bump

docs/concepts/caching.md

@@ -33,12 +33,12 @@ def extract(data) -> UserDetail:
 start = time.perf_counter()  # (1)
 model = extract("Extract jason is 25 years old")
 print(f"Time taken: {time.perf_counter() - start}")
-#> Time taken: 0.5028559579513967
+#> Time taken: 0.6282629589550197
 
 start = time.perf_counter()
 model = extract("Extract jason is 25 years old")  # (2)
 print(f"Time taken: {time.perf_counter() - start}")
-#> Time taken: 1.0831281542778015e-06
+#> Time taken: 1.9171275198459625e-06
 ```
 
 1. Using `time.perf_counter()` to measure the time taken to run the function is better than using `time.time()` because it's more accurate and less susceptible to system clock changes.

docs/concepts/fields.md

@@ -100,12 +100,11 @@ These all work as great opportunities to add more information to the JSON schema
 Here's an example:
 
 ```py
-from pydantic import BaseModel, EmailStr, Field, SecretStr
+from pydantic import BaseModel, Field, SecretStr
 
 
 class User(BaseModel):
     age: int = Field(description='Age of the user')
-    email: EmailStr = Field(examples=['[email protected]'])
     name: str = Field(title='Username')
     password: SecretStr = Field(
         json_schema_extra={
@@ -121,12 +120,6 @@ print(User.model_json_schema())
 {
     'properties': {
         'age': {'description': 'Age of the user', 'title': 'Age', 'type': 'integer'},
-        'email': {
-            'examples': ['[email protected]'],
-            'format': 'email',
-            'title': 'Email',
-            'type': 'string',
-        },
         'name': {'title': 'Username', 'type': 'string'},
         'password': {
             'description': 'Password of the user',
@@ -137,14 +130,14 @@ print(User.model_json_schema())
             'writeOnly': True,
         },
     },
-    'required': ['age', 'email', 'name', 'password'],
+    'required': ['age', 'name', 'password'],
     'title': 'User',
     'type': 'object',
 }
 """
 ```
 
-## General notes on JSON schema generation
+# General notes on JSON schema generation
 
 - The JSON schema for Optional fields indicates that the value null is allowed.
 - The Decimal type is exposed in JSON schema (and serialized) as a string.

docs/concepts/lists.md

@@ -160,7 +160,7 @@ async def print_iterable_results():
     async for m in model:
         print(m)
         #> name='John Doe' age=30
-        #> name='Jane Doe' age=35
+        #> name='Jane Smith' age=25
 
 
 import asyncio