def pyxll_stock_price(endpoint, api_token, symbol):
"""not supported in this version of Excel"""
if aiohttp is None:
return "aiohttp module could not be imported"
if json is None:
return "json module could not be imported"
return "async functions are not supported in Excel %s" % xl_version()
def show_last_error():
selection = xl_app().Selection
exc_type, exc_value, exc_traceback = get_last_error(selection)
if exc_type is None:
xlcAlert("No error found for the selected cell")
return
msg = "".join(
traceback.format_exception(exc_type, exc_value, exc_traceback))
if xl_version() < 12:
msg = msg[:254]
xlcAlert(msg)
def yahoo_stock_price(symbol):
"""not supported in this version of Excel"""
return "async functions are not supported in Excel %s" % xl_version()
performance.
"""
from pyxll import xl_func, xl_version, xlAsyncReturn
#
# this example uses urllib2 to perform an asynchronous http
# request and return the data to Excel.
#
import urllib2
import threading
#
# Async functions are only supported from Excel 2010
#
if xl_version() >= 14:
@xl_func("string, async_handle: void")
def yahoo_stock_price(symbol, handle):
"""returns the last price for a symbol from Yahoo Finance"""
def thread_func(symbol, async_handle):
result = None
try:
# get the price using an http request (f=l1 means get the last price)
url = "http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=l1" % symbol
data = urllib2.urlopen(url).read()
# the returned data is in csv format, but only has one row and one column
result = float(data.strip())
except Exception, e:
except ImportError:
_log.warning("json could not be imported. Async example will not work",
exc_info=True)
json = None
try:
import aiohttp
except ImportError:
_log.warning("aiohttp could not be imported. Async example will not work",
exc_info=True)
aiohttp = None
#
# Async functions are only supported from Excel 2010
#
if xl_version() >= 14 and json is not None and aiohttp is not None:
@xl_func
async def pyxll_stock_price(endpoint, api_token, symbol):
"""Return the latest price for a symbol from iextrading.com"""
url = "{endpoint}/stock/{symbol}/quote?token={api_token}".format(
endpoint=endpoint, symbol=symbol, api_token=api_token)
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 200
data = await response.read()
data = json.loads(data.decode("utf-8"))
return data.get("latestPrice", "#NoLatestPrice")
else:
def yahoo_stock_price(symbol):
"""not supported in this version of Excel"""
return "async functions are not supported in Excel %s" % xl_version()
performance.
"""
from pyxll import xl_func, xl_version, xlAsyncReturn
#
# this example uses urllib2 to perform an asynchronous http
# request and return the data to Excel.
#
import urllib.request, urllib.error, urllib.parse
import threading
#
# Async functions are only supported from Excel 2010
#
if xl_version() >= 14:
@xl_func("string, async_handle: void")
def yahoo_stock_price(symbol, handle):
"""returns the last price for a symbol from Yahoo Finance"""
def thread_func(symbol, async_handle):
result = None
try:
# get the price using an http request (f=l1 means get the last price)
url = "http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=l1" % symbol
data = urllib.request.urlopen(url).read()
# the returned data is in csv format, but only has one row and one column
result = float(data.strip())
except Exception as e:
xlcCalculateNow,
xlcCalculateDocument,
)
import pyxll
import hashlib
import win32com.client
import json
import requests
import multiprocessing
from multiprocessing.pool import ThreadPool
# Excel 2010 or newer is needed since we require async_handle support.
if xl_version() < 14:
raise Exception("Gemini calls not supported in older Excel versions")
# global hash which stores Gemini call results
RESULTS = {}
# FIXME: hard-coded pool size
pool = ThreadPool(processes=20)
def xl_app():
"""returns a Dispatch object for the current Excel instance"""
# get the Excel application object from PyXLL and wrap it
xl_window = pyxll.get_active_object()
xl_app = win32com.client.Dispatch(xl_window).Application
# it's helpful to make sure the gen_py wrapper has been created