HTTP and Requests

Data too large for file format source Similar Notebooks py 1 1en 5 3 requests http py 1 1en 5 3 requests http checkpoint advanced scraping form submission 15 4 http postrequest multipleparameters 15 9 http responseformats 15 11 http redirectsandtimeout 15 1 http getbasics 6 derived outputs Copyright © Code Fetcher 2022    

Django Allauth Social Login For Pre Approved Users Only

Snippet 1  from allauth.account.adapter import DefaultAccountAdapterfrom allauth.socialaccount.adapter import DefaultSocialAccountAdapterfrom django.conf import settingsfrom django.http import HttpRequestfrom django.contrib.auth import get_user_modelfrom django.http import HttpResponsefrom allauth.exceptions import ImmediateHttpResponseclass AccountAdapter(DefaultAccountAdapter):  def is_open_for_signup(self, request: HttpRequest):      return getattr(settings, “ACCOUNT_ALLOW_REGISTRATION”, False)class SocialAccountAdapter(DefaultSocialAccountAdapter):  def pre_social_login(self, request, sociallogin):      try:          get_user_model().objects.get(      except get_user_model().DoesNotExist:       … Continue reading Django Allauth Social Login For Pre Approved Users Only

How To Change User Password Using Django Admin

Snippet 1 ‘’’We can change the password using admin or superuser. Assuming you have super useralready created. Please add following urls in your‘’’from django.contrib import adminfrom django.urls import path, includeurlpatterns = [   path(‘admin/’,,   path(”, include (‘main.urls’)),   path(‘accounts/’, include(‘django.contrib.auth.urls’)),]‘’’In your browser go to url your your superuser name and password.Then click on users.Click… Continue reading How To Change User Password Using Django Admin

Multithreading With Queue In Python 3

Snippet 1 import pandas as pdimport threadingimport timefrom multiprocessing import Queuemy_queue = Queue(maxsize=0)#Let us define our workerdef worker(my_queue): #Add some time to fill up the queue time.sleep(5) while(my_queue.qsize() > 0):      entry = my_queue.get() #Let us define our threads herenum_threads = 10threads = []try:  for i in range(num_threads):      t = threading.Thread(target=worker,args=(my_queue)      t.start()     … Continue reading Multithreading With Queue In Python 3

Sqlalchemy Create Engine

from sqlalchemy import create_engine source engine = create_engine(“sqlite:///hawaii.sqlite”) source engine = create_engine(f’sqlite:///../../../ih_final_project_DB/ih_final_project’) con = engine.connect() nombre_tabla = engine.table_names() source def db_connection(path): engine = create_engine(path) connection = engine.connect() return connection source #endpoint = ‘sqlite:///insiders_db.sqlite’ #local endpoint = ‘sqlite:////Users/Alysson/Documents/Projects/Hotel-Booking-Cancelation/data/hotels.sqlite’ #local db = create_engine(endpoint, poolclass=NullPool) connection = db.connect() source protocol = ‘postgresql’ password=ETL_config.password username=ETL_config.username host = ‘localhost’ port… Continue reading Sqlalchemy Create Engine

Regression Trees

Estimated time needed: 20 minutes In this lab you will learn how to implement regression trees using ScikitLearn. We will show what parameters are important, how to train a regression tree, and finally how to determine our regression trees accuracy. Objectives After completing this lab you will be able to: Train a Regression Tree Evaluate… Continue reading Regression Trees

This is an IPython notebook, backed by a ruby kernel.

I wrote a kernel in Ruby that adheres to the IPython messaging protocol. Then I modified IPython, with the help of minrk from #ipython, to instantiate my Ruby Kernel instead of its own Python kernel. The IPython KernelManager start the RubyKernel as a subprocess, and from that point communication occurs over ZeroMQ, exactly as if… Continue reading This is an IPython notebook, backed by a ruby kernel.

Data Profiling

In [1]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from sklearn.linear_model import LinearRegression from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import MinMaxScaler from sklearn.metrics import mean_absolute_error from sklearn.metrics import mean_absolute_percentage_error import warnings warnings.filterwarnings(‘ignore’) In [2]: df = pd.read_csv(‘Salary_Data.csv’) In [3]: df.head() Out[3]: YearsExperience Salary 0 1.1… Continue reading Data Profiling

Stable Diffusion AI Notebook (Release 2.0.0)

Instructions: Execute each cell in order to mount a Dream bot and create images from text. Once cells 1-8 were run correctly you’ll be executing a terminal in cell #9, you’ll need to enter python scripts/ command to run Dream bot. After launching dream bot, you’ll see: Dream > in terminal. Insert a command, eg.… Continue reading Stable Diffusion AI Notebook (Release 2.0.0)

Time Series Forecasting with Python (ARIMA, LSTM, Prophet)

In [1]: import numpy as np import pandas as pd import os from statsmodels.tsa.statespace.sarimax import SARIMAX from import plot_acf,plot_pacf from statsmodels.tsa.seasonal import seasonal_decompose #from pmdarima import auto_arima from sklearn.metrics import mean_squared_error from import rmse import warnings warnings.filterwarnings(“ignore”) import matplotlib.pyplot as plt %matplotlib inline In this article we will try to forecast a time series… Continue reading Time Series Forecasting with Python (ARIMA, LSTM, Prophet)