Thanks for sharing. We use all pytest-style tests using pytest fixtures. I’ll keep my eyes open for memory issues when we test upgrading to python 3.12+.

Very helpful info!

I’m most excited about the new REPL. I’m going to push for 3.13 upgrade as soon as we can (hipefully early next year). I’ve messed around with rc1 and the REPL is great.

Do you know why pytest was taking up so much RAM? We are also on 3.11 and I’m probably going to wait until 3.13 is useable for us.

EOL for 3.8 is coming up in a few short weeks!

TIL this exists

I also like the POSIX “seconds since 1970” standard, but I feel that should only be used in RAM when performing operations (time differences in timers etc.). It irks me when it’s used for serialising to text/JSON/XML/CSV.

I’ve seen bugs where programmers tried to represent date in epoch time in seconds or milliseconds in json. So something like “pay date” would be presented by a timestamp, and would get off-by-one errors because whatever time library the programmer was using would do time zone conversions on a timestamp then truncate the date portion.

If the programmer used ISO 8601 style formatting, I don’t think they would have included the timepart and the bug could have been avoided.

Use dates when you need dates and timestamps when you need timestamps!

Do you use it? When?

Parquet is really used for big data batch data processing. It’s columnar-based file format and is optimized for large, aggregation queries. It’s non-human readable so you need a library like apache arrow to read/write to it.

I would use parquet in the following circumstances (or combination of circumstances):

• The data is very large
• I’m integrating this into an analytical query engine (Presto, etc.)
• I’m transporting data that needs to land in an analytical data warehouse (Snowflake, BigQuery, etc.)
• Consumed by data scientists, machine learning engineers, or other data engineers

Since the data is columnar-based, doing queries like select sum(sales) from revenue is much cheaper and faster if the underlying data is in parquet than csv.

The big advantage of csv is that it’s more portable. csv as a data file format has been around forever, so it is used in a lot of places where parquet can’t be used.

The autocomplete is nice but I don’t find it a game-changer. The comment about writing tests is on point though, but that’s the only place I found out useful.

While it would be ideal to have all datetime fields in databases and other data stores be time zone aware, that is certainly not the case. Also, SQLite (and probably others) do not have great support for time zones and it’s recommended to store datetimes as UTC (typically unix timestamps).

Deprecating utcnow was a good idea, but they should have replaced it with naive_utcnow. Oh well.

The code in the community’s banner is in python 2. Can we get that changed?