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from scapy.all import *
from tqdm import tqdm
import pandas as pd

raw = rdpcap(mypcap.pcap)
ip_data = []
tcp_data = []

for frame in tqdm(raw, desc='Converting'):
    if 'options' in frame['IP'].fields: del frame['IP'].fields['options']

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"""Read pdf files and extract tabular data."""
from tabula import read_pdf


def file_to_dataframe(file_path):
    """Read and save tables from pdf."""
    tables = read_pdf(file_path, multiple_tables=True)
    # extract and format potency table
    potency_table = tables[0]
    potency_table = potency_table.drop(potency_table.index[[0, 1]])

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"""Save pdf files from lab website."""

from bs4 import BeautifulSoup
from bs4.dammit import EncodingDetector
import requests
from tqdm import tqdm

# connect to the webpage
url = 'https://forwardgro.com/testresults/'
resp = requests.get(url)

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import numpy as np
from keras.datasets import mnist
from keras.layers import Input, Dense, Reshape, Flatten, Dropout
from keras.layers import BatchNormalization
from keras.layers.advanced_activations import LeakyReLU
from keras.models import Sequential
from keras.optimizers import Adam
from logger import logger
import matplotlib.pyplot as plt

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import numpy as np
import pandas as pd
import requests
from sklearn.linear_model import BayesianRidge

#load market data
market_data = get_market_data('BTC/USD')

#shift target variable one day back 
#in order to train model to predict one day into future