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The complete Python code that I am using in this tutorial can be downloaded from my GitHub repository: The sqlite3 that we will be using throughout this tutorial is part of the Python Standard Library and is a nice and easy interface to SQLite databases: There are no server processes involved, no configurations required, and no other obstacles we have to worry about.
Conveniently, a new database file. In the following section, we will take a look at some example code of how to create a new SQLite database files with tables for storing some data. To round up this section about connecting to a SQLite database file, there are two more operations that are worth mentioning. If we are finished with our operations on the database file, we have to close the connection via the.
And if we performed any operation on the database other than sending queries, we need to commit those changes via the. Let us have a look at some example code to create a new SQLite database file with two tables: Download the script at: Throughout this article, I will use this tool to provide screenshots of the database structures that we created below the corresponding code sections.
Using the code above, we created a new. Looking at the table above, You might have noticed that SQLite 3 has no designated Boolean data type. Every table can only have max. But more on column indexing in the a later section. If we want to add a new column to an existing SQLite database table, we can either leave the cells for each row empty NULL value , or we can set a default value for each cell, which is pretty convenient for certain applications.
Inserting and updating rows into an existing SQLite database table - next to sending queries - is probably the most common database operation. Unfortunately, this convenient syntax is not supported by the more compact SQLite database implementation that we are using here. However, there are some workarounds.
But let us first have a look at the example code:. Just like hashtable-datastructures, indexes function as direct pointers to our data in a table for a particular column i.
The downside of indexes is that every row value in the column must be unique. However, it is recommended and pretty useful to index certain columns if possible, since it rewards us with a significant performance gain for the data retrieval. The example code below shows how to add such an unique index to an existing column in an SQLite database table.
And if we should decide to insert non-unique values into a indexed column later, there is also a convenient way to drop the index, which is also shown in the code below. The code below illustrates how we can retrieve row entries for all or some columns if they match certain criteria. The print output for the 5 different cases shown in the code above would look like this note that we only have a table with 1 row here: This is fine if we just want to use the database for ourselves.
However, this leaves our database vulnerable to injection attacks. For example, if our database would be part of a web application, it would allow hackers to directly communicate with the database in order to bypass login and password verification and steal data. In order to prevent this, it is recommended to use? For example, instead of using. However, the problem with this approach is that it would only work for values, not for column or table names.
So what are we supposed to do with the rest of the string if we want to protect ourselves from injection attacks? The easy solution would be to refrain from using variables in SQLite queries whenever possible, and if it cannot be avoided, we would want to use a function that strips all non-alphanumerical characters from the stored content of the variable, e.
The screenshot below shows the print outputs of the code that we used to query for entries that lie between a specified date interval using.
In the previous two sections we have seen how we query SQLite databases for data contents. Now let us have a look at how we retrieve its metadata here: If we would print the contents of the variable names now, the output would look like this:.
I hope we covered most of the basics about SQLite database operations in the previous sections, and by now we should be well equipped to get some serious work done using SQLite in Python. I really hope this tutorial was helpful to you to get started with SQLite database operations via Python. I have been using the sqlite3 module a lot recently, and it has found its way into most of my programs for larger data analyses.
If you are interested, you can check it out at: I am looking forward to your opinions and ideas, and I hope I can improve and extend this tutorial in future. Retrieving column names Printing a database summary Conclusion The complete Python code that I am using in this tutorial can be downloaded from my GitHub repository: DATE 'now' returns current date, e.