def setenv():
path = Path(os.path.dirname(os.path.abspath(__file__)))
file_to_load = Path(os.path.join(path.parent.parent, ".env"))
if file_to_load.is_file():
env_file.load(file_to_load)
# Now PUBKEY, SUBKEY and PUBNUBID are defined
else:
# .env not found, assuming anv variable are defined elsewhere
pass
def main():
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'fool_articles.settings')
env_file.load()
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
raise ImportError(
"Couldn't import Django. Are you sure it's installed and "
"available on your PYTHONPATH environment variable? Did you "
"forget to activate a virtual environment?") from exc
execute_from_command_line(sys.argv)
def read(path=None):
"""return a dictionary with environment variables depending on the current directory"""
if not path:
path = os.getcwd()
result = dict()
while os.path.dirname(path) != path:
f = os.path.join(path, ".envrc")
if os.path.exists(f) or os.path.lexists(f):
vars = env_file.load(f)
result.update(vars)
path = os.path.dirname(path)
return result
native = fromstr(wkt, srid=SRID)
native.transform(API_SRID)
extent = native.extent
width = extent[2] - extent[0]
native = native.buffer(width * buffer)
return tuple(native.extent)
ROOT_URL = ""
PROJECT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
VAR_DIR = '/opt/geotrek-admin/var'
TMP_DIR = os.path.join(VAR_DIR, 'tmp')
DOT_ENV_FILE = os.path.join(VAR_DIR, 'conf/env')
if os.path.exists(DOT_ENV_FILE):
env_file.load(path=DOT_ENV_FILE)
ALLOWED_HOSTS = os.getenv('SERVER_NAME', 'localhost').split(' ')
ALLOWED_HOSTS = ['*' if host == '_' else host for host in ALLOWED_HOSTS]
CACHE_ROOT = os.path.join(VAR_DIR, 'cache')
TITLE = _("Geotrek")
DEBUG = False
TEST = 'test' in sys.argv
VERSION = __version__
ADMINS = ()
MANAGERS = ADMINS
"num_of_detected": len(faces),
"method": method
}
except KeyboardInterrupt:
sys.exit()
except:
print("An exception occurred: detect_anomaly_review", sys.exc_info()[0])
return {
"num_of_detected": -1,
"method": -1
}
env_file.load()
print(os.environ.get('DETECT_VERSION'))
mysql_helper = MysqlHelper()
reviewHandler = ReviewDetector()
offset = 0
limit = 100
while True:
mysql_helper.get_reviews(offset, limit)
count = mysql_helper.queryCursor.rowcount
if count <= 0 :
break
offset += limit
for (review_id, file_path) in mysql_helper.queryCursor:
print("=====================================================================")
faces_count = reviewHandler.detect_anomaly_review(file_path)
For more information on this file, see
https://docs.djangoproject.com/en/3.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/ref/settings/
"""
import env_file
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
try:
d = int(os.environ.get('DEBUG'))
except Exception:
env_file.load(os.path.join(BASE_DIR, '../.env.dev'))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = os.environ.get('SECRET_KEY')
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = int(os.environ.get('DEBUG', default=0))
ALLOWED_HOSTS = os.environ.get('DJANGO_ALLOWED_HOSTS').split(' ')
# Application definition
INSTALLED_APPS = [
Generated by 'django-admin startproject' using Django 3.1.4.
For more information on this file, see
https://docs.djangoproject.com/en/3.1/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.1/ref/settings/
"""
from pathlib import Path
import os
import dj_database_url
import django_heroku
import env_file
env_file.load('.env')
# Build paths inside the project like this: BASE_DIR / 'subdir'.
from django.conf.global_settings import DATABASES
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = os.getenv('SECRET_KEY')
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = os.environ.get('DEBUG')
ALLOWED_HOSTS = ['*']
"""
WSGI config for twitter_feels project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.6/howto/deployment/wsgi/
"""
import os
import env_file
env_file.load()
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "twitter_feels.settings")
# https://github.com/kennethreitz/dj-static
import dj_static
from django.conf import settings
from django.contrib.staticfiles.handlers import StaticFilesHandler as DebugHandler
class PrefixableDebugHandler(DebugHandler):
def get_base_url(self):
url = super(PrefixableDebugHandler, self).get_base_url()
if url.startswith(settings.SITE_PREFIX):
url = url[len(settings.SITE_PREFIX) - 1:]
return url
def get_response(self, request):
if request.path.startswith(settings.SITE_PREFIX):
request.path = request.path[len(settings.SITE_PREFIX) - 1:]
framework.
"""
import os
import sys
from path import path
PROJECT_ROOT = path(__file__).abspath().realpath().dirname().parent.parent
sys.path.append(PROJECT_ROOT)
# We defer to a DJANGO_SETTINGS_MODULE already in the environment. This breaks
# if running multiple sites in the same mod_wsgi process. To fix this, use
# mod_wsgi daemon mode with each site in its own daemon process, or use
# os.environ["DJANGO_SETTINGS_MODULE"] = "jajaja.settings"
os.environ['CELERY_LOADER'] = 'django'
os.environ.setdefault("DJANGO_SETTINGS_MODULE",
"message_coding.settings.production")
import env_file
env_file.load(PROJECT_ROOT / '.env')
# This application object is used by any WSGI server configured to use this
# file. This includes Django's development server, if the WSGI_APPLICATION
# setting points here.
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
# Apply WSGI middleware here.
# from helloworld.wsgi import HelloWorldApplication
# application = HelloWorldApplication(application)
#!/usr/bin/env python
import env_file
import os
os.chdir(os.path.dirname(__file__))
env_file.load()
env_file.load(".env")
env_file.load([".env", "dev.env"])
for var, value in os.environ.items():
print("%s=%s" % (var, value))
os.path.join(BASE_DIR, 'templates'),
],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
path = os.path.join(os.path.dirname(os.path.dirname(__file__)), ".env")
env_file.load(path)
SECRET_KEY = "https://www.youtube.com/channel/UCTZUTvv_1Onm-f-533Hyurw"
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql',
'NAME': os.getenv('DB_NAME'),
'USER': os.getenv('DB_USER', os.getenv('USER', 'postgres')),
'PASSWORD': os.getenv('DB_PASS', ''),
'HOST': os.getenv('DB_HOST'),
'PORT': os.getenv('DB_PORT', '5432'),
}
}
WSGI_APPLICATION = 'project.wsgi.application'
import os
import json
import env_file
from wit import Wit
"""
Running command:
python build_buckets.py
"""
"""
Load environment variables
"""
env = env_file.load(".env")
AUTH_TOKEN = os.environ.get("AUTH_TOKEN")
JSON_FILE = os.environ.get("JSON_FILE")
QUOTE_FILE = os.environ.get("QUOTE_FILE")
"""
Decode intent numbers
"""
decode = {
"intent_0": "none",
"intent_1": "anger",
"intent_2": "disgust",
"intent_3": "fear",
"intent_4": "happiness",
"intent_5": "sadness",
"intent_6": "surprise",
}
"""
Connect to WitAI client
"""
client = Wit(AUTH_TOKEN)
def main():
LabelEncoder = pp.LabelEncoder()
OneHotEncoder = pp.OneHotEncoder(sparse=False)
reload_sql_data = 1
if reload_sql_data:
print('downloading sql data...', end=' ')
env_file.load('../env')
conn = pyodbc.connect('DRIVER={};SERVER={};UID={};PWD={}'.format(
os.environ['DRIVER'], os.environ['SERVER'], os.environ['DB_USER'],
os.environ['DB_PASSWORD']))
cursor = conn.cursor()
sql_result = []
cursor.execute("EXEC [KEPServer].[dbo].[ML_Base]")
for row in cursor.fetchall():
sql_result.append(row)
np.save('data/ML_Base', sql_result, allow_pickle=True)
print('done')
print('reading data...', end=' ')
data = np.load('data/ML_Base.npy', allow_pickle=True)
data = data[data[:, 1] < 3600]
print('done')
print('discarding rows...', end=' ')
data = discard_rows_with_few_designation_copies(data, 10)
print('done')
print('normalizing fields...', end=' ')
bcn81, min_bcn81, max_bcn81 = process(data[:, 2].astype('float64'))
ord10, min_ord10, max_ord10 = process(data[:, 3].astype('float64'))
ird01, min_ird01, max_ird01 = process(data[:, 4].astype('float64'))
bcw30, min_bcw30, max_bcw30 = process(data[:, 5].astype('float64'))
bcm01, min_bcm01, max_bcm01 = process(data[:, 8].astype('float64'))
days_ago_normed, seconds_normed = get_day_and_time_of_day(data[:, 9])
onehot_station, station_categories = get_onehot_encoding(
data[:, 10], LabelEncoder, OneHotEncoder)
onehot_design, design_categories = get_onehot_encoding(
data[:, 6], LabelEncoder, OneHotEncoder)
onehot_glapp, glapp_categories = get_onehot_encoding(
data[:, 7], LabelEncoder, OneHotEncoder)
ct, min_ct, max_ct = process(data[:, 1])
print('done')
print('calculating CDF...')
CDF = get_cdf_per_designation(data[:, 0])
print('done')
print('formatting and saving...', end=' ')
source = np.concatenate(
(bcn81, ord10, ird01, bcw30, bcm01, days_ago_normed, seconds_normed,
onehot_station, onehot_design, onehot_glapp),
axis=1)
source_valid = source[CDF[:, -1] == 0]
source_train = source[CDF[:, -1] == 1]
target_valid = ct[CDF[:, -1] == 0]
target_train = ct[CDF[:, -1] == 1]
helpers = np.array([[min_bcn81, max_bcn81], [min_ord10, max_ord10],
[min_ird01, max_ird01], [min_bcw30, max_bcw30],
[min_bcm01, max_bcm01], [min_ct, max_ct],
[station_categories], [design_categories],
[glapp_categories]])
np.save('../app/data/helpers', helpers)
np.save('data/source_valid', source_valid)
np.save('data/source_train', source_train)
np.save('data/target_valid', target_valid)
np.save('data/target_train', target_train)
print('done')