/** The key of the message: Delete old user logs */
    public static final String LABELS_PURGE_USER_INFO_DAY = "{labels.purgeUserInfoDay}";

    /** The key of the message: Reading */
    public static final String LABELS_READING = "{labels.reading}";

    /** The key of the message: Role IDs */
    public static final String LABELS_ROLE_TYPE_IDS = "{labels.roleTypeIds}";

    /** The key of the message: Script */

///

### <a href="https://webargs.readthedocs.io/en/latest/" class="external-link" target="_blank">Webargs</a> { #webargs }

Another big feature required by APIs is <abbr title="reading and converting to Python data">parsing</abbr> data from incoming requests.

Webargs is a tool that was made to provide that on top of several frameworks, including Flask.

     *
     * @param inputStream the input stream to read from
     * @return the detected character set name, or null if not found
     * @throws CrawlingAccessException if an error occurs while reading the content
     */
    protected String loadCharset(final InputStream inputStream) {
        BufferedInputStream bis = null;
        String encoding = null;
        try {

  }

  private fun failConnection(e: IOException?) {
    close(ErrorCode.PROTOCOL_ERROR, ErrorCode.PROTOCOL_ERROR, e)
  }

  /**
   * Sends any initial frames and starts reading frames from the remote peer. This should be called
   * after [Builder.build] for all new connections.
   *
   * @param sendConnectionPreface true to send connection preface frames. This should always be true

    ImmutableList<String> ancestorParts = parts.subList(levels, parts.size());

    // levels equals the number of dots that are getting clipped away, then add the length of each
    // clipped part to get the length of the leading substring that is being removed.
    int substringFrom = levels;
    for (int i = 0; i < levels; i++) {
      substringFrom += parts.get(i).length();
    }
    String ancestorName = name.substring(substringFrom);

    * Introduced API `tf.saved_model.experimental.read_fingerprint(export_dir)` for reading the fingerprint of a SavedModel.
* `tf.random`
  * Added non-experimental aliases for `tf.random.split` and `tf.random.fold_in`, the experimental endpoints are still available so no code changes are necessary.

            int totalLen = testMessage.encode(buffer, 0);

            assertTrue(totalLen > testMessage.getLength());

            // Check next command offset was written
            int nextOffset = SMBUtil.readInt4(buffer, 20);
            assertTrue(nextOffset > 0);
        }

        @Test
        @DisplayName("Should sign chained messages with digest")
        void testEncodeChainedWithDigest() {

gain (about 100 nanoseconds), please note that in **FastAPI** the effect would be quite opposite. In these cases, it's better to use `async def` unless your *path operation functions* use code that performs blocking <abbr title="Input/Output: disk reading or writing, network communications.">I/O</abbr>.

Still, in both situations, chances are that **FastAPI** will [still be faster](index.md#performance){.internal-link target=_blank} than (or at least comparable to) your previous framework....

  @J2ktIncompatible
  @GwtIncompatible
    private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException {
    stream.defaultReadObject();
    @SuppressWarnings("unchecked")
    // reading data stored by writeObject
    Comparator<? super E> comparator = (Comparator<? super E>) requireNonNull(stream.readObject());
    deserializationReplacement = new TreeMultiset<>(comparator);

## Ready to Work { #ready-to-work }

Now you're ready to start working on your project.



/// tip

Do you want to understand what's all that above?

Continue reading. 👇🤓

///

## Why Virtual Environments { #why-virtual-environments }

To work with FastAPI you need to install <a href="https://www.python.org/" class="external-link" target="_blank">Python</a>.