📝 Use dfn tag for definitions instead of abbr in docs (fastapi#14744)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Sebastián Ramírez <tiangolo@gmail.com>

Author: 3 people

README.md

@@ -34,7 +34,7 @@ The key features are:
 * **Fast**: Very high performance, on par with **NodeJS** and **Go** (thanks to Starlette and Pydantic). [One of the fastest Python frameworks available](#performance).
 * **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
 * **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
-* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
+* **Intuitive**: Great editor support. <dfn title="also known as auto-complete, autocompletion, IntelliSense">Completion</dfn> everywhere. Less time debugging.
 * **Easy**: Designed to be easy to use and learn. Less time reading docs.
 * **Short**: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
 * **Robust**: Get production-ready code. With automatic interactive documentation.
@@ -371,15 +371,15 @@ item: Item
 * Validation of data:
     * Automatic and clear errors when the data is invalid.
     * Validation even for deeply nested JSON objects.
-* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
+* <dfn title="also known as: serialization, parsing, marshalling">Conversion</dfn> of input data: coming from the network to Python data and types. Reading from:
     * JSON.
     * Path parameters.
     * Query parameters.
     * Cookies.
     * Headers.
     * Forms.
     * Files.
-* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of output data: converting from Python data and types to network data (as JSON):
+* <dfn title="also known as: serialization, parsing, marshalling">Conversion</dfn> of output data: converting from Python data and types to network data (as JSON):
     * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
     * `datetime` objects.
     * `UUID` objects.
@@ -442,7 +442,7 @@ For a more complete example including more features, see the <a href="https://fa
 
 * Declaration of **parameters** from other different places as: **headers**, **cookies**, **form fields** and **files**.
 * How to set **validation constraints** as `maximum_length` or `regex`.
-* A very powerful and easy to use **<abbr title="also known as components, resources, providers, services, injectables">Dependency Injection</abbr>** system.
+* A very powerful and easy to use **<dfn title="also known as components, resources, providers, services, injectables">Dependency Injection</dfn>** system.
 * Security and authentication, including support for **OAuth2** with **JWT tokens** and **HTTP Basic** auth.
 * More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
 * **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
@@ -527,7 +527,7 @@ Used by Starlette:
 
 * <a href="https://www.python-httpx.org" target="_blank"><code>httpx</code></a> - Required if you want to use the `TestClient`.
 * <a href="https://jinja.palletsprojects.com" target="_blank"><code>jinja2</code></a> - Required if you want to use the default template configuration.
-* <a href="https://github.com/Kludex/python-multipart" target="_blank"><code>python-multipart</code></a> - Required if you want to support form <abbr title="converting the string that comes from an HTTP request into Python data">"parsing"</abbr>, with `request.form()`.
+* <a href="https://github.com/Kludex/python-multipart" target="_blank"><code>python-multipart</code></a> - Required if you want to support form <dfn title="converting the string that comes from an HTTP request into Python data">"parsing"</dfn>, with `request.form()`.
 
 Used by FastAPI:
 

docs/en/docs/advanced/dataclasses.md

@@ -64,7 +64,7 @@ In that case, you can simply swap the standard `dataclasses` with `pydantic.data
 
 6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.
 
-    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.
+    FastAPI is still capable of <dfn title="converting the data to a format that can be transmitted">serializing</dfn> the data to JSON.
 
 7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.
 

docs/en/docs/advanced/path-operation-advanced-configuration.md

@@ -141,7 +141,7 @@ You could do that with `openapi_extra`:
 
 {* ../../docs_src/path_operation_advanced_configuration/tutorial006_py39.py hl[19:36, 39:40] *}
 
-In this example, we didn't declare any Pydantic model. In fact, the request body is not even <abbr title="converted from some plain format, like bytes, into Python objects">parsed</abbr> as JSON, it is read directly as `bytes`, and the function `magic_data_reader()` would be in charge of parsing it in some way.
+In this example, we didn't declare any Pydantic model. In fact, the request body is not even <dfn title="converted from some plain format, like bytes, into Python objects">parsed</dfn> as JSON, it is read directly as `bytes`, and the function `magic_data_reader()` would be in charge of parsing it in some way.
 
 Nevertheless, we can declare the expected schema for the request body.
 

docs/en/docs/alternatives.md

@@ -137,15 +137,15 @@ There are several Flask REST frameworks, but after investing the time and work i
 
 ### <a href="https://marshmallow.readthedocs.io/en/stable/" class="external-link" target="_blank">Marshmallow</a> { #marshmallow }
 
-One of the main features needed by API systems is data "<abbr title="also called marshalling, conversion">serialization</abbr>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.
+One of the main features needed by API systems is data "<dfn title="also called marshalling, conversion">serialization</dfn>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.
 
 Another big feature needed by APIs is data validation, making sure that the data is valid, given certain parameters. For example, that some field is an `int`, and not some random string. This is especially useful for incoming data.
 
 Without a data validation system, you would have to do all the checks by hand, in code.
 
 These features are what Marshmallow was built to provide. It is a great library, and I have used it a lot before.
 
-But it was created before there existed Python type hints. So, to define every <abbr title="the definition of how data should be formed">schema</abbr> you need to use specific utils and classes provided by Marshmallow.
+But it was created before there existed Python type hints. So, to define every <dfn title="the definition of how data should be formed">schema</dfn> you need to use specific utils and classes provided by Marshmallow.
 
 /// check | Inspired **FastAPI** to
 
@@ -155,7 +155,7 @@ Use code to define "schemas" that provide data types and validation, automatical
 
 ### <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.
+Another big feature required by APIs is <dfn title="reading and converting to Python data">parsing</dfn> data from incoming requests.
 
 Webargs is a tool that was made to provide that on top of several frameworks, including Flask.
 
@@ -419,7 +419,7 @@ Handle all the data validation, data serialization and automatic model documenta
 
 ### <a href="https://www.starlette.dev/" class="external-link" target="_blank">Starlette</a> { #starlette }
 
-Starlette is a lightweight <abbr title="The new standard for building asynchronous Python web applications">ASGI</abbr> framework/toolkit, which is ideal for building high-performance asyncio services.
+Starlette is a lightweight <dfn title="The new standard for building asynchronous Python web applications">ASGI</dfn> framework/toolkit, which is ideal for building high-performance asyncio services.
 
 It is very simple and intuitive. It's designed to be easily extensible, and have modular components.
 

docs/en/docs/css/custom.css

@@ -203,3 +203,8 @@ Inspired by Termynal's CSS tricks with modifications
   -webkit-box-shadow: 25px 0 0 #f4c025, 50px 0 0 #3ec930;
           box-shadow: 25px 0 0 #f4c025, 50px 0 0 #3ec930;
 }
+
+.md-typeset dfn {
+  border-bottom: .05rem dotted var(--md-default-fg-color--light);
+  cursor: help;
+}

docs/en/docs/deployment/docker.md

@@ -454,7 +454,7 @@ Without using containers, making applications run on startup and with restarts c
 
 ## Replication - Number of Processes { #replication-number-of-processes }
 
-If you have a <abbr title="A group of machines that are configured to be connected and work together in some way.">cluster</abbr> of machines with **Kubernetes**, Docker Swarm Mode, Nomad, or another similar complex system to manage distributed containers on multiple machines, then you will probably want to **handle replication** at the **cluster level** instead of using a **process manager** (like Uvicorn with workers) in each container.
+If you have a <dfn title="A group of machines that are configured to be connected and work together in some way.">cluster</dfn> of machines with **Kubernetes**, Docker Swarm Mode, Nomad, or another similar complex system to manage distributed containers on multiple machines, then you will probably want to **handle replication** at the **cluster level** instead of using a **process manager** (like Uvicorn with workers) in each container.
 
 One of those distributed container management systems like Kubernetes normally has some integrated way of handling **replication of containers** while still supporting **load balancing** for the incoming requests. All at the **cluster level**.
 

docs/en/docs/deployment/https.md

@@ -65,7 +65,7 @@ Here's an example of how an HTTPS API could look like, step by step, paying atte
 
 It would probably all start by you **acquiring** some **domain name**. Then, you would configure it in a DNS server (possibly your same cloud provider).
 
-You would probably get a cloud server (a virtual machine) or something similar, and it would have a <abbr title="That doesn't change">fixed</abbr> **public IP address**.
+You would probably get a cloud server (a virtual machine) or something similar, and it would have a <dfn title="Doesn't change over time. Not dynamic.">fixed</dfn> **public IP address**.
 
 In the DNS server(s) you would configure a record (an "`A record`") to point **your domain** to the public **IP address of your server**.
 

docs/en/docs/features.md

@@ -6,7 +6,7 @@
 
 ### Based on open standards { #based-on-open-standards }
 
-* <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank"><strong>OpenAPI</strong></a> for API creation, including declarations of <abbr title="also known as: endpoints, routes">path</abbr> <abbr title="also known as HTTP methods, as POST, GET, PUT, DELETE">operations</abbr>, parameters, request bodies, security, etc.
+* <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank"><strong>OpenAPI</strong></a> for API creation, including declarations of <dfn title="also known as: endpoints, routes">path</dfn> <dfn title="also known as HTTP methods, as POST, GET, PUT, DELETE">operations</dfn>, parameters, request bodies, security, etc.
 * Automatic data model documentation with <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (as OpenAPI itself is based on JSON Schema).
 * Designed around these standards, after a meticulous study. Instead of an afterthought layer on top.
 * This also allows using automatic **client code generation** in many languages.
@@ -136,7 +136,7 @@ All built as reusable tools and components that are easy to integrate with your
 
 ### Dependency Injection { #dependency-injection }
 
-FastAPI includes an extremely easy to use, but extremely powerful <abbr title='also known as "components", "resources", "services", "providers"'><strong>Dependency Injection</strong></abbr> system.
+FastAPI includes an extremely easy to use, but extremely powerful <dfn title='also known as "components", "resources", "services", "providers"'><strong>Dependency Injection</strong></dfn> system.
 
 * Even dependencies can have dependencies, creating a hierarchy or **"graph" of dependencies**.
 * All **automatically handled** by the framework.
@@ -153,8 +153,8 @@ Any integration is designed to be so simple to use (with dependencies) that you
 
 ### Tested { #tested }
 
-* 100% <abbr title="The amount of code that is automatically tested">test coverage</abbr>.
-* 100% <abbr title="Python type annotations, with this your editor and external tools can give you better support">type annotated</abbr> code base.
+* 100% <dfn title="The amount of code that is automatically tested">test coverage</dfn>.
+* 100% <dfn title="Python type annotations, with this your editor and external tools can give you better support">type annotated</dfn> code base.
 * Used in production applications.
 
 ## Starlette features { #starlette-features }
@@ -190,7 +190,7 @@ With **FastAPI** you get all of **Pydantic**'s features (as FastAPI is based on
 * **No brainfuck**:
     * No new schema definition micro-language to learn.
     * If you know Python types you know how to use Pydantic.
-* Plays nicely with your **<abbr title="Integrated Development Environment: similar to a code editor">IDE</abbr>/<abbr title="A program that checks for code errors">linter</abbr>/brain**:
+* Plays nicely with your **<abbr title="Integrated Development Environment: similar to a code editor">IDE</abbr>/<dfn title="A program that checks for code errors">linter</dfn>/brain**:
     * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
 * Validate **complex structures**:
     * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.

docs/en/docs/index.md

@@ -40,7 +40,7 @@ The key features are:
 * **Fast**: Very high performance, on par with **NodeJS** and **Go** (thanks to Starlette and Pydantic). [One of the fastest Python frameworks available](#performance).
 * **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
 * **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
-* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
+* **Intuitive**: Great editor support. <dfn title="also known as auto-complete, autocompletion, IntelliSense">Completion</dfn> everywhere. Less time debugging.
 * **Easy**: Designed to be easy to use and learn. Less time reading docs.
 * **Short**: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
 * **Robust**: Get production-ready code. With automatic interactive documentation.
@@ -368,15 +368,15 @@ item: Item
 * Validation of data:
     * Automatic and clear errors when the data is invalid.
     * Validation even for deeply nested JSON objects.
-* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
+* <dfn title="also known as: serialization, parsing, marshalling">Conversion</dfn> of input data: coming from the network to Python data and types. Reading from:
     * JSON.
     * Path parameters.
     * Query parameters.
     * Cookies.
     * Headers.
     * Forms.
     * Files.
-* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of output data: converting from Python data and types to network data (as JSON):
+* <dfn title="also known as: serialization, parsing, marshalling">Conversion</dfn> of output data: converting from Python data and types to network data (as JSON):
     * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
     * `datetime` objects.
     * `UUID` objects.
@@ -439,7 +439,7 @@ For a more complete example including more features, see the <a href="https://fa
 
 * Declaration of **parameters** from other different places as: **headers**, **cookies**, **form fields** and **files**.
 * How to set **validation constraints** as `maximum_length` or `regex`.
-* A very powerful and easy to use **<abbr title="also known as components, resources, providers, services, injectables">Dependency Injection</abbr>** system.
+* A very powerful and easy to use **<dfn title="also known as components, resources, providers, services, injectables">Dependency Injection</dfn>** system.
 * Security and authentication, including support for **OAuth2** with **JWT tokens** and **HTTP Basic** auth.
 * More advanced (but equally easy) techniques for declaring **deeply nested JSON models** (thanks to Pydantic).
 * **GraphQL** integration with <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> and other libraries.
@@ -524,7 +524,7 @@ Used by Starlette:
 
 * <a href="https://www.python-httpx.org" target="_blank"><code>httpx</code></a> - Required if you want to use the `TestClient`.
 * <a href="https://jinja.palletsprojects.com" target="_blank"><code>jinja2</code></a> - Required if you want to use the default template configuration.
-* <a href="https://github.com/Kludex/python-multipart" target="_blank"><code>python-multipart</code></a> - Required if you want to support form <abbr title="converting the string that comes from an HTTP request into Python data">"parsing"</abbr>, with `request.form()`.
+* <a href="https://github.com/Kludex/python-multipart" target="_blank"><code>python-multipart</code></a> - Required if you want to support form <dfn title="converting the string that comes from an HTTP request into Python data">"parsing"</dfn>, with `request.form()`.
 
 Used by FastAPI: