timefhuman 0.1.4
Extract datetimes, datetime ranges, and datetime lists from natural language text
License: Apache-2.0
Requires Python: >=3.6

# timefhuman

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Extract datetimes, datetime ranges, and datetime lists from natural language text. Supports Python3+[^1].

✨ Try the [demo](https://pytwiddle.com/app/?id=example%3Adatetime.py) or [code](https://pytwiddle.com/?id=example%3Adatetime.py) online. No installation needed. ✨

[^1]: https://github.com/alvinwan/timefhuman/issues/3

----

## Getting Started

Install with pip using

```shell
$ pip install timefhuman
```

Then, find natural language dates and times in any text.

```python
# All these tests assume the current date is August 4, 2018 at 2 PM
>>> from timefhuman import timefhuman

>>> timefhuman("How does 5p mon sound? Or maybe 4p tu?")
[datetime.datetime(2018, 8, 6, 17, 0), datetime.datetime(2018, 8, 7, 16, 0)]
```

The text can contain not only datetimes but also ranges of datetimes or lists of datetimes.

```python
>>> timefhuman('3p-4p')  # time range
[(datetime.datetime(2018, 8, 4, 15, 0), datetime.datetime(2018, 8, 4, 16, 0))]

>>> timefhuman('7/17 4PM to 7/17 5PM')  # range of datetimes
[(datetime.datetime(2018, 7, 17, 16, 0), datetime.datetime(2018, 7, 17, 17, 0))]

>>> timefhuman('Monday 3 pm or Tu noon')  # list of datetimes
[[datetime.datetime(2018, 8, 6, 15, 0), datetime.datetime(2018, 8, 7, 12, 0)]]

>>> timefhuman('7/17 4-5 or 5-6 PM')  # list of ranges of datetimes!
[[(datetime.datetime(2018, 7, 17, 16, 0), datetime.datetime(2018, 7, 17, 17, 0)),
  (datetime.datetime(2018, 7, 17, 17, 0), datetime.datetime(2018, 7, 17, 18, 0))]]
```

Durations are also supported.

```python
>>> timefhuman('30 minutes')  # duration
[datetime.datetime(2018, 8, 4, 14, 30)]

>>> timefhuman('30-40 mins')  # range of durations
[(datetime.datetime(2018, 8, 4, 14, 30), datetime.datetime(2018, 8, 4, 14, 40))]

>>> timefhuman('30 or 40m')  # list of durations
[[datetime.datetime(2018, 8, 4, 14, 30), datetime.datetime(2018, 8, 4, 14, 40)]]
```

When possible, timefhuman will infer any missing information, using context from other datetimes.

```python
>>> timefhuman('3-4p')  # infer "PM" for "3"
[(datetime.datetime(2018, 8, 4, 15, 0), datetime.datetime(2018, 8, 4, 16, 0))]

>>> timefhuman('7/17 4 or 5 PM')  # infer "PM" for "4" and infer "7/17" for "5 PM"
[[datetime.datetime(2018, 7, 17, 16, 0), datetime.datetime(2018, 7, 17, 17, 0)]]

>>> timefhuman('7/17, 7/18, 7/19 at 9')  # infer "9a" for "7/17", "7/18"
[[datetime.datetime(2018, 7, 17, 9, 0), datetime.datetime(2018, 7, 18, 9, 0),
  datetime.datetime(2018, 7, 19, 9, 0)]]

>>> timefhuman('3p -4p PDT')  # infer timezone "PDT" for "3p"
[(datetime.datetime(2018, 8, 4, 15, 0, tzinfo=<DstTzInfo 'US/Pacific' ...>),
  datetime.datetime(2018, 8, 4, 16, 0, tzinfo=<DstTzInfo 'US/Pacific' ...>))]
```

You can also use natural language descriptions of dates and times.

```python
>>> timefhuman('next Monday')
[datetime.datetime(2018, 8, 6, 0, 0)]

>>> timefhuman('next next Monday')
[datetime.datetime(2018, 8, 13, 0, 0)]

>>> timefhuman('last Wednesday of December')
[datetime.datetime(2018, 12, 26, 0, 0)]

>>> timefhuman('afternoon')
[datetime.datetime(2018, 8, 4, 15, 0)]

>>> timefhuman('1 month ago')
[datetime.datetime(2018, 7, 5, 14, 0)]
```

See more examples in [`tests/test_e2e.py`](tests/test_e2e.py).

## Advanced Usage

For more configuration options, simply create a `tfhConfig` object.

```python
from timefhuman import tfhConfig
config = tfhConfig()
```

**Return matched text**: You can additionally grab the matched text from the input string, as well as the string indices of the matched substring. This is useful for modifying the input string, for example. 

```python
>>> config = tfhConfig(return_matched_text=True, now=datetime.datetime(2025, 2, 23))

>>> timefhuman('We could maybe do 3 PM, if you still have time', config=config)
[('3 PM', (18, 22), datetime.datetime(2025, 2, 23, 15, 0))]
```

**Change 'Now'**: You can configure the default date that timefhuman uses to fill in missing information. This would be useful if you're extracting dates from an email sent a year ago.

```python
>>> config = tfhConfig(now=datetime.datetime(2018, 8, 4, 0, 0))

>>> timefhuman('upcoming Monday noon', config=config)
[datetime.datetime(2018, 8, 6, 12, 0)]
```

You can also set a default timezone, by again using the config's `now`.

```python
>>> config = tfhConfig(
...     now=datetime.datetime(2018, 8, 4, tzinfo=pytz.timezone('US/Pacific'))
... )

>>> timefhuman('Wed', config=config)
[datetime.datetime(2018, 8, 8, 0, 0, tzinfo=<DstTzInfo 'US/Pacific' ...>)]

>>> timefhuman('Wed EST', config=config)  # EST timezone in the input takes precedence
[datetime.datetime(2018, 8, 8, 0, 0, tzinfo=<DstTzInfo 'US/Michigan' ...>)]
```

**Use explicit information only**: Say you only want to extract *dates* OR *times* OR *timedeltas*. You don't want the library to infer information. You can disable most inference by setting `infer_datetimes=False`. Instead of always returning a datetime, timefhuman will be able to return date, time, or timedelta objects depending on what's provided.

```python
>>> config = tfhConfig(infer_datetimes=False)

>>> timefhuman('3 PM', config=config)  # time
[datetime.time(15, 0)]

>>> timefhuman('12/18/18', config=config)  # date
[datetime.date(2018, 12, 18)]

>>> timefhuman('30 minutes', config=config)  # duration
[datetime.timedelta(seconds=1800)]
```

**Past datetimes**: By default, datetimes are assumed to occur in the future, so if "3pm" today has already passed, the returned datetime will be for *tomorrow*. However, if datetimes are assumed to have occurred in the past (e.g., from an old letter, talking about past events), you can configure the direction.

```python
>>> from timefhuman import Direction
>>> config = tfhConfig(direction=Direction.previous, now=datetime.datetime(2018, 8, 4, 14))

>>> timefhuman('3PM')  # the default
[datetime.datetime(2018, 8, 4, 15, 0)]

>>> timefhuman('3PM', config=config)  # changing direction
[datetime.datetime(2018, 8, 3, 15, 0)]
```

**Change global defaults**: You can also modify the default configuration used by timefhuman, if you don't want to manually pass in configs everywhere.

```python
>>> from timefhuman import DEFAULT_CONFIG
>>> DEFAULT_CONFIG.now = datetime.datetime(2025, 2, 23, 12, 0, 0)

>>> timefhuman('3PM')
[datetime.datetime(2025, 2, 23, 15, 0)]
```

Here is the full set of supported configuration options:

```python
@dataclass
class tfhConfig:
    # Default to the next valid datetime or the previous one
    direction: Direction = Direction.next
    
    # Always produce datetime objects. If no date, use the current date. If no time,
    # use midnight. If timedelta, add it to the current datetime. Still allows ranges
    # (tuples) of datetimes and lists of datetimes.
    infer_datetimes: bool = True
    
    # The 'current' datetime, used if infer_datetimes is True
    now: datetime | None = None
    
    # Return the matched text from the input string
    return_matched_text: bool = False
```

## Development

Install the development version.

```shell
$ pip install -e .\[test\]  # for zsh
```

To run tests and simultaneously generate a coverage report, use the following commands:

```shell
$ py.test --cov --cov-report=html
$ open htmlcov/index.html
```