Brandon Rose brandomr

## data_profiling.py
import io
import pandas
import requests
import json

##########################
# generate dataset metadata
# I assume this will come from the HMI during user upload
##########################
dataset = {

## es-mapping-update.py
from elasticsearch import Elasticsearch
import json

es = Elasticsearch('http://localhost:9200')

q = {
    "query": {
        "match_all": {}
    }
}

## test.csv

          
            date
            EthiopiaArrivals
            Itoobiya
            qaxooti
            UN
            abaar
            shaqada
            Oromiya
            gargaar
            skype

            
              2017-02-28
              9834
              5.5
              4.0
              17.75
              0.0
              4.25
              2.25
              0.0
              19.25

            
              2017-03-31
              20515
              8.5
              3.0
              27.0
              2.5
              5.0
              0.0
              0.0
              21.0

            
              2017-04-30
              10797
              8.0
              0.0
              20.0
              0.8
              5.6
              0.0
              3.2
              13.2

            
              2017-05-31
              4876
              6.5
              1.25
              16.75
              2.5
              3.5
              2.5
              0.0
              14.0

            
              2017-06-30
              6184
              3.5
              1.25
              17.0
              0.0
              2.5
              0.0
              2.5
              14.75

            
              2017-07-31
              3311
              3.4
              0.0
              22.8
              0.0
              1.4
              3.0
              0.0
              18.6

            
              2017-08-31
              9288
              7.5
              0.0
              21.25
              0.0
              3.25
              2.25
              2.25
              21.0

            
              2017-09-30
              27144
              12.75
              1.5
              33.25
              0.0
              2.25
              13.0
              3.25
              25.25

            
              2017-10-31
              3229
              12.2
              0.0
              25.2
              0.0
              6.0
              2.4
              0.0
              15.2

## world-modeler-search.yaml
openapi: 3.0.0
info:
  title: "World Modelers Search API"
  description: "This API specification is for the World Modelers search."
  version: "1.0.0"

paths:
  /search:
    post:
      tags:

## gemini.py
class gemini(object):
    """
    An object for interacting with the Gemini API. Full Gemini API documentation is
    available at https://docs.gemini.com
    """

    def __init__(self, gemini_api_key, gemini_api_secret, base_url):
        """
        Initializes gemini object.


## austin_dallas.py
from datetime import datetime
import requests
import json

def find_traffic_time(dt):
    epoch = datetime(1970,1,1)
    delta_time = (dt - epoch).total_seconds()
    epoch_t = str(delta_time).split('.')[0]

    # build query

## merkle_tree.py
from hashlib import sha256 as sha

def chunks(l, n):
    """Yield successive n-sized chunks from l."""
    for i in range(0, len(l), n):
        yield l[i:i + n]

def m_tree(transactions):
	"""Takes an array of transactions and computes a Merkle root"""
    sub_t = []

## email_2_name.py
from fuzzywuzzy import process

names = ['Megan Sherman','Jin Zhang','Amr Ahmed','Jeffrey De Fauw','Linus Upson','Jonathan Binghman']
emails = ['jon.bingham@gmail.com','megansherman@google.com','jbingham@google.com','jinzhang@google.com','linus@google.com']

names_cleaned = [i.lower() for i in names]
emails_cleaned = [i.split('@')[0] for i in emails]

for email in emails_cleaned:
    print '######'

## treat_number.py
def treat_number(i):
    i = str(i)
    i = i.replace('+','')
    i = i.replace('-','')
        #i = int(i)
    if i[0] == '1' and len(i) == 11:
        i = i[1:11]
    return i
	import io
	import pandas
	import requests
	import json

	##########################
	# generate dataset metadata
	# I assume this will come from the HMI during user upload
	##########################
	dataset = {
	from elasticsearch import Elasticsearch
	import json

	es = Elasticsearch('http://localhost:9200')

	q = {
	"query": {
	"match_all": {}
	}
	}
date	EthiopiaArrivals	Itoobiya	qaxooti	UN	abaar	shaqada	Oromiya	gargaar	skype
2017-02-28	9834	5.5	4.0	17.75	0.0	4.25	2.25	0.0	19.25
2017-03-31	20515	8.5	3.0	27.0	2.5	5.0	0.0	0.0	21.0
2017-04-30	10797	8.0	0.0	20.0	0.8	5.6	0.0	3.2	13.2
2017-05-31	4876	6.5	1.25	16.75	2.5	3.5	2.5	0.0	14.0
2017-06-30	6184	3.5	1.25	17.0	0.0	2.5	0.0	2.5	14.75
2017-07-31	3311	3.4	0.0	22.8	0.0	1.4	3.0	0.0	18.6
2017-08-31	9288	7.5	0.0	21.25	0.0	3.25	2.25	2.25	21.0
2017-09-30	27144	12.75	1.5	33.25	0.0	2.25	13.0	3.25	25.25
2017-10-31	3229	12.2	0.0	25.2	0.0	6.0	2.4	0.0	15.2
	openapi: 3.0.0
	info:
	title: "World Modelers Search API"
	description: "This API specification is for the World Modelers search."
	version: "1.0.0"

	paths:
	/search:
	post:
	tags:
	class gemini(object):
	"""
	An object for interacting with the Gemini API. Full Gemini API documentation is
	available at https://docs.gemini.com
	"""

	def __init__(self, gemini_api_key, gemini_api_secret, base_url):
	"""
	Initializes gemini object.
	from datetime import datetime
	import requests
	import json

	def find_traffic_time(dt):
	epoch = datetime(1970,1,1)
	delta_time = (dt - epoch).total_seconds()
	epoch_t = str(delta_time).split('.')[0]

	# build query
	from hashlib import sha256 as sha

	def chunks(l, n):
	"""Yield successive n-sized chunks from l."""
	for i in range(0, len(l), n):
	yield l[i:i + n]

	def m_tree(transactions):
	"""Takes an array of transactions and computes a Merkle root"""
	sub_t = []
	from fuzzywuzzy import process

	names = ['Megan Sherman','Jin Zhang','Amr Ahmed','Jeffrey De Fauw','Linus Upson','Jonathan Binghman']
	emails = ['jon.bingham@gmail.com','megansherman@google.com','jbingham@google.com','jinzhang@google.com','linus@google.com']

	names_cleaned = [i.lower() for i in names]
	emails_cleaned = [i.split('@')[0] for i in emails]

	for email in emails_cleaned:
	print '######'
	def treat_number(i):
	i = str(i)
	i = i.replace('+','')
	i = i.replace('-','')
	#i = int(i)
	if i[0] == '1' and len(i) == 11:
	i = i[1:11]
	return i