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import this

# A fun python easter egg for everyone!!

import this

# Spoiler
# import this will print the following
"""
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
"""

# Not written by me, but the code answer is by Codexel (me)
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import this

#python easter egg
import this
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import

import exportParDefaut from "nom-module";
import * as nom from "nom-module";
import { export } from "nom-module";
import { export as alias } from "nom-module";
import { export1 , export2 } from "nom-module";
import { export1 , export2 as alias2 , [...] } from "nom-module";
import exportParDefaut, { export [ , [...] ] } from "nom-module";
import exportParDefaut, * as nom from "nom-module";
import "nom-module";
import { toto , truc } from "nom-module/chemin/vers/fichier-non-exporte";
let promesse = import("nom-module");
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import

<script src="https://threejs.org/build/three.js"></script>
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import

import 'package:flutter/material.dart';
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import

import pandas as pd
aapl.to_csv('data/aapl_ohlc.csv')
df = pd.read_csv('data/aapl_ohlc.csv', header=0, index_col='Date', parse_dates=True)
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Import this

# By executing this code, you are given a poem called "The Zen of Python"
import this
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import

import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
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