## Motivation
No-op `uv lock` in apache airflow
(891c67f210ab7c877d1f00ea6ea3d3cdbb0e96ef) is slow, which makes `uv run`
slow, too.
Reference project:
```
$ hyperfine "uv run python -c \"print('hi')\""
Benchmark 1: uv run python -c "print('hi')"
Time (mean ± σ): 16.3 ms ± 1.5 ms [User: 9.8 ms, System: 6.4 ms]
Range (min … max): 13.0 ms … 20.0 ms 186 runs
```
Apache airflow before:
```
$ hyperfine "uv run python -c \"print('hi')\""
Benchmark 1: uv run python -c "print('hi')"
Time (mean ± σ): 161.0 ms ± 5.2 ms [User: 135.3 ms, System: 24.1 ms]
Range (min … max): 155.0 ms … 176.3 ms 18 runs
```
## Optimization
`FlatRequiresDist::from_requirements` is taking 50% of main thread
runtime.
Before:
After both commits:
Apache airflow after the first commit:
```
$ hyperfine "uv-profiling run python -c \"print('hi')\""
Benchmark 1: uv-profiling run python -c "print('hi')"
Time (mean ± σ): 122.3 ms ± 5.4 ms [User: 96.1 ms, System: 24.7 ms]
Range (min … max): 114.0 ms … 133.2 ms 23 runs
```
Apache airflow after the second commit:
```
$ hyperfine "uv-profiling run python -c \"print('hi')\""
Benchmark 1: uv-profiling run python -c "print('hi')"
Time (mean ± σ): 108.5 ms ± 3.4 ms [User: 83.2 ms, System: 24.2 ms]
Range (min … max): 103.6 ms … 119.9 ms 28 runs
```
## Summary
These are used for coordination across processes. If you run uv under,
e.g., the root user, then under a different user, I don't think we
should prevent you from acquiring the lock.
Closes https://github.com/astral-sh/uv/issues/11324.
Includes https://pypy.org/posts/2025/02/pypy-v7318-release.html
These are labeled as betas in the post but not anywhere obvious to me?
I'm not sure we need to portray this to users.
Co-authored-by: zanieb <2586601+zanieb@users.noreply.github.com>
## Summary
No behavior changes... This just separates the formatting from the
collection of the results, and also fixes a bug whereby we didn't say
"No changes detected" in some cases.
Given an input in the shape:
```
foo[bar]==1.0.0; sys_platform == 'linux'
foo==1.0.0; sys_platform != 'linux'
```
We would write either
```
foo==1.0.0; sys_platform == 'linux'
```
or
```
foo==1.0.0
```
depending on the iteration order, as the first one is from the marker
proxy package and the second one from the package without marker.
The fix correctly merges graph entries when there are two nodes with
different extras and different markers.
I tried to write a packse test but it failed due to a different
iteration order showing the correct case directly instead of the failing
one we'd need.
Only `strip_extras` is affected, since `combine_extras` uses
`version_marker`.
## Summary
I followed the docs to install flash-attn with uv and got the following
issue
```uv sync
Resolved 27 packages in 12ms
× Failed to build `flash-attn==2.7.4.post1`
├─▶ The build backend returned an error
╰─▶ Call to `setuptools.build_meta:__legacy__.build_wheel` failed (exit status: 1)
[stderr]
Traceback (most recent call last):
File "<string>", line 8, in <module>
ModuleNotFoundError: No module named 'setuptools'
hint: This usually indicates a problem with the package or the build environment.
```
installing setuptools before running uv sync as done with torch helps
fix it.
## Test Plan
I tested locally before it failed to install, after it worked
When stderr is not a tty, we currently don't show any messages for build
or large downloads, since indicatif is hidden. We can improve this by
showing a message for:
* Starting and finishing a large download (>1MB)
* Starting and finishing a build
Downloads are limited to 1MB or unknown size to keep the logs concise
and not scroll the entire terminal away for a download that finishes
almost immediately.
These messages are not captured in the tests since their order is
non-deterministic (downloads and builds race to finish).
There are no "tick" messages for large downloads yet, we could e.g. show
an update on runnning downloads every n seconds.
Part of #11121
**Test Plan**
```
$ uv venv && FORCE_COLOR=1 cargo run -q pip install numpy --no-binary :all: --no-cache 2>&1 | tee a.txt
Using CPython 3.13.0
Creating virtual environment at: .venv
Activate with: source .venv/bin/activate
Resolved 1 package in 221ms
Building numpy==2.2.2
Built numpy==2.2.2
Prepared 1 package in 2m 34s
Installed 1 package in 6ms
+ numpy==2.2.2
```
```
$ uv venv && FORCE_COLOR=1 cargo run -q pip install torch --no-cache 2>&1 | tee b.txt
Using CPython 3.13.0
Creating virtual environment at: .venv
Activate with: source .venv/bin/activate
Resolved 24 packages in 648ms
Downloading setuptools (1.2MiB)
Downloading nvidia-cuda-cupti-cu12 (13.2MiB)
Downloading torch (731.1MiB)
Downloading nvidia-nvjitlink-cu12 (20.1MiB)
Downloading nvidia-cufft-cu12 (201.7MiB)
Downloading nvidia-cuda-nvrtc-cu12 (23.5MiB)
Downloading nvidia-curand-cu12 (53.7MiB)
Downloading nvidia-nccl-cu12 (179.9MiB)
Downloading nvidia-cudnn-cu12 (634.0MiB)
Downloading nvidia-cublas-cu12 (346.6MiB)
Downloading sympy (5.9MiB)
Downloading nvidia-cusparse-cu12 (197.8MiB)
Downloading nvidia-cusparselt-cu12 (143.1MiB)
Downloading networkx (1.6MiB)
Downloading nvidia-cusolver-cu12 (122.0MiB)
Downloading triton (241.4MiB)
Downloaded setuptools
Downloaded networkx
Downloaded sympy
Downloaded nvidia-cuda-cupti-cu12
Downloaded nvidia-nvjitlink-cu12
Downloaded nvidia-cuda-nvrtc-cu12
Downloaded nvidia-curand-cu12
[...]
```
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## Summary
- PowerShell isn't Windows-only
- Bash/Elvish isn't UNIX-only
- PowerShell profile won't necessarily exist
- Extracted the `echo $SHELL` tip to a tip tooltip
The new PowerShell lines are taken directly from
https://learn.microsoft.com/en-us/powershell/module/microsoft.powershell.core/about/about_profiles?view=powershell-7.5#how-to-create-a-profile
Note that the "Standalone installer" commands are unaffected. Running
the Linux one through PowerShell worked just fine.
## Test Plan
Look at the page generated from this PR
<!-- How was it tested? -->
## Summary
This is attempting to solve the same problem surfaced in #11208 and
#11209. However, those PRs only worked for our own managed Pythons. In
Gentoo, for example, they disable the managed Pythons, which led to
failures in the test suite, because the "base Python" returned after
creating a virtual environment would differ from the "base Python" that
you get after _querying_ an existing virtual environment.
The fix here is to apply our same base Python normalization and
discovery logic, to non-standalone / non-managed Pythons. We continue to
use `sys._base_executable` for such Pythons when creating the
virtualenv, but when _caching_, we perform this second discovery step.
Closes https://github.com/astral-sh/uv/issues/11237.
This is a rewrite of the groups subsystem to have more clear semantics,
and some adjustments to the CLI flag constraints. In doing so, the
following bugs are fixed:
* `--no-default-groups --no-group foo` is no longer needlessly rejected
* `--all-groups --no-default-groups` now correctly evaluates to
`--all-groups` where previously it was erroneously being interpretted as
just `--no-default-groups`
* `--all-groups --only-dev` is now illegal, where previously it was
accepted and mishandled, as if it was a mythical `--only-all-groups`
flag
Fixes#10890Closes#10891
## Summary
If you `uv run` from the same directory via multiple processes at the
same time, some of them will fail as they'll see an "incomplete" virtual
environment.
Closes https://github.com/astral-sh/uv/issues/11219.
I think `UV_PROJECT_ENVIRONMENT` is too complicated for use-cases where
the user wants to sync to the active environment. I don't see a
compelling reason not to make opt-in easier. I see a lot of questions
about how to deal with this warning in the issue tracker, but it seems
painful to collect them here for posterity.
A notable behavior here — we'll treat this as equivalent to
`UV_PROJECT_ENVIRONMENT` so... if you point us to a valid virtual
environment that needs to be recreated for some reason (e.g., new Python
version request), we'll happily delete it and start over.
## Summary
I need to look into this later, but the test step is failing to install
Python:
3669416083.
We already disable this for the non-`le` variant, so this seems ok to
revisit.
## Summary
This PR removes the ephemeral `.pth` overlay when using a cached
environment. This solution isn't _completely_ safe, since we could
remove the `.pth` file just as another process is starting the
environment... But that risk already exists today, since we could
_overwrite_ the `.pth` file just as another process is starting the
environment, so I think what I've added here is a strict improvement.
Ideally, we wouldn't write this file at all, and we'd instead somehow
(e.g.) pass a file to the interpreter to run at startup? Or find some
other solution that doesn't require poisoning the cache like this.
Closes https://github.com/astral-sh/uv/issues/11117.
# Test Plan
Ran through the great reproduction steps from the linked issue.
Before:
After:
## Summary
I'm not sure that this has much of an effect in practice, but currently,
when we return a virtual environment, the `sys_base_executable ` of the
parent ends up being retained as `sys_base_executable` of the created
environment. But these can be, like, subtly different? If you have a
symlink to a Python, then for the symlink, `sys_base_executable` will be
equal to `sys_executable`. But when you create a virtual environment for
that interpreter, we'll set `home` to the resolved symlink, and so
`sys_base_executable` will be the resolved symlink too, in general.
Anyway, this means that we should now have a consistent value between
(1) returning `Virtualenv` from the creation routine and (2) querying
the created interpreter.
## Summary
It turns out that we were returning slightly different interpreter paths
on repeated `uv run --with` commands. This likely didn't affect many (or
any?) users, but it does affect our test suite, since in the test suite,
we use a symlinked interpreter.
The issue is that on first invocation, we create the virtual
environment, and that returns the path to the `python` executable in the
environment. On second invocation, we return the `python3` executable,
since that gets priority during discovery. This on its own is
potentially ok. The issue is that these resolve to different
`sys._base_executable` values in these flows... The latter gets the
correct value (since it's read from the `home` key), but the former gets
the incorrect value (since it's just the `base_executable` of the
executable that created the virtualenv, which is the symlink).
We now use the same logic to determine the "cached interpreter" as in
virtual environment creation, to ensure consistency between those paths.
Closes https://github.com/astral-sh/uv/issues/11214
Special-cases the first Python executable we find on the `PATH`,
allowing it to be considered during searches for virtual environments.
For some context, there are two stages to Python interpreter discovery
1. We find possible Python executables in various sources
2. We query the executables to determine canonical metadata about the
interpreter
We can't really be "sure" if an executable is a complaint virtual
environment during (1), we need to query the interpreter first. This
means that if you're only allowed to installed into virtual
environments, we'll query every interpreter on your PATH. This is not
performant, and causes confusion for users. Notably, I recently improved
error messaging when we can't find any valid interpreters, by showing
the error message we encounter while querying an interpreter (if any).
However, this is problematic when there's an error for an interpreter
that is not relevant to your search. In
https://github.com/astral-sh/uv/pull/11143, I added filtering to avoid
querying additional interpreters, but that regressed some user
experiences where they were relying on us finding implicitly active
virtual environments via the PATH.
In https://github.com/astral-sh/tokio-tar/pull/2, we accidentally
changed the `target_base` from the target base to the parent of the
file. This would cause hardlink unpacking to fail.
Example: A hardlink at `hardlinked-0.1.0/pyproject.toml` pointing to
`hardlinked-0.1.0/pyproject.toml.real` would try pointing to
`hardlinked-0.1.0/hardlinked-0.1.0/pyproject.toml.real` instead and fail
the unpacking.
The actual fix is in astral-tokio-tar, on the uv side there are only tests.
Fixes#11213
Since the resolver internals docs were written, we added a lot more
features to the resolver, which should be documented.
As usual, these docs are not targeted at regular users, but should give
interested readers an insight into the internals of uv and help advanced
users with especially hard resolver problems.
