Contributing to Tryceratops

I read about a project called Tryceratops on Twitter when it was tweeted about by Jeff Triplet

I checked it out and it seemed interesting. I decided to use it on my simplest Django project just to give it a test drive running this command:

tryceratops .

and got this result:

Done processing! 🦖✨
Processed 16 files
Found 0 violations
Failed to process 1 files
Skipped 2340 files

This is nice, but what is the file that failed to process?

This left me with two optons:

  1. Complain that this awesome tool created by someone didn't do the thing I thought it needed to do


  1. Submit an issue to the project and offer to help.

I went with option 2 😀

My initial commit was made in a pretty naive way. It did the job, but not in the best way for maintainability. I had a really great exchange with the maintaner Guilherme Latrova about the change that was made and he helped to direct me in a different direction.

The biggest thing I learned while working on this project (for Python at least) was the logging library. Specifically I learned how to add:

  • a formatter
  • a handler
  • a logger

For my change, I added a simple format with a verbose handler in a custom logger. It looked something like this:

The formatter:

"simple": {
    "format": "%(message)s",

The handler:

"verbose_output": {
    "class": "logging.StreamHandler",
    "level": "DEBUG",
    "formatter": "simple",
    "stream": "ext://sys.stdout",

The logger:

"loggers": {
    "tryceratops": {
        "level": "INFO",
        "handlers": [

This allows the verbose flag to output the message to Standard Out and give and INFO level of detail.

Because of what I learned, I've started using the logging library on some of my work projects where I had tried to roll my own logging tool. I should have known there was a logging tool in the Standard Library BEFORE I tried to roll me own 🤦🏻‍♂️

The other thing I (kind of) learned how to do was to squash my commits. I had never had a need (or desire?) to squash commits before, but the commit message is what Guilherme uses to generate the change log. So, with his guidance and help I tried my best to squash those commits. Although in the end he had to do it (still not entiredly sure what I did wrong) I was exposed to the idea of squashing commits and why they might be done. A win-win!

The best part about this entire experience was getting to work with Guilherme Latrova. He was super helpful and patient and had great advice without telling me what to do. The more I work within the Python ecosystem the more I'm just blown away by just how friendly and helpful everyone is and it's what make me want to do these kinds of projects.

If you haven't had a chance to work on an open source project, I highly recommend it. It's a great chance to learn and to meet new people.

Contributing to django-sql-dashboard

Last Saturday (July 3rd) while on vacation, I dubbed it “Security update Saturday”. I took the opportunity to review all of the GitHub bot alerts about out of date packages, and make the updates I needed to.

This included updated django-sql-dashboard to version 1.0 … which I was really excited about doing. It included two things I was eager to see:

  1. Implemented a new column cog menu, with options for sorting, counting distinct items and counting by values. #57
  2. Admin change list view now only shows dashboards the user has permission to edit. Thanks, Atul Varma. #130

I made the updates on my site using my normal workflow:

  1. Make the change locally on my MacBook Pro
  2. Run the tests
  3. Push to UAT
  4. Push to PROD

The next day, on July 4th, I got the following error message via my error logging:

Internal Server Error: /dashboard/games-seen-in-person/

ProgrammingError at /dashboard/games-seen-in-person/
could not find array type for data type information_schema.sql_identifier

So I copied the url /dashboard/games-seen-in-person/ to see if I could replicate the issue as an authenticated user and sure enough, I got a 500 Server error.

Troubleshooting process

The first thing I did was to fire up the local version and check the url there. Oddly enough, it worked without issue.

OK … well that’s odd. What are the differences between the local version and the uat / prod version?

The local version is running on macOS 10.15.7 while the uat / prod versions are running Ubuntu 18.04. That could be one source of the issue.

The local version is running Postgres 13.2 while the uat / prod versions are running Postgres 10.17

OK, two differences. Since the error is could not find array type for data type information_schema.sql_identifier I’m going to start with taking a look at the differences on the Postgres versions.

First, I looked at the Change Log to see what changed between version 0.16 and version 1.0. Nothing jumped out at me, so I looked at the diff between several files between the two versions looking specifically for information_schema.sql_identifier which didn’t bring up anything.

Next I checked for either information_schema or sql_identifier and found a chance in the file. On line 151 (version 0.16) this change was made:

string_agg(column_name, ', ' order by ordinal_position) as columns

to this:

array_to_json(array_agg(column_name order by ordinal_position)) as columns

Next, I extracted the entire SQL statement from the file to run in Postgres on the UAT server

            with visible_tables as (
              select table_name
                from information_schema.tables
                where table_schema = 'public'
                order by table_name
            reserved_keywords as (
              select word
                from pg_get_keywords()
                where catcode = 'R'
              array_to_json(array_agg(column_name order by ordinal_position)) as columns
              visible_tables on
              information_schema.columns.table_name = visible_tables.table_name
              information_schema.columns.table_schema = 'public'
            group by
            order by

Running this generated the same error I was seeing from the logs!

Next, I picked apart the various select statements, testing each one to see what failed, and ended on this one:

select information_schema.columns.table_name,
array_to_json(array_agg(column_name order by ordinal_position)) as columns
from information_schema.columns

Which generated the same error message. Great!

In order to determine how to proceed next I googled sql_identifier to see what it was. Turns out it’s a field type in Postgres! (I’ve been working in MSSQL for more than 10 years and as far as I know, this isn’t a field type over there, so I learned something)

Further, there were changes made to that field type in Postgres 12!

OK, since there were changes made to that afield type in Postgres 12, I’ll probably need to cast the field to another field type that won’t fail.

That led me to try this:

select information_schema.columns.table_name,
array_to_json(array_agg(cast(column_name as text) order by ordinal_position)) as columns
from information_schema.columns

Which returned a value without error!

Submitting the updated code

With the solution in hand, I read the Contribution Guide and submitting my patch. And the most awesome part? Within less than an hour Simon Willison (the project’s maintainer) had replied back and merged by code!

And then, the icing on the cake was getting a shout out in a post that Simon wrote up about the update that I submitted!

Holy smokes that was sooo cool.

I love solving problems, and I love writing code, so this kind of stuff just really makes my day.

Now, I’ve contributed to an open source project (that makes 3 now!) and the issue with the /dashboard/ has been fixed.