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