import pytest
from dirty_equals import IsDict, IsInt
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from sqlalchemy import StaticPool
from sqlmodel import SQLModel, create_engine
from sqlmodel.main import default_registry

from tests.utils import needs_py39, needs_py310


def clear_sqlmodel():
    # Clear the tables in the metadata for the default base model
    SQLModel.metadata.clear()

Now you know that you have to fix it, convert `age` to a string with `str(age)`:

{* ../../docs_src/python_types/tutorial004.py hl[2] *}

## Declaring types

You just saw the main place to declare type hints. As function parameters.

This is also the main place you would use them with **FastAPI**.

### Simple types

You can declare all the standard Python types, not only `str`.

You can use, for example:

* `int`

Job makePolicyJob makePolicyJob: podAnnotations: annotations: securityContext: enabled: false runAsUser: 1000 runAsGroup: 1000 fsGroup: 1000 resources: requests: memory: 128Mi nodeSelector: {} tolerations: [] affinity: {} # Command to run after the main command on exit exitCommand: "" ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies...

makePolicyJob makePolicyJob: podAnnotations: {} annotations: {} securityContext: enabled: false runAsUser: 1000 runAsGroup: 1000 fsGroup: 1000 resources: requests: memory: 128Mi nodeSelector: {} tolerations: [] affinity: {} # Command to run after the main command on exit exitCommand: "" ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies...

Job makePolicyJob makePolicyJob: podAnnotations: annotations: securityContext: enabled: false runAsUser: 1000 runAsGroup: 1000 fsGroup: 1000 resources: requests: memory: 128Mi nodeSelector: {} tolerations: [] affinity: {} # Command to run after the main command on exit exitCommand: "" ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies...

        new CyclicBarrier(
            6 // for the setter threads
                + 50 // for the listeners
                + 50 // for the blocking get threads,
                + 1); // for the main thread
    final ExecutorService executor = Executors.newFixedThreadPool(barrier.getParties());
    final AtomicReference<AbstractFuture<String>> currentFuture = Atomics.newReference();

    // need a long enough string for the buffer to hit 0 remaining before the copy completes
    String string = Strings.repeat("0123456789", 100);
    StringBuilder b = new StringBuilder();
    // the main assertion of this test is here... the copy will fail if the buffer size goes down
    // each time it is not filled completely
    long copied = CharStreams.copy(newNonBufferFillingReader(new StringReader(string)), b);

    private BelowAll() {
      /*
       * No code ever sees this bogus value for `endpoint`: This class overrides both methods that
       * use the `endpoint` field, compareTo() and endpoint(). Additionally, the main implementation
       * of Cut.compareTo checks for belowAll before reading accessing `endpoint` on another Cut
       * instance.
       */
      super("");
    }

    @Override

    // need a long enough string for the buffer to hit 0 remaining before the copy completes
    String string = Strings.repeat("0123456789", 100);
    StringBuilder b = new StringBuilder();
    // the main assertion of this test is here... the copy will fail if the buffer size goes down
    // each time it is not filled completely
    long copied = CharStreams.copy(newNonBufferFillingReader(new StringReader(string)), b);

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.