Profiling is already extensively documented in ruff, so we can just link
to that guide. I added `tracing-durations-export` to the guide because i
found it a useful tool for optimizing.
Windows doesn't support symlinks, doesn't use a `bin` directory and all
pythons are called `python.exe`.
Note that this is still broken, `.\bin\python3.10.13` is missing its
.exe extension and renaming it to `.\bin\python3.10.13.exe` makes it
complain about not finding python310.dll.
Closes#884
e.g.
```
❯ cargo run -q -- pip compile --python-version 3.12 requirements.in
× No solution found when resolving dependencies:
╰─▶ Because the requested Python version (3.12) does not satisfy Python>=3.6,<3.10 and recommenders==1.0.0 depends on Python>=3.6,<3.9, we can conclude that recommenders==1.0.0 cannot be used.
And because only the following versions of recommenders are available:
recommenders<=0.7
recommenders==1.0.0
recommenders==1.1.0
recommenders==1.1.1
we can conclude that recommenders>0.7,<1.1.0 cannot be used. (1)
Because the requested Python version (3.12) does not satisfy Python>=3.6,<3.10 and recommenders>=1.1.0 depends on Python>=3.6,<3.10, we can conclude that recommenders>=1.1.0 cannot be used.
And because we know from (1) that recommenders>0.7,<1.1.0 cannot be used, we can conclude that recommenders>0.7 cannot be used.
And because you require recommenders>0.7, we can conclude that the requirements are unsatisfiable.
```
## Summary
Previously, we were blocking operations that could run in parallel. We
would send request through our main requests channel, but not yield so
that the receiver could only start processing requests much later than
necessary. We solve this by switching to the async
`tokio::sync::mpsc::channel`, where send is an async functions that
yields.
Due to the increased parallelism cache deserialization and the
conversion from simple api request to version map became bottlenecks, so
i moved them to `spawn_blocking`. Together these result in a 30-60%
speedup for larger warm cache resolution. Small cases such as black
already resolve in 5.7 ms on my machine so there's no speedup to be
gained, refresh and no cache were to noisy to get signal from.
Note for the future: Revisit the bounded channel if we want to produce
requests from `process_request`, too, (this would be good for
prefetching) to avoid deadlocks.
## Details
We can look at the behavior change through the spans:
```
RUST_LOG=puffin=info TRACING_DURATIONS_FILE=target/traces/jupyter-warm-branch.ndjson cargo run --features tracing-durations-export --bin puffin-dev --profile profiling -- resolve jupyter 2> /dev/null
```
Below, you can see how on main, we have discrete phases: All (cached)
simple api requests in parallel, then all (cached) metadata requests in
parallel, repeat until done. The solver is mostly waiting until it has
it's version map from the simple API query to be able to choose a
version. The main thread is blocked by process requests.
In the PR branch, the simple api requests succeeds much earlier,
allowing the solver to advance and also to schedule more prefetching.
Due to that `parse_cache` and `from_metadata` became bottlenecks, so i
moved them off the main thread (green color, and their spans can now
overlap because they can run on multiple threads in parallel). The main
thread isn't blocked on `process_request` anymore, instead it has
frequent idle times. The spans are all much shorter, which indicates
that on main they could have finished much earlier, but a task didn't
yield so they weren't scheduled to finish (though i haven't dug deep
enough to understand the exact scheduling between the process request
stream and the solver here).
**main**
**PR**
## Benchmarks
```
$ hyperfine --warmup 3 "target/profiling/main-dev resolve jupyter" "target/profiling/branch-dev resolve jupyter"
Benchmark 1: target/profiling/main-dev resolve jupyter
Time (mean ± σ): 29.1 ms ± 0.7 ms [User: 22.9 ms, System: 11.1 ms]
Range (min … max): 27.7 ms … 32.2 ms 103 runs
Benchmark 2: target/profiling/branch-dev resolve jupyter
Time (mean ± σ): 18.8 ms ± 1.1 ms [User: 37.0 ms, System: 22.7 ms]
Range (min … max): 16.5 ms … 21.9 ms 154 runs
Summary
target/profiling/branch-dev resolve jupyter ran
1.55 ± 0.10 times faster than target/profiling/main-dev resolve jupyter
$ hyperfine --warmup 3 "target/profiling/main-dev resolve meine_stadt_transparent" "target/profiling/branch-dev resolve meine_stadt_transparent"
Benchmark 1: target/profiling/main-dev resolve meine_stadt_transparent
Time (mean ± σ): 37.8 ms ± 0.9 ms [User: 30.7 ms, System: 14.1 ms]
Range (min … max): 36.6 ms … 41.5 ms 79 runs
Benchmark 2: target/profiling/branch-dev resolve meine_stadt_transparent
Time (mean ± σ): 24.7 ms ± 1.5 ms [User: 47.0 ms, System: 39.3 ms]
Range (min … max): 21.5 ms … 28.7 ms 113 runs
Summary
target/profiling/branch-dev resolve meine_stadt_transparent ran
1.53 ± 0.10 times faster than target/profiling/main-dev resolve meine_stadt_transparent
$ hyperfine --warmup 3 "target/profiling/main pip compile scripts/requirements/home-assistant.in" "target/profiling/branch pip compile scripts/requirements/home-assistant.in"
Benchmark 1: target/profiling/main pip compile scripts/requirements/home-assistant.in
Time (mean ± σ): 229.0 ms ± 2.8 ms [User: 197.3 ms, System: 63.7 ms]
Range (min … max): 225.8 ms … 234.0 ms 13 runs
Benchmark 2: target/profiling/branch pip compile scripts/requirements/home-assistant.in
Time (mean ± σ): 91.4 ms ± 5.3 ms [User: 289.2 ms, System: 176.9 ms]
Range (min … max): 81.0 ms … 104.7 ms 32 runs
Summary
target/profiling/branch pip compile scripts/requirements/home-assistant.in ran
2.50 ± 0.15 times faster than target/profiling/main pip compile scripts/requirements/home-assistant.in
```
In the scenario tests, we want to make sure we're actually conforming to
the scenario's expectations, so we now have an extra assertion on
whether resolution failed or succeeded as well as that it includes the
given packages.
Closes#1112Closes#1030
We need more flexible filters than those `inta` offers, and `insta_cmd`
makes it impossible to plug in programmatic filters. At the same time we
use barely any of `insta_cmd`'s features. We can replace the subset we
need in about 50 loc.
Mostly a mechanical refactor to use the `puffin_snapshot!` and
`TestContext` infrastructure in the add, remove, venv and pip uninstall
tests, in preparation for adding programmatic windows testing filters.
The is only one remaining usage of `assert_cmd_snapshot!` now in the
`puffin_snapshot!` macro.
Mostly a mechanical refactor to use the `puffin_snapshot!` and
`TestContext` infrastructure in the pip install and pip sync tests, in
preparation for adding programmatic windows testing filters.
Split out from the large test refactoring PR. Use `normalized_display`
in tests and two more thiserror derives to match snapshots and output,
and other small windows fixes.
## Summary
See: https://github.com/astral-sh/puffin/issues/1224
## Test Plan
Ran `python -m scripts.bench --puffin
scripts/requirements/compiled/jupyter.txt --min-runs 100 --benchmark
install-warm --verbose` several times, which failed eventually on `main`
but not on this branch.
Mostly a mechanical refactor to use the `puffin_snapshot!` and
`TestContext` infrastructure in the pip compile and pip install
scenarios, in preparation for adding programmatic windows testing
filters.
## Summary
Oops -- this was using a different cache key than the route above (this
is the wheel _metadata_ route vs. the wheel build route), so we were
saving and building source distributions twice in `pip install`.
I originally used Python 3.10, since 3.10 and 3.11 are by far the most
common (at least for [Ruff](https://pypistats.org/packages/ruff)). But
3.12 should give Python tools the most favorable benchmarks.
## Summary
Overall, similar to Poetry, with some simplifications (e.g., we don't
need to translate to Poetry's dependency syntax), and the need to adjust
how we manage the cache and virtual environment.
It turns out that the pattern I coded up for SimpleMetadataRaw is
generally useful when working with rkyv. This commit makes it generic by
supporting any type that implements rkyv's traits, and makes a few
simplifying assumptions by picking a concrete serializer, validator and
deserializer. In effect, this lets use own any archived value.
We also rejigger the API a little bit and double-down on
`OwnedArchive<A>` just being a owned wrapper for `Archived<A>`. Namely,
we implement `Deref` and turn its inherent methods into methods that
require fully qualified syntax. (As is standard for things that
implement `Deref` to avoid ambiguity with the deref target's methods.)
(This PR also makes a couple small simplifications to our custom rkyv
serializer since we no longer need to use it directly. We do still need
to name the type in trait bounds, so it has to be public.)
In preparation for the new windows handling, i want to introduce a
`TestContext` and `puffin_snapshot!` abstraction. This PR applies those
changes for pip-compile. My plan is to use those for all venv-based
integration tests and build the custom windows filters on top of
`puffin_snapshot!`.
## Summary
Enables tests for macOS in CI, using the M1 runners (which are free in
public, but count against our quota in private
repos). For now, I'm just running them on `main` to save quota.
I did the math, and the M1 runners are the best value:
Closes#1053.
## Summary
We have some flags in Puffin that enable us to opt-in to certain tests.
To date, they've been opt-in, so we've run our tests with
`--all-features`. This PR makes them opt-out, and we now run tests with
default features.
The main motivation here is that I want to get tests working for macOS
on CI, but for unknown reasons, macOS can't compile the PyO3 features at
the same time as everything else due to strange linker issues. By
avoiding `--all-features` for tests, we thus avoid unnecessarily
including features that we don't actually use in Puffin.
I verified that the exact same number of tests (439) are run before and
after this change. For users, the primary difference is that you now
need to specify `--no-default-features --features pypi --features
python` to avoid (e.g.) including the Git tests.
The `http-cache-semantics` crate is polymorphic on the types of requests
and responses it accepts. We had previously been explicitly converting
between `http` and `reqwest` types, but this isn't necessary. We can
provide impls of the traits in `http-cache-semantics` for `reqwest`'s
types (via a wrapper). This saves us from the awkward request/response
type conversions.
While this does clone the request, this is:
1. Not new. We were previously cloning the request to do the conversion.
2. An artifact (I believe) of http-cache-semantics API. (It kind of
seems like an API bug to me?)
There is also a little bit of messiness around inter-operating between
http::uri::Uri and url::Url. But overall shouldn't be a big deal.
## Summary
This is an attempt to https://github.com/astral-sh/puffin/pull/1163 by
removing the `WaitMap` and gaining more granular control over the values
that we hold over `await` boundaries.
## Summary
Like https://github.com/astral-sh/puffin/pull/1180, this PR adds logic
for `requirements.txt` parsing whereby if a requirement _looks like_ a
local requirements file or an editable directory, we prompt the user to
correct the error (typically, by adding `-r`).
Lacking windows compatible aarch64 hardware, i cross compiled the
trampoline from x86_64 linux to aarch64-pc-windows-msvc; I added the
instructions to the puffin-trampoline readme. With some testing on an
aarch64 windows machine, this should be sufficient to build working
win_arm64 tagged wheels.
i686-pc-windows-msvc is failing with an error:
```
error: linking with `lld-link` failed: exit status: 1
= note: lld-link: error: undefined symbol: __aulldiv
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced 4 more times
lld-link: error: undefined symbol: __aullrem
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced by libcompiler_builtins-2fb09dee087e9f64.rlib(compiler_builtins-2fb09dee087e9f64.compiler_builtins.597f0152646f1b8-cgu.0.rcgu.o):(compiler_builtins::int::specialized_div_rem::u128_div_rem::h06aed1e23a3f8f5c)
>>> referenced 4 more times
```
Instrument the main function as anchor span for checking overhead and
update tracing-durations-export to 0.2.0 for differentiating
blocking/non-blocking tasks.
Add a `jupyter.in` requirement since `pip install jupyter` is a common
operation. I tried `jupyterlab` too but there is no difference in
performance (1.00 ± 0.07).
Use `virtualenv` consistently, remove unused error variants and hint the
user towards installing missing python versions.
I didn't touch the Readme but i replaced `virtualenv environment` with
`virtualenv` in the strings i found.
Fixes https://github.com/astral-sh/puffin/issues/1167
## Summary
See: https://github.com/astral-sh/puffin/issues/1181.
## Test Plan
```
❯ cargo run -- pip install packse@../../zanieb/packse
Finished dev [unoptimized + debuginfo] target(s) in 0.15s
Running `target/debug/puffin pip install 'packse@../../zanieb/packse'`
error: Distribution not found at: file:///Users/crmarsh/zanieb/packse
```
