Utilities¶

General athlib utility functions

athlib.utils.check_performance_for_discipline(discipline, textvalue)[source]¶

Fix up and return what they typed in, or raise ValueError

athlib.utils.event_sort_key(event_name)[source]¶

Return a tuple which will sort into programme order

Track should be ordered by distance.

athlib.utils.get_distance(discipline)[source]¶

Return approx distance in metres, for sanity checking :param discipline: :return:

athlib.utils.normalize_gender(gender)[source]¶

Return M, F or raise a ValueError

athlib.utils.parse_hms(t)[source]¶

Parse a time duration with 0, 1 or 2 colons and return seconds.

>>> from athlib.utils import parse_hms
>>> parse_hms('10')
10
>>> parse_hms('1:10')
70
>>> parse_hms('1:1:10')
3670
>>> parse_hms('1:1:10.1')
3670.1
>>> parse_hms(3670.1)
3670.1

athlib.utils.sort_by_discipline(stuff, attr='discipline')[source]¶

Sort dicts or objects into the normal athletics order

athlib.utils.text_event_sort_key(event_name)[source]¶

Return a text version of the event_sort_key

Utilities for working with JSON and json-like structures - deeply nested Python dicts and lists.

This lets us iterate over child nodes and access elements with a dot-notation.

class athlib.jsondict.JSONDict[source]¶

Allows dotted access

class athlib.jsondict.JSONDictSafe[source]¶

Allows dotted access

Age Groups¶

athlib.uka.agegroups.calc_age_group(birth_date, match_date, category, vets=True, underage=False)[source]¶

Return UKA age group

IAAF scoring¶

This file contains definitions and utility functions for determining IAAF event scores.

athlib.iaaf_score.performance(gender, event_code, score)[source]¶

Function to determine performance required to achieve IAAF score, given gender and event.

In the interface, we assume performance is <seconds> for track events, and <metres> for throws and jumps. Ihe the Wikipedia-sourced factors, jumps are <centimetres>. Therefore there is a factor of 100 applied at the end.

athlib.iaaf_score.score(gender, event_code, value)[source]¶

Function to determine IAAF score, based on gender, event and performance.

In the interface, we assume performance is <seconds> for track events, and <metres> for throws and jumps. Ihe the Wikipedia-sourced factors, jumps are <centimetres>. Therefore there is a factor of 100 applied at the end.

athlib.iaaf_score.scoring_key(gender, event_code)[source]¶

Utility function to get the <gender>-<event> scoring key.

athlib.iaaf_score.unit_name(event_code)[source]¶

Utility function to get the unit name based on event type.

Masters utilities¶

class athlib.wma.agegrader.AgeGrader[source]¶

We implement an object to cache the data used for lookups.

end users will appear to be calling a function.

calculate_age_grade(gender, age, event, performance, verbose=False)[source]¶

Return the age grade score (0 to 100ish) for this result.

>>> from athlib.wma.agegrader import AgeGrader
>>> ag=AgeGrader()
>>> "%0.4f" % ag.calculate_age_grade('m',50,'5K', '16:23')
'0.9004'
>>> "%0.4f" %  ag.calculate_age_grade('f',50,'5K', '18:00')
'0.9179'
>>>

calculate_factor(gender, age, event, distance=None)[source]¶

Work out ‘slowdown factor’ for a geezer of this age taking part in this event e.g.

>>> from athlib.wma.agegrader import AgeGrader
>>> ag=AgeGrader()
>>> ag.calculate_factor('M',68,'5k')
0.7592
>>> ag.calculate_factor('M',68,'200K')
0.7561
>>> ag.calculate_factor('M',68.5,'200K')
0.7522
>>> ag.calculate_factor('f',35,'5k')
0.9935
>>> ag.calculate_factor('f',35,'200K')
0.9926
>>> ag.calculate_factor('F',35.5,'200K')
0.99095
>>> ag.calculate_factor('M',65,'10000')
0.7691
>>> ag.calculate_factor('M',69,'10000')
0.7402
>>> ag.calculate_factor('F',35,'1500')
0.9822
>>> ag.calculate_factor('f',39,'1500')
0.9547
>>> ag.calculate_factor('f',35,'SH')
0.9791
>>> ag.calculate_factor('f',39,'SH')
0.9576
>>> ag.calculate_factor('m',35,'LH')
0.9647
>>> ag.calculate_factor('m',39,'LH')
0.9254

get_data()[source]¶

Defer this until the first call, so we can bubble a function up to the top of the package

world_best(gender, event)[source]¶

The relevant world-record performance on the date stats were compiled

Codes¶

codes.JUMPS = ('HJ', 'PV', 'LJ', 'TJ')¶

codes.THROWS = ('DT', 'JT', 'HT', 'SP', 'WT')¶

codes.MULTI_EVENTS = ('PEN', 'HEP', 'DEC', 'PENI', 'PENWT')¶

codes.FIELD_EVENTS = ('HJ', 'PV', 'LJ', 'TJ', 'DT', 'JT', 'HT', 'SP', 'WT')¶

codes.FIELD_SORT_ORDER = ['HJ', 'PV', 'LJ', 'TJ', 'SP', 'DT', 'HT', 'JT']¶