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import os

import google.generativeai as genai
import mesop as me
import mesop.labs as mel


genai.configure(api_key=os.getenv("GOOLGLE_API_KEY"))

SYSTEM_INSTRUCTION = "Talk like Shakespeare."

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@contextmanager
def timer(name):
  """Context manager for timing code blocks with custom name."""
  start_time = time.time()
  yield
  end_time = time.time()
  elapsed_time = (end_time - start_time) * 1000
  print(f"{name} took {elapsed_time:.2f} ms")

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Array

• Two Sum
• Best Time to Buy and Sell Stock
• Contains Duplicate
• Product of Array Except Self
• Maximum Subarray
• Maximum Product Subarray
• Find Minimum in Rotated Sorted Array

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<p>
<details>
<summary>Click this to collapse/fold.</summary>

These details <em>remain</em> <strong>hidden</strong> until expanded.

<pre><code>PASTE LOGS HERE</code></pre>

</details>
</p>

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git checkout -B master origin/master

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conda create --name name python=3.7
conda activate name
conda deactivate

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alembic init
alembic revision --autogenerate -m "Migration comment"
alembic upgrade head

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// Constants
const test_const = 1;

// Scoped variables - use `let` for local scope
let callbacks = [];
for (let i = 0; i < 3; ++i) {
  callbacks[i] = function() { return i; };
}

// Arrow functions

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var CalendarViewType = {
  CALENDAR: 1,
  MONTH: 2,
  YEAR: 3
};

var DAYS_IN_WEEK = 7;

var MONTHS_IN_YEAR = 12;

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import csv
import numpy as np
from sklearn import cross_validation
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.feature_selection import SelectPercentile, f_classif, chi2
from sklearn.naive_bayes import MultinomialNB, BernoulliNB
from sklearn.metrics import accuracy_score, classification_report
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline