Python has numerous ways of outputting and storing data. Recently, I investigated using shelves in Python. This is a way to store indexed data that uses command syntax similar to that of Python dictionaries, but I found it too time consuming to create shelves of large datasets. Searching for a way to efficiently build databases in Python, I came across the SQL functionality. The library sqlite3 is an indispensable way to create databases in Python. This package permits Python users to create and query large databases using syntax borrowed from SQL. SQL stands for Structured Query Language and is used for managing data held in a relational database management system. The sqlite3 is a nonstandard variant of SQL query language that is compliant with the DB-API 2.0 specification. As a quick reference, I thought I would create an example script that could be used to build a SQL database using the Python programming language. Below is a simple tutorial to follow that hopefully is useful for learning how to use the sqlite3 package.
A repository of programs, scripts, and tips essential to
genetic epidemiology, statistical genetics, and bioinformatics
Welcome to the Genome Toolbox! I am glad you navigated to the blog and hope you find the contents useful and insightful for your genomic needs. If you find any of the entries particularly helpful, be sure to click the +1 button on the bottom of the post and share with your colleagues. Your input is encouraged, so if you have comments or are aware of more efficient tools not included in a post, I would love to hear from you. Enjoy your time browsing through the Toolbox.
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