I have created a database in the Robo3T and the connection is also developed between django and MongoDB. I used Djongo to develop the connection between django and MongoDB. I am using MongoDB as a database for the first time. For example, calculating the average grade per restaurant and rank them with SQL will be fun.I am trying to develop a website in Django. Once the data is loaded into the postgres, you can use it to analyse the data. Pg_load_table ( './grades.csv', 'ades' ) Pg_load_table ( './restaurants.csv', 'mongodb.restaurants' ) # (4-1) Transform data into a structured tablesĬreate_table (rest_records, rest_headers, './restaurants.csv' )Ĭreate_table (grades_records, grades_headers, './grades.csv' )
# (4) Retrieve all data from the restaurants collection Print ( 'Total Record for the collection: ' + str (restaurants. # (3) Choose the collection and create Collection Object # (2) Choose database and create the db object
#Robo 3t django install#
The user was then added to the user group postgres which is the default credential comes with postgres when you install it.Ĭlient = MongoClient ( 'mongodb://admin: :27017/test' ) I created a database called mydatahack and credentials with username as mydatahack and password as Password1. I have Postgres installed on my local computer. You can check documentations here for further details. For example, using copy_from() will not ignore double quotes when you load data. Subscribe to PRO for just 10 / month and convert up to 50 MB (and unlock some useful features).
#Robo 3t django for free#
Upload your JSON file by clicking the blue button (or paste your JSON text / URL into the textbox) Convert up to 1 MB for free every 24 hours. I am using the copy_expert function because it has a better control. Convert JSON to CSV using this online tool. String + = quote + record + quote + delimiter String + = quote + record + quote + ' \n'
format (file_path ) )ĭef format_list ( list, length, delimiter, quote ): Print ( 'CSV file successfully created: '. write (format_list (record, row_len, ',', '"' ) ) "Take a list of records and headers and generate csv"į = open (file_path, 'w', encoding = 'utf-8' )į. For Python 2, you can set default encoding as below.ĭef create_table (records, headers, file_path ): Double quotes are important because some records contain comma. (3) Create a csv file for each table with double quotes. 'address_street', 'address_zipcode', 'address_borough', 'cuisine', 'name' ,\ Headers = [ 'id', 'address_building', 'address_coord1', 'address_coord2' ,\ Take the query outcome and convert to a list and return it. The key point for Windows installation is to create a data directory to set up the environment. (1) Donwload the community server from MongoDB Download Center and install it.
#Robo 3t django how to#
In this post, I will use the official MongoDB example dataset and show you how to grab data from MongoDB, convert it into structured tables and load them to Postgres database.įirst of all, let’s install MongoDB, create the test database and user credential with the right privilege and upload an example data set, restaurants into the test.
#Robo 3t django driver#
If you are having trouble with connection like authentication, Conncet to MongoDB via the Python Driver from the official website has a detailed examples and explanations that help you to troubleshoot your code.
I recommend PyMongo documentation for getting stated. The pymongo package makes it really easy for us to use Python with MongoDB. Here are two useful MongoDB tutorials for beginners: Learn Mongo DB from Tutorial Point and Getting Started with MongoDB from the official website. Once you understand the way MongoDB stores data, all you need to do is to connect to the database, query the data and convert it into a structured file with the same way as we do with JSON files. Data is stored in MongoDB as BSON, which looks like JSON files. MongoDB is one of the most popular no SQL databases used as a backend database for web and mobile applications.
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