diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/bbg_newids.py | 32 |
1 files changed, 14 insertions, 18 deletions
diff --git a/python/bbg_newids.py b/python/bbg_newids.py index 241e57a8..e5e1bd16 100644 --- a/python/bbg_newids.py +++ b/python/bbg_newids.py @@ -1,10 +1,8 @@ from sqlalchemy import create_engine, MetaData, select, Column, func, bindparam from collections import defaultdict import pandas as pd -from db import conn import numpy as np -from bbg_helpers import init_bbg_session, retreive_data, process_msgs -from psycopg2 import IntegrityError +from bbg_helpers import init_bbg_session, retrieve_data, BBG_IP engine = create_engine('postgresql://et_user@debian/ET') meta = MetaData(bind=engine) @@ -31,7 +29,7 @@ def f(s): if s: return "{%s}" % ",".join(s) else: - return "" + return None clean_mapping = {cusip: f(loanxid) for cusip, loanxid in clean_mapping} mapping = pd.DataFrame.from_dict(clean_mapping, orient='index') @@ -41,20 +39,18 @@ currentdata = pd.read_sql_query("select id_bb_unique, cusip from bloomberg_corp_ engine, index_col='cusip') mapping = mapping.ix[mapping.index.difference(currentdata.index)] -session = init_bbg_session('192.168.1.108', 8194) -all_fields = ["ISSUE_DT", "LN_ISSUE_STATUS", "ID_CUSIP", "ID_BB_UNIQUE", - "SECURITY_TYP", "AMT_OUTSTANDING", "PX_LAST","LAST_UPDATE_DT", - "ISSUER", "MATURITY","CPN","CPN_TYP", "CPN_FREQ","FLT_SPREAD", - "LIBOR_FLOOR","LN_CURRENT_MARGIN", "LN_TRANCHE_SIZE", "AMT_ISSUED", - "LN_COVENANT_LITE","SECOND_LIEN_INDICATOR","DEFAULTED", "DEFAULT_DATE", - "CALLED", "CALLED_DT", "PRICING_SOURCE"] - -securities = ["{0} Corp".format(cusip) for cusip in mapping.index] -data = retreive_data(session, securities, all_fields) -df = process_msgs(data, all_fields) -df.security = df.security.str.slice(0,9) -df.set_index('security', inplace=True) -df.reset_index(inplace=True) +with init_bbg_session(BBG_IP) as session: + all_fields = ["ISSUE_DT", "LN_ISSUE_STATUS", "ID_CUSIP", "ID_BB_UNIQUE", + "SECURITY_TYP", "AMT_OUTSTANDING", "PX_LAST","LAST_UPDATE_DT", + "ISSUER", "MATURITY","CPN","CPN_TYP", "CPN_FREQ","FLT_SPREAD", + "LIBOR_FLOOR","LN_CURRENT_MARGIN", "LN_TRANCHE_SIZE", "AMT_ISSUED", + "LN_COVENANT_LITE","SECOND_LIEN_INDICATOR","DEFAULTED", "DEFAULT_DATE", + "CALLED", "CALLED_DT", "PRICING_SOURCE"] + securities = ["{0} Corp".format(cusip) for cusip in mapping.index] + df = retrieve_data(session, securities, all_fields) +df = pd.DataFrame.from_dict(df, orient='index') +df.index = df.index.str.slice(0,9) +df.security = df.index.to_series() df['loanxid'] = mapping.loanxid df.dropna(subset=['ID_BB_UNIQUE'], inplace=True) df.loc[df.LN_TRANCHE_SIZE.isnull(),'LN_TRANCHE_SIZE'] = df[df.LN_TRANCHE_SIZE.isnull()].AMT_ISSUED.values |