,v_x,v_y = sol_rk4.T plt.grid() plt.plot(x,y) plt.show()... |
[
"in apps.get_app_configs(): factory_app_generator = FactoryAppGenerator(app) created_files += factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created",
"+= factory_app_generator.create_files() self.stdout.write(self.style.SUCCESS('Successfully created factories:')) for crea... |
[
"if args.skip: return {'chunks': [{'__mem_gb': h5_constants.MIN_MEM_GB}]} chunks = [] #",
"chunk_outs] analysis_io.combine_h5_files(chunk_h5s, outs.diffexp_h5, [analysis_constants.ANALYSIS_H5_DIFFERENTIAL_EXPRESSION_GROUP, analysis_constants.ANALYSIS_H5_KMEANS_DIFFERENTIAL_EXPRESSION_GROUP]) for csv_dir in chunk_... |
[
"permutations as sets. This is used for testing purposes. Since",
"import get_symmetric_group_sgs >>> from sympy.combinatorics import Permutation, PermutationGroup >>> g",
"size - 2)) S = PermutationGroup(sgens) D = PermutationGroup([Permutation(x) for",
"= v[i] v1.append((base_i, gens_i, [[]]*n_i, sym_i)) si... |
[
"localhost = \"http://localhost/\" # your local host database = \"mysql://root@localhost/vaticChecker\"",
"videos to be considered recaptcha_secret = \"\" # recaptcha secret",
"recaptcha secret for verification duplicate_annotations = False # Should the",
"to be considered recaptcha_secret = \"\" # recaptcha ... |
[
"value def now(): \"\"\" Returns an aware or naive datetime.datetime,",
"by settings.TIME_ZONE. \"\"\" if hasattr(_active, \"value\"): del _active.value class override(object):",
"by the current time zone, unless another time zone is",
"= timezone elif isinstance(timezone, basestring) and pytz is not None:",
... |
[
"resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Process' '/ows:Identifier') assert sorted(names.split()) == [ 'download', 'esgsearch',",
"resp = client.get(service='wps', request='getcapabilities', version='1.0.0') names = resp.xpath_text('/wps:Capabilities' '/wps:ProcessOfferings' '/wps:Proces... |
[
":: Python :: 3.7\", \"Programming Language :: Python :: Implementation",
"author_email=\"<EMAIL>\", url=\"https://github.com/alexdlaird/pyngrok\", download_url=\"https://github.com/alexdlaird/pyngrok/archive/{}.tar.gz\".format(__version__), keywords=[\"ngrok\", \"tunnel\", \"tunneling\", \"webhook\", \"localhost... |
[
"arguments=[\"train.py\"], ).apply(gcp.use_gcp_secret() )#.set_gpu_limit(1) def serve_op(): return dsl.ContainerOp( name='serve', image=\"{}:{}\".format(KUBECTL_IMAGE, KUBECTL_IMAGE_VERSION),",
"\"kubeflow\", \"--command\", \"apply -f /src/k8s/serve.yaml\", ] ).apply(gcp.use_gcp_secret()) def resultsgen_op(): ret... |
[
"publish_event, publisher, TICK_2_MINUTES, network, secs, mins) if mins % 5",
"secs, mins) if mins % 60 == 0: utils.do_stuff_with_exponential_backoff(rabbitmq_exceptions, publish_event,",
"import utils from infrabbitmq import factory as infrabbitmq_factory from infrabbitmq.rabbitmq",
"def main(network): publi... |
[
"a pretrained model), or - the model was saved using",
"let the specific kwargs override the common ones in case",
"be instantiated as a transformer architecture with one of the",
"2.0 (the \"License\"); # you may not use this file",
"been done) - If a configuration is not provided, ``kwargs``",
"containi... |
[
"python_callable=mean_homem, dag=dag ) def mean_mulher(): df = pd.read_csv('/usr/local/airflow/data/train.csv') med =",
"} # Dag definition dag = DAG( 'treino-03', description=\"Extrai dados",
"med = df.loc[df.Sex == 'male'].Age.mean() print(f'Media de idade dos homens",
"de idade dos homens no Titanic: {med}... |
[
"variable.\\n\" \"In that case it will list only the system",
"Dictionary of types from Tcl command, needs to be ordered",
"collections.OrderedDict([ ('selection', str), ]) # Dictionary of types from Tcl",
"from Tcl command, needs to be ordered , this is",
"unnamed_args: :return: \"\"\" if 'selection' in ar... |