import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

!pip install faker

Collecting faker
  Using cached Faker-33.1.0-py3-none-any.whl.metadata (15 kB)
Requirement already satisfied …

from ipwhois import IPWhois
from pprint import pprint

obj = IPWhois('133.1.2.5')
results = obj.lookup_whois(inc_nir=True)
pprint(results)

{'asn': '4730',
 'asn_cidr': '133.1.0.0/16',
 'asn_country_code': 'JP',
 'asn_date': '1997-03-01',
 'asn_description': 'ODINS …

import math

class AuthException(Exception):
    pass

def ip_to_long(ip_address):
    '''

    '''

    if(ip_address == '0:0:0:0:0:0:0:1'):
        ip_address = '127.0.0.1'

    ip_address_array = ip_address.split('.')

    if(len(ip_address_array) != 4):    
        raise AuthException('Invalid Ip …

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

import ipaddress

def ip_to_long(ip):
    # Convert IP string to a long integer
    return int(ipaddress.IPv4Address(ip))

# Example usage
ip = "192 …

import numpy as np
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier, export_graphviz
from sklearn.model_selection import train_test_split
import pydotplus
from IPython.display import Image

# Load the dataset
iris = load_iris()
X = iris.data
y = iris.target

# Split the dataset
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0 …

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

from sklearn.linear_model import LinearRegression
from sklearn.isotonic import IsotonicRegression
from sklearn.utils import check_random_state

n = 100
x = np.arange(n)
rs = check_random_state(0)
y …

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

from sklearn.linear_model import LinearRegression
from sklearn.isotonic import IsotonicRegression
from sklearn.utils import check_random_state

n = 100
x = np.arange(n)
rs = check_random_state(0)
y = rs.randint(-50, 50, size=(n,)) + 50. * np.log(1 + np …

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml311; pyv: 3.11.10 (main, Oct  3 2024, 07:29:13) [GCC 11.2.0]'

print(pyu.ps2("haystack-ai ollama-haystack python-dotenv"))

haystack-ai==2.8.0
ollama-haystack is not installed in the current environment.
python-dotenv==0.21.0

model_cache = {
    "test1.joblib" : {"one …

from itertools import chain

string = 'Toronto'
chain(string)

<itertools.chain at 0x108ed2ba8>

chars = chain(string)

type(chars)

itertools.chain

chars

<itertools.chain at 0x108ed2b70>

for c in chars:
    print(c)

T
o
r
o
n
t …

def get_jaccard_sim(str1, str2): 
    a = set(str1.split()) 
    b = set(str2.split())
    c = a.intersection(b)
    return float(len(c)) / (len(a) + len(b) - len(c))

content1 = "AI is our friend and it has been friendly"
content2 …