Tutorial on using pdblp¶
This tutorial provides some simple use cases for pdblp . To start with,
import the library and create a BCon() object
In [1]: import pdblp
In [2]: con = pdblp.BCon(debug=True, port=8194, timeout=5000)
Make sure that you are logged in to a Bloomberg terminal, after which you should be able to to start a connection as follows
In [3]: con.start()
To get some historical data, we can call bdh()
In [4]: con.bdh('SPY US Equity', 'PX_LAST',
'20150629', '20150630')
DEBUG:root:Sending Request:
HistoricalDataRequest = {
securities[] = {
"SPY US Equity"
}
fields[] = {
"PX_LAST"
}
periodicityAdjustment = ACTUAL
periodicitySelection = DAILY
startDate = "20150629"
endDate = "20150630"
overrides[] = {
}
}
DEBUG:root:Message Received:
HistoricalDataResponse = {
securityData = {
security = "SPY US Equity"
eidData[] = {
}
sequenceNumber = 0
fieldExceptions[] = {
}
fieldData[] = {
fieldData = {
date = 2015-06-29
PX_LAST = 205.420000
}
fieldData = {
date = 2015-06-30
PX_LAST = 205.850000
}
}
}
}
Out[4]:
ticker SPY US Equity
2015-06-29 205.42
2015-06-30 205.85
Notice that when con.debug == True that the Response and Request messages
are printed to stdout. This can be quite useful for debugging but gets
annoying for normal use, so let’s turn it off and get some more data. This time
we request two fields which returns a DataFrame with a MultiIndex by default.
In [5]: con.debug = False
In [6]: con.bdh('SPY US Equity', ['PX_LAST', 'VOLUME'],
...: '20150629', '20150630')
...:
Out[6]:
ticker SPY US Equity
field PX_LAST VOLUME
date
2015-06-29 205.42 202621332.0
2015-06-30 205.85 182925106.0
But can also return data in long format
In [7]: con.bdh('SPY US Equity', ['PX_LAST', 'VOLUME'],
...: '20150629', '20150630', longdata=True)
...:
Out[7]:
date ticker field value
0 2015-06-29 SPY US Equity PX_LAST 2.054200e+02
1 2015-06-29 SPY US Equity VOLUME 2.026213e+08
2 2015-06-30 SPY US Equity PX_LAST 2.058500e+02
3 2015-06-30 SPY US Equity VOLUME 1.829251e+08
You can also override different FLDS’s, for example
In [8]: con.bdh('MPMIEZMA Index', 'PX_LAST',
...: '20150101', '20150830')
...:
Out[8]:
ticker MPMIEZMA Index
field PX_LAST
date
2015-06-30 52.5
2015-07-31 52.4
In [9]: con.bdh('MPMIEZMA Index', 'PX_LAST',
...: '20150101', '20150830',
...: ovrds=[('RELEASE_STAGE_OVERRIDE', 'P')])
...:
Out[9]:
ticker MPMIEZMA Index
field PX_LAST
date
2015-04-30 51.9
The context can also be managage using bopen
In [10]: with pdblp.bopen(port=8194) as bb:
....: df = bb.bdh('SPY US Equity', 'PX_LAST',
....: '20150629', '20150630')
....:
The libary also contains functions for accessing reference data, a variety of usages are shown below
In [11]: con.ref('AUDUSD Curncy', 'SETTLE_DT')
Out[11]:
ticker field value
0 AUDUSD Curncy SETTLE_DT 2018-06-06
In [12]: con.ref(['NZDUSD Curncy', 'AUDUSD Curncy'], 'SETTLE_DT')
Out[12]:
ticker field value
0 NZDUSD Curncy SETTLE_DT 2018-06-06
1 AUDUSD Curncy SETTLE_DT 2018-06-06
In [13]: con.ref('AUDUSD Curncy', ['SETTLE_DT', 'DAYS_TO_MTY'])
Out[13]:
ticker field value
0 AUDUSD Curncy SETTLE_DT 2018-06-06
1 AUDUSD Curncy DAYS_TO_MTY 0
In [14]: con.ref(['NZDUSD Curncy', 'AUDUSD Curncy'],
....: ['SETTLE_DT', 'DAYS_TO_MTY'])
....:
Out[14]:
ticker field value
0 NZDUSD Curncy SETTLE_DT 2018-06-06
1 NZDUSD Curncy DAYS_TO_MTY 0
2 AUDUSD Curncy SETTLE_DT 2018-06-06
3 AUDUSD Curncy DAYS_TO_MTY 0
In [15]: con.ref('AUDUSD Curncy', 'SETTLE_DT',
....: [('REFERENCE_DATE', '20150715')])
....:
Out[15]:
ticker field value
0 AUDUSD Curncy SETTLE_DT 2015-07-17
In [16]: con.ref(['NZDUSD Curncy', 'AUDUSD Curncy'],
....: ['SETTLE_DT', 'DAYS_TO_MTY'],
....: [('REFERENCE_DATE', '20150715')])
....:
Out[16]:
ticker field value
0 NZDUSD Curncy SETTLE_DT 2015-07-17
1 NZDUSD Curncy DAYS_TO_MTY 0
2 AUDUSD Curncy SETTLE_DT 2015-07-17
3 AUDUSD Curncy DAYS_TO_MTY 0
In [17]: con.bulkref('W 1 Comdty', 'FUT_CHAIN',
....: [('INCLUDE_EXPIRED_CONTRACTS', 'Y')]).head()
....:
Out[17]:
ticker field name value position
0 W 1 Comdty FUT_CHAIN Security Description W N59 Comdty 0
1 W 1 Comdty FUT_CHAIN Security Description W U59 Comdty 1
2 W 1 Comdty FUT_CHAIN Security Description W Z59 Comdty 2
3 W 1 Comdty FUT_CHAIN Security Description W H60 Comdty 3
4 W 1 Comdty FUT_CHAIN Security Description W K60 Comdty 4
There are some types of reference data which cannot be downloaded in batch
but support overriding the reference date. For this type of data, ref_hist()
is useful to sequentially override the reference date to generate a time
series. A word of caution, under the hood this is making a number of
ReferenceDataRequest s and thus can throttle your daily data limits if
queried over large date ranges.
In [18]: con.ref_hist('AUD1M Curncy', 'DAYS_TO_MTY',
....: dates=['20150625', '20150626'])
....:
Out[18]:
date ticker field value
0 20150625 AUD1M Curncy DAYS_TO_MTY 30
1 20150626 AUD1M Curncy DAYS_TO_MTY 31
In [19]: con.ref_hist(['AUD1M Curncy', 'NZD1M Curncy'],
....: 'DAYS_TO_MTY',
....: dates=['20150625', '20150626'])
....:
Out[19]:
date ticker field value
0 20150625 AUD1M Curncy DAYS_TO_MTY 30
1 20150625 NZD1M Curncy DAYS_TO_MTY 30
2 20150626 AUD1M Curncy DAYS_TO_MTY 31
3 20150626 NZD1M Curncy DAYS_TO_MTY 31
In [20]: con.ref_hist('AUD1M Curncy', ['DAYS_TO_MTY', 'SETTLE_DT'],
....: dates=['20150625', '20150626'])
....:
Out[20]:
date ticker field value
0 20150625 AUD1M Curncy DAYS_TO_MTY 30
1 20150625 AUD1M Curncy SETTLE_DT 2015-07-29
2 20150626 AUD1M Curncy DAYS_TO_MTY 31
3 20150626 AUD1M Curncy SETTLE_DT 2015-07-31
In [21]: con.ref_hist(['AUD1M Curncy', 'NZD1M Curncy'],
....: ['DAYS_TO_MTY', 'SETTLE_DT'],
....: dates=['20150625', '20150626'])
....:
Out[21]:
date ticker field value
0 20150625 AUD1M Curncy DAYS_TO_MTY 30
1 20150625 AUD1M Curncy SETTLE_DT 2015-07-29
2 20150625 NZD1M Curncy DAYS_TO_MTY 30
3 20150625 NZD1M Curncy SETTLE_DT 2015-07-29
4 20150626 AUD1M Curncy DAYS_TO_MTY 31
5 20150626 AUD1M Curncy SETTLE_DT 2015-07-31
6 20150626 NZD1M Curncy DAYS_TO_MTY 31
7 20150626 NZD1M Curncy SETTLE_DT 2015-07-31
In [22]: con.ref_hist(['AUD1M Curncy', 'NZD1M Curncy'],
....: ['DAYS_TO_MTY', 'SETTLE_DT'],
....: dates=['20150625', '20150626'])
....:
Out[22]:
date ticker field value
0 20150625 AUD1M Curncy DAYS_TO_MTY 30
1 20150625 AUD1M Curncy SETTLE_DT 2015-07-29
2 20150625 NZD1M Curncy DAYS_TO_MTY 30
3 20150625 NZD1M Curncy SETTLE_DT 2015-07-29
4 20150626 AUD1M Curncy DAYS_TO_MTY 31
5 20150626 AUD1M Curncy SETTLE_DT 2015-07-31
6 20150626 NZD1M Curncy DAYS_TO_MTY 31
7 20150626 NZD1M Curncy SETTLE_DT 2015-07-31
In [23]: con.bulkref_hist("BVIS0587 Index", "CURVE_TENOR_RATES",
....: dates=['20160625'],
....: date_field="CURVE_DATE").head()
....:
Out[23]:
date ticker field name value position
0 20160625 BVIS0587 Index CURVE_TENOR_RATES Tenor 3M 0
1 20160625 BVIS0587 Index CURVE_TENOR_RATES Tenor Ticker BV3M0101 Index 0
2 20160625 BVIS0587 Index CURVE_TENOR_RATES Ask Yield -2.42454e-14 0
3 20160625 BVIS0587 Index CURVE_TENOR_RATES Mid Yield -2.42454e-14 0
4 20160625 BVIS0587 Index CURVE_TENOR_RATES Bid Yield 0.504 0
A useful trick to avoid throttling your connection when querying large data or
to ensure you can reproduce your results without a connection in the future is
to make use of the excellent joblib library. For example
In [24]: import joblib
In [25]: import shutil
In [26]: from tempfile import mkdtemp
In [27]: temp_dir = mkdtemp()
In [28]: cacher = joblib.Memory(temp_dir)
In [29]: bdh = cacher.cache(con.bdh, ignore=['self'])
In [30]: bdh('SPY US Equity', 'PX_LAST', '20150629', '20150630')
________________________________________________________________________________
[Memory] Calling pdblp.pdblp.bdh...
bdh('SPY US Equity', 'PX_LAST', '20150629', '20150630')
______________________________________________________________bdh - 0.1s, 0.0min
Out[30]:
ticker SPY US Equity
field PX_LAST
date
2015-06-29 205.42
2015-06-30 205.85
In [31]: bdh('SPY US Equity', 'PX_LAST', '20150629', '20150630')
Out[31]:
ticker SPY US Equity
field PX_LAST
date
2015-06-29 205.42
2015-06-30 205.85
In [32]: shutil.rmtree(temp_dir)
You can also access Bloomberg SRCH data using bsrch
In [33]: con.bsrch("COMDTY:VESSEL").head()
Out[33]:
0
0 IMO1000019 Index
1 LADY K II
2 IMO1000021 Index
3 MONTKAJ
4 IMO1000033 Index