import hashlib import json from math import radians, cos, sqrt import os import sys from elodie import constants class Db(object): def __init__(self): # verify that the application directory (~/.elodie) exists, # else create it if not os.path.exists(constants.application_directory): os.makedirs(constants.application_directory) # If the hash db doesn't exist we create it. # Otherwise we only open for reading if not os.path.isfile(constants.hash_db): with open(constants.hash_db, 'a'): os.utime(constants.hash_db, None) self.hash_db = {} # We know from above that this file exists so we open it # for reading only. with open(constants.hash_db, 'r') as f: try: self.hash_db = json.load(f) except ValueError: pass # If the location db doesn't exist we create it. # Otherwise we only open for reading if not os.path.isfile(constants.location_db): with open(constants.location_db, 'a'): os.utime(constants.location_db, None) self.location_db = [] # We know from above that this file exists so we open it # for reading only. with open(constants.location_db, 'r') as f: try: self.location_db = json.load(f) except ValueError: pass def add_hash(self, key, value, write=False): self.hash_db[key] = value if(write is True): self.update_hash_db() def check_hash(self, key): return key in self.hash_db def get_hash(self, key): if(self.check_hash(key) is True): return self.hash_db[key] return None def update_hash_db(self): with open(constants.hash_db, 'w') as f: json.dump(self.hash_db, f) """ http://stackoverflow.com/a/3431835/1318758 """ def checksum(self, file_path, blocksize=65536): hasher = hashlib.sha256() with open(file_path, 'r') as f: buf = f.read(blocksize) while len(buf) > 0: hasher.update(buf) buf = f.read(blocksize) return hasher.hexdigest() return None # Location database # Currently quite simple just a list of long/lat pairs with a name # If it gets many entryes a lookup might takt to long and a better # structure might be needed. Some speed up ideas: # - Sort it and inter-half method can be used # - Use integer part of long or lat as key to get a lower search list # - Cache a smal number of lookups, photos is likey to be taken i clusters # around a spot during import. def add_location(self, latitude, longitude, place, write=False): data = {} data['lat'] = latitude data['long'] = longitude data['name'] = place self.location_db.append(data) if(write is True): self.update_location_db() def get_location_name(self, latitude, longitude, threshold_m): last_d = sys.maxint name = None for data in self.location_db: # As threshold is quite smal use simple math # From http://stackoverflow.com/questions/15736995/how-can-i-quickly-estimate-the-distance-between-two-latitude-longitude-points # noqa # convert decimal degrees to radians lon1, lat1, lon2, lat2 = map( radians, [longitude, latitude, data['long'], data['lat']] ) R = 6371000 # radius of the earth in m x = (lon2 - lon1) * cos(0.5*(lat2+lat1)) y = lat2 - lat1 d = R * sqrt(x*x + y*y) # Use if closer then threshold_km reuse lookup if(d <= threshold_m and d < last_d): name = data['name'] last_d = d return name def get_location_coordinates(self, name): for data in self.location_db: if data['name'] == name: return (data['lat'], data['long']) return None def update_location_db(self): with open(constants.location_db, 'w') as f: json.dump(self.location_db, f)