View query_comparison.shell
In [1]: data_point = WindData.objects.raw('SELECT * FROM meteo_winddata ORDER BY geom <-> ST_SetSRID(ST_MakePoint(%s, %s),4326) LIMIT 1', [foo.location.x, foo.location.y])[0] | |
DEBUG (0.282) SELECT * FROM meteo_winddata ORDER BY geom <-> ST_SetSRID(ST_MakePoint( -0.12574, 51.50853),4326) LIMIT 1; args=[-0.12574, 51.50853] | |
In [2]: data_point = WindDataPolygon.objects.get(geom__intersects = foo.location) | |
DEBUG (0.003) SELECT "meteo_winddatapolygon"."id", "meteo_winddatapolygon"."lat", "meteo_winddatapolygon"."lng", "meteo_winddatapolygon"."windspeed", "meteo_winddatapolygon"."geom" FROM "meteo_winddatapolygon" WHERE ST_Intersects("meteo_winddatapolygon"."geom", ST_GeomFromEWKB('\x0101000020e6100000f146e6913f18c0bf7784d38217c14940'::bytea)); args=(<django.contrib.gis.db.backends.postgis.adapter.PostGISAdapter object at 0x11080f810>,) |
View query.shell
data_point = WindData.objects.raw('SELECT * FROM meteo_winddata ORDER BY location <-> ST_SetSRID(ST_MakePoint(%s, %s),4326) LIMIT 1', [location.x, location.y])[0] |
View install_postgis_osx.sh
# Some good references are: | |
# http://russbrooks.com/2010/11/25/install-postgresql-9-on-os-x | |
# http://www.paolocorti.net/2008/01/30/installing-postgis-on-ubuntu/ | |
# http://postgis.refractions.net/documentation/manual-1.5/ch02.html#id2630392 | |
#1. Install PostgreSQL postgis and postgres | |
brew install postgis | |
initdb /usr/local/var/postgres | |
pg_ctl -D /usr/local/var/postgres -l /usr/local/var/postgres/server.log start |
View flask_m2m_problem.py
''' | |
This code example is a little gist example of the m2m problem | |
I am facing with flask and sqlalchemy. The purpose of this short | |
code sample is to select one or many grocery lists (List) based | |
on the grocery items (Grocery). | |
All query examples return either an empty list or all lists which contain | |
any of the items (OR selection instead of AND) | |
Below I have listed three approaches I have tried without any luck. |
View redis.config
packages: | |
yum: | |
gcc-c++: [] | |
make: [] | |
sources: | |
/home/ec2-user: http://download.redis.io/releases/redis-2.8.4.tar.gz | |
commands: | |
redis_build: | |
command: make | |
cwd: /home/ec2-user/redis-2.8.4 |
View Editable Fields with ReactJS and ES2015
### Try it out with JSBin | |
(JSBin)[http://jsbin.com/dijefajalo/edit?html,js,console,output] |
View track_celery.py
import time | |
from memory_profiler import memory_usage | |
import logging | |
celery_logger = logging.getLogger('celery') | |
def track_celery(method): | |
""" |
View celery.sh
/* Useful celery config. | |
app = Celery('tasks', | |
broker='redis://localhost:6379', | |
backend='redis://localhost:6379') | |
app.conf.update( | |
CELERY_TASK_RESULT_EXPIRES=3600, | |
CELERY_QUEUES=( | |
Queue('default', routing_key='tasks.#'), |
View keras_bidirectional_tagger.py
# Keras==1.0.6 | |
from keras.models import Sequential | |
import numpy as np | |
from keras.layers.recurrent import LSTM | |
from keras.layers.core import TimeDistributedDense, Activation | |
from keras.preprocessing.sequence import pad_sequences | |
from keras.layers.embeddings import Embedding | |
from sklearn.cross_validation import train_test_split | |
from keras.layers import Merge | |
from keras.backend import tf |
View keras_bidirectional_tagger.py
# Keras==1.0.6 | |
from keras.models import Sequential | |
import numpy as np | |
from keras.layers.recurrent import LSTM | |
from keras.layers.core import TimeDistributedDense, Activation | |
from keras.preprocessing.sequence import pad_sequences | |
from keras.layers.embeddings import Embedding | |
from sklearn.cross_validation import train_test_split | |
from keras.layers import Merge | |
from keras.backend import tf |
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