uv pip sync requirements.txt
instead of python3 -m pip install -r requirements.txt Read: https://www.gutenberg.org/files/59844/59844-h/59844-h.htm
Listen (3 versions): https://librivox.org/author/848?primary_key=848
It sounds like a motivational self-help or spiritual book, but if you can get past that, the main idea is to not throw away our progress, but instead: 1) always build on what you've built already in terms of expertise and experience and ability to add value, and
2) always give people more value (at work) than they expect or think they deserve
I think (2) is your ticket to adding depth and (1) is your way to finding that path. # Make an env for the project with appropriate Python and use it
uv venv ~/.venvs/myprojpy312 --python 3.12
source ~/.venvs/myprojpy312/bin/activate
# Make sure pip exists and is up to date
python -m ensurepip --upgrade
python -m pip install --upgrade pip
# Fill in requirements.txt in readable/meaningful syntax per needs
$ cat requirements.txt
requests>=2.31.0,<3.0.0
black==24.4.2
# Install the requirements initially (or again after changing requirements.txt)
python -m pip install -r requirements.txt
# List outdated modules
python -m pip list --outdated
# Upgrade modules, respecting the constraints
python -m pip install --upgrade -r requirements.txt
And in the age of the supply chain attacks, requiring a certain staleness could be useful, too (providing time to catch recent and revoke reasonably major and recently discovered issues, though at the cost of also blocking recent fixes): $ cat ~/.config/uv/uv.toml
exclude-newer = "7 days"
# per https://news.ycombinator.com/item?id=47884491
Am I doing it wrong? Should I be thinking about `uv lock --upgrade`, `uv add`, and `uv tree --outdated` like the author? I'd rather just avoid all that, and have been able to so far. Synology 8-bay DS: $1150 (Amazon price)
8x 22TB Seagate 22TB external 3.5" = 8 x $390 = $3120 (also the #1 least expensive disk per TB for 3.5" external at https://diskprices.co currently)
So we're at $1150+$3120 = $4270 for one library. In grand summary, roughly every 5 years:
Done "right": $15,965
Done "cheap": $4,430 and only 112TB usable.
You know what, 112TB starts to feel like not that much, when we look at the size of some of the libraries out there. - Right: $15,965 / 5yr = about $3,200/yr (plus tax) for 125TB usable library
- Cheap: $4,430 / 5yr = $886/yr (plus tax) for 112TB usable library
If a techie makes $150K, that's about 0.6%-2% of income, if we forget taxes (sales or income) entirely.
WSJ refers to 2026 college grads as "AI native". I don't really know about that; to me, native would be truly imply having grown up with it moreso.
In any case, this crop entering the workforce (theoretically) would have had ample time during between/for class to use and ramp on AI, especially compared with those already used to or busy doing things the older fashioned way at $dayjob, however much AI crept or jolted in. So, I guess the moniker fits, comparatively.
Native in terms of AI being already in full-ish force when entering the workplace, perhaps.
Curious how HN thinks this matters, if anything.