type EditRangeResult<V, R = number> = {
    value?: V;
    break?: R;
    delete?: boolean;
};
/**
 * A reasonably fast collection of key-value pairs with a powerful API.
 * Largely compatible with the standard Map. BTree is a B+ tree data structure,
 * so the collection is sorted by key.
 *
 * B+ trees tend to use memory more efficiently than hashtables such as the
 * standard Map, especially when the collection contains a large number of
 * items. However, maintaining the sort order makes them modestly slower:
 * O(log size) rather than O(1). This B+ tree implementation supports O(1)
 * fast cloning. It also supports freeze(), which can be used to ensure that
 * a BTree is not changed accidentally.
 *
 * Confusingly, the ES6 Map.forEach(c) method calls c(value,key) instead of
 * c(key,value), in contrast to other methods such as set() and entries()
 * which put the key first. I can only assume that the order was reversed on
 * the theory that users would usually want to examine values and ignore keys.
 * BTree's forEach() therefore works the same way, but a second method
 * `.forEachPair((key,value)=>{...})` is provided which sends you the key
 * first and the value second; this method is slightly faster because it is
 * the "native" for-each method for this class.
 *
 * Out of the box, BTree supports keys that are numbers, strings, arrays of
 * numbers/strings, Date, and objects that have a valueOf() method returning a
 * number or string. Other data types, such as arrays of Date or custom
 * objects, require a custom comparator, which you must pass as the second
 * argument to the constructor (the first argument is an optional list of
 * initial items). Symbols cannot be used as keys because they are unordered
 * (one Symbol is never "greater" or "less" than another).
 *
 * @example
 * Given a {name: string, age: number} object, you can create a tree sorted by
 * name and then by age like this:
 *
 *     var tree = new BTree(undefined, (a, b) => {
 *       if (a.name > b.name)
 *         return 1; // Return a number >0 when a > b
 *       else if (a.name < b.name)
 *         return -1; // Return a number <0 when a < b
 *       else // names are equal (or incomparable)
 *         return a.age - b.age; // Return >0 when a.age > b.age
 *     });
 *
 *     tree.set({name:"Bill", age:17}, "happy");
 *     tree.set({name:"Fran", age:40}, "busy & stressed");
 *     tree.set({name:"Bill", age:55}, "recently laid off");
 *     tree.forEachPair((k, v) => {
 *       console.log(`Name: ${k.name} Age: ${k.age} Status: ${v}`);
 *     });
 *
 * @description
 * The "range" methods (`forEach, forRange, editRange`) will return the number
 * of elements that were scanned. In addition, the callback can return {break:R}
 * to stop early and return R from the outer function.
 *
 * - TODO: Test performance of preallocating values array at max size
 * - TODO: Add fast initialization when a sorted array is provided to constructor
 *
 * For more documentation see https://github.com/qwertie/btree-typescript
 *
 * Are you a C# developer? You might like the similar data structures I made for C#:
 * BDictionary, BList, etc. See http://core.loyc.net/collections/
 *
 * @author David Piepgrass
 */
export declare class BTree<K = any, V = any> {
    private _root;
    _size: number;
    _maxNodeSize: number;
    /**
     * provides a total order over keys (and a strict partial order over the type K)
     * @returns a negative value if a < b, 0 if a === b and a positive value if a > b
     */
    _compare: (a: K, b: K) => number;
    /**
     * Initializes an empty B+ tree.
     * @param compare Custom function to compare pairs of elements in the tree.
     *   If not specified, defaultComparator will be used which is valid as long as K extends DefaultComparable.
     * @param entries A set of key-value pairs to initialize the tree
     * @param maxNodeSize Branching factor (maximum items or children per node)
     *   Must be in range 4..256. If undefined or <4 then default is used; if >256 then 256.
     */
    constructor(compare: (a: K, b: K) => number, entries?: Array<[K, V]>, maxNodeSize?: number);
    /** Gets the number of key-value pairs in the tree. */
    get size(): number;
    /** Gets the number of key-value pairs in the tree. */
    get length(): number;
    /** Returns true iff the tree contains no key-value pairs. */
    get isEmpty(): boolean;
    /** Releases the tree so that its size is 0. */
    clear(): void;
    /**
     * Finds a pair in the tree and returns the associated value.
     * @param defaultValue a value to return if the key was not found.
     * @returns the value, or defaultValue if the key was not found.
     * @description Computational complexity: O(log size)
     */
    get(key: K, defaultValue?: V): V | undefined;
    /**
     * Adds or overwrites a key-value pair in the B+ tree.
     * @param key the key is used to determine the sort order of
     *        data in the tree.
     * @param value data to associate with the key (optional)
     * @param overwrite Whether to overwrite an existing key-value pair
     *        (default: true). If this is false and there is an existing
     *        key-value pair then this method has no effect.
     * @returns true if a new key-value pair was added.
     * @description Computational complexity: O(log size)
     * Note: when overwriting a previous entry, the key is updated
     * as well as the value. This has no effect unless the new key
     * has data that does not affect its sort order.
     */
    set(key: K, value: V, overwrite?: boolean): boolean;
    /**
     * Returns true if the key exists in the B+ tree, false if not.
     * Use get() for best performance; use has() if you need to
     * distinguish between "undefined value" and "key not present".
     * @param key Key to detect
     * @description Computational complexity: O(log size)
     */
    has(key: K): boolean;
    /**
     * Removes a single key-value pair from the B+ tree.
     * @param key Key to find
     * @returns true if a pair was found and removed, false otherwise.
     * @description Computational complexity: O(log size)
     */
    delete(key: K): boolean;
    /** Returns the maximum number of children/values before nodes will split. */
    get maxNodeSize(): number;
    /** Gets the lowest key in the tree. Complexity: O(log size) */
    minKey(): K | undefined;
    /** Gets the highest key in the tree. Complexity: O(1) */
    maxKey(): K | undefined;
    /** Gets an array of all keys, sorted */
    keysArray(): K[];
    /** Returns the next pair whose key is larger than the specified key (or undefined if there is none).
     * If key === undefined, this function returns the lowest pair.
     * @param key The key to search for.
     * @param reusedArray Optional array used repeatedly to store key-value pairs, to
     * avoid creating a new array on every iteration.
     */
    nextHigherPair(key: K | undefined, reusedArray?: [K, V]): [K, V] | undefined;
    /** Returns the next key larger than the specified key, or undefined if there is none.
     *  Also, nextHigherKey(undefined) returns the lowest key.
     */
    nextHigherKey(key: K | undefined): K | undefined;
    /** Returns the next pair whose key is smaller than the specified key (or undefined if there is none).
     *  If key === undefined, this function returns the highest pair.
     * @param key The key to search for.
     * @param reusedArray Optional array used repeatedly to store key-value pairs, to
     *        avoid creating a new array each time you call this method.
     */
    nextLowerPair(key: K | undefined, reusedArray?: [K, V]): [K, V] | undefined;
    /** Returns the next key smaller than the specified key, or undefined if there is none.
     *  Also, nextLowerKey(undefined) returns the highest key.
     */
    nextLowerKey(key: K | undefined): K | undefined;
    /** Adds all pairs from a list of key-value pairs.
     * @param pairs Pairs to add to this tree. If there are duplicate keys,
     *        later pairs currently overwrite earlier ones (e.g. [[0,1],[0,7]]
     *        associates 0 with 7.)
     * @param overwrite Whether to overwrite pairs that already exist (if false,
     *        pairs[i] is ignored when the key pairs[i][0] already exists.)
     * @returns The number of pairs added to the collection.
     * @description Computational complexity: O(pairs.length * log(size + pairs.length))
     */
    setPairs(pairs: Array<[K, V]>, overwrite?: boolean): number;
    forRange(low: K, high: K, includeHigh: boolean, onFound?: (k: K, v: V, counter: number) => void, initialCounter?: number): number;
    /**
     * Scans and potentially modifies values for a subsequence of keys.
     * Note: the callback `onFound` should ideally be a pure function.
     *   Specfically, it must not insert items, call clone(), or change
     *   the collection except via return value; out-of-band editing may
     *   cause an exception or may cause incorrect data to be sent to
     *   the callback (duplicate or missed items). It must not cause a
     *   clone() of the collection, otherwise the clone could be modified
     *   by changes requested by the callback.
     * @param low The first key scanned will be greater than or equal to `low`.
     * @param high Scanning stops when a key larger than this is reached.
     * @param includeHigh If the `high` key is present, `onFound` is called for
     *        that final pair if and only if this parameter is true.
     * @param onFound A function that is called for each key-value pair. This
     *        function can return `{value:v}` to change the value associated
     *        with the current key, `{delete:true}` to delete the current pair,
     *        `{break:R}` to stop early with result R, or it can return nothing
     *        (undefined or {}) to cause no effect and continue iterating.
     *        `{break:R}` can be combined with one of the other two commands.
     *        The third argument `counter` is the number of items iterated
     *        previously; it equals 0 when `onFound` is called the first time.
     * @returns The number of values scanned, or R if the callback returned
     *        `{break:R}` to stop early.
     * @description
     *   Computational complexity: O(number of items scanned + log size)
     *   Note: if the tree has been cloned with clone(), any shared
     *   nodes are copied before `onFound` is called. This takes O(n) time
     *   where n is proportional to the amount of shared data scanned.
     */
    editRange<R = V>(low: K, high: K, includeHigh: boolean, onFound: (k: K, v: V, counter: number) => EditRangeResult<V, R> | void, initialCounter?: number): R | number;
}
export {};