import matplotlib.pyplot as plt

x = [1, 2, 3, 4]

y = [2, 4, 9, 16]

x, y

([1, 2, 3, 4], [2, 4, 9, 16])

plt.plot(x, y, 'ro')
plt.axis([0, 10, 0, 20 …

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]

y = [1, 4, 9, 16]

z = [1, 8, 27, 64]

x, y, z

([1, 2, 3, 4], [1, 4, 9, 16], [1, 8 …

import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String

engine = create_engine('sqlite:///:memory:', echo=True)
Base = declarative_base()

/tmp/ipykernel_4126507/3500228846.py:2: MovedIn20Warning: The ``declarative_base()`` function is now available as sqlalchemy.orm.declarative_base(). (deprecated since: 2.0) (Background on SQLAlchemy 2 …

from gensim import corpora, models, similarities

corpus = [
    [(0, 1.0), (1, 1.0), (2, 1.0)],
    [(2, 1.0), (3, 1.0), (4, 1.0), (5, 1.0), (6, 1.0), (8, 1.0)],
    [(1, 1 …

import nltk.collocations
import nltk.corpus
import collections

bgm    = nltk.collocations.BigramAssocMeasures()
finder = nltk.collocations.BigramCollocationFinder.from_words(nltk.corpus.brown.words())
scored = finder.score_ngrams( bgm.likelihood_ratio  )

# Group bigrams by first word in bigram.                                        
prefix_keys = collections.defaultdict(list)
for key …

import nltk.collocations
import nltk.corpus
import collections

# import nltk
# nltk.download('brown')

bgm    = nltk.collocations.BigramAssocMeasures()
finder = nltk.collocations.BigramCollocationFinder.from_words(nltk.corpus.brown.words())
scored = finder.score_ngrams( bgm.likelihood_ratio  )

# Group bigrams by first word in bigram.                                        
prefix_keys = collections.defaultdict(list)
for key, scores in scored:
   prefix_keys[key[0 …

def binary_search(lys, val):  
    first = 0
    last = len(lys)-1
    index = -1
    while (first <= last) and (index == -1):
        mid = (first+last)//2
        if lys[mid] == val:
            index = mid
        else:
            if val<lys[mid]:
                last = mid -1 …

!python --version

Python 3.12.4

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")

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "Get the current weather in a given location",
            "parameters …

!python --version

Python 3.12.4

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")

# https://python.langchain.com/docs/how_to/binding/

from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import …

from bokeh.plotting import figure, output_file, show
from bokeh.io import output_notebook
from bokeh.models import ColumnDataSource

# Set Bokeh output to notebook
output_notebook()