String[] values = data.getValues("nonexistent");
        assertNull(values);
    }

    public void test_getKeySet() {
        // Test getKeySet method
        ExtractData data = new ExtractData();

        data.putValue("key1", "value1");
        data.putValue("key2", "value2");
        data.putValue("key3", "value3");

        Set<String> keySet = data.getKeySet();

        elif isinstance(item, dict):
            assert len(item) == 1
            values = list(item.values())
            if not values:
                continue
            if isinstance(values[0], str):
                resolve_file(item=values[0], files=files, config=config)
            elif isinstance(values[0], list):
                resolve_files(items=values[0], files=files, config=config)
            else:

        final String value = decodeId(id);
        final String[] values = split(value, "/").get(stream -> stream.filter(StringUtil::isNotEmpty).toArray(n -> new String[n]));
        if (values.length == 0) {
            // invalid?
            return new PathInfo(StringUtil.EMPTY, StringUtil.EMPTY);
        }
        if (values.length == 1) {

        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity()) {
        assertWithMessage("mean of %s", values).that(mean).isPositiveInfinity();
        assertWithMessage("mean by addAll(Stats) of %s", values)
            .that(meanByAddAllStats)
            .isPositiveInfinity();
      } else if (values.hasAnyNegativeInfinity()) {

    public void test_parsePath() {
        String[] values;

        values = gcsClient.parsePath("bucket/path");
        assertEquals("bucket", values[0]);
        assertEquals("path", values[1]);

        values = gcsClient.parsePath("bucket/path1/path2");
        assertEquals("bucket", values[0]);
        assertEquals("path1/path2", values[1]);

        values = gcsClient.parsePath("bucket/");

        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =

        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);
      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =

            final String[] values = sort.split("\\.");
            final boolean asc;
            if (values.length > 1) {
                asc = !"desc".equalsIgnoreCase(values[1]);
            } else {
                asc = true;
            }
            if (values.length > 0) {
                if ("term".equals(values[0]) || "key".equals(values[0])) {
                    return BucketOrder.key(asc);

    if is_sequence_field(field) and isinstance(values, (ImmutableMultiDict, Headers)):
        value = values.getlist(alias)
    else:
        value = values.get(alias, None)
    if (
        value is None
        or (
            isinstance(field.field_info, params.Form)
            and isinstance(value, str)  # For type checks
            and value == ""
        )

* Retrieve the stored data.
* Put that data in a Pydantic model.
* Generate a `dict` without default values from the input model (using `exclude_unset`).
    * This way you can update only the values actually set by the user, instead of overriding values already stored with default values in your model.
* Create a copy of the stored model, updating its attributes with the received partial updates (using the `update` parameter).