We’re dropping the Slack group as the NetNewsWire forum and switching to Discourse — here’s the new forum.
Slack’s been pretty great for us, but it does have some limitations: conversations are automatically deleted and they’re not findable on the web in the first place.
It’s a shame that the Slack archives were deleted, but I think this will increase the longevity and accessibility of the information going forward.
Previously:
Michael Kennedy (via Hacker News):
For example, how fast or slow is it to add an item to a list in Python? What about opening a file? Is that less than a millisecond? Is there something that makes that slower than you might have guessed? If you have a performance sensitive algorithm, which data structure should you use? How much memory does a floating point number use? What about a single character or the empty string? How fast is FastAPI compared to Django?
I wanted to take a moment and write down performance numbers specifically focused on Python developers. Below you will find an extensive table of such values.
Previously:
Jonas Bonér (based on work by Peter Norvig and Jeff Dean from 2012):
L1 cache reference 0.5 ns Branch mispredict 5 ns L2 cache reference 7 ns 14x L1 cache Mutex lock/unlock 25 ns Main memory reference 100 ns 20x L2 cache, 200x L1 cache Compress 1K bytes with Zippy 3,000 ns 3 us Send 1K bytes over 1 Gbps network 10,000 ns 10 us Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD Read 1 MB sequentially from memory 250,000 ns 250 us Round trip within same datacenter 500,000 ns 500 us Read 1 MB sequentially from SSD* 1,000,000 ns 1,000 us 1 ms ~1GB/sec SSD, 4X memory Disk seek 10,000,000 ns 10,000 us 10 ms 20x datacenter roundtrip Read 1 MB sequentially from disk 20,000,000 ns 20,000 us 20 ms 80x memory, 20X SSD Send packet CA->Netherlands->CA 150,000,000 ns 150,000 us 150 ms
Colin Scott has a page that helps visualize how these types of numbers have changed over time (Hacker News).
Mohammad Zeya Ahmad has an informative post [archive] that answers that question. He has a list of how much time various common operations take. That’s interesting but what make his list stand out is that he draws conclusions from his results.
For example, SSDs are about 30 times faster than HDDs so if you have a high performance disk-based task, it makes sense to use SSDs. Of course, there are reasons to prefer HDDs but if performance is your controlling metric, SSDs are probably your best choice.
For each group of comparable metrics, Ahmad offers an actionable suggestion. Those groups range from CPU versus Cache and Memory speeds to network transfer times.
Previously:
Can anyone explain why there’s no “Clear Documents & Data” button?
Reinstalling the app just to clear it is dumb.
I can see why Apple doesn’t want to make it easier for users to accidentally delete data that they meant to keep. But I would like to at least see a standard system button for clearing an app’s caches. It’s backwards that to clear the cache you have to Delete App, which also removes its data, then reinstall it and somehow restore. You might think that Offload App would delete the app as well as the purgeable data, leaving only that which can’t be recreated automatically, but as far as I’m aware it leaves the caches in place.
Previously:
Update (2026-01-06): Craig Grannell:
I have a 130MB health app that’s so far ballooned to 1.5GB due to downloading everything each day. It keeps growing. Natch, there is no way to delete old data. (Nor can you get at the data to get the audio files – which is 99% of it – out of the thing.)
