def establishConnectionWithReuters(app_id):
"""
Establish the connection wth EIKON Reuters
"""
ek.set_app_id(app_id)
return ek
def wrapper_func(*args, **kwargs):
log = logging.getLogger(__name__)
# Check if Eikon is running (if not start it)
ps = os.popen('tasklist').read()
if 'EikonBox' not in ps:
log.info('Start Eikon and wait 60 seconds for initialization')
sub.Popen(
r'C:\Program Files (x86)\Thomson Reuters\Eikon\Eikon.exe')
time.sleep(120)
# API Key for Eikon
ek.set_app_id('a3613aeaa2a14b6ea8aaff7950114a2d19bdc03a')
# Execute Function
ret_val = func(*args, **kwargs)
return ret_val
def index(request):
app_id = str('CE9D75E3B5ECDE27DC3BDA')
eikon.set_app_id(app_id)
# import pdb; pdb.set_trace()
codes = [
str(c)
for c in str(urllib.unquote(request.GET.get("codes"))).split(',')
]
start_date = str(request.GET.get("start_date"))
end_date = str(request.GET.get("end_date"))
interval = str(request.GET.get("interval"))
prices = eikon.get_timeseries(codes,
fields=[str('Close')],
start_date=start_date,
end_date=end_date,
interval=interval)
price_list = {p: prices[p].values.tolist() for p in prices}
dates = [str(row[0]) for row in [t for t in prices.to_records()]]
price_list['dates'] = dates
return JsonResponse(price_list)
def wrapper_func(*args, **kwargs):
log = logging.getLogger(__name__)
p = None
# Check if Proxy is running (if not start it)
ps = os.popen('tasklist').read()
if 'EikonAPIProxy' not in ps:
log.info(
'Start Eikon Proxy and wait 60 seconds for initialization')
p = sub.Popen(
r'C:\Users\Laurent\AppData\Local\Eikon API Proxy\EikonAPIProxy.exe'
)
time.sleep(60)
# API Key for Eikon
ek.set_app_id('a3613aeaa2a14b6ea8aaff7950114a2d19bdc03a')
# Execute Function
ret_val = func(*args, **kwargs)
# Terminate process
if p is not None:
p.terminate()
return ret_val
import sys
import eikon as ek
ek.set_app_id("your_eikon_id")
ric = input("Enter RIC (e.g. IBM, TD.TO): ")
def drawRange(num):
tNum = (5 - num) * 6.25
print("\t\t ", end="")
for i in range(int(tNum) - 1):
print(" ", end="")
print(u"▼", end="")
print("")
print("\t\t ", end="")
print(u"┌────┬────┬────┬────┬────┐")
print("\t\tSell ", end="")
print(u"│ │░░░░│▒▒▒▒│▓▓▓▓│████│", end="")
print(" Buy")
print("\t\t ", end="")
print(u"└────┴────┴────┴────┴────┘")
try:
# check if it is a valid equity stock
print("Getting primary RIC")
# get the primary RIC associated with this equity stock
pRICDF, err = ek.get_data(ric, "TR.PrimaryQuote")
pRIC = pRICDF.loc[0]["Primary Quote RIC"]
import xlwings as xw
import os
import numpy as np
import pandas as pd
import time
import pandas as pd
import eikon as ek
ek.set_app_id('604ea22425e048d39af0ef760ec9c64ebbe1fe68')
from sklearn import preprocessing
import functions
import pickle
import statsmodels.api as sm
import zipfile
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import RobustScaler
from scipy import stats
@xw.func
@xw.ret(expand='table')
def get_traindata(headers,
tickers,
FX,
start_date='2015-01-01',
month_dummies=0):
tickers_train = dict(zip(headers, tickers))
dataset = functions.get_train_data(tickers_train, ek, start_date)
for i in range(len(FX)):
if FX[i] == "USD":
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import eikon as ek
import pandas as pd
import pickle
ek.set_app_id('E9DE83B192F920DC8739C')
df = ek.get_timeseries(["SPXo161828000.U"],
start_date="2018-02-12",
interval='daily')
data = {}
for i in range(1100, 3525, 25):
try:
df = ek.get_timeseries(
["SPXo1618{}0.U".format(i)],
# start_date="2018-02-12",
interval='daily')
except:
continue
data[i] = df
dataset = pd.DataFrame()
for i in range(1100, 3525, 25):
try:
dataset = pd.concat([dataset, data[i]['CLOSE']], axis=1)
import eikon as ek # the Eikon Python wrapper package
import numpy as np # NumPy
import pandas as pd # pandas
import cufflinks as cf # Cufflinks
import configparser as cp
from eikon import Profile as profile
profile.get_scripting_proxy_port = 49152
ek.set_app_id('0a845119ab7548339124ed3f965d50480c0f4205')
#!eikonrest/bin/python
from flask import Flask, request, jsonify
from flask_restful import Resource, Api
# from json import dumps
import eikon as ek
import yaml
app = Flask(__name__)
api = Api(app)
conf = yaml.load(open('config.yml'))
ek.set_app_id(conf['eikon']['apikey'])
class Query(Resource):
def get(self, syms, fs, params=''):
# Check UUID in Bearer of API request. This is a simple wrapper.
token = request.headers.get('Authorization', None)
if token is None:
return None
method, tokenstr = token.split()
if method.lower() == "bearer" and tokenstr == conf['pywrapper']['apikey']:
df = ek.get_data(instruments=str(syms).split(','), fields=str(fs).split(','), parameters=params,
raw_output=True)
return jsonify(df)
else:
return None
class ListHSIOptions(Resource):
def get(self, fs, params=''):
# Check UUID in Bearer of API request. This is a simple wrapper.
import re
import pandas as pd
import datetime
import chinese_tagging_api
import csv
companies = chinese_tagging_api.load_company_names(
'Data/2000_Chinese_Companies.xlsx', 'Chinese Lexicon',
'Data/exclude_alias.txt')
ric_list = ['财经']
for x in companies:
ric_list.append(companies[x]['Name'])
ek.set_app_id('F5FA9CCFBBD5247AE06A30D6')
today = datetime.datetime.now()
from_date = datetime.date.strftime(today - datetime.timedelta(days=1),
'%Y-%m-%dT%H:%M:%S')
today = datetime.date.strftime(today, '%Y-%m-%dT%H:%M:%S')
def get_news(ric):
headlines = ek.get_news_headlines(ric + ' IN CHINESE',
date_from=from_date,
date_to=today,
count=100)
return [{
'time': datetime.date.strftime(a, '%Y-%m-%dT%H:%M:%S'),
'source': d,
'headline': b,
def years_ago(end_date, years):
if type(end_date) == str:
end_date = parse(end_date)
if end_date.month == 2 and end_date.day == 29:
end_date = end_date.replace(day=28)
return end_date.replace(year=end_date.year - years).replace(month = end_date.month - 1)
len_hist = 5
end_date = datetime.date.today()
dates = pd.bdate_range(years_ago(end_date,len_hist),end_date)
df_TS = pd.DataFrame(index=dates).sort_index(axis = 0,ascending = False)
cpi = ['AAPL.O']
pwd = os.getcwd()
#ek.set_app_id('8B2D38D084ECE14EBF190BC7')
ek.set_app_id('B2AA4B3A4A8EE1BCEFA9B')
df2,err = ek.get_data(cpi,['TR.PriceClose.date','TR.PriceClose','TR.PriceClose.currency','TR.EV',
'TR.PE','TR.CompanyMarketCap','TR.WACCBeta','TR.WACCCostofEquity',
'TR.TotalReturn1Wk','TR.Volume'],
{'SDate': 0, 'EDate': -len_hist*252, 'FRQ': 'D'})
df1,err = ek.get_data(cpi,['TR.NormalizedEbitda.date','TR.NormalizedEbitda','TR.TotalEquity','TR.TotalCurrentAssets','TR.NetIncome'],{'SDate': 0, 'EDate': -len_hist*4, 'FRQ': 'FY'})
df_bm,err = ek.get_data('.SPLRCTHSP',['TR.PriceClose.date','TR.PriceClose'],{'SDate': 0, 'EDate': -len_hist*252, 'FRQ': 'D'})
df_spx,err = ek.get_data('.SPX',['TR.PriceClose.date','TR.PriceClose'],{'SDate': 0, 'EDate': -len_hist*252, 'FRQ': 'D'})
df2.set_index(['Date'],inplace = True)
#df1.set_index(['Date'],inplace = True)
df_spx.set_index(['Date'],inplace = True)
df_bm.set_index(['Date'],inplace = True)
# Do some data prep on missing values
df = oj.copy()
## NaN indicator column
# for k in df:
# s = 'NaN.' + k
# df[s] = df[k].isnull()
# forward fill NaN's with previous value
df = df.fillna(method='pad')
# fill with zeroes what doesn't have a past value
df = df.fillna(0)
return df
if __name__ == "__main__":
# import sys
# parse_data(list(sys.argv[1]))
from datetime import datetime
import eikon as ek
ek.set_app_id('D79B714919385CD9D749D1')
import pandas as pd
start_date = datetime(2009, 1, 1)
end_date = datetime(2016, 5, 31)
df2 = parse_data(start_date, end_date, ["Cc1", "Sc1", "Wc1"])
from datetime import date, timedelta
import math
from dateutil.relativedelta import relativedelta
import error_log as log
import re
import helper
import os
import time
import failed_log as fl
import mail_helper as mailservice
try:
"""Eikon App ID
"""
ek.set_app_id('93D5C93060C3ECEAD451638')
except ek.EikonError as e:
if (e.code == '401'):
StartEikon()
else:
log.Error(e)
"""
Function to get ticker data for date. Here we get all tickers from Database and
and the data is got for individual tickers from the end for which the last job stopped for the ticker
till todays date
"""
def get_data_for_date(start_date, end_date):
tickers = db.call_procedure("get_ticker_details", "")
import eikon as ek
ek.set_app_id('your app key')
dfFY0, err = ek.get_data("IBM", [
'TR.RevenueActValue(Period=FY0, Scale=6, Curn=USD)',
'TR.EBITDAActValue(Period=FY0, Scale=6, Curn=USD)',
'TR.EPSActValue(Period=FY0, Curn=USD)'
])
dfFY1, err = ek.get_data("IBM", [
'TR.RevenueMeanEstimate(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.RevenueHigh(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.RevenueLow(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.EBITDAMean(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.EBITDAHigh(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.EBITDALow(Period=FY1, Scale=6, Curn=USD, Precision=0)',
'TR.EPSMeanEstimate(Period=FY1, Curn=USD)',
'TR.EPSHigh(Period=FY1, Curn=USD)', 'TR.EPSLow(Period=FY1, Curn=USD)'
])
# there can be only one request to get the field in get_data call
# for the same field but with different parameters, we use another call
dfFY1Roll, err = ek.get_data("IBM", [
'TR.RevenueMeanEstimate(Period=FY1, Scale=6, Curn=USD, RollPeriods=False, Precision=0)',
'TR.EBITDAMean(Period=FY1, Scale=6, Curn=USD, RollPeriods=False, Precision=0)',
'TR.EPSMeanEstimate(Period=FY1, Curn=USD, RollPeriods=False)'
])
dfFY2, err = ek.get_data("IBM", [
'TR.RevenueMeanEstimate(Period=FY2, Scale=6, Curn=USD, Precision=0)',
import eikon as ek
ek.set_app_id('F1968B7782740096D4E66')
dfFY0, err = ek.get_data("IBM", [('TR.RevenueActValue', {
'Period': 'FY0',
'Scale': 6,
'Curn': 'USD'
}), ('TR.EBITDAActValue', {
'Period': 'FY0',
'Scale': 6,
'Curn': 'USD'
}), ('TR.EPSActValue', {
'Period': 'FY0',
'Curn': 'USD'
})],
sort_on=None,
output='pandas',
debug=True)
dfFY1, err = ek.get_data("IBM", [('TR.RevenueMeanEstimate', {
'Period': 'FY1',
'Scale': 6,
'Curn': 'USD',
'Precision': 2
}), ('TR.RevenueHigh', {
'Period': 'FY1',
'Scale': 6,
'Curn': 'USD'
}), ('TR.RevenueLow', {
'Period': 'FY1',
'Scale': 6,
import eikon as ek
from datetime import date
import re
import lxml.html
import pandas as pd
import win32com.client
outlook = win32com.client.Dispatch("Outlook.Application")
mail = outlook.CreateItem(0)
ek.set_app_id('<Eikon_token_id>')
#start_date, end_date = date(2017, 10, 22), date.today()
start_date, end_date = date(2017, 10, 1), date(2017, 12, 14)
q = "Product:IFRC AND Topic:ISU AND (\"PRICED\" OR \"DEAL\")"
headlines = ek.get_news_headlines(query=q, date_from=start_date, date_to=end_date, count=100)
headlines = headlines[headlines['storyId'].str.contains('nIFR')]
headlines.to_csv('test.csv')
def termsheet_to_dict(storyId):
x = ek.get_news_story(storyId)
story = lxml.html.document_fromstring(x).text_content()
matches = dict(re.findall(pattern=r"\[(.*?)\]:\s?([A-Z,a-z,0-9,\-,\(,\),\+,/,\n,\r,\.,%,\&,>, ]+)", string=story))
clean_matches = {key.strip(): item.strip() for key, item in matches.items()}
return clean_matches
result = []
index = pd.DataFrame(headlines, columns=['storyId']).values.tolist()
for i, storyId in enumerate(index):
x = termsheet_to_dict(storyId[0])
import eikon as ek
import numpy as np
import pandas as pd
import cufflinks as cf
import configparser as cp
cf.set_config_file(offline=True)
cfg = cp.ConfigParser()
cfg.read('eikon.cfg')
ek.set_app_id(cfg['eikon']['app_id'])
ric = 'AAPL.O'
data = ek.get_timeseries(ric,
fields='CLOSE',
start_date='2015-01-01',
end_date='2018-08-15')
data.normalize().iplot(kind='lines')
SMA1 = 42 # days
SMA2 = 252 # days
data['SMA1'] = data['CLOSE'].rolling(SMA1).mean()
data['SMA2'] = data['CLOSE'].rolling(SMA2).mean()
data.iplot()
data.dropna(
inplace=True
) #dropping na to account for SMA periods with not enough data to smooth.
data['position'] = np.where(data['SMA1'] > data['SMA2'], 1, -1)
data.iplot(secondary_y='position')
import asyncio
import datetime
import random
import websockets
import eikon
import requests
import json
ric_codes = []
data_url = 'http://52.87.248.54/ric_codes'
app_id = 'CE9D75E3B5ECDE27DC3BDA'
eikon.set_app_id(app_id)
# async def consumer(ric_codes):
# data = ric_codes.split(',')
# async def producer():
# if not data:
# return ''
# rst, err = eikon.get_data(instruments=data, fields=['CF_LAST'])
# return [str(d) for d in rst['CF_LAST']]
# async def consumer_handler(websocket, path):
# while True:
# ric_codes = await websocket.recv()
# await consumer(ric_codes)
# async def producer_handler(websocket, path):
# while True: