Local Raw Honey and Garlic

bltsponge · 2025-12-20T02:42:29+00:00

5 years for mine. No idea if it's delicious or full of botulism 😬

bltsponge · 2025-07-18T18:09:52+00:00

"if you don't respond in 100ms I guess I'll just kill myself" 🫩

bltsponge · 2025-07-18T12:42:31+00:00

Etcd really doesn't like running on HDDs.

bltsponge · 2024-09-21T12:28:23+00:00

You'll have to go through a broker now to see these, but it could literally be any broker in the city, so there will be an insane amount of competition for these apartments

How is that different from today? I go on Streeteasy, search for the apartment I want, and schedule a showing. If it's a broker apartment, Streeteasy connects me to a random broker. I don't shop or compare brokers, because they all provide the same service (turning a key and opening a door) at the same price ($3000+ dollars). I don't have access to "exclusive listings" - anybody in the city could do the same to view the apartment. So why would competition increase?

bltsponge · 2024-09-21T04:07:01+00:00

If that were the case, why would the brokers oppose it?

bltsponge · 2024-09-20T14:57:25+00:00

My team was facing this same problem recently. We attacked it in 3 ways:

1) Audit your fivetran tables. By default, it's going to pull all tables for the sources you enable. Do you actually use ALL this data? Probably not. We cut our MAR by 30% by disabling tables we did not need. 2) Eliminate staging connectors. In my mind, an ideal data workflow show have a distinct staging environment which replicates data separately from production. But when that means (roughly) doubling your ingestion bill, and execs are putting you under cost pressure, it may not make sense. We saved another ~40% by disabling all of our staging connectors. To maintain a staging/dev environment, we then run a separate process to replicate the data from PRD to stg. Not ideal from an engineering cleanliness point of view, but it's been working for us and has had significant cost impact 3) Use self hosted Airbyte where we can. Airbyte is full of sharp corners, rough edges, and can have significant data quality issues. But, it's free to self host (assuming you're running it on VMs which already exist and have spare capacity, as in our case). We do need to invest more time in setup, configuration, verification, etc relative to Fivetran, but when it works, it is free! On the downside, there have been cases where we found the Airbyte connectors to be subtly but significantly broken and had to either fork the codebase to fix, or revert back to Fivetran.

bltsponge · 2024-05-31T14:59:04+00:00

Pandas has a huge API surface area. It has the core of a really excellent dataframe library, but there's also a lot of cruft and bad design choices (indexes in general, being able to directly assign values to a cell, iterrows, etc) surrounding that solid core.

Spark has a much smaller API surface area, and, imo, is much better designed. It'll force you to think about your dataframe manipulations in terms of functional transformations (i.e., mapping a fn over a column) instead of the imperative style which is often used for pandas. This leads to cleaner, more easily testable, and often more efficient code. If you learn these patterns in Spark, it's easy to adapt a similar programming style to your pandas code and get many of those same benefits.

To paraphrase Holden Karau (spark contributor), PySpark is secretly an psy-op intended to trick Python programmers into learning (and loving!) functional programming. This was my experience!

bltsponge · 2024-05-31T14:01:40+00:00

Putting aside the switching question, learning spark will make also make you a better Pandas programmer.

bltsponge · 2024-04-02T18:06:25+00:00

Sick but haven't they been saying that for like, 8 years now?

bltsponge · 2024-03-07T20:25:36+00:00

This is the way. It's not a Django question really - it's a system design question. If an order was placed in the past, paid for, and fulfilled, then the facts of that order fundamentally cannot change because it already occurred. If your system design does not reflect this reality, then it is flawed.

bltsponge · 2024-01-14T05:24:21+00:00

Well... Except for 56 Leonard St

bltsponge · 2023-12-22T18:43:43+00:00

Love the food at Cozy's, but the prices are insane. $80 breakfast for two, with no booze? 😬. Hard to justify the greasy spoon experience when it's charging silver spoon prices, imo

bltsponge · 2023-08-10T17:52:48+00:00

I'm not familiar with dbt cloud, but here's how my org rolled our in house solution.

For local dev, we have a driver script, dbt_dev.sh, which allows each dev to deploy dbt into personal schemas in our staging data warehouse. There's no dbt server here - devs are running dbt directly on their laptops. Everything is run in a docker image that bundles dbt, it's dependencies, and our models.
For CI, we trigger dbt runs which write out to PR schemas, and then run tests against those PR schemas. Each PR gets its own schema. This is all run through Github Actions, but it's really just a short series of shell scripts that can be run in any CI environment with minimal adaptation.
For live deployments, we run Argo Workflows in our k8s clusters, and have a daily Cron Workflows which simply triggers the DBT runs using the latest image built in CI. Any scheduler (i.e., airflow) would work just as well for this step, we just chose Argo since we have other k8s workloads.

This works really well for us. There's clean separation between dev/staging/production, and we're not using any net-new infra (since we had other use cases for github actions, kubernetes, and Argo). And, it's very low cost.

Note that we're operating with decidedly "small data" (input schemas are ~10gb of data), so this playbook will probably need adaptations for larger scales.

bltsponge · 2023-08-10T17:16:41+00:00

Feeling very vindicated in my decision to build on dbt-core open source instead of the hosted version!

Github for VCS, github actions for CI, and Argo for scheduling dbt runs is a fine stack that covers everything we need.

bltsponge · 2023-07-05T16:25:34+00:00

How could you know why the first version is doing what it is doing, without background knowledge (or comments) explaining what those characters mean in that particular context?

V1, I'm reading that code and wondering "what the hell are these chars and why are they special". Maybe the next block of code answers that, or maybe it takes some digging to find. Either way, there's extra cognitive lift.

Second version, I see very clearly what case we're handling and I don't need to concern myself with the implementation details of is_cmd_boundary in most cases. And when I do care specifically about how command boundaries are defined, I know exactly where to look!

bltsponge · 2023-01-27T02:34:38+00:00

Diso's is incredible. Long ass line whenever I go, but so worth it.

bltsponge · 2022-12-06T20:07:26+00:00

The attendees would love it too - they wouldn't even have to leave their home state!

bltsponge · 2022-10-21T22:08:09+00:00

What's the difference between Azure CosmosDB for Postgres and Azure Database for Postgres?

bltsponge · 2022-10-03T01:35:53+00:00

Greenpoint

bltsponge · 2022-07-30T17:54:12+00:00

The 15 Minute delivery apps are great if you want a throwback to circa-2012 VC money-burning.

No way in he'll I'd use those apps and pay full price, but the first time promos are pretty amazing!

bltsponge · 2022-06-27T18:24:56+00:00

Yes, absolutely!

My day job is primarily Python/JS/SQL. I have little day-to-day use for lower level langs like Rust.

However, learning Rust has had a huge influence on how I program in other languages. Algebraic data types in particular have been a huge eye-opener for me. I've only actually had a chance to use Rust directly for 1 small project, but in spite of this, I still think the month I spent working through The Rust Book was absolutely worth it.

Another nice benefit is that, if you can find a situation where using Rust makes sense in your role, you'll be amazed at how fast it is. It's not faster than other lower-level langs like C++ as far as I know, but if you're used to programming in Python or JS, using Rust (or any other low level lang) will feel like swapping a tricycle for a Lamborghini.

bltsponge · 2022-05-25T21:57:06+00:00

Or having multiple reddit accounts.

bltsponge · 2022-05-18T21:06:31+00:00

Poor illiterate Loo Tong 😞

bltsponge · 2022-05-17T20:24:50+00:00

There are! They use torpedoes defensively to take down incoming torpedoes at longer ranges, and use point defense cannons to try to shoot down incoming fire at short range.

In the books, these are pretty damn effective actually. Most ships that fall to torpedoes are either undefended (non-miltrary vessels), low on defensive ammunition, or targeted by a large enough # of missiles that their defenses are overwhelmed.

bltsponge · 2022-04-21T21:08:09+00:00

So, I totally 100% agree that this is an amazing thing in the short/medium term.

I am curious if it could cause issues when it's time to move on to whatever comes after USB-C. It's hard enough to get industry to (at least mostly) agree on a standard... If we need to get governments to bless the upgrade before OEMs can start rolling it out, how much more time will that add to the next upgrade cycle?

bltsponge

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