Alright, let me tell you about this thing I was messing around with called “jared odrick.” It’s not some fancy framework or anything, just a little project I cooked up to scratch an itch.
It all started when I was trying to wrangle a bunch of data from different sources. You know how it is – one source gives you JSON, another spits out CSV, and yet another insists on some ancient XML format. Dealing with that mess was eating up way too much time, so I thought, “There’s gotta be a better way.”
So, I started sketching out some ideas. I wanted something that could:
- Take data in various formats as input.
- Clean it up and transform it into a consistent structure.
- Let me easily query and manipulate the data.
- Spit it out in whatever format I needed.
First, I grabbed Python. It’s my go-to for quick and dirty data stuff. I started with a simple class that could load data from a file. Something like this:
Then came the fun part – figuring out how to handle different file formats. I ended up using libraries like json, csv, and to parse the data. I wrapped each of these in a separate function that would take a file path and return a dictionary or a list of dictionaries. It was pretty basic stuff, but it worked.
Next up, data transformation. This was where things got a little more interesting. I wanted to be able to define a set of rules for cleaning and transforming the data. For example, I might want to:
- Rename certain fields.
- Convert data types (e.g., string to integer).
- Remove unwanted characters.
- Combine multiple fields into one.
I ended up creating a simple DSL (Domain Specific Language) using Python dictionaries. It looked something like this:
I wrote a function that would take this transformation map and apply it to the data. It iterated through each rule in the map and performed the corresponding transformation. It was a bit clunky, but it got the job done.
After that, I needed a way to query the data. I didn’t want to pull in a full-blown database, so I decided to use Python’s built-in filter and map functions. I created a simple query language that allowed me to specify conditions for filtering the data. For example:
I implemented a function that would parse this query string and generate a Python lambda function that could be used with filter. Again, it was pretty basic, but it allowed me to quickly filter the data based on certain criteria.
Finally, I added the ability to output the data in different formats. I created functions that would convert the data back into JSON, CSV, or XML. I also added the ability to write the data to a file.
After a few weeks of hacking, I had a working prototype. It wasn’t pretty, but it solved my original problem. I could now load data from different sources, clean it up, transform it, query it, and output it in whatever format I needed. It saved me a ton of time and made my life a lot easier.
Of course, there’s still a lot of room for improvement. The DSL could be more expressive, the query language could be more powerful, and the whole thing could be more efficient. But for now, it’s good enough. It’s a little piece of code that I’m proud of.
So yeah, that’s the story of “jared odrick.” It’s not gonna change the world, but it helps me get my work done. And that’s all that matters, right?
