false, false, false, "keyword", 0, 0, null, null, false, null, null, null, null, null, false);
    protected final ColumnInfo _columnReading = cci("reading", "reading", null, null, String.class, "reading", null, false, false, false,
            "keyword", 0, 0, null, null, false, null, null, null, null, null, false);

            }, this::asEditHtml);
        }
        if (form.segmentation != null && form.reading != null && form.segmentation.split(" ").length != form.reading.split(" ").length) {
            throwValidationError(messages -> {
                messages.addErrorsInvalidKuromojiSegmentation("segmentation", form.segmentation, form.reading);
            }, this::asEditHtml);
        }
    }

### Create Pydantic *models* / schemas for reading / returning

Now create Pydantic *models* (schemas) that will be used when reading data, when returning it from the API.

For example, before creating an item, we don't know what will be the ID assigned to it, but when reading it (when returning it from the API) we will already know its ID.

                    } else if (StringUtil.isBlank(reading) && StringUtil.isBlank(boost)) {
                        elevateWordBhv.delete(elevateWord);
                        final String id = elevateWord.getId();
                        elevateWordToLabelBhv.queryDelete(cb -> cb.query().setElevateWordId_Equal(id));
                    } else {
                        elevateWord.setReading(reading);

### Creating the `Settings` only once with `lru_cache`

Reading a file from disk is normally a costly (slow) operation, so you probably want to do it only once and then re-use the same settings object, instead of reading it for each request.

But every time we do:

```Python
Settings()
```

	// ensure that this error is sticky.
	err error
}

type fileReader interface {
	io.Reader
	fileState

	WriteTo(io.Writer) (int64, error)
}

// NewReader creates a new [Reader] reading from r.
func NewReader(r io.Reader) *Reader {
	return &Reader{r: r, curr: &regFileReader{r, 0}}
}

// Next advances to the next entry in the tar archive.

     * builds an empty map.
     *
     * <p>If the {@code resolve} parameter value is {@code false}, then some or all map values may
     * be null instead of the actual module name. This option can avoid the cost of reading module
     * descriptors when only the modules existence needs to be verified.</p>
     *
     * <p><b>Algorithm:</b>
     * If the given path is a directory, then there is a choice:
     * </p>
     * <ul>

    public void addElevateWord(final String word, final String reading, final String[] tags, final String[] permissions, final Float boost,
            final boolean apply) {
        final String[] readings;
        if (StringUtil.isBlank(reading)) {
            readings = word.replace("　", TEXT_SEP).replaceAll(TEXT_SEP + "+", TEXT_SEP).split(TEXT_SEP);
        } else {

     * @param test the test output directory, or {@code null} if none
     * @param cache cache of module information about each dependency
     * @throws IOException if an error occurred while reading module information
     *
     * TODO: this is currently not called
     */
    void addOutputDirectory(Path main, Path test, PathModularizationCache cache) throws IOException {
        if (outputModules != null) {

     * builds an empty map.
     *
     * <p>If the {@code resolve} parameter value is {@code false}, then some or all map values may
     * be null instead of the actual module name. This option can avoid the cost of reading module
     * descriptors when only the modules existence needs to be verified.</p>
     *
     * <p><b>Algorithm:</b>
     * If the given path is a directory, then there is a choice:
     * </p>
     * <ul>