不幸的是我在论坛上被引导相信（但不是100％确定）Bloomberg Desktop API一次不允许多个IntradayBarRequest或IntradayTickRequest，这与HistoricalDataRequest或Subscriptions不同，其中多个允许同时发出请求。
因此，这个问题可能没有实际意义，除非有人告诉我上述情况并非如此
如果为true，则处理下面问题的唯一方法是仅在处理完上一个请求后发送每个新请求。
我正在使用Python Bloomberg Desktop API访问金融证券的订阅（实时更新）和历史日常数据。在这两种情况下，我都可以发送多个同时发出的请求，当响应到来时（不一定按发送请求的顺序），我可以使用msg.getElement（“securityData”）找出响应所关联的安全性。 .getElementAsString（“security”）在历史数据的情况下，或者在订阅数据的情况下，通过使用msg.correlationIds（）[0] .value（）查询我预先设置的correlationId（在订阅请求时） 。
但是我不知道如何为IntradayBarResponse请求执行此操作（并且WAPI文档没有帮助）。这些似乎没有setable correlationId，也没有上面的“securityData”字段。如果我发送多个intradayBarRequests，我怎样才能找出响应的安全性？
这是我的代码（改编自API Python示例）。
import blpapi # interface to bloomberg
import time # will need this for time parsing
from optparse import OptionParser
import pdb # debugger, when necessary
import csv # for csv reading
import string # for string parsing
from pymongo import MongoClient
import inspect
from datetime import datetime
from bson.son import SON
def parseCmdLine():
parser = OptionParser(description="Retrieve realtime data.")
parser.add_option("-a",
"--ip",
dest="host",
help="server name or IP (default: %default)",
metavar="ipAddress",
default="localhost")
parser.add_option("-p",
dest="port",
type="int",
help="server port (default: %default)",
metavar="tcpPort",
default=8194)
parser.add_option("--me",
dest="maxEvents",
type="int",
help="stop after this many events (default: %default)",
metavar="maxEvents",
default=100000000000)
parser.add_option("--mongohost",
dest="mongohost",
default="192.168.1.30")
parser.add_option("--mongoport",
dest="mongoport",
type="int",
default=27017)
(options, args) = parser.parse_args()
return options
def main():
options = parseCmdLine()
# connect to MongoDB MONGO MONGO MONGO MONGO ----------------
print "Connecting to MongoDB"
print options.mongohost
print options.mongoport
client = MongoClient(options.mongohost, options.mongoport) # connect to MongoDB
db = client.bb # connect to the DB database
bbsecs = db.bbsecs
bbticks = db.bbticks
# now get the securities list
# Fill SessionOptions
sessionOptions = blpapi.SessionOptions()
sessionOptions.setServerHost(options.host)
sessionOptions.setServerPort(options.port)
print "connecting to Bloomberg"
print "Connecting to %s:%d" % (options.host, options.port)
# Create a Session
session = blpapi.Session(sessionOptions)
# Start a Session
if not session.start():
print "Failed to start session."
return
# open the market data subscription service
if not session.openService("//blp/mktbar"):
print "Failed to open //blp/mktbar"
return
if not session.openService("//blp/refdata"):
print "Failed to open //blp/refdata"
return
# now startup the subscription list
# Now open the secs.dat file and read it, append each to subscription list
maxtimes = bbticks.aggregate([{'$group': {'_id':'$ticker', 'maxtime':{'$max': '$time'}}}]) # get the last updates by ticker
refDataService = session.getService("//blp/refdata") # start the ref
for i in maxtimes["result"]:
ticker = i["_id"]
tstamp = i["maxtime"]
request = refDataService.createRequest("IntradayBarRequest")
request.set("security", ticker)
request.set("eventType", "TRADE")
request.set("interval", 1)
request.set("startDateTime", tstamp)
request.set("endDateTime", datetime.now())
print "Sending Request:", ticker
session.sendRequest(request)
subscriptions = blpapi.SubscriptionList()
secdic = dict() # a new dictionary
for post in bbsecs.find():
print(post["ticker"])
# subscribe tick
#subscriptions.add(str(post["ticker"]), "LAST_PRICE", [], blpapi.CorrelationId("TICK:" + str(post["ticker"])))
#subscribe 1 minute bars
subscriptions.add("//blp/mktbar/ticker/"+str(post["ticker"]),
"LAST_PRICE",
"interval=1.0",
blpapi.CorrelationId(str(post["ticker"])))
# setup the dictionary
secdic[post["bbsecnum"]] = post["ticker"]
if not session.openService("//blp/refdata"):
print "Failed to open //blp/refdata"
return
# now subscribe
session.subscribe(subscriptions)
# HISTORICALHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
# Obtain previously opened service
#refDataService = session.getService("//blp/refdata")
# Create and fill the request for the historical data
#request = refDataService.createRequest("HistoricalDataRequest")
#for post in bbsecs.find():
# request.getElement("securities").appendValue(str(post["ticker"]))
#request.getElement("fields").appendValue("LAST_PRICE")
#request.set("periodicityAdjustment", "ACTUAL")
#request.set("periodicitySelection", "DAILY")
#request.set("startDate", "20100101")
#request.set("endDate", "20121231")
#request.set("maxDataPoints", 2000)
#print "Sending Request:", request
# Send the request
#session.sendRequest(request)
#hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh
try:
# Process received events
eventCount = 0
while(True):
# We provide timeout to give the chance to Ctrl+C handling:
event = session.nextEvent(500)
for msg in event:
if event.eventType() == blpapi.Event.SUBSCRIPTION_STATUS:
#print "%s - %s" % (msg.correlationIds()[0].value(), msg)
print "subscription status"
elif event.eventType() == blpapi.Event.SUBSCRIPTION_DATA:
key = msg.correlationIds()[0].value()
if msg.messageType() == "MarketBarStart":
open = msg.getElementAsFloat("OPEN")
high = msg.getElementAsFloat("HIGH")
low = msg.getElementAsFloat("LOW")
close = msg.getElementAsFloat("CLOSE")
btstamp = msg.getElementAsDatetime("TIME")
tstamp = datetime.now()
print "bar", key, close, tstamp
bbticks.insert({"type": "BAR", "ticker": key, "value": close, \
"open": open, "high": high, "low": low, "close": close, \
"time": tstamp})
elif msg.messageType() == "MarketBarUpdate":
close = msg.getElementAsFloat("CLOSE")
#print "tick", close,
#bbticks.insert({"type": "TICK", "ticker": key, "value": close, "time": tstamp})
#if etype == "TRADE":
# if msg.hasElement("LAST_TRADE"):
# key = msg.correlationIds()[0].value(),
# keytype = key[:(key.index(":"))]
# key = key[(key.index(":") + 1):]
# value = msg.getElementAsString("LAST_TRADE")
# timestamp = msg.getElementAsDatetime("TRADE_UPDATE_STAMP_RT")
# print key, value,
# bbticks.insert({"ticker": key, "value": value, "timestamp": timestamp})
else:
if msg.messageType() == "HistoricalDataResponse":
securityData = msg.getElement("securityData")
security = securityData.getElementAsString("security")
fieldDataArray = securityData.getElement("fieldData")
for j in range(0, fieldDataArray.numValues()):
fieldData = fieldDataArray.getValueAsElement(j)
field = fieldData.getElement(0)
tstamp = field.getValueAsDatetime()
tstamp = datetime(tstamp.year, tstamp.month, tstamp.day)
field = fieldData.getElement(1)
close = field.getValueAsFloat()
#print "history", security, close,
#bbticks.insert({"type": "DAILY", "ticker": security, "value": close, "close": close, \
# "time": tstamp})
elif msg.messageType() == "IntradayBarResponse":
print "IntradayBarResponse"
data = msg.getElement("barData").getElement("barTickData")
numvals = data.numValues()
print numvals
if numvals > 0:
print data.getValueAsElement(1).getElement(1).getValueAsFloat()
if event.eventType() == blpapi.Event.SUBSCRIPTION_DATA:
eventCount += 1
if eventCount >= options.maxEvents:
break
finally:
# Stop the session
session.stop()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
print "Ctrl+C pressed. Stopping..."
我已经查看了eidData，即使我要求将其返回，也是空的。我在看货币而不是股票，所以没有交换权利。
> (Pdb) print eid._Element__dataHolder IntradayBarResponse = {
> barData = {
> eidData[] = {
> }
> barTickData[] = {
> barTickData = {
> time = 2013-08-02T18:36:00.000
> open = 4.233100
> high = 4.233600
> low = 4.233100
> close = 4.233400
> volume = 0
> numEvents = 119
> value = 0.000000
> }
> barTickData = {
> time = 2013-08-02T18:37:00.000
> open = 4.233400
> high = 4.233700
> low = 4.233100
> close = 4.233500
> volume = 0
> numEvents = 96
> value = 0.000000
> }
> barTickData = {
> time = 2013-08-02T18:38:00.000
> open = 4.233500
> high = 4.233600
> low = 4.233300
> close = 4.233500
> volume = 0
> numEvents = 135
> value = 0.000000
> }
> barTickData = {
> time = 2013-08-02T18:39:00.000
我仍在寻找一种方法将请求与响应相关联，而不必执行低效请求....等待响应....请求等等。但是，我不确定Bloomberg是否提供此功能。这种限制似乎也存在于历史刻度数据中。
答案 0 :(得分：2)
Thomas，您应该始终使用响应的correlationId来查找与之关联的请求。 IIRC，参考数据和历史数据请求支持多种证券，但市场数据和日内柱可能每个请求只有一个证券。
这就是为什么在refdata和历史响应中有额外的“securityData”字段。对于市场数据和日内柱，correlationId足以识别请求，从而确定安全性。
希望它有所帮助。
答案 1 :(得分：2)
我不知道python API，但我确实使用Java API。
我仍在寻找一种方法将请求与响应相关联，而不必执行低效请求....等待响应....请求等。
正如您所发现的，您无法为IntradayBarRequests发送多个证券的查询，并且Feed不包含安全ID（例如代码），以便轻松地映射回您的查询。
最简单的解决方案是使用相关ID。向会话提交请求时，您可以提供自己的关联ID。下面的例子是Java，但我认为python API类似：
Session session = ...; //Bloomberg Session
CorrelationId cId = new CorrelationId(); //Unique ID
session.sendRequest(bbRequest, cId); //provide your own ID
然后，如果您使用异步会话，则会收到异步消息，其中包含指向原始CorrelationId的链接：
public void processEvent(Event event, Session session) {
for (Message msg : event) {
CorrelationID cId = msg.correlationID();
//here you can link the result back to your original query
}
}
答案 2 :(得分：0)
我不相信你可以下标来勾选或禁止数据。这就是为什么......的一个原因 对于定价数据，您会在每次更改值时得到响应。蜱数据不仅仅是那些价格的历史吗？对于条形数据，不是通过按期间（即10分钟，1小时）分组来删除某些细节的价格历史。因此，如果您可以订阅任何一个，您何时应该收到Bloomberg的每个新回复？从本质上讲，您可以创建自己的侦听器来执行分组，然后以您自己选择的频率从侦听器发出响应。
BTW：我使用CLR与python中的.net blp对象进行通信。我的解决方案早于支持Bloomberg for Python，基本上做了“无法做”的事情。