import java.io.File;
import java.io.FileNotFoundException;
import java.io.PrintStream;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.concurrent.Callable;

/**
 * <p>Stage 2 of the start-up for a worker process with the application classes loaded in the system ClassLoader. Takes
 * care of deserializing and invoking the worker action.</p>
 *

# (1)
FROM python:3.9 as requirements-stage

# (2)
WORKDIR /tmp

# (3)
RUN pip install poetry

# (4)
COPY ./pyproject.toml ./poetry.lock* /tmp/

# (5)
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes

# (6)
FROM python:3.9

# (7)
WORKDIR /code

# (8)
COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt

	// Run all the require functions first, then the setup functions.
	setupFns := append(append([]resource.SetupFn{}, s.requireFns...), s.setupFns...)

	// don't waste time setting up if already skipped
	if s.isSkipped(ctx) {
		return nil
	}

	start := time.Now()
	for _, fn := range setupFns {
		err := s.runSetupFn(fn, ctx)
		if err != nil {

}

type protoPod struct {
	mf       string
	elements []fileWithAnnotations
}

// collectPodsImpl examines the specified list of files and picks out
// subsets that correspond to coverage pods. The first stage in this
// process is collecting a set { M1, M2, ... MN } where each M_k is a
// distinct coverage meta-data file. We then create a single pod for
// each meta-data file M_k, then find all of the counter data files

[[build-scan-performance]]
image::performance/build-scan-performance-page.png[title="Build scan performance page"]

In the above build scan, configuration takes over 13 seconds.
Click on the _"Configuration"_ tab to break this stage into component parts,
exposing the cause of the slowness.

image::performance/build-scan-configuration-breakdown.png[title="Build scan configuration breakdown"]

			maxID = id
		}
		if id < minID {
			minID = id
		}
	}
	if maxID >= math.MaxInt {
		// We can't create a slice big enough to hold maxID elements
		return
	}
	// We're willing to waste at most 2x memory.
	if int(maxID-minID) > max(len(d.sparse), 2*len(d.sparse)) {
		return
	}
	if int(minID) > len(d.sparse) {
		return
	}
	size := int(maxID) + 1
	d.present = make([]uint8, (size+7)/8)

# (1)
FROM python:3.9 as requirements-stage

# (2)
WORKDIR /tmp

# (3)
RUN pip install poetry

# (4)
COPY ./pyproject.toml ./poetry.lock* /tmp/

# (5)
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes

# (6)
FROM python:3.9

# (7)
WORKDIR /code

# (8)
COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt

		profiles                    []schedulerapi.KubeSchedulerProfile
		waitSchedulingPods          []*v1.Pod
		expectPodNamesInWaitingPods []string
	}{
		{
			name: "pods with same profile are waiting on permit stage",
			profiles: []schedulerapi.KubeSchedulerProfile{
				{
					SchedulerName: testSchedulerProfile1,
					Plugins: &schedulerapi.Plugins{

      ) ?: return null

    // If we coalesced our connection, remember the replaced connection's route. That way if the
    // coalesced connection later fails we don't waste a valid route.
    if (planToReplace != null) {
      nextRouteToTry = planToReplace.route
      planToReplace.closeQuietly()
    }

    connectionUser.connectionAcquired(result)

import java.util.Collection;
import java.util.Collections;
import java.util.List;
import java.util.Optional;
import java.util.Set;

/**
 * Provides a central location for handling failures encountered during
 * each stage of the variant selection process during dependency resolution.
 *
 * All variant selection failures encountered during selection by the {@link GraphVariantSelector} or
 * {@link AttributeMatchingArtifactVariantSelector}