Bump anyhow from 1.0.72 to 1.0.75

[dependabot]

Bumps anyhow from 1.0.72 to 1.0.75.

Release notes

Sourced from anyhow's releases.

1.0.75

• Partially work around rust-analyzer bug (rust-lang/rust-analyzer#9911)

1.0.74

• Add bootstrap workaround to allow rustc to depend on anyhow (#320, thanks @​RalfJung)

1.0.73

• Update backtrace support to nightly's new Error::provide API (rust-lang/rust#113464, #319)

Commits

• 6485cae Release 1.0.75
• 238223a Work around ridiculous rust-analyzer behavior
• cbade7d Release 1.0.74
• 0798a9a Reword bootstrap comment
• 61d8676 Merge pull request #320 from RalfJung/bootstrap
• 663c663 don't run build probes in rustc bootstrap
• e471b2b Release 1.0.73
• 8cf1d15 Merge pull request #319 from dtolnay/errorprovide
• 31c8dff Update to nightly's new Error::provide API
• 496b958 Ignore ignored_unit_patterns pedantic clippy lint in test suite
• Additional commits viewable in compare view

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[github-actions]

Regression Detector Results

Run ID: eabef872-2095-417a-a7d9-59fefba8ca11
Baseline: d113370
Comparison: fbee2e2
Total lading-target CPUs: 4

Explanation

A regression test is an integrated performance test for lading-target in a repeatable rig, with varying configuration for lading-target. What follows is a statistical summary of a brief lading-target run for each configuration across SHAs given above. The goal of these tests are to determine quickly if lading-target performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.

experiment	goal	Δ mean %	Δ mean % CI	confidence
blackhole_from_apache_common_http	ingress throughput	-0.17	[-0.21, -0.13]	100.00%
apache_common_http_both_directions_this_doesnt_make_sense	ingress throughput	-0.44	[-0.47, -0.42]	100.00%

[blt]

@dependabot squash and merge