i have following case: need time of feature in csv file , compare time of pictures taken someone. need find 2 (or less) matches. assign first 2 pictures find in 2 mins interval time of feature feature. managed create 2 dictionaries details: feature_hours contains id , time of feature. photo_hours contains photo_path , time of photo. sorted_feature , sorted_photo 2 lists sorted 2 dictionaries. problem in output csv file have 84 rows completed , blank. feature csv file has 199 features. think incremented j often. need clear pro, because cannot figure out. here code:
j=1 sheet1.write(0,71,"id") sheet1.write(0,72,"feature_time") sheet1.write(0,73,"picture1") sheet1.write(0,74,"picture_time") sheet1.write(0,75,"picture2") sheet1.write(0,76,"picture_time") def write_first_picture(): sheet1.write(j,71,feature_time[0]) sheet1.write(j,72,feature_time[1]) sheet1.write(j,73,photo_time[0]) sheet1.write(j,74,photo_time[1]) def write_second_picture(): sheet1.write(j-1,75,photo_time[0]) sheet1.write(j-1,76,photo_time[1]) def write_pictures(): if i==1: write_first_picture() elif i==2: write_second_picture() feature_time in sorted_features: i=0 photo_time in sorted_photo: if i<2: if feature_time[1][0]==photo_time[1][0]: if feature_time[1][1]==photo_time[1][1]: if feature_time[1][2]<photo_time[1][2]: i=i+1 write_pictures() j=j+1 elif int(feature_time[1][1])+1==photo_time[1][1]: i=i+1 write_pictures() j=j+1 elif int(feature_time[1][1])+2==photo_time[1][1]: i=i+1 write_pictures() j=j+1 elif int(feature_time[1][0])+1==photo_time[1][0]: if feature_time[1][1]>=58: if photo_time[1][1]<=02: = i+1 write_pictures() j=j+1 edit: here examples of 2 lists: features list: [('-70', ('10', '27', '03')), ('-73', ('10', '29', '50'))] photo list: [('20160801_125133-1151969393.jpg', ('12', '52', '04')), ('20160801_125211342753906.jpg', ('12', '52', '16'))]
there csv module python load these files. sort results try more efficient/short-circuit checks well. cannot tell , j variables meant represent, pretty sure can following:
import csv def hmstoseconds(hhmmss): # 60 * 60 seconds in hour, 60 seconds in min, 1 second in second return sum(x*y x, y in zip(hhmmss, (60*60, 60, 1))) features = [] # features model looks tuple(id, (hh, mm, ss)) open("features.csv") f: reader = csv.reader(f) features = list(reader) photos = [] # photos model looks tuple(filename, (hh, mm, ss)) open("photos.csv) f: reader = csv.reader(f) photos = list(reader) feature in features: photo in photos: # convert hh, mm, ss seconds , find within 2 min (60s * 2) # .. todo:: instead of nested loops, use filter() if abs(hmstoseconds((feature[1]) - hmstoseconds(photo[1])) <=(60 * 2): # photo taken within 2 min of feature <here, write photo> in order make more maintainable/readable, use namedtuples better represent data models:
import csv collections import namedtumple # model definitions readability/maintainence # if order of indices changes or add more fields, need # change them directly here instead of tracking indexes everywhere feature = namedtuple("feature", "id, date") photo = namedtuple("photo", "file, date") def hmstoseconds(hhmmss): # 60 * 60 seconds in hour, 60 seconds in min, 1 second in second return sum(x*y x, y in zip(hhmmss, (60*60, 60, 1))) def within_two_min(date1, date2): # convert hh, mm, ss seconds both dates # return whether absolute difference between them within 2 min (60s * 2) return abs(hmstoseconds(date1) - hmstoseconds(date2)) <= 60 * 2 if __name__ == '__main__': # using main here means avoid nasty global variables # , execute code when file run directly features = [] open("features.csv") f: reader = csv.reader(f) features = [feature(f) f in reader] photos = [] open("photos.csv) f: reader = csv.reader(f) photos = [photo(p) p in reader] feature in features: photo in photos: # .. todo:: instead of nested loops, use filter() if within_two_min(feature.date, photo.date): <here, write photo> hopefully gets moving in right direction. don't understand trying , j , first/second "write_picture" stuff, hoping understand better scope , access in python.
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