"""
from pdb import set_trace as debug
import os
import datetime
import json
from pathlib import Path
from urllib.request import urlretrieve
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.utils import formatdate
from pydsutils.generic import create_logger
logger = create_logger('scrape_and_email')
now = datetime.datetime.today()
email_subject_map = {
'http://daily.awesomeport.cn': {
'subject': u'好东西传送门 - daily - ' + now.strftime("%Y-%m-%d %H:%M:%S")
}
}
def get_email_passwd(sender: str) -> str:
"""Retrieve email pass code
pass code must be saved in JSON format: {email_address: passwd}
Args:
sender: Sender email
"""
https://towardsdatascience.com/gan-by-example-using-keras-on-tensorflow-backend-1a6d515a60d0
"""
from pdb import set_trace as debug
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
from keras.models import Sequential
from keras.layers import Dense, Activation, Flatten, Reshape, Conv2D, Conv2DTranspose, UpSampling2D
from keras.layers import LeakyReLU, Dropout, BatchNormalization
from keras.optimizers import RMSprop
from pydsutils.generic import create_logger
logger = create_logger(__name__)
class DCGAN(object):
def __init__(self, img_rows, img_cols, channel):
self.img_rows = img_rows
self.img_cols = img_cols
self.channel = channel
self.d = None # discriminator
self.g = None # generator
self.adv_model = None # adversarial model
self.d_model = None # discriminator model
def get_discrimonator(self):
return self.d
"""
Links:
https://developers.nest.com/documentation/cloud/how-to-read-data
"""
from pdb import set_trace as debug
import os
import http.client
from urllib.parse import urlparse
import sseclient
import requests
import json
from pydsutils.generic import create_logger
logger = create_logger(__name__, level="info")
def _read_client_secret(secret_file):
with open(secret_file) as f:
data = json.load(f)
return data["client_id"], data["client_secret"]
def _read_access_token(secret_file):
with open(secret_file) as f:
data = json.load(f)
return data["access_token"]
class NestCamAccess(object):
"""Time series sampling functions
"""
from pdb import set_trace as debug
import copy
import numpy as np
import pandas as pd
from sklearn.metrics import classification_report, confusion_matrix
from sklearn.model_selection import KFold
from pymlearn.metrics import clf_perf_scores
from pydsutils.generic import create_logger
logger = create_logger(__name__, 'info')
##############################################################
# Splitter's output must be a pair of train and validation sets
###############################################################
class CVSplitter(object):
def __init__(self, folds, shuffle=False):
self.folds = folds
self.shuffle = shuffle
def split(self, data):
"""Split the data into a series of train and validate sets
Args:
data: Data to be split on
Returns:
