}

	info.StatsSummary = make(map[string]madmin.SRSiteSummary, len(c.state.Peers))
	info.BucketStats = make(map[string]map[string]srBucketStatsSummary)
	info.PolicyStats = make(map[string]map[string]srPolicyStatsSummary)
	info.UserStats = make(map[string]map[string]srUserStatsSummary)
	info.GroupStats = make(map[string]map[string]srGroupStatsSummary)
	info.ILMExpiryRulesStats = make(map[string]map[string]srILMExpiryRuleStatsSummary)

     * @param map the document data map to process
     * @return the processed document map after applying all ingesters
     */
    protected Map<String, Object> ingest(final AccessResult<String> accessResult, final Map<String, Object> map) {
        if (ingestFactory == null) {
            return map;
        }
        Map<String, Object> target = map;

		}
		Toys []Toy `gorm:"polymorphic:Owner;"`
	}

	s, err := schema.Parse(&User{}, &sync.Map{}, schema.NamingStrategy{})
	if err != nil {
		t.Fatalf("Failed to parse schema, got error %v", err)
	}

	checkEmbeddedRelations(t, s.Relationships.EmbeddedRelations, map[string]EmbeddedRelations{
		"Cat": {
			Relations: map[string]Relation{
				"Toy": {
					Name:        "Toy",
					Type:        schema.HasOne,

			nidx++
			continue
		}
		h[nidx] += v[oidx]
		oidx++
		nidx++
	}
}

// toMap returns the map to a map[string]uint64.
func (h *sizeHistogram) toMap() map[string]uint64 {
	res := make(map[string]uint64, dataUsageBucketLen)
	var splCount uint64
	for i, count := range h {
		szInt := ObjectsHistogramIntervals[i]
		switch {

type MetricV2 struct {
	Description          MetricDescription `json:"Description"`
	StaticLabels         map[string]string `json:"StaticLabels"`
	Value                float64           `json:"Value"`
	VariableLabels       map[string]string `json:"VariableLabels"`
	HistogramBucketLabel string            `json:"HistogramBucketLabel"`
	Histogram            map[string]uint64 `json:"Histogram"`
}

        # TF 2.9
        map sigbuild-r2.9 2.9-python3.9
        map sigbuild-r2.9-python3.8 2.9-python3.8
        map sigbuild-r2.9-python3.9 2.9-python3.9
        map sigbuild-r2.9-python3.10 2.9-python3.10
        # TF 2.10
        map sigbuild-r2.10 2.10-python3.9
        map sigbuild-r2.10-python3.8 2.10-python3.8
        map sigbuild-r2.10-python3.9 2.10-python3.9
        map sigbuild-r2.10-python3.10 2.10-python3.10

type allHealState struct {
	sync.RWMutex

	// map of heal path to heal sequence
	healSeqMap map[string]*healSequence // Indexed by endpoint
	// keep track of the healing status of disks in the memory
	//   false: the disk needs to be healed but no healing routine is started
	//    true: the disk is currently healing
	healLocalDisks map[Endpoint]bool
	healStatus     map[string]healingTracker // Indexed by disk ID
}

            public RescorerBuilder<?> evaluate(Map<String, Object> params) {
                if (params == null) {
                    return null;
                }

                // Check for nested map
                if (params.containsKey("nested") && params.get("nested") instanceof Map) {
                    @SuppressWarnings("unchecked")
                    Map<String, Object> nestedMap = (Map<String, Object>) params.get("nested");

		Table:            tableName,
		DBNames:          make([]string, 0, 10),
		Fields:           make([]*Field, 0, 10),
		FieldsByName:     make(map[string]*Field, 10),
		FieldsByBindName: make(map[string]*Field, 10),
		FieldsByDBName:   make(map[string]*Field, 10),
		Relationships:    Relationships{Relations: map[string]*Relationship{}},
		cacheStore:       cacheStore,
		namer:            namer,
		initialized:      make(chan struct{}),
	}

- OpenOffice/LibreOffice documents
- RTF, WordPerfect

#### PDFs and Images
- PDF documents (text and metadata extraction)
- Images (JPEG, PNG, GIF, TIFF, BMP)
- Image metadata (EXIF, IPTC, XMP)

#### Archives and Compressed Files
- ZIP, TAR, GZ archives
- LHA compression format
- Nested archive extraction

#### Web and Markup
- HTML, XHTML with XPath support
- XML documents