1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
|
import io
import logging
import os
import requests
import shutil
import zipfile
import time
from pandas.tseries.offsets import BDay
import pandas as pd
logger = logging.getLogger(__name__)
def convertToNone(v):
return v if v else None
def download_cds_data(payload):
r = requests.post("https://www.markit.com/export.jsp", params=payload)
with zipfile.ZipFile(io.BytesIO(r.content)) as z:
f2 = open(
os.path.join(
os.environ["BASE_DIR"],
"Tranche_data",
"CDS",
"cds eod {0}.csv".format(payload["date"]),
),
"wb",
)
for f in z.namelist():
if "csv" in f:
f1 = z.open(f)
next(f1)
next(f1)
shutil.copyfileobj(f1, f2)
f1.close()
f2.close()
def download_composite_data(payload, historical=False):
# if historical, we want to maintain the invariant mtime(f)== payload['date'] + BDay(1)
if historical:
ts = (pd.Timestamp(payload["date"]) + BDay(1)).timestamp()
for report in ["COMPOSITES", "TRANCHE_COMPOSITES"]:
for family in ["CDX", "ITRAXX-EUROPE"]:
payload.update({"family": family, "report": report})
while True:
r = requests.post("https://www.markit.com/export.jsp", params=payload)
try:
with zipfile.ZipFile(io.BytesIO(r.content)) as z:
for f in z.namelist():
if "csv" in f:
path = z.extract(
f,
path=os.path.join(
os.environ["BASE_DIR"],
"Tranche_data",
"Composite_reports",
),
)
if historical:
os.utime(path, (ts, ts))
except zipfile.BadZipfile:
logger.error(r.content.decode())
time.sleep(5)
continue
else:
break
|