* Construisez votre image FastAPI :

<div class="termy">

```console
$ docker build -t myimage .

---> 100%
```

</div>

## Démarrer le conteneur Docker

* Exécutez un conteneur basé sur votre image :

<div class="termy">

```console
$ docker run -d --name mycontainer -p 80:80 myimage
```

</div>

                return true;
            });
        }
        return Collections.emptyList();
    }

    private String toLowerCase(final String term) {
        return term != null ? term.toLowerCase(Locale.ROOT) : term;
    }

# Run a Server Manually

## Use the `fastapi run` Command

In short, use `fastapi run` to serve your FastAPI application:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

        });

    }

    protected void setupListCondition(final KeyMatchCB cb, final KeyMatchPager keyMatchPager) {
        if (StringUtil.isNotBlank(keyMatchPager.term)) {
            cb.query().setTerm_Wildcard(wrapQuery(keyMatchPager.term));
        }
        if (StringUtil.isNotBlank(keyMatchPager.query)) {
            cb.query().setQuery_Wildcard(wrapQuery(keyMatchPager.query));
        }

    }

    protected void setupListCondition(final RelatedQueryCB cb, final RelatedQueryPager relatedQueryPager) {
        if (StringUtil.isNotBlank(relatedQueryPager.term)) {
            cb.query().setTerm_Wildcard(wrapQuery(relatedQueryPager.term));
        }
        if (StringUtil.isNotBlank(relatedQueryPager.queries)) {
            cb.query().setQueries_Wildcard(wrapQuery(relatedQueryPager.queries));
        }

```
fastapi>=0.68.0,<0.69.0
pydantic>=1.8.0,<2.0.0
uvicorn>=0.15.0,<0.16.0
```

E você normalmente instalaria essas dependências de pacote com `pip`, por exemplo:

<div class="termy">

```console
$ pip install -r requirements.txt
---> 100%
Successfully installed fastapi pydantic uvicorn
```

</div>

/// info

            int offset = 0;
            while (stream.incrementToken()) {
                final CharTermAttribute att = stream.getAttribute(CharTermAttribute.class);
                final String term = att.toString();
                final int pos = inputStr.indexOf(term, offset);
                if (pos > 0) {
                    final String tmp = inputStr.substring(offset, pos);
                    kanaBuf.append(transliterator.transliterate(tmp));

    }

    @Override
    public String toString() {
        return "KeyMatch [boost=" + boost + ", createdBy=" + createdBy + ", createdTime=" + createdTime + ", maxSize=" + maxSize
                + ", query=" + query + ", term=" + term + ", updatedBy=" + updatedBy + ", updatedTime=" + updatedTime + ", docMeta="
                + docMeta + "]";
    }

Um eines der Beispiele auszuführen, kopieren Sie den Code in eine Datei `main.py`, und starten Sie `uvicorn` mit:

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)

Все блоки кода можно копировать и использовать напрямую (на самом деле это проверенные файлы Python).

Чтобы запустить любой из примеров, скопируйте код в файл `main.py` и запустите `uvicorn` с параметрами:

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)