| """ |
| Import sample data for classification engine |
| """ |
| |
| import predictionio |
| import argparse |
| |
| def import_events(client, file): |
| f = open(file, 'r') |
| count = 0 |
| print "Importing data..." |
| for line in f: |
| data = line.rstrip('\r\n').split(",") |
| plan = data[0] |
| #Not strictly CSV, after the first comma, no longer delimiting |
| text = ",".join(data[1:]) |
| client.create_event( |
| event="$set", |
| entity_type="user", |
| entity_id=str(count), # use the count num as user ID |
| properties= { |
| "text" : text, |
| "category" : plan, |
| "label" : int(plan) |
| } |
| ) |
| count += 1 |
| f.close() |
| print "%s events are imported." % count |
| |
| if __name__ == '__main__': |
| parser = argparse.ArgumentParser( |
| description="Import sample data for classification engine") |
| parser.add_argument('--access_key', default='invald_access_key') |
| parser.add_argument('--url', default="http://localhost:7070") |
| parser.add_argument('--file', default="./data/Twitter140sample.txt") |
| |
| args = parser.parse_args() |
| print args |
| |
| client = predictionio.EventClient( |
| access_key=args.access_key, |
| url=args.url, |
| threads=5, |
| qsize=500) |
| import_events(client, args.file) |
