""" 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: