Use the Python client elasticsearch.
from elasticsearch import Elasticsearch
es_client = Elasticsearch() # local
| # Copyright (C) 2016 Martina Pugliese | |
| from boto3 import resource | |
| from boto3.dynamodb.conditions import Key | |
| # The boto3 dynamoDB resource | |
| dynamodb_resource = resource('dynamodb') | |
| def get_table_metadata(table_name): |
| # Copyright (C) 2016 Martina Pugliese | |
| # Imports | |
| from datetime import datetime | |
| # #################### ANSI Escape codes for terminal ######################### | |
| codes_dict = { |
| # Copyright (C) 2016 Martina Pugliese | |
| def plot_freqdist_freq(fd, | |
| max_num=None, | |
| cumulative=False, | |
| title='Frequency plot', | |
| linewidth=2): | |
| """ | |
| As of NLTK version 3.2.1, FreqDist.plot() plots the counts and has no kwarg for normalising to frequency. Work this around here. |
| # Copyright (C) 2016 Martina Pugliese | |
| def run_methods(): | |
| print '\n' | |
| print '* Count occurrences of substring in string' | |
| print 'Martina'.count('art') | |
| print 'Martina'.count('a') |
for key in d.keys() and for key in dvm_stat is the command, this makes output user friendly, thanks to this.
vm_stat | perl -ne '/page size of (\d+)/ and $size=$1; /Pages\s+([^:]+)[^\d]+(\d+)/ and printf("%-16s % 16.2f Mi\n", "$1:", $2 * $size / 1048576);'