Calendar-based time window filtering, age calculations, and business logic for dates and times.
Project description
Frist: Unified Age and Calendar Logic
Fristis a modern Python library designed to make working with time, dates, intervals and business calendars with a 'simple' and expressive property based API. Frist provides property-based APIs for Age, Cal and Biz. The Age object lets you answer “How old is this?” for two datetimes (often defaulting the second date to “now”), making it perfect for file aging, log analysis, or event tracking. The Cal object lets you ask “Is this date in a specific window?”—such as today, yesterday, this month, this quarter, or this fiscal year—using intuitive properties for calendar logic. Calendar ranges are always aligned to a calendar time scale, day, business day, month, year, quarter, hour. Finally, the Biz class lets you establish a business policy for work days, work hours, fiscal years to make use of business calendars.
Frist is not a replacement for datetime or timedelta. If tools from the std-library work for you,keep using them.
Frist is a way to reduce the cognitive load on dealing with ages, calendar windows, and business dates. You almost never do math or manipulate get pieces of datetimes and you' deal directly with readable properties.
Here are some examples of a dataset with a bunch of dates where one field is a date time
from frist import Age, Cal, Biz, CalendarPolicy
# In these excamples a second datetime is not provided, when this happens the constrctures take the referenct time to be "now"
dates = large_list_of_date_times()
# Policy only required if you want business date info
policy = CalendarPolicy(fiscal_year_start_month=4,holidays={"2026-1-1"})
# If no second date provided then now() assumend.
last_four_and_half_minutes = [date for date in dates if Age(date).age.minutes <= 4.5]
last_three_years = [date for date in dates if Age(date).age.years < 3.0]
dates_today = [date for date in dates if Cal(date).in_days(0)]
last_two_months = [date for date in dates if Cal(date)in_months(-2,0)]
last_three_cal_years = [date for date in dates if Cal(date).in_years(-3,0)]
last_five_business_days = [date for date in dates if Biz(date).in_business_days(-5,0)]
this_fiscal_year = [date for date in dates if Biz(date,policy).in_fiscal_years(0)]
last_3_fiscal_year = [date for date in dates if Biz(date,policy)in_fiscal_years(-2,0)]
ignore_holidays = [data for date in dates if not Biz(date,policy).is_holiday]
# Shortcut examples
dates_today_shortcut = [date for date in dates if Cal(date).is_today]
dates_this_quarter = [date for date in dates if Cal(date).is_this_quarter]
dates_last_year = [date for date in dates if Cal(date).is_last_year]
Age
The Age object answers "How old is X?" for two datetimes (start and end). It exposes common elapsed-time metrics as properties so you can write intent‑revealing one‑liners.
- Purpose: elapsed / duration properties (seconds, minutes, hours, days, weeks, months, years).
- Special:
months_preciseandyears_precisecompute calendar-accurate values;parse()converts human-friendly duration strings to seconds. - Default behaviour: if
end_timeis omitted it defaults to set todatetime.now().
Example:
>>> from frist import Age
>>> import datetime as dt
>>> a = Age(start_time=dt.datetime(2025,9,1), end_time=dt.datetime(2025,11,20))
>>> a.days
80.125
>>> a.years
0.21
Cal
The Cal object provides calendar-aligned window queries (minute/hour/day/week/month/quarter/year and fiscal variants) using half-open semantics. Use in_* methods to ask whether a target falls in a calendar window relative to a reference date.
- Purpose: calendar-window membership (in_days, in_months, in_quarters, in_fiscal_years, ...).
- Behaviour: calendar-aligned, half-open intervals; supports custom week starts and fiscal start month via Chrono/CalendarPolicy composition.
- Use-case: one-liners for "was this date in the last two months?" or "is this in the current fiscal quarter?"
Practical note on half-open intervals:
It is normal English to define time spans as half-open intervals. For example, when you say "from 1:00 PM to 2:00 PM" you mean a meeting that starts at 1:00 PM and ends at 2:00 PM (one hour long). You do not mean "any time whose hour is 1 or 2" or that the instant at 2:00 PM is included in the 1:00–2:00 meeting. In half-open semantics the start is inclusive and the end is exclusive — i.e. the interval contains times t where 1:00 PM <= t < 2:00 PM. This convention avoids overlapping windows (e.g., an event that ends exactly at 2:00 PM belongs to the next interval, not the previous one) and makes unit-based queries like in_hours(1) intuitive.
Example:
>>> from frist import Cal
>>> import datetime as dt
>>> target = dt.datetime(2025,9,15)
>>> ref = dt.datetime(2025,11,20)
>>> c = Cal(target_dt=target, ref_dt=ref)
>>> c.in_months(-2, -1)
True # target was in Sept/Oct (the two full months before Nov)
>>> c.in_days(-7, -1)
False # not in the 7..1 days before ref
Biz
The Biz object performs policy-aware business calendar calculations. It relies on CalendarPolicy to determine workdays, holidays, business hours, and fiscal rules.
- Purpose: business/working-day arithmetic (fractional day spans, range membership, fiscal helpers).
- Key differences:
working_dayscounts weekdays per policy (ignores holidays);business_daysexcludes holidays. Fractional days computed using policy business hours. - Common methods:
working_days,business_days,in_working_days,in_business_days,get_fiscal_year,get_fiscal_quarter.
Example:
>>> from frist import Biz, CalendarPolicy
>>> import datetime as dt
>>> policy = CalendarPolicy(workdays={0,1,2,3,4}, holidays={"2025-12-25"})
>>> start = dt.datetime(2025,12,24,9,0)
>>> end = dt.datetime(2025,12,26,17,0)
>>> b = Biz(start, end, policy)
>>> b.working_days
3.0 # counts Wed/Thu/Fri as workdays (holidays ignored)
>>> b.business_days
2.0 # Dec 25 removed from business-day total
>>> b.in_business_days(0)
False # target is a holiday -> not a business day
>>> b.in_working_days(0)
True # still a weekday per policy
CalendarPolicy
The CalendarPolicy object lets you customize business logic for calendar calculations using half open intervals You can define:
- Workdays: Any combination of weekdays (e.g., Mon, Wed, Fri, Sun)
- Holidays: Any set of dates to exclude from working day calculations
- Business hours: Custom start/end times for each day
- Fiscal year start: Set the starting month for fiscal calculations
Default Policy:
If you do not provide a CalendarPolicy, Frist uses a default policy:
- Workdays: Monday–Friday (0–4)
- Work hours: 9AM–5PM
- Holidays: none
This is suitable for most standard business use cases. You only need to provide a custom CalendarPolicy if your calendar logic requires non-standard workweeks, holidays, or business hours.
Example (custom policy):
>>> from frist import CalendarPolicy
>>> import datetime as dt
>>> policy = CalendarPolicy(workdays={0,1,2,3,4}, holidays={"2025-1-1"}, work_hours=(9,17), fy_start_month=4)
>>> date = dt.datetime(2025, 5, 15)
>>> policy.get_fiscal_year(date)
2026
>>> policy.get_fiscal_quarter(date)
1
>>> policy.is_holiday(dt.datetime(year=2025,month=1,day=1))
True
API Reference
Here is a brief overview of the various classes that makeup Frist.
Age Object
Age(start_time: datetime, end_time: datetime = None, cal_policy: CalendarPolicy = None)
| Property | Description |
|---|---|
seconds |
Age in seconds |
minutes |
Age in minutes |
hours |
Age in hours |
days |
Age in days |
weeks |
Age in weeks |
months |
Age in months (approximate, 30.44 days) |
months_precise |
Age in months (precise, calendar-based) |
years |
Age in years (approximate, 365.25 days) |
years_precise |
Age in years (precise, calendar-based) |
working_days |
Fractional working days between start and end, per policy |
fiscal_year |
Fiscal year for start_time |
fiscal_quarter |
Fiscal quarter for start_time |
start_time |
Start datetime |
end_time |
End datetime |
cal_policy |
CalendarPolicy used for business logic |
| Method | Description |
|---|---|
set_times(start_time=None, end_time=None) |
Update start/end times |
parse(age_str) |
Parse age string to seconds |
The months_precise and years_precise properties calculate the exact number of calendar months or years between two dates, accounting for the actual length of each month and year. Unlike the approximate versions (which use averages like 30.44 days/month or 365.25 days/year), these properties provide results that match real-world calendar boundaries. They are more intuitively correct but are slower to compute since the first and last month/year need to be handled differently. Basically, Feb 1 to Feb 28 (non leap year) is 1.0 precise months long, while Jan 1 to Jan31 is also 1 precise month long. And Jan 1 to Feb 14 is 1.5 precise months. For years it is similar but the effect is smaller. The 365 days in 2021 is 1 precise year as are the 366 days in 2024.
Cal Object
The Cal object provides a family of in_* methods (e.g., in_days, in_months, in_years etc) to check if the target date falls within a calendar window relative to the reference date. These methods use calendar units (not elapsed time) using half-open intervals. The start is inclusive, the end is exclusive. This makes it easy to check if a date is in a specific calendar range (e.g., last week, next month, fiscal quarter) using intuitive, unit-based logic.
in_days(-1): Is the target date yesterday?in_days(-1, 1): Is the target date within ±1 calendar day of the reference?
Cal(target_dt: datetime, ref_dt: datetime, fy_start_month: int = 1, holidays: set[str] = None)
| Property | Description | Return |
|---|---|---|
dt_val |
Target datetime | datetime |
base_time |
Reference datetime | datetime |
fiscal_year |
Fiscal year for dt_val |
int |
fiscal_quarter |
Fiscal quarter for dt_val |
int |
holiday |
True if dt_val is a holiday |
bool |
| Interval Method | Description | Return |
|---|---|---|
in_minutes(start=0, end=None) |
Is target in minute window | bool |
in_hours(start=0, end=None) |
Is target in hour window | bool |
in_days(start=0, end=None) |
Is target in day window | bool |
in_weeks(start=0, end=None, week_start="monday") |
Is target in week window | bool |
in_months(start=0, end=None) |
Is target in month window | bool |
in_quarters(start=0, end=None) |
Is target in quarter window | bool |
in_years(start=0, end=None) |
Is target in year window | bool |
Shortcuts (convenience boolean properties):
| Shortcut | Equivalent in_* call |
|---|---|
is_today |
in_days(0) |
is_yesterday |
in_days(-1) |
is_tomorrow |
in_days(1) |
is_last_week |
in_weeks(-1) |
is_this_week |
in_weeks(0) |
is_next_week |
in_weeks(1) |
is_last_month |
in_months(-1) |
is_this_month |
in_months(0) |
is_next_month |
in_months(1) |
is_last_quarter |
in_quarters(-1) |
is_this_quarter |
in_quarters(0) |
is_next_quarter |
in_quarters(1) |
is_last_year |
in_years(-1) |
is_this_year |
in_years(0) |
is_next_year |
in_years(1) |
Biz Object
The Biz object performs business-aware calculations using a CalendarPolicy. It counts
working days (defined by the policy's workday set) and business days (working days that are not holidays).
It also computes fractional day contributions using the policy's business hours.
Business days and work days are tricky to calculate an involve iteration because no/few assumptions can be made about the way the days fall. Normally this isn't a huge deal becase the time spans are a few days, not 1000's of days.
Biz(target_time: datetime, ref_time: datetime | None, policy: CalendarPolicy | None)
| Property / Attribute | Description | Return |
|---|---|---|
cal_policy |
CalendarPolicy instance used by this Biz |
CalendarPolicy |
target_time |
Target datetime | datetime |
ref_time |
Reference datetime | datetime |
holiday |
True if target_time is a holiday |
bool |
is_workday |
True if target_time falls on a workday |
bool |
is_business_day |
True if target_time is a business day (workday and not holiday) |
bool |
working_days |
Fractional working days between target and ref (ignores holidays) | float |
business_days |
Fractional business days between target and ref (excludes holidays) | float |
| Method | Description | Return |
|---|---|---|
in_working_days(start=0, end=0) |
Range membership by working days (ignores holidays) | bool |
in_business_days(start=0, end=0) |
Range membership by business days (excludes holidays) | bool |
get_fiscal_year(dt, fy_start_month) |
Static helper to compute fiscal year for a datetime | int |
get_fiscal_quarter(dt, fy_start_month) |
Static helper to compute fiscal quarter | int |
Shortcuts (convenience boolean properties):
| Shortcut | Equivalent in_* call |
|---|---|
is_business_last_day |
in_business_days(-1) (observes holidays) |
is_business_this_day |
in_business_days(0) (observes holidays) |
is_business_next_day |
in_business_days(1) (observes holidays) |
is_workday_last_day |
in_working_days(-1) |
is_workday_this_day |
in_working_days(0) |
is_workday_next_day |
in_working_days(1) |
is_last_fiscal_quarter |
in_fiscal_quarters(-1) |
is_this_fiscal_quarter |
in_fiscal_quarters(0) |
is_next_fiscal_quarter |
in_fiscal_quarters(1) |
is_last_fiscal_year |
in_fiscal_years(-1) |
is_this_fiscal_year |
in_fiscal_years(0) |
is_next_fiscal_year |
in_fiscal_years(1) |
Chrono Object
In some situations you will need to have all three of these classes together because the filtering you are doing is related
to the multiple classes. The best way to handle this is with the chrono object. The Chrono class initiaizlizes all three so you have access to each of the classes, with no race conditions when setting the reference time.
# Brief Chrono example: create a Chrono and print Age / Cal / Biz properties
>>> from frist import Chrono, CalendarPolicy
>>> import datetime as dt
>>> target = dt.datetime(2025, 4, 25, 15, 0)
>>> ref = dt.datetime(2025, 4, 30, 12, 0)
>>> policy = CalendarPolicy(workdays={0,1,2,3,4}, holidays={"2025-04-28"})
>>> z = Chrono(target_time=target, reference_time=ref, policy=policy)
# Age (elapsed-time properties)
>>> z.age.days # elapsed days (float)
3.875
>>> z.age.years_precise # calendar-accurate years
0.0106
# Cal (calendar-window queries)
>>> z.cal.in_days(-5) # was target 5 days before reference?
True
>>> z.cal.in_months(0) # same calendar month as reference?
True
# Biz (policy-aware business logic — properties are floats)
>>> z.biz.working_days # fractional working days (counts workdays per policy)
1.0
>>> z.biz.business_days # fractional business days (excludes holidays from policy)
0.0
>>> z.biz.in_working_days(0) # range-membership helper (bool)
True
>>> z.biz.in_business_days(0) # range-membership helper (bool)
False
Chrono(target_time: datetime, reference_time: datetime = None, cal_policy:CalendarPolicy|None)
| Property | Description |
|---|---|
age |
Age object for span calculations (see Age above) |
cal |
Cal object for calendar window logic (see Cal above) |
biz |
Biz object for calendar window logic (see Cal above) |
Status
Pytest (100% pass/100% coverage)
src\frist\__init__.py 8 0 0 0 100%
src\frist\_age.py 119 0 34 0 100%
src\frist\_biz.py 176 4 28 0 98% 80, 104, 129, 153
src\frist\_cal.py 142 0 12 0 100%
src\frist\_cal_policy.py 79 0 38 0 100%
src\frist\_constants.py 15 0 0 0 100%
src\frist\_frist.py 71 0 18 0 100%
src\frist\_util.py 13 0 2 0 100%
Tox
py310: OK (17.03=setup[13.64]+cmd[3.39] seconds)
py311: OK (10.53=setup[7.45]+cmd[3.08] seconds)
py312: OK (11.76=setup[8.69]+cmd[3.06] seconds)
py313: OK (11.46=setup[8.52]+cmd[2.94] seconds)
py314: OK (11.45=setup[9.47]+cmd[1.98] secon
congratulations :) (59.61 seconds)
Notes
This test code was written as a test case in using agentic AI. As such I wrote very little of the code but I 100% "drive the car" in coming to this solution. There were many dead ends and dead ends and me swearing at VSCode, but in the end the result is better than what I could have done without it, especially in the beginning phases. Asking AI to make large strutureal changes to the code was very problematic. Often times a simple search and replace would work and it would get very stuck, or decided it needed to fundamentally change stuff.
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