Using Databases with Python – A Must Know

It is a good idea to understand the importance of using databases with Python while learning Python. If you are analyzing data, pulling data from over the network, then it makes sense to store that data in a database. You can then set up a process of pulling data from the database as you need it. Overall, it can speed up your workflow.

A good database system to learn using databases with Python is DB Browser for SQLite.

using databases with python

Relational databases comprise a whole sub-field of computer science. They are relevant because you can pull out an entry from huge amounts of data in a split-second. It would take you much longer if you had to read through the data.

relational databases

You can look no further than Oracle to understand the relevance of relational databases. The majority of their revenue comes from database products.

The underlying foundation of databases is rooted in mathematics. This is present in the terminology that experts use to describe databases.

database terminology

The idea behind databases is that you model data at a connection point.

database model

However, programmers tend to think of it in terms of rows and columns.

Typically, when you make a table, the first row becomes metadata for the table. You often use the first row to title what each column is for. Therefore, you can refer to this first row as the schema for the table. It sets the rules for each column with regard to what goes there, for example, a string, an integer, etc.

In the early 1960s, the database pioneers figured out ways to quickly retrieve data from random access memory, without having to go through the data sequentially. However, databases were very complex. As a result, a new component of internet architecture evolved called the database application. This allows you, the programmer, to talk with the database, by way of the database application. At this point, an industry standard was desired for the language for the API between a database and its application. The name of the language the industry agreed on was SQL (Structured Query Language).

metadata

SQL is a great language, but it depends on the data being clean . The nice thing about Python, is it can deal really well with unstructured data. So together, Python and SQL, you have a powerful combination.

SQL

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