friendlydateparser 0.2.0

A flexible date parsing library that can handle complex natural language expressions, making date manipulation easy and intuitive.

friendlydateparser

This Python module provides three key methods for parsing text into time, date, or datetime objects.

The aim is to be able to accept natural language date expressions that, even if complex, are frequently used in everyday life.

API

parse_time(text)

Extracts time information from a given string and returns a time object. This function is suitable for parsing times like "2:45 PM", "14:30", "midnight", etc.

• Parameters:

  • text (str): The text containing time information to be parsed.

• Returns: A datetime.time object.

• Example:

  time_obj = parse_time("2:45 PM")
  # Returns: datetime.time(14, 45)
  

parse_date(text, now=None, month_first=True)

Parses date information from a given string and returns a date object. The function can handle different formats including relative date descriptions (e.g., "next month", "last Friday") or explicit dates (e.g., "10/3/2017", "15th of July").

• Parameters:

  • text (str): The text containing date information to be parsed.
  • now (datetime.date or datetime.datetime, optional): The reference date to use for relative expressions. Defaults to the current date if not specified.
  • month_first (bool, optional): Indicates whether the month appears first in numerical dates (e.g., 10/3 is treated as October 3rd if month_first=True). Defaults to True.

• Returns: A datetime.date object.

• Example:

  date_obj = parse_date("the first of next month")
  # Assuming today is 2023-10-10, returns: datetime.date(2023, 11, 1)
  

parse_datetime(text, now=None, month_first=True)

Parses both date and time information from a given string and returns a datetime object. The function handles a wide range of date and time formats, including explicit and relative formats.

• Parameters:

  • text (str): The text containing datetime information to be parsed.
  • now (datetime.date or datetime.datetime, optional): The reference date to use for relative expressions. Defaults to the current date and time if not specified.
  • month_first (bool, optional): Indicates whether the month appears first in numerical dates (e.g., 10/3 is treated as October 3rd if month_first=True). Defaults to True.

• Returns: A datetime.datetime object.

• Example:

  datetime_obj = parse_datetime("january 1, 2017 at 14:30")
  # Returns: datetime.datetime(2017, 1, 1, 14, 30)
  

Supported Formats

The module can parse a wide variety of date and time formats, including but not limited to:

• Relative Dates: Expressions like "the first of next month", "next week", "last Friday", "the day after tomorrow" are supported, allowing flexible parsing of commonly used phrases.

• Explicit Dates: Formats such as "10/3/2017", "march 15, 2017", "15/july/2023" are accepted, with the ability to handle both mm/dd/yyyy and dd/mm/yyyy formats based on the month_first parameter.

• Relative Weekdays: Phrases like "monday next week", "last monday", "second sunday of 2023" are parsed, allowing users to reference specific weekdays in relative terms.

• Datetime Formats: Full date and time expressions such as "january 1, 2017 at 14:30", "february 14, 2017 at 2:45 PM" are supported, making it easy to parse datetime values from text.

• Special Terms: Terms like "midnight", "noon" are also supported, allowing parsing of common time-related expressions.

• Implicit Dates: Natural expressions like "tomorrow at 5 PM", "next Monday", or "this month" are parsed effectively to provide accurate datetime objects.

• Week Numbers: References like "week 42 of 2023" can be parsed, providing an easy way to handle week-based scheduling.

• Ordinal Dates: Phrases like "the third of next month" or "the first Sunday in June" are supported, allowing flexibility with ordinal references.

The module supports both common formats like mm/dd/yyyy and dd/mm/yyyy, with the ability to distinguish based on the month_first parameter.

Note: If you think a new format should be supported, feel free to ask for it, and I will try to add it in a future update.

Error Handling

• If the input text is incomplete or not recognizable as a valid date/time, a ValueError may be raised.

• The module tries to handle incomplete dates (for instance, "october" is equivalent to "the first of october of this year"), but very ambiguous cases as "9" are just rejected.

Example Usage

from friendlydateparser import parse_date, parse_time, parse_datetime

# Parsing a date
date_obj = parse_date("the last day of next jan")
# Returns: datetime.date(2024, 1, 31)

# Parsing a time
time_obj = parse_time("2:00 PM")
# Returns: datetime.time(14, 0)

# Parsing a datetime
datetime_obj = parse_datetime("march 15, 2017 11:59 PM")
# Returns: datetime.datetime(2017, 3, 15, 23, 59)

See Also

• datetime: For working with date and time objects in Python.

• time: Provides various time-related functions, such as working with timestamps or sleep functions. This can be useful in combination with date and time parsing.

• dateutil.relativedelta: For relative date calculations, like adding or subtracting months or years.

• calendar: For calendar-related functions, such as determining leap years or getting the number of days in a month.

• pytz: For handling time zones in Python. It can be useful when parsing dates and times that involve different time zones or when converting between local times and UTC.

• pendulum: A library that provides easy-to-use functions for parsing, formatting, and manipulating dates and times, with a focus on improved datetime management and natural language parsing.

• dateparser: A library similar to this module, which parses natural language dates. Note that as of October 2024, it has not been updated for a long time.

• Arrow: A datetime alternative with a focus on usability. The dehumanize feature allows one to parse time deltas expressed in natural language.

License

Copyright (c) 2024 Salvador Fandiño García

This project is licensed under the MIT License. See the LICENSE file for more details.