om/blog/building-a-machine-learning-microservice-with-fastapi/ title: Building a Machine Learning Microservice with FastAPI - author: Ravgeet Dhillon - Twilio link: https://www.twilio.com/en-us/blog/booking-appointments-twilio-notion-fastapi title: Booking Appointments with Twilio, Notion, and FastAPI - author: Abhinav Tripathi - Microsoft Blogs link: https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-python-and-fastapi/ title: Write a Python data layer with Azure Cosmos DB and FastAPI - author:...

          "intervalFactor": 1,
          "legendFormat": "{{instance}}",
          "metric": "process_start_time_seconds",
          "refId": "A",
          "step": 60
        }
      ],
      "title": "Uptime",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "description": "",
      "fieldConfig": {

    * اعتبارسنجی، حتی برای اشیاء JSON تو در تو.
* <abbr title="serialization, parsing, marshalling">تبدیل</abbr> داده ورودی: که از شبکه رسیده به انواع و داد‌ه‌ پایتونی. این داده‌ شامل:
    * JSON.
    * <abbr title="Path parameters">پارامترهای مسیر</abbr>.
    * <abbr title="Query parameters">پارامترهای پرسمان</abbr>.
    * <abbr title="Cookies">کوکی‌ها</abbr>.
    * <abbr title="Headers">سرآیند‌ها (هدرها)</abbr>.

    }

    public void test_convertWildcardQuery_searchField() throws Exception {
        // Test with search field (title)
        QueryContext queryContext = new QueryContext("title:test*", false);
        WildcardQuery wildcardQuery = new WildcardQuery(new Term("title", "test*"));

        QueryBuilder queryBuilder = queryCommand.convertWildcardQuery(queryContext, wildcardQuery, 1.5f);

          "intervalFactor": 1,
          "legendFormat": "",
          "metric": "process_start_time_seconds",
          "refId": "A",
          "step": 60
        }
      ],
      "title": "Total Drives",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "description": "",
      "fieldConfig": {

### 🗄 `APIRouter`

👆 🗄 ⚫️ & ✍ "👐" 🎏 🌌 👆 🔜 ⏮️ 🎓 `FastAPI`:

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../docs_src/bigger_applications/app/routers/users.py!}
```

### *➡ 🛠️* ⏮️ `APIRouter`

& ⤴️ 👆 ⚙️ ⚫️ 📣 👆 *➡ 🛠️*.

⚙️ ⚫️ 🎏 🌌 👆 🔜 ⚙️ `FastAPI` 🎓:

```Python hl_lines="6  11  16" title="app/routers/users.py"
{!../../docs_src/bigger_applications/app/routers/users.py!}
```

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../docs_src/bigger_applications/app/routers/users.py!}
```

### *Path operations* with `APIRouter` { #path-operations-with-apirouter }

And then you use it to declare your *path operations*.

Use it the same way you would use the `FastAPI` class:

```Python hl_lines="6  11  16" title="app/routers/users.py"

<img src="/img/tutorial/path-params/image03.png">

### Mit Python-*<abbr title="Enumeration – Aufzählung">Enums</abbr>* arbeiten

Der *Pfad-Parameter* wird ein *<abbr title="Member – Mitglied: Einer der möglichen Werte einer Enumeration">Member</abbr> eines Enums* sein.

#### *Enum-Member* vergleichen

* ожидание завершения операции с базой данных
* получение результатов запроса к базе данных
* и т. д.

Поскольку в основном время тратится на ожидание выполнения операций <abbr title="Ввода-вывода">I/O</abbr>,
их обычно называют операциями, <abbr title="I/O bound">ограниченными скоростью ввода-вывода</abbr>.

Код называют "асинхронным", потому что компьютеру / программе не требуется "синхронизироваться" с медленной задачей и,

          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{bucket,range}}",
          "refId": "A",
          "step": 300
        }
      ],
      "title": "Object Size Distribution",
      "type": "bargauge"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {