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# Print all numpy array, without truncation
import sys
import numpy
numpy.set_printoptions(threshold=sys.maxsize)

# Print all pandas dataframe, without truncation
with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also
    print(df)

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def filtro(self, df, uid):
	"""Filter forecasted values
	Check acceptable values, replacing when it isn't
	"""
	import statistics
	if uid == 215:
		lower_limit = 10
		upper_limit = 3000
	elif uid == 216:
		lower_limit = 10

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y_true['ds'] = pd.to_datetime(y_true['ds'])
print(y_true.dtypes)

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ls *VS00* *VSS.* | zip -@ saida/arquivo.zip

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envio_email(){
	# Escrever corpo do e-mail
	echo "Seguem anexos" >> $arq_email
	printf "\n" >> $arq_email
	# Arquivo de texto no corpo de e-mail
	cat $arq_descr >> $arq_email
	
	# Criar lista de e-mails a partir de arquivo
	readarray -t lista_emails < <(cat $DIR/helpers/destinatarios_teste.txt | grep $grupo | awk -F',' '{print $1}')
	

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diretorio = '/home/user/model'
uid = 1
filename = sprintf('%s/saida/saida_%s/prevaz_%s.csv', diretorio, 'semanal', uid)
values = tryCatch(read.csv(filename,as.is = TRUE),
	 error = function(e) NA, warning = function(w) print('Without semanal file'))

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openssl rand -base64 8

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import random
random.seed(42) 
df['column_name'] = df['column_name'].apply(lambda v: random.random() * 100)

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def print_all_df(self, df):
    with pd.option_context('display.max_rows', None, 'display.max_columns', None):
        print(df)

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from subprocess import check_output
# List files using pattern and get most recent
bashCommand = ("ls -1t %s/saida/arquivos_clientes/cn*.txt | head -1" %path)
# Define file name as last string, striping by '/'
filename = str(check_output(bashCommand, shell=True).strip(), 'utf-8')
remoteFileName = filename.split('/')[-1]