That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md).

// Copyright 2014 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package asm

import (
	"fmt"
	"internal/abi"
	"strconv"
	"strings"
	"text/scanner"

	"cmd/asm/internal/arch"
	"cmd/asm/internal/flags"
	"cmd/asm/internal/lex"
	"cmd/internal/obj"
	"cmd/internal/obj/arm64"
	"cmd/internal/obj/ppc64"
	"cmd/internal/obj/riscv"

// Copyright 2024 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// This file is for validation errors only, i.e., errors reported by the validate function.
// Negative test cases for errors generated earlier in the assembler's preprocess stage
// should be added to riscv64error.s.  If they are added to this file, they will prevent

Ça, ajouté au fait que Python soit le langage le plus populaire pour la **Data Science**, le **Machine Learning** et surtout le **Deep Learning**, font de **FastAPI** un très bon choix pour les APIs et applications de **Data Science** / **Machine Learning**.

Pour comprendre comment mettre en place ce parallélisme en production, allez lire la section [Déploiement](deployment/index.md).

* [`orjson`](https://github.com/ijl/orjson) - потрібно, якщо ви хочете використовувати `ORJSONResponse`.
* [`ujson`](https://github.com/esnme/ultrajson) - потрібно, якщо ви хочете використовувати `UJSONResponse`.

## Ліцензія { #license }

    "tf_cuda_tests_tags",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

tf_cuda_library(
    name = "c_api",
    srcs = [
        "c_api.cc",
        "c_api_debug.cc",
        "c_api_experimental.h",
        "c_api_internal.h",

/*! bootstrap-timepicker v0.5.2 
* http://jdewit.github.com/bootstrap-timepicker 
* Copyright (c) 2016 Joris de Wit and bootstrap-timepicker contributors 
* MIT License 

Це, плюс простий факт, що Python є основною мовою для **Data Science**, машинного навчання і особливо глибокого навчання, робить FastAPI дуже вдалим вибором для веб API та застосунків Data Science / машинного навчання (серед багатьох інших).

Щоб побачити, як досягти цього паралелізму у продакшні, див. розділ про [Розгортання](deployment/index.md).

/*!
 * Font Awesome Free 5.12.0 by @fontawesome - https://fontawesome.com
 * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
 */

* [`orjson`](https://github.com/ijl/orjson) – erforderlich, wenn Sie `ORJSONResponse` verwenden möchten.
* [`ujson`](https://github.com/esnme/ultrajson) – erforderlich, wenn Sie `UJSONResponse` verwenden möchten.

## Lizenz { #license }