Viewing profile — pgjones

The `sql_context` feature is meant to protect against SQL injection. I think for your usecase you would need to supply all columns, but you could used nested t-strings included bas…

It does parse the SQL. At the moment an expression is defined as all the text between the appropriate separators given the clause.

Sorry that is a typo, I meant, with sql_context(columns={"x"}):

Thank you! My Google foo did not find this.

The presence of Absent removes the entire expression, and if that removal results in an empty clause (or group) it will remove that as well. For example if `a = Absent` `WHERE a = …

Thanks, do you have a reference for SQL grammar - I've had no success finding an official source.

SQL-tString is a SQL builder that utilises the recently accepted PEP-750, https://peps.python.org/pep-0750/ , t-strings to build SQL queries, for example, from sql_tstring import s…

If you want to see a usage for this I've built, and use, [SQL-tString]( https://github.com/pgjones/sql-tstring ) as an SQL builder.

Quart, the ASGI version of Flask, also has background tasks, https://quart.palletsprojects.com/en/latest/how_to_guides/ba... , and there is an extension Quart-Tasks, https://github…

It is a shame GCRA is not more well known and used for rate limiting. It is, in my view, a better algorithm. https://medium.com/smarkets/implementing-gcra-in-python-5df1... https:/…

Yes, I've written about this comparison in detail https://pgjones.dev/blog/fastapi-flask-quart-2022/ .

There are new logos for all the Pallets projects and Pallets itself, based on a common theme.

Flask is a web microframework built to be used with WSGI servers and synchronous code. Quart is the same web microframework built to be used with ASGI servers and asynchronous code…

https://pgjones.dev I blog mostly about Python web developed, especially Flask, Quart and Hypercorn related aspects.

I've three things :), 1. Quart, https://quart.palletsprojects.com , an ASGI (async/await) re-implementation of the Python web MicroFramework Flask. It is now maintained alongside, …

It is also easier to manage for Flask - it is very mature and we fixed most of the issues present in FastAPI many years ago.

Flask supports async, see https://flask.palletsprojects.com/en/2.1.x/async-await/ . Also see Quart https://github.com/pgjones/quart (which is Flask re-implemented with async-await)…

Or Hypercorn https://gitlab.com/pgjones/hypercorn if you want HTTP/1, HTTP/2, and HTTP/3.

You can already do this using Hypothesis with the Pydantic plugin, https://pydantic-docs.helpmanual.io/hypothesis_plugin/ . Here is an example for Quart-Schema (similar setup to Fa…

Hypercorn a Python ASGI server supports HTTP/3 built on aioquic which is a Python library supports QUIC. (I'm the author of Hypercorn).

Hi Hacker News, I’ve reached an age now where I need to start thinking about my retirement, in addition to buying a house, saving for a wedding, starting a family, affording to pay…