I recently worked on an ETL project in Python. Among other things, the script had to process JSON files that users dropped into a specific folder.
As this was a sensitive application, it was important to validate the script by submitting fake JSON files, but also to ensure the quality of the files received.
For the fake files, I used a tool like the Faker library for Python.
Exactly like my SQL - Formatting tool, it's always useful to have a tool in your favourites that lets you copy/paste a JSON character string and display it as a tree-view with or without code folding feature.
I use it quite regularly when I'm writing a JSON string and I want to check that there are no syntax errors (lint) or, on the other hand, and for example, when I call an API that returns JSON and I want to analyse the code received. In these cases, the collapse functionality comes in very handy.
When faced with legacy code, it is often useful to reformat it to make it readable. And from there, the study of the code can begin.
There are plenty of reformatting tools for json, php, javascript and other languages, but far fewer for a query written in SQL.
Just copy/paste SELECT LAT_N, CITY, TEMP_F FROM STATS, STATION WHERE MONTH = 7 AND STATS.ID = STATION.ID ORDER BY TEMP_F in the tool and get
SELECT
LAT_N,
CITY,
TEMP_F
FROM
STATS,
STATION
WHERE
MONTH = 7
AND STATS.ID = STATION.ID
ORDER BY
TEMP_F
If you are developing your own API (whatever the language) or if you need to consume some, Postman can be really handy.
Calling an API and getting the response is one thing, quite simple in fact, but a nice feature of Postman is the ability to validate the response like making sure the returned type is, f.i. application/json, the HTTP status code is 200, the response body is a JSON object (or an XML string), that the body contains some required information and so on.
You can also validate the response against a given schema to make sure the structure is well the one expected.
In this article, we'll use Postman like a unit test tool i.e. run checks on our own API and make a lot of assertions. This is improving the quality of your code by highlighting potential errors and, for any refactoring you'll do in the future, by running the tests again, you'll make sure you've not broken something; that you don't have any regression. Make sure you've not broken an API when you upgrade some code is gold.
Imagine you're a web developer or you work in a web agency and you'd like to keep an eye on the sites you've developed for your clients, free of charge. Are these sites online now, or are they down?
This work is carried out by site monitoring platforms. Could you install one on your computer? Of course!