Python standard library

#EventID | Time | Latitude | Longitude | Depth/km | Author | Catalog | Contributor | ContributorID | MagType | Magnitude | MagAuthor | EventLocationName

9993759|2017-01-22T04:30:22|-6.2145|155.1442|135.0|pt,us,at|NEIC PDE|us|us10007uph,pt17022050,at00ok5z6p|mww|7.9|us|SOLOMON ISLANDS

9993037|2017-01-19T23:04:21|-10.3433|161.318|36.0|pt,us,at|NEIC PDE|us|us10007u7n,at00ok1ura,pt17019050|mww|6.5|us|SOLOMON ISLANDS

9953968|2017-01-10T06:13:47|4.4634|122.575|612.71|at,us|NEIC PDE|us|us10007s9c,at00ojjvz0|Mww|7.3|us|CELEBES SEA

9951821|2017-01-03T21:52:30|-19.3542|176.058|12.0|at,us,pt|NEIC PDE|us|us10007pj6,at00oj84rf,pt17003051|Mww|6.9|us|SOUTH OF FIJI ISLANDS

with open("events.csv") as csvfile:

    reader = csv.DictReader(csvfile, delimiter="|")

    reader.fieldnames = [field.strip() for field in reader.fieldnames]

    for row in reader:

        print(row['Time'])

from multiprocessing import Pool

def func2run(c1, c2, v1, c3, v4):

    print(c1, c2, v1, c3, v4)

pool = Pool(processes=4)

c1, c2, c3, c4 = 1, 2, 3, 4

args = [(c1, c2, v, c3, c4) for v in range(1, 10)]

pool.starmap(func2run, args)

1 2 1 3 4

1 2 2 3 4

1 2 3 3 4

1 2 5 3 4

1 2 4 3 4

1 2 7 3 4

1 2 6 3 4

1 2 8 3 4

1 2 9 3 4

from  multiprocessing.dummy import Pool

with Pool(4) as p:

    p.map(f, args)

from  multiprocessing.pool import ThreadPool

with ThreadPool(4) as p:

    p.map(f, args)