with sql_context(columns={"x"}):> Do you support templating a sql tstring into an sql tstring for composition?
Yep
https://github.com/pgjones/sql-tstring
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 sql val = 2 query, values = sql(t"SELECT x FROM y WHERE x = {val}") assert query == "SELECT x FROM y WHERE x = ?" assert values == [2] db.execute(query, values) # Most DB engines support...
@tasks.cron("*/5 * * * *") # every 5 minutes
async def infrequent_task():
...
https://medium.com/smarkets/implementing-gcra-in-python-5df1... https://en.m.wikipedia.org/wiki/Generic_cell_rate_algorithm
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. In other words Flask and Quart are now the same base framework as they share the majority of their codebases.This means that you can use the same framework API and understanding to write synchronous code with Flask,...
I blog mostly about Python web developed, especially Flask, Quart and Hypercorn related aspects.
1. Quart, https://quart.palletsprojects.com, an ASGI (async/await) re-implementation of the Python web MicroFramework Flask. It is now maintained alongside, by the same people, as Flask.
2. Hypercorn, https://hypercorn.readthedocs.io, an ASGI/WSGI server that supports HTTP/1, HTTP/2, and HTTP/3.
3. My book "A Blueprint for Production-Ready Web Applications", which uses both of the above and shows a beginner how to build a full stack app (React frontend) running on AWS. See https://pgjones.dev/tozo/ for details, code, and link to the example app.
Also see Quart https://github.com/pgjones/quart (which is Flask re-implemented with async-await) and Quart-Schema, https://github.com/pgjones/quart-schema for swagger docs.
(I'm the author of Hypercorn).
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 for childcare, amongst other things. Frustratingly, it is really hard to know if I’m saving enough, or even how much I should be aiming to save. The best tools to solve my problem model cash flows and are only available through expensive financial advisors. I’ve built Moneyed to solve my own, and many other people’s, problem.
Moneyed, at the core, takes into account personalised financial goals and models cash flows i.e. the growth of assets, savings rates, and spending. Difficulties arise in the details, especially taking into account tax rules, and building a plan that is fully optimised (i.e. one where you minimise the amount you save whilst still being tax efficient and meeting your goals).
Moneyed also utilises Open Banking to give a full financial overview (UK current accounts, credit cards, savings, investments, pensions), to understand current spending, and to make it easy to know if you’re on track.
The backend of the app is built in Quart, an async version of Flask (Python), and utilises React for the frontend. The site also uses Quart for the backend but uses Svelte for the frontend. I’m the author of Quart, so it is an obvious choice for me. As for the frontend, React works really well for the app given the complexity, but I find it too heavy for the site. Fortunately Svelte exists, which I think is perfect for the site.
To build an optimised financial plan, we’re implementing SciPy’s minimize function as it enables us to model both linear and non-linear constraints and is relatively quick to solve (provided the initial first guess is good). We’re planning on leveraging more data science techniques: building a recommender engine to help people decide where to save/invest and cohort analysis to give for social validation and insights.
As for our go-to-market, we’re targeting young professionals working in tech as part of their employer’s benefits and wellbeing strategy as this enables us to create a “trigger” to get people thinking about their financial future.
When I compared late last year I found HTTP/3 to be noticeably slower, https://pgjones.dev/blog/early-look-at-http3-2019/ however my test was much less comprehensive than the one here.
(That site is also served over HTTP/3 if you want to try it out).
We are a wealth management company, here to blow away the cobwebs and breathe new life into personal finance. We believe that getting help should be a positive and uplifting experience: an aspiration, not an anxiety.
We’re developing technology that’ll create a new type of user experience for clients of financial advisers. It’ll also be the key to lowering our costs, helping us bring the benefits of tailored financial advice to more and more people.
Our tech stack is based on Python and Typescript utilizing the Quart and React frameworks respectively. We practice continuous deployment via docker containers to a k8s environment.
Current positions,
- Software engineer, 40 - 70k pa | https://medium.com/octopus-wealth/software-engineer-2be03a48...
- Senior software engineer, 70 - 100k pa | https://medium.com/octopus-wealth/senior-software-engineer-c...
- Design lead, 50 - 70k pa | https://medium.com/octopus-wealth/design-lead-4ef23c5ea445
We offer a comprehensive benefits package, including generous holiday allowance, private healthcare and a host of workplace rewards.