selimslab

""" 
Machine Learning model to predict the genres of a movie from its summary 
"""
import os
import pickle
from io import StringIO

from flask import Flask, request

from sklearn.preprocessing import MultiLabelBinarizer

selimslab

import os
from flask.json import JSONEncoder
import datetime


class CustomJSONEncoder(JSONEncoder):
    "Add support for serializing time"

    def default(self, o):

selimslab

# coding: utf-8
"""
a simple concurrent web server

socket -> bind -> listen -> accept -> loop 
"""
import socket
import os 
import time
import signal

selimslab

"""
Lispy: Scheme Interpreter in Python

Peter Norvig's lis.py studied here

http://norvig.com/lispy.html

The beauty of Scheme is that the full language only needs 5 keywords and 8 syntactic forms.
In comparison, Python has 33 keywords and 110 syntactic forms,
and Java has 50 keywords and 133 syntactic forms.

selimslab

import re
import math
import operator
import logging
from collections import defaultdict, Counter
import numpy as np


class Tokenizer:
    def __init__(self, stop_words, ):

selimslab

import asyncio
import logging
import collections
import urllib.parse
from pprint import pprint
import aiohttp
import bs4


class AsyncCrawler:

selimslab

#include <stdio.h>
#include <stdlib.h>

#define STACK_MAX 256

typedef enum
{
    OBJ_INT,
    OBJ_PAIR
} ObjectType;

selimslab

#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#include <math.h>

typedef struct {
    char* key;
    char* value;
} key_value_pair;

selimslab

import time
import hashlib
import uuid
import random 
from dataclasses import dataclass
from typing import List

@dataclass
class Node:
    uid: str

selimslab

INTEGER
BOOLEAN 
TEXT
FLOAT
DOUBLE
CHARACTER(num_chars)
VARCHAR(num_chars)
DATE
DATETIME
BLOB