https://hubdesk.io/ . Create Github issues from emails and respond to them by starting a comment with "@reply". If you've got a side project, already use Github issues, and want to manage support emails the same as bugs. Easier and cheaper than signing up for a help desk SaaS.
Do you have a longer term strategy for monetisation? $20/month does not seem like enough.
At the moment my costs are about $100/mo, so it only takes a handful of subscribers to keep it going. Beyond that it was something I wanted for myself and I'm just glad if other people find it useful. I also learned a ton from making it and have been able to carry that over to my day job.
Data frames for Python (and some other stuff): https://github.com/otsaloma/dataiter Comparison against dplyr and Pandas for a quick overview: https://dataiter.readthedocs.io/en/latest/_static/comparison...
I've always wanted to make a simpler API called RowCol.
I really thought enough people liked esolangs and zachlikes, but it failed to get a single upvote, so never even made it to the “Show” page (well, not until like a week later, at which point it was buried anyway) :(
https://crowdview.ai - search engine for forums and discussion sites Like many of you, I find Google results to be full of SEO spam and have resorted to adding "site:reddit.com" or "site:news.ycombinator.com" to all my queries (since 2015!). Otherwise, it's really hard to figure out "what does a genuine, real life human think about this thing?". But limiting my results to just Reddit isn't ideal because so much great…
This is really nice. I am always appending forums names and reddit to my searches.
https://grizzlybulls.com It's a freemium subscription service to the algorithmic trading models / hedging systems I've been developing over the last few years. 2022 performance: SPX (benchmark): -18.77% Free models: TA - Mean Reversion Basic ( https://grizzlybulls.com/models/ta-mr-basic ): -9.93% TA - Trend Basic ( https://grizzlybulls.com/models/ta-trend-basic ): -17.79% Vix Basic ( https://grizzlybulls.com/models/v…
Do you have some suggestions for how to get into the basics of algorithmic trading from first principles without spending months or years?
I would start with learning the basics about the primary forces that move markets (examples are earnings expectations, macroeconomic health indicators, and sentiment measurement via VIX and TA). The hard part is identifying legitimate leading indicators / patterns of combinations of these that have lasting and tradeable impact, i.e. building your trading strategy with as little overfitting of noise as possible. Actually automating that strategy is the relative easy part, though still a pain the ass because brokerage APIs are garbage and often you'll find no API exists for a particular set of data you want so you have to settle for brittle scraping. I would also check out videos from a couple respectable algotraders on Youtube such as Kevin Davey and Jacob Amaral.
It supports page stacking, linked references, block references, a graph view, and all that good stuff. Think of it as similar to Roam Research / Obsidian.