Question

我有这段代码：

import urllib2, json, csv
import requests
import itertools
import multiprocessing
import numpy
from datetime import datetime, date, timedelta

def getTaxiTrips(date):
    """
    Gets the taxi trips occurred in NY from a starting date.
    :param date: (Y-m-d).
    :return: list of tuples (long, lat, drop off date).
    """
    today = str(datetime.date(datetime.now())).split('-')
    today_y = today[0]
    today_m = today[1]

    start = date.split('-')
    start_y = start[0]
    start_m = start[1]

    print start_m + "-" + start_y + " / " + today_m + "-" + today_y

    data = []
    y = int(start_y)
    m = int(start_m)
    while int(start_y) <= int(today_y):
        # Month transformation
        if m > 12:
            m %= 12
            y += 1

        mt = str(m) if m > 9 else '0' + str(m)
        # Green cabs
        if readCSV("https://storage.googleapis.com/tlc-trip-data/" + str(y) + \
                   "/green_tripdata_" + str(y) + "-" + mt + ".csv") is not None:
            data.append("https://storage.googleapis.com/tlc-trip-data/" + str(y) + \
                        "/green_tripdata_" + str(y) + "-" + mt + ".csv")

        # Yellow cabs
        if readCSV("https://storage.googleapis.com/tlc-trip-data/" + str(y) +
                   "/yellow_tripdata_" + str(y) + "-" + mt + ".csv") is not None:
            data.append("https://storage.googleapis.com/tlc-trip-data/" + str(y) +
                        "/yellow_tripdata_" + str(y) + "-" + mt + ".csv")

        if m == int(today_m):
            break
        m += 1

    pool = multiprocessing.Pool(mps-1)
    result = pool.map(consumeTaxiData, data)
    pool.close()
    pool.join()

    return list(itertools.chain(*result))


def consumeTaxiData(url):
    """
    Given a url, reads its content and process its data.
    :param url: the url to be readen.
    :return: a list of tuples in the form (long, lat, hour).
    """
    print "Processing", url
    points = []

    data = readCSV(url)
    for line in data:
        latitude = line.get('dropoff_latitude', None)
        if latitude is None:
            latitude = line.get('Dropoff_latitude', None)

        longitude = line.get('dropoff_longitude', None)
        if longitude is None:
            longitude = line.get('Dropoff_longitude', None)

        time = line.get('tpep_dropoff_datetime', None)
        if time is None:
            time = line.get('Lpep_dropoff_datetime', None)

        if time is not None:
            time = datetime.strptime(time, '%Y-%m-%d %H:%M:%S')
            if latitude is not None and longitude is not None and time >= datetime.strptime(date, '%Y-%m-%d') and \
                    time.weekday():
                time = roundTime(time, roundTo=60 * 60).hour
                points.append((float(longitude), float(latitude), time))

    return points

def readCSV(url):
    """
    Read a csv file.
    :param url: url to be read.
    :return: an array of dictionaries.
    """
    try:
        response = urllib2.urlopen(url)
        return csv.DictReader(response, delimiter=',')
    except urllib2.HTTPError as e:
        return None

def roundTime(dt=None, roundTo=60):
   """
   Round a datetime object to any time laps in seconds
   :param dt: datetime.datetime object, default now.
   :param roundTo: closest number of seconds to round to, default 1 minute.
   :return: the rounded time.
   """
   if dt == None : dt = datetime.now()
   seconds = (dt - dt.min).seconds
   rounding = (seconds+roundTo/2) // roundTo * roundTo
   return dt + timedelta(0, rounding-seconds, -dt.microsecond)

if __name__ == '__main__':
    mps = multiprocessing.cpu_count()

    date = str(datetime.date(datetime.now()) - timedelta(31*8))
    print "-----> Inital date:", date

    print "-----> Getting taxi data..."
    taxi_dropoffs = getTaxiTrips(date)
    print len(taxi_dropoffs), "taxi trips"

这对这些数据来说效果很好：

https://storage.googleapis.com/tlc-trip-data/2015/green_tripdata_2015-06.csv
https://storage.googleapis.com/tlc-trip-data/2015/yellow_tripdata_2015-06.csv

现在我正在尝试处理更多数据：

https://storage.googleapis.com/tlc-trip-data/2015/green_tripdata_2015-06.csv
https://storage.googleapis.com/tlc-trip-data/2015/green_tripdata_2015-07.csv
https://storage.googleapis.com/tlc-trip-data/2015/green_tripdata_2015-08.csv
https://storage.googleapis.com/tlc-trip-data/2015/yellow_tripdata_2015-08.csv
https://storage.googleapis.com/tlc-trip-data/2015/yellow_tripdata_2015-07.csv
https://storage.googleapis.com/tlc-trip-data/2015/yellow_tripdata_2015-06.csv
https://storage.googleapis.com/tlc-trip-data/2015/green_tripdata_2015-09.csv

我一直收到这条消息：

Traceback (most recent call last):
  File "noiseInference.py", line 489, in <module>
    taxi_dropoffs = getTaxiTrips(date)
  File "noiseInference.py", line 300, in getTaxiTrips
    result = pool.map(consumeTaxiData, data)
  File "/usr/local/Cellar/python/2.7.11/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/pool.py", line 251, in map
    return self.map_async(func, iterable, chunksize).get()
  File "/usr/local/Cellar/python/2.7.11/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/pool.py", line 567, in get
    raise self._value
socket.error: [Errno 60] Operation timed out

因为每个.csv文件很大而且我正在处理很多文件，所以我期待处理方法需要一些时间。但是，处理正在终止。我该如何解决这个问题？

数据来自此处：http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml

Answer 1

multiprocessing.Pool的输出通常会产生误导。

追溯：

  return self.map_async(func, iterable, chunksize).get()
File "/usr/local/Cellar/python/2.7.11/Frameworks/Python.framework/Versions/2.7/lib/python2.7/multiprocessing/pool.py", line 567, in get
  raise self._value
  socket.error: [Errno 60] Operation timed out

显示map_async.get引发存储在其_value属性中的错误。此属性仅包含在此过程中引发的错误。错误很明显：套接字操作超时。

为了更好地了解问题，我建议您在multiprocessing.Pool.map_async之外复制该问题。

多处理池：操作超时

1 个答案: