{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from json_buffered_reader import JSON_buffered_reader as JSON_br\n", "\n", "import settings" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* load all ingredients from the yummly dataset and merge them into a huge set" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "ingredients = []\n", "ingredient_count = {}\n", "\n", "min_count = 100" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "for recipe in JSON_br(settings.yummly_train):\n", " for ingredient in recipe['ingredients']:\n", " if ingredient in ingredient_count:\n", " ingredient_count[ingredient] += 1\n", " if ingredient_count[ingredient] == min_count:\n", " ingredients.append(ingredient)\n", " else:\n", " ingredient_count[ingredient] = 1\n", " \n", " " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "all_ingredients_set = set(ingredients)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "648" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(all_ingredients_set)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* save to python file:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "filename = 'cooking_ingredients.py'" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "file_obj = open(filename,'w')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "file_obj.write(\"#!/usr/bin/env python3\\n\")\n", "\n", "file_obj.write(\"\\ningredients = [\\n\")\n", "\n", "\n", "first_item = ingredients[0]\n", "\n", "file_obj.write(' \"' + first_item + '\"')\n", "for ingredient in ingredients[1:]:\n", " file_obj.write(',\\n \"' + ingredient + '\"')\n", "\n", "file_obj.write(\"\\n]\\n\")\n", "\n", "file_obj.close()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }