#Db browser for sqlite export to db code#

#Db browser for sqlite export to db code#

We now need to establish a cursor object, which is a tool that executes SQL code against the database of interest. Cool! But wait…how do we actually run the SQL code that will create the data tables? Glad you asked. db_conn is also pointing to the superstore.db database and can be thought of as an interface for working with this database. The newly created superstore.db file is an empty SQLite database at this point (i.e., it has no tables). When this code above is executed, a new file named superstore.db will be created in the data directory (assuming superstore.db does not already exist in this directory). We can initiate a new SQLite database connection object and assign this object to a variable. This is a lightweight SQL database engine that can be used to create databases stored as files on one’s personal computer.

There are multiple relational database products available and the specific product we will use here is SQLite. Reading The Data In Pythonįirst, if you have not installed the xlrd package using condaor pip, do so before starting a Python session, or else you will encounter the following error when trying to read in the Excel file (even with pandas installed). This dataset is stored as an Excel workbook and contains example sales transaction data stored across the following four sheets: sales, orders, customers, and products. The example in this post uses data from the Superstore-Sales dataset, which can be found here. With that thought in mind, this post moves through an example using Python to transform an Excel spreadsheet into a database that can be queried using Structured Query Language (SQL). In this way, a relational database is not totally dissimilar from an Excel workbook with related datasets stored across multiple worksheets. If this doesn’t work, you may need to use a different compression utility.Transforming spreadsheets into queryable database tables IntroductionĪ relational database is a collection of data tables - sets of rows and columns that store individual pieces of data - that can be connected to each other. This may or may not work depending on your system. So the file created in the earlier example could be reconstructed using the zcat utility. The zcat utility allows you to view the contents of a compressed file without actually uncompressing it. You can reconstruct the database with zcat.

If you don’t do this, you’ll need to include the path in the backup file. I simply opened a new terminal window and ran that command.Īctually, I navigated to the backup folder first. In other words, I didn’t connect to SQLite before running this command. If your database is large and contains a lot of data, you might be better off creating a compressed backup file. All tables have been created and all data has been inserted. The database has been reconstructed from the. Now that you’re in SQLite, you can read the contents of the backup file. sql backup file, you can reconstruct the whole database by simply reading that file from within SQLite.įor example, you can connect to SQLite while specifying a new database file (one that doesn’t already exist): sqlite3 Store2.dbīy specifying a database file that doesn’t exist, SQLite will create a blank database. This could have unintended consequences if you’re not careful. output, but this will direct the results of all future commands/SQL statements into the file. dump dot command, which by default, renders all database content as SQL. This simply directs the results of the next command or SQL statement into the specified file. This file will contain all the SQL statements required to reconstruct the database (including creating all tables, inserting all data, etc). The text file contains all the SQL statements required to create the tables, insert data, etc. In other words, it renders the whole database as SQL. dump command enables you to convert a whole database to a single ASCII text file.

The SQLite command line provides several methods for exporting or backing up an entire database.