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import os
import os.path
import psycopg2
import pdb
import pandas as pd
if os.name =='nt':
root = "//WDsentinel/share/CorpCDOs"
elif os.name == 'posix':
root = '/home/share/CorpCDOs'
conn = psycopg2.connect(database="ET",
user="et_user",
password="Serenitas1",
host="192.168.1.108")
cursor = conn.cursor()
def cusips_from_dealname(dealname, curr = cursor):
curr.execute("SELECT \"Deal Cusip List\" FROM latest_clo_universe "
" WHERE dealname = %s", (dealname,))
return curr.fetchone()[0]
def sanitize_float(string):
if isinstance(string, float):
return string
else:
string = string.replace(",","")
if "(" in string:
return - float(string[1:-1])
else:
return float(string)
fields = ["Price", "WAL", "Market Value", "Modified Duration"]
dealdata = {}
workdate = '2013-01-09'
for dealname in ["abcl071", "ammcclo5"]:
tranches = os.listdir(os.path.join(root, "Scenarios", "Prices_" + workdate, dealname))
d = {}
for tranche in tranches:
data = pd.read_table(os.path.join(root, "Scenarios", "Prices_" + workdate, dealname, tranche))
datamod = data[data.columns[2:-1]].T
datamod.columns = data[data.columns[1]]
for field in fields:
datamod[field] = datamod[field].apply(sanitize_float)
d[tranche[:-7]] = datamod[fields]
dealdata[dealname] = pd.concat(d)
dealdata = pd.concat(dealdata)
cursor.close()
conn.close()
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