# Patterned Date and Time

This feature, introduced in v0.35.0, allows parsing custom date and time formats into Python’s `date`, `time`, and `datetime` objects. For example, strings like `November 2, 2021` can now be parsed using customizable patterns – specified as format codes.

Key Features:

- Supports standard, timezone-aware, and UTC patterns.

- Annotate fields using `DatePattern`, `TimePattern`, or `DateTimePattern`.

- Retains ISO 8601 serialization for compatibility.

Supported Patterns:

> 1. Naive Patterns (default)

>      - `DatePattern`, `DateTimePattern`, `TimePattern`

> 2. Timezone-Aware Patterns

>      - `AwareDateTimePattern`, `AwareTimePattern`

> 3. UTC Patterns

>      - `UTCDateTimePattern`, `UTCTimePattern`

## Pattern Comparison

The following table compares the different types of date-time patterns: Naive, Timezone-Aware, and UTC patterns. It summarizes key features and example use cases for each.

Pattern Type | Key Characteristics | Example Use Cases
--- | --- | ---

Naive Patterns

No timezone info

- `DatePattern` (local date)

- `TimePattern` (local time)

- `DateTimePattern` (local datetime)

Timezone-Aware Patterns

Specifies a timezone

- `AwareDateTimePattern` (e.g., ‘Europe/London’)

- `AwareTimePattern` (timezone-aware time)

UTC Patterns

Interprets as UTC time

- `UTCDateTimePattern` (UTC datetime)

- `UTCTimePattern` (UTC time)

## Standard Date-Time Patterns

Hint

Note that the “naive” implementations `TimePattern` and `DateTimePattern` do not store timezone information – or `tzinfo` – on the de-serialized object (as explained in the Naive datetime concept). However, Timezone-Aware Date and Time Patterns do store this information.

Additionally, `date` does not have any timezone-related data, nor does its counterpart `DatePattern`.

To use, simply annotate fields with `DatePattern`, `TimePattern`, or `DateTimePattern` with supported format codes. These patterns support the most common date formats.

    from dataclass_wizard import DataclassWizard
    from dataclass_wizard.patterns import DatePattern, TimePattern

    class MyClass(DataclassWizard):
        date_field: DatePattern['%b %d, %Y']
        time_field: TimePattern['%I:%M %p']

    data = {'date_field': 'Jan 3, 2022', 'time_field': '3:45 PM'}
    c1 = MyClass.from_dict(data)
    print(c1)
    print(c1.to_dict())
    assert c1 == MyClass.from_dict(c1.to_dict())  # > True

## Timezone-Aware Date and Time Patterns

Hint

Timezone-aware date-time objects store timezone information, as detailed in the Timezone-aware section. This is accomplished using the built-in zoneinfo module in Python 3.9+.

Tip

On Windows, install `tzdata` with the `tz` extra:

    pip install dataclass-wizard[tz]

This is required because Windows does not ship IANA time zone data.

To handle timezone-aware `datetime` and `time` values, use the following patterns:

- `AwareDateTimePattern`

- `AwareTimePattern`

- `AwarePattern` (with `typing.Annotated`)

These patterns allow you to specify the timezone for the date and time, ensuring that the values are interpreted correctly relative to the given timezone.

Example: Using Timezone-Aware Patterns

    from dataclasses import dataclass
    from pprint import pprint
    from typing import Annotated

    from dataclass_wizard import Alias, fromdict, asdict
    from dataclass_wizard.patterns import AwareTimePattern, AwareDateTimePattern

    @dataclass
    class MyClass:
        my_aware_dt: AwareTimePattern['Europe/London', '%H:%M:%S']
        my_aware_dt2: Annotated[AwareDateTimePattern['Asia/Tokyo', '%m-%Y-%H:%M-%Z'], Alias('key')]

    d = {'my_aware_dt': '6:15:45', 'key': '10-2020-15:30-UTC'}
    c = fromdict(MyClass, d)

    pprint(c)
    print(asdict(c))
    assert c == fromdict(MyClass, asdict(c))  # > True

## UTC Date and Time Patterns

Hint

For UTC-specific time, use UTC patterns, which handle Coordinated Universal Time (UTC) as described in the UTC article.

For UTC-specific `datetime` and `time` values, use the following patterns:

- `UTCDateTimePattern`

- `UTCTimePattern`

- `UTCPattern` (with `typing.Annotated`)

These patterns are used when working with date and time in Coordinated Universal Time (UTC), and ensure that timezone data – or `tzinfo` – is correctly set to `UTC`.

Example: Using UTC Patterns

    from typing import Annotated

    from dataclass_wizard import Alias, DataclassWizard
    from dataclass_wizard.patterns import UTCTimePattern, UTCDateTimePattern

    class MyClass(DataclassWizard):
        my_utc_time: UTCTimePattern['%H:%M:%S']
        my_utc_dt: Annotated[UTCDateTimePattern['%m-%Y-%H:%M-%Z'], Alias('key')]

    d = {'my_utc_time': '6:15:45', 'key': '10-2020-15:30-UTC'}
    c = MyClass.from_dict(d)
    print(c)
    print(c.to_dict())

## Containers of Date and Time

For more complex annotations like `list[date]`, you can use `typing.Annotated` with one of `Pattern`, `AwarePattern`, or `UTCPattern` to specify custom date-time formats.

Tip

The `typing.Annotated` type is used to apply additional metadata (like timezone information) to a field. When combined with a date-time pattern, it tells the library how to interpret the field’s value in terms of its format or timezone.

Example: Using Pattern with Annotated

    from datetime import time
    from typing import Annotated
    from dataclass_wizard import DataclassWizard
    from dataclass_wizard.patterns import Pattern

    class MyTime(time):
        def get_hour(self):
            return self.hour

    class MyClass(DataclassWizard):
        time_field: Annotated[list[MyTime], Pattern['%I:%M %p']]

    data = {'time_field': ['3:45 PM', '1:20 am', '12:30 pm']}
    c1 = MyClass.from_dict(data)
    print(c1)  # > MyClass(time_field=[MyTime(15, 45), MyTime(1, 20), MyTime(12, 30)])

## Multiple Date and Time Patterns

You can also use multiple date and time patterns (format codes) to parse and serialize your date and time fields. This feature allows for flexibility when handling different formats, making it easier to work with various date and time strings.

### Example: Using Multiple Patterns

In the example below, the `DatePattern` and `TimePattern` are configured to support multiple formats. The class `MyClass` demonstrates how the fields can accept different formats for both dates and times.

    from dataclass_wizard import DataclassWizard
    from dataclass_wizard.patterns import DatePattern, UTCTimePattern

    class MyClass(DataclassWizard):
        date_field: DatePattern['%b %d, %Y', '%I %p %Y-%m-%d']
        time_field: UTCTimePattern['%I:%M %p', '(%H)+(%S)']

    # Using the first date pattern format: 'Jan 3, 2022'
    data = {'date_field': 'Jan 3, 2022', 'time_field': '3:45 PM'}
    c1 = MyClass.from_dict(data)

    print(c1)
    print(c1.to_dict())
    assert c1 == MyClass.from_dict(c1.to_dict())  # > True
    print()

    # Using the second date pattern format: '3 PM 2025-01-15'
    data = {'date_field': '3 PM 2025-01-15', 'time_field': '(15)+(45)'}
    c2 = MyClass.from_dict(data)
    print(c2)
    print(c2.to_dict())
    assert c2 == MyClass.from_dict(c2.to_dict())  # > True
    print()

    # ERROR! The date is not a valid format for the available patterns.
    data = {'date_field': '2025-01-15 3 PM', 'time_field': '(15)+(45)'}
    _ = MyClass.from_dict(data)

#### How It Works

1. DatePattern and TimePattern: These are special types that support multiple patterns (format codes). Each pattern is tried in the order specified, and the first one that matches the input string is used for parsing or formatting.

2. DatePattern Usage: The `date_field` in the example accepts two formats:

   - `%b %d, %Y` (e.g., ‘Jan 3, 2022’)

   - `%I %p %Y-%m-%d` (e.g., ‘3 PM 2025-01-15’)

3. TimePattern Usage: The `time_field` accepts two formats:

   - `%I:%M %p` (e.g., ‘3:45 PM’)

   - `(%H)+(%S)` (e.g., ‘(15)+(45)’)

4. Error Handling: If the input string doesn’t match any of the available patterns, an error will be raised.

This feature is especially useful for handling date and time formats from various sources, ensuring flexibility in how data is parsed and serialized.

### Key Points

- Multiple patterns are specified as a list of format codes in `DatePattern` and `TimePattern`.

- The system automatically tries each pattern in the order provided until a match is found.

- If no match is found, an error is raised, as shown in the example with the invalid date format `'2025-01-15 3 PM'`.

—

Serialization:

Hint

ISO 8601: Serialization of all date-time objects follows the ISO 8601 standard, a widely-used format for representing date and time.

All date-time objects are serialized as ISO 8601 format strings by default. This ensures compatibility with other systems and optimizes parsing.

Note: Parsing uses `datetime.fromisoformat` for ISO 8601 strings, which is much faster than `datetime.strptime`.