ordigi/elodie/localstorage.py

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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)