I download Data over a restAPI and wrote a module. The download takes lets say 10sec. During this time, the rest of the script in 'main' and in the module is not running until the download is finished. How can I change it, e.g. by processing it in another core?
I tried this code but it does not do the trick (same lag). Then I tried to implement this approach and it just gives me errors, as I suspect it 'map' does not work with 'wget.download'?
My code from the module:
from multiprocessing.dummy import Pool as ThreadPool
import urllib.parse
#define the needed data
function='TIME_SERIES_INTRADAY_EXTENDED'
symbol='IBM'
interval='1min'
slice='year1month1'
adjusted='true'
apikey= key[0].rstrip()
#create URL
SCHEME = os.environ.get("API_SCHEME", "https")
NETLOC = os.environ.get("API_NETLOC", "www.alphavantage.co") #query?
PATH = os.environ.get("API_PATH","query")
query = urllib.parse.urlencode(dict(function=function, symbol=symbol, interval=interval, slice=slice, adjusted=adjusted, apikey=apikey))
url = urllib.parse.urlunsplit((SCHEME, NETLOC,PATH, query, ''))
#this is my original code to download the data (working but slow and stopping the rest of the script)
wget.download(url, 'C:\\Users\\x\\Desktop\\Tool\\RAWdata\\test.csv')
#this is my attempt to speed things up via multithreading from code
pool = ThreadPool(4)
if __name__ == '__main__':
futures = []
for x in range(1):
futures.append(pool.apply_async(wget.download, url,'C:\\Users\\x\\Desktop\\Tool\\RAWdata\\test.csv']))
# futures is now a list of 10 futures.
for future in futures:
print(future.get())
any suggestions or do you see the error i make?