dataUsageObjName       = ".usage.json"
	dataUsageObjNamePath   = bucketMetaPrefix + SlashSeparator + dataUsageObjName
	dataUsageBloomName     = ".bloomcycle.bin"
	dataUsageBloomNamePath = bucketMetaPrefix + SlashSeparator + dataUsageBloomName

	backgroundHealInfoPath = bucketMetaPrefix + SlashSeparator + ".background-heal.json"

	dataUsageCacheName = ".usage-cache.bin"
)

}

// DataUsageInfo represents data usage stats of the underlying Object API
type DataUsageInfo struct {
	TotalCapacity     uint64 `json:"capacity,omitempty"`
	TotalUsedCapacity uint64 `json:"usedCapacity,omitempty"`
	TotalFreeCapacity uint64 `json:"freeCapacity,omitempty"`

	// LastUpdate is the timestamp of when the data usage info was last updated.
	// This does not indicate a full scan.

	for _, usage := range dataUsageInfo.BucketsUsage {
		clusterBuckets++
		clusterSize += usage.Size
		clusterObjectsCount += usage.ObjectsCount
		clusterVersionsCount += usage.VersionsCount
		clusterDeleteMarkersCount += usage.DeleteMarkersCount
		for k, v := range usage.ObjectSizesHistogram {
			clusterObjectSizesHistogram[k] += v
		}
		for k, v := range usage.ObjectVersionsHistogram {

      value: |
        <details>

        ```console
        # On Linux:
        $ cat /etc/os-release
        # paste output here
        $ uname -a
        # paste output here

        # On Windows:
        C:\> wmic os get Caption, Version, BuildNumber, OSArchitecture
        # paste output here
        ```

        </details>

  - type: textarea
    id: installer
    attributes:

Krishnan Parthasarathi <******@****.***> 1705132268 -0800

		"Total cluster raw storage free in bytes")
	healthCapacityUsableTotalBytesMD = NewGaugeMD(healthCapacityUsableTotalBytes,
		"Total cluster usable storage capacity in bytes")
	healthCapacityUsableFreeBytesMD = NewGaugeMD(healthCapacityUsableFreeBytes,
		"Total cluster usable storage free in bytes")
)

// loadClusterHealthCapacityMetrics - `MetricsLoaderFn` for cluster storage
// capacity metrics.

   * algorithms should document their behavior in the presence of duplicates.
   *
   * <p>The elements of the returned {@code Iterable} must each be:
   *
   * <ul>
   *   <li>Non-null
   *   <li>Usable as {@code Map} keys (see the Guava User Guide's section on <a
   *       href="https://github.com/google/guava/wiki/GraphsExplained#graph-elements-nodes-and-edges">
   *       graph elements</a> for details)
   * </ul>
   *

   * algorithms should document their behavior in the presence of duplicates.
   *
   * <p>The elements of the returned {@code Iterable} must each be:
   *
   * <ul>
   *   <li>Non-null
   *   <li>Usable as {@code Map} keys (see the Guava User Guide's section on <a
   *       href="https://github.com/google/guava/wiki/GraphsExplained#graph-elements-nodes-and-edges">
   *       graph elements</a> for details)
   * </ul>
   *

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import subprocess
import time

import httpx
from playwright.sync_api import Playwright, sync_playwright


# Run playwright codegen to generate the code below, copy paste the sections in run()
def run(playwright: Playwright) -> None:
    browser = playwright.chromium.launch(headless=False)
    # Update the viewport manually
    context = browser.new_context(viewport={"width": 960, "height": 1080})
    page = context.new_page()