CSV to JSON with Python for MySQL upload

Admittedly, I have jumped head-first into the world of JSON within MySQL. I also have a thing for Python, of which I find myself using a lot of in my day job as Pipeline Survey Data Analyst. CSV’s are everywhere: in data at work, on the web, even in my personal life (as you’ll see). Loading CSV data into MySQL is nothing new to anyone working with either of the technologies. As a matter of fact, there are several ways you can get your CSV data into MySQL. I wrote the post, Pyodbc SQL CRUD – Create: Examples with MySQL, you can read where I cover loading CSV data using the Python pyodbc module. But, how about type-casting CSV data – which typically are strings – to a compatible JSON data type? Then push the JSON data to a MySQL JSON column? And that my friends, is the focus of this post. Turns out, Python’s csv and json standard libraries makes the whole process virtually painless. Keep reading and see a simple script I devised…

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CREATE TABLE using Python in the MySQL Shell – with examples.

Not only are basic SQL CRUD operations supported in MySQL Shell Python mode, but you can also execute DDL commands such as CREATE TABLE. While there is not a specific create_table() method per se, there is a sql() method for this – and other – types of commands that don’t have an individual method such as those for each of the individual CRUD operations. Keep reading to see a simple example use of the sql() method…

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MySQL Shell CRUD with Python: Create – with examples.

I honestly feel like MySQL hit a home run with the release of version 8. Having included so many fantastic features, it is hard to single one out above the others. However, there is one – besides Window Functions – that is really a game-changer. To be exact, the one actually makes 3 (whatever kind of sense that makes). I am talking about the MySQL Shell, the Document Store, and the X DevAPI. The focus of this post is on the Shell itself. What is it about the Shell that intrigues me? I’m sure your curiosity is piqued so keep reading to find out about the functionality you simply cannot ignore… [Keep reading for more SQL database and Python-centric content >>>]

Pyodbc SQL CRUD – Create: Examples with MySQL

In my day job as a Pipeline Survey Data Analyst, I lean heavily on the Python pyodbc package for interactions with an Access Database. To gain more knowledge and better proficiency with pyodbc, I thought to use it with one of my favorite open-source databases, MySQL. Having recently written a 4-part series on SQL CRUD operations using MySQL, this post is a continuation of sorts. However, Create operations are executed with the pyodbc driver instead of native SQL

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Pyodbc meta-data methods you should be using – interactions with MySQL.

In my day job, I have recently begun to leverage the Python pyodbc package for MS Access related database tasks. Working with any database, it goes without saying that understanding the schema is paramount. What tables are present? What are their columns and types? How are they related? Among the many methods pyodbc provides, to answer these types of questions, it provides 3 ‘meta-data’ methods you simply cannot live without. Want to know which ones they are? Keep reading…

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