and so on we're only interested in the name and ingredients list sample recipe is shown in the following listing listing sample json recipe "_id"$oid" cc cc db }"name"drop biscuits and sausage gravy""ingredients"biscuits\ cups all-purpose flour\ tablespoons baking powder\ / teaspoon salt\ stick ( / cupcold buttercut into pieces\ cup butermilk\ sausage gravy\ pound breakfast sausagehot or mild\ / cup all-purpose flour\ cups whole milk\ / teaspoon seasoned salt\ teaspoons black peppermore to taste""url""image"bisgrav jpg""ts"$date }"cooktime"pt ""source"thepioneerwoman""recipeyield" ""datepublished"""preptime"pt ""description"late saturday afternoonafter marlboro man had returned home with the soccer-playing girlsand had returned home with the because we're dealing with text data herethe problem is two-foldfirstpreparing the textual data as described in the text mining thenonce the data is thoroughly cleansedit can be used to produce recipe recommendations based on network of ingredients this doesn' focus on the text data preparation because this is described elsewhereso we'll allow ourselves the luxury of shortcut during the upcoming data preparation step data preparation we now have two data files at our disposaland we need to combine them into one graph database the "dirtyrecipes data poses problem that we can address using our clean ingredients list and the use of the search engine and nosql database elasticsearch we already relied on elasticsearch in previous and now it will clean the recipe data for us implicitly when it creates an index we can then search this data to link each ingredient to every recipe in which it occurs we could clean the text data using pure pythonas we did in the text mining but this shows it' good to be aware of the strong points of each nosql databasedon' pin yourself to single technologybut use them together to the benefit of the project let' start by entering our recipe data into elasticsearch if you don' understand what' happeningplease check the case study of again and it should become clear make sure to turn on your local elasticsearch instance and activate python environment with the elasticsearch module installed before running the code