class Employee:
    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary

    def __repr__(self):
        return repr((self.name, self.age, self.salary))

employees = [
    Employee('Peter', 21, 6),
    Employee('Kevin', 22 …

import json

class City:
    def toJSON(self):
        return json.dumps(self, default=lambda o: o.__dict__, sort_keys=True, indent=4)

me = City()
me.name = "Onur"
me.id = 1

print(me.toJSON())  

{
    "id": 1,
    "name": "Onur …

class Person:  
    """
    revisit the Person class to validate argument
    """
    def __init__(self, name, job, pay):
        self.job  = job
        self.pay  = pay
                                          # arg 0 is the self instance here
                                          # giveRaise = rangetest(..)(giveRaise)
    def giveRaise(self, percent):
        self …

import os
import urllib.parse
from urllib.parse import urlparse

class Client:
    def __init__(self, base_url, http_client):
        self.base_url = base_url
        self.http_client = http_client


def client_from_environment():
    default_port = "11434"
    ollama_host = os.getenv("OLLAMA_HOST", "")

    # Parse scheme and hostport
    if "://" in ollama_host:
        scheme, hostport = ollama_host.split("://", 1)
    else:
        scheme, hostport = "http", ollama_host

    # Adjust default …

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_template("tell me a joke about {topic}")

chain = prompt | model …

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

import pandas as pd …

# !pip install scikit-learn

import pandas as pd
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.impute import SimpleImputer

# Step 1: Create a dummy dataset
data = {
    "User": ["User1", "User1", "User1", "User2", "User2", "User3", "User3", "User4"],
    "Video": ["Video1", "Video2", "Video3", "Video1", "Video4", "Video2", "Video3", "Video4"],
    "Rating": [5, 3, 4, 4, 5, 2 …

from collections import Counter

cnt = Counter()

for word in ['Toronto', 'Montreal', 'Montreal', 'Waterloo', 'Toronto', 'Toronto']:
    cnt[word] += 1

cnt

Counter({'Montreal': 2, 'Toronto': 3, 'Waterloo': 1})

type(cnt)

collections.Counter

# https://python.langchain.com/docs/how_to/structured_output/
# https://python.langchain.com/docs/how_to/
# https://platform.openai.com/usage

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")

from typing import Optional …

import re

# precompile regex patterns
regex_entries = [
    re.compile(p)
    for p in ['awesome', 'ocean']
]

content = 'Duckduck go is awesome and it is getting better everyday'

print('Text : {!r}'.format(content))

Text : 'Duckduck go is awesome and it is getting better everyday'

for regex in regex_entries:
    print('Finding  {} -> '.format(regex.pattern …