Skip to main content

dice statistics module

Project description

###############
dicetables v1.0
###############
(version 1.0 is an intermediate version. it breaks the old API but has speed and
modularity improvements. version 2.0 is a much bigger break from version 0.4.6 and
there was no attempt to keep it with the old API. if i find improvements in speed
for version 2.x, i should be able to apply them to 1.x as well, so this should be
get the occasional update.)

=====================================================
a module for statistics of die rolls and other events
=====================================================
This module uses DiceTable and AdditiveEvents to combine
dice and other events that can be added together. It is used to
figure out the probability of events occurring. For instance, if you
roll 100 six-sided dice, the chance of rolling any number between 100
and 300 is 0.15 percent.

There are many changes from the previous version, and they will
be listed in "CHANGES" at the bottom of this README.

contents:

- THE BASICS
- Die Classes
- AdditiveEvents And IntegerEvents
- DiceTable And DetailedDiceTable
- EventsInformation And EventsCalculations
- HOW TO GET ERRORS AND BUGS
- CHANGES

----------
THE BASICS
----------
DiceTable is the main object for adding and removing dice. It


| Here's a quick bit of math. if you combine a 2-sided die and a 3-sided die,
| you get the following combinations.
| (1,1) / (1, 2) (2, 1) / (2, 2), (1, 3) / (2, 3):

- roll - 2: 1 occurrence (1 in 6 chance)
- roll - 3: 2 occurrences (2 in 6 chance)
- roll - 4: 2 occurrences (2 in 6 chance)
- roll - 5: 1 occurrence (1 in 6 chance)

::

In [1]: import dicetables as dt

In [2]: table = dt.DiceTable.new()

In [3]: table.add_die(1, dt.Die(2))

In [4]: table.add_die(1, dt.Die(3))

In [5]: table.get_dict()
Out[5]: {2: 1, 3: 2, 4: 2, 5: 1}


Here are basic table functions::

In [5]: str(table)
Out[5]: '1D2\n1D3'

In [6]: table.add_die(100, dt.Die(2))

In [7]: table.remove_die(99, dt.Die(2))

In [17]: print(table)
2D2
1D3

In [20]: table.get_list()
Out[20]: [(Die(2), 2), (Die(3), 1)]

In [22]: table.number_of_dice(dt.Die(10))
Out[22]: 0

In [22]: table.number_of_dice(dt.Die(2))
Out[22]: 2

In [21]: print(table.weights_info())
2D2
No weights

1D3
No weights

To get useful information, use EventsInformation object and EventsCalculations object::

In [1]: table = dt.DiceTable.new()
In [2]: table.add_die(2, dt.StrongDie(dt.Die(2), 3))

In [3]: table.get_dict()
Out[3]: {6: 1, 9: 2, 12: 1}

In [4]: info = dt.EventsInformation(table)

In [5]: info.all_events()
Out[5]: [(6, 1), (9, 2), (12, 1)]


In [6]: info.all_events_include_zeroes()
Out[6]: [(6, 1), (7, 0), (8, 0), (9, 2), (10, 0), (11, 0), (12, 1)]

In [7]: info.events_keys()
Out[7]: [6, 9, 12]

In [8]: info.events_range()
Out[8]: (6, 12)

In [9]: info.get_event(4)
Out[9]: (4, 0)

In [11]: info.get_range_of_events(7, 13)
Out[11]: [(7, 0), (8, 0), (9, 2), (10, 0), (11, 0), (12, 1)]

In [12]: info.biggest_event()
Out[12]: (9, 2)

In [13]: info.total_occurrences()
Out[13]: 4

In [14]: calc = dt.EventsCalculations(table)

In [15]: calc.mean()
Out[15]: 9.0

In [16]: calc.stddev()
Out[16]: 2.1213

In [17]: calc.percentage_points()
Out[17]: [(6, 25.0), (7, 0.0), (8, 0.0), (9, 50.0), (10, 0.0), (11, 0.0), (12, 25.0)]

In [18]: print(calc.full_table_string())
6: 1
7: 0
8: 0
9: 2
10: 0
11: 0
12: 1

In [19]: without_zeroes = EventsCalculations(table, include_zeroes=False)

In [20]: print(without_zeroes.full_table_string())
6: 1
9: 2
12: 1

In [21]: stats_str = "{} occurred {} times out of {} combinations.\nThat's a one in {} chance or {}%"

In [22]: print(stats_str.format(*without_zeroes.stats_strings([1, 2, 5, 8, 9, 10])))
1-2, 5, 8-10 occurred 2 times out of 4 combinations.
That's a one in 2.000 chance or 50.00%

In [23]: without_zeroes.percentage_axes()
Out[23]: [(6, 9, 12), (25.0, 50.0, 25.0)]

Please note that these objects do not follow changes to the DiceTable. You can use
DetailedDiceTable which keeps a copy of these objects at .info and .calc::

In [3]: table = dt.DiceTable.new()

In [5]: info = dt.EventsInformation(table)

In [6]: calc = dt.EventsCalculations(table)

In [7]: info.events_range()
Out[7]: (0, 0)

In [8]: calc.mean()
Out[8]: 0.0

In [9]: table.add_die(100, dt.Die(6))

In [10]: info.events_range()
Out[10]: (0, 0)

In [11]: calc.mean()
Out[11]: 0.0

In [20]: dt.EventsInformation(table).events_range()
Out[20]: (100, 600)

In [12]: d_table = dt.DetailedDiceTable.new()

In [13]: d_table.info.events_range()
Out[13]: (0, 0)

In [14]: d_table.calc.mean()
Out[14]: 0.0

In [15]: d_table.add_die(100, dt.Die(6))

In [16]: d_table.info.events_range()
Out[16]: (100, 600)

In [17]: d_table.calc.mean()
Out[17]: 350.0



You may also access this functionality with wrapper functions:

- events_range
- mean
- stddev
- stats
- full_table_string
- percentage_points
- percentage_axe
::

In [43]: silly_table = dt.AdditiveEvents({1: 123456, 100: 12345*10**1000})

In [47]: print(dt.full_table_string(silly_table, include_zeroes=False))
1: 123,456
100: 1.234e+1004

In [49]: stats_info = dt.stats(silly_table, list(range(-5000, 5)))

In [51]: print(stats_str.format(*stats_info))
(-5,000)-4 occurred 123,456 times out of 1.234e+1004 combinations.
That's a one in 1.000e+999 chance or 1.000e-997%

Finally, here are all the kinds of dice you can add

- dt.Die(6)
- dt.ModDie(6, -2)
- dt.WeightedDie({1:1, 2:5, 3:2})
- dt.ModWeightedDie({1:1, 2:5, 3:2}, 5)
- dt.StrongDie(dt.Die(6), 5)

That's all of the basic implementation. The rest of this is details about base classes, details of the
die classes, details of dicetable classes, what causes errors and the changes from the previous version.

-----------
Die Classes
-----------
All dice are subclasses of ProtoDie, which is a subclass of IntegerEvents.
They all require implementations of get_size(), get_weight(), weight_info(),
multiply_str(number), __str__(), __repr__() and get_dict() <-required for any IntegerEvents.

They are all immutable , hashable and rich-comparable. Multiple names can safely point
to the same instance of a Die, they can be used in sets and dictionary keys and they can be
sorted with any other kind of die. Comparisons are done by (size, weight, get_dict, __repr__(as a last resort)).
So::

In [54]: dice_list
Out[54]:
[ModDie(2, 0),
WeightedDie({1: 1, 2: 1}),
Die(2),
ModWeightedDie({1: 1, 2: 1}, 0),
StrongDie(Die(2), 1),
StrongDie(WeightedDie({1: 1, 2: 1}), 1)]

In [58]: [die.get_dict() == {1: 1, 2: 1} for die in dice_list]
Out[58]: [True, True, True, True, True, True]

In [56]: sorted(dice_list)
Out[56]:
[Die(2),
ModDie(2, 0),
StrongDie(Die(2), 1),
ModWeightedDie({1: 1, 2: 1}, 0),
StrongDie(WeightedDie({1: 1, 2: 1}), 1),
WeightedDie({1: 1, 2: 1})]

In [67]: [die == dt.Die(2) for die in sorted(dice_list)]
Out[67]: [True, False, False, False, False, False]

In [61]: my_set = {dt.Die(6)}

In [62]: my_set.add(dt.Die(6))

In [63]: my_set
Out[63]: {Die(6)}

In [64]: my_set.add(dt.ModDie(6, 0))

In [65]: my_set
Out[65]: {Die(6), ModDie(6, 0)}

The dice:

Die
A basic die. dt.Die(4) rolls 1, 2, 3, 4 with equal weight

No added methods


ModDie
A die with a modifier. The modifier is added to each die roll.
dt.ModDie(4, -2) rolls -1, 0, 1, 2 with equal weight.

added methods:

- .get_modifier()

WeightedDie
A die that rolls different rolls with different frequencies.
dt.WeightedDie({1:1, 3:3, 4:6}) is a 4-sided die. It rolls 4
six times as often as 1, rolls 3 three times as often as 1
and never rolls 2

added methods:

- .get_raw_dict()

ModWeightedDie
A die with a modifier that rolls different rolls with different frequencies.
dt.ModWeightedDie({1:1, 3:3, 4:6}, 3) is a 4-sided die. 3 is added to all
die rolls. The same as WeightedDie.

added methods:

- .get_raw_dict()
- .get_modifier()

StrongDie
A die that is a strong version of any other die (including another StrongDie
if you're feeling especially silly). So a StrongDie with a multiplier of 2
would add 2 for each 1 that was rolled.

dt.StrongDie(dt.Die(4), 5) is a 4-sided die that rolls 5, 10, 15, 20 with
equal weight. dt.StrongDie(dt.Die(4), -1) is a 4 sided die that rolls -1, -2, -3, -4.

added methods:

- .get_multiplier()
- .get_input_die()

--------------------------------
AdditiveEvents And IntegerEvents
--------------------------------
All tables and dice inherit from IntegerEvents. All subclasses of IntegerEvents need the method
get_dict() which returns {event: occurrences, ...} for each NON-ZERO occurrence. When you instantiate
any subclass, it checks to make sure you're get_dict() is legal.

AdditiveEvents is the parent of DiceTable. You can add and remove events using the ".combine" method which tries
to pick the fastest combining algorithm. You can pick it yourself by calling ".combine_by_<algorithm>". You can
combine and remove DiceTable, AdditiveEvents, Die or any other IntegerEvents with the "combine" and "remove" methods,
but there's no record of it::

In [31]: first = dt.DiceTable.new()

In [32]: first.add_die(20, dt.Die(6))

In [33]: first.add_die(7, dt.Die(9))

In [34]: second = dt.DiceTable.new()

In [35]: second.combine(1, first)

In [36]: second.get_dict() == first.get_dict()
Out[36]: True

In [37]: second.get_list()
Out[37]: []

In [41]: print(first)
20D6
7D9
10D10

In [42]: first.combine_by_dictionary(2, dt.Die(1234))

In [43]: first.combine_by_indexed_values(2, dt.AdditiveEvents({1: 2, 3: 4})

In [44]: print(first)
20D6
7D9
10D10

In [45]: second.get_dict() == first.get_dict()
Out[45]: False

-------------------------------
DiceTable And DetailedDiceTable
-------------------------------
You can instantiate any DiceTable or DetailedDiceTable with any data you like.
This allows you to create a DiceTable from stored information or to copy.
::

In [14]: old = dt.DiceTable.new()

In [16]: old.add_die(100, dt.Die(6))

In [17]: events_record = old.get_dict()

In [18]: dice_record = old.get_list()

In [19]: new = dt.DiceTable(events_record, dice_record)

In [20]: print(new)
100D6

In [21]: also_new = dt.DetailedDiceTable(new.get_list(), [(dt.Die(6), 100)], calc_includes_zeroes=False)

In [46]: old.get_dict() == new.get_dict() == also_new.get_dict()
Out[46]: True

In [47]: old.get_list() == new.get_list() == also_new.get_list()
Out[47]: True


To get an identity table,
use the class method DiceTable.new() or DetailedDiceTable.new().
This creates a table with an empty dice record and the events
identity {0: 1}.

DetailedDiceTable.calc_includes_zeroes is as follows.
::

In [85]: d_table = dt.DetailedDiceTable.new()

In [91]: d_table.calc_includes_zeroes = True

In [88]: d_table.add_die(1, dt.StrongDie(dt.Die(2), 2))

In [89]: print(d_table.calc.full_table_string())
2: 1
3: 0
4: 1

In [91]: d_table.calc_includes_zeroes = False

In [92]: print(d_table.calc.full_table_string())
2: 1
4: 1

In [93]: d_table.add_die(1, dt.StrongDie(dt.Die(2), 2))

In [94]: print(d_table.calc.full_table_string())
4: 1
6: 2
8: 1

In [95]: d_table.calc_includes_zeroes = True

In [96]: print(d_table.calc.full_table_string())
4: 1
5: 0
6: 2
7: 0
8: 1

----------------------------------------
EventsInformation And EventsCalculations
----------------------------------------

The methods are

EventsInformation:
- all_events
- all_events_include_zeroes
- biggest_event
- biggest_events_all <- returns the list of all events that have biggest occurrence
- events_keys
- events_range
- get_event
- get_items <- returns dict.items(): a list in py2 and an iterator in py3.
- get_range_of_events
- total_occurrences

EventsCalculations:
- full_table_string
- info
- mean
- percentage_axes <- very fast but only good to 10 decimal places
- percentage_axes_exact
- percentage_points
- percentage_points_exact
- stats_strings
- stddev

EventsCalculations.include_zeroes is only settable at instantiation. It does
exactly what it says. EventCalculations owns an EventsInformation. So that
instantiating EventsCalculations gets you
two for the price of one. It's accessed with the property
EventsCalculations.info .
::

In[4]: table.add_die(1, dt.StrongDie(dt.Die(3), 2))

In[5]: calc = dt.EventsCalculations(table, True)

In[6]: print(calc.full_table_string())
2: 1
3: 0
4: 1
5: 0
6: 1

In[7]: calc = dt.EventsCalculations(table, False)

In[8]: print(calc.full_table_string())
2: 1
4: 1
6: 1

In [10]: calc.info.events_range()
Out[10]: (2, 6)

--------------------------
HOW TO GET ERRORS AND BUGS
--------------------------
Every time you instantiate any IntegerEvents, it is checked. The get_dict() method returns a dict, and every value
in get_dict().values() must be >=1. get_dict() may not be empty.
since dt.Die(-2).get_dict() returns {}::

In [3]: dt.Die(-2)
dicetables.baseevents.InvalidEventsError: events may not be empty. a good alternative is the identity - {0: 1}.

In [5]: dt.AdditiveEvents({1.0: 2})
dicetables.baseevents.InvalidEventsError: all values must be ints

In [6]: dt.WeightedDie({1: 1, 2: -5})
dicetables.baseevents.InvalidEventsError: no negative or zero occurrences in Events.get_dict()

Because AdditiveEvents and WeightedDie specifically
scrub the zeroes from their get_dict() methods, these will not throw errors.
::

In [9]: dt.AdditiveEvents({1: 1, 2: 0}).get_dict()
Out[9]: {1: 1}

In [11]: weird = dt.WeightedDie({1: 1, 2: 0})

In [12]: weird.get_dict()
Out[12]: {1: 1}

In [13]: weird.get_size()
Out[13]: 2

In [14]: weird.get_raw_dict()
Out[14]: {1: 1, 2: 0}

Special rule for WeightedDie and ModWeightedDie::

In [15]: dt.WeightedDie({0: 1})
ValueError: rolls may not be less than 1. use ModWeightedDie

In [16]: dt.ModWeightedDie({0: 1}, 1)
ValueError: rolls may not be less than 1. use ModWeightedDie

Here's how to add 0 one time (which does nothing, btw)::

In [18]: dt.ModWeightedDie({1: 1}, -1).get_dict()
Out[18]: {0: 1}

StrongDie also has a weird case that can be unpredictable. Basically, don't multiply by zero::

In [43]: table = dt.DiceTable.new()

In [44]: table.add_die(1, dt.Die(6))

In [45]: table.add_die(100, dt.StrongDie(dt.Die(100), 0))

In [46]: table.get_dict()

Out[46]: {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1}

In [47]: print(table)
1D6
(100D100)X(0)

In [48]: table.add_die(2, dt.StrongDie(dt.ModWeightedDie({1: 2, 3: 4}, -1), 0)) <- this rolls zero with weight 4

In [49]: print(table)
(2D3-2 W:6)X(0)
1D6
(100D100)X(0)

In [50]: table.get_dict()
Out[50]: {1: 16, 2: 16, 3: 16, 4: 16, 5: 16, 6: 16} <- this is correct, it's just stupid.


"remove_die" and "add_die" are safe. They raise an error if you
remove too many dice or add or remove a negative number.
If you remove or combine with a negative number, nothing should happen.
If you use "remove" to remove what you haven't added,
it may or may not raise an error, but it's guaranteed buggy::

In [19]: table = dt.DiceTable()

In [20]: table.add_die(1, dt.Die(6))

In [21]: table.remove_die(4, dt.Die(6))
dicetables.dicetable.DiceRecordError: Removed too many dice from DiceRecord. Error at (Die(6), -3)

In [22]: table.remove_die(1, dt.Die(10))
dicetables.dicetable.DiceRecordError: Removed too many dice from DiceRecord. Error at (Die(10), -1)

In [26]: table.add_die(-3, dt.Die(6))
dicetables.dicetable.DiceRecordError: May not add negative dice to DiceRecord. Error at (Die(6), -3)

In [27]: table.remove_die(-3, dt.Die(6))
dicetables.dicetable.DiceRecordError: May not remove negative dice from DiceRecord. Error at (Die(6), -3)

In [30]: table.get_dict()
Out[30]: {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1}

In [31]: table.remove(10, dt.Die(2))
ValueError: min() arg is an empty sequence <-didn't know this would happen, but at least failed loudly

In [32]: table.remove(2, dt.Die(2))

In [33]: table.get_dict()
Out[33]: {-1: 1, 1: 1} <-bad. this is a random answer

In [34]: table.remove(1, dt.AdditiveEvents({-5: 100}))

In [35]: table.get_dict()
Out[35]: {} <-very bad. this is an illegal answer.

Since you can instantiate a DiceTable with any legal input,
you can make a table with utter nonsense. It will work horribly.
for instance, the dictionary for 2D6 is

{2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 5, 9: 4, 10: 3, 11: 2, 12: 1}
::

In[22]: nonsense = dt.DiceTable({1: 1}, [(dt.Die(6), 2)]) <- BAD DATA!!!!

In[23]: print(nonsense) <- the dice record says it has 2D6, but the events dictionary is WRONG
2D6

In[24]: nonsense.remove_die(2, dt.Die(6)) <- so here's your error. I hope you're happy.
ValueError: min() arg is an empty sequence

But, you cannot instantiate a DiceTable with negative values for dice.
::

In[11]: dt.DiceTable({1: 1}, [(dt.Die(3), 3), (dt.Die(5), -1)])
dicetables.dicetable.DiceRecordError: DiceRecord may not have negative dice. Error at (Die(5), -1)

Calling combine_by_flattened_list can be risky::

In [36]: x = dt.AdditiveEvents({1:1, 2: 5})

In [37]: x.combine_by_flattened_list(5, dt.AdditiveEvents({1: 2, 3: 4}))

In [39]: x.combine_by_flattened_list(5, dt.AdditiveEvents({1: 2, 3: 4*10**10}))
MemoryError

In [42]: x.combine_by_flattened_list(1, dt.AdditiveEvents({1: 2, 3: 4*10**700}))
OverflowError: cannot fit 'int' into an index-sized integer

Combining events with themselves is safe::

In [51]: x = dt.AdditiveEvents({1: 1, 2: 1})

In [52]: x.combine(1, x)

In [53]: x.get_dict()
Out[53]: {2: 1, 3: 2, 4: 1}

In [54]: x.combine(1, x)

In [55]: x.get_dict()
Out[55]: {4: 1, 5: 4, 6: 6, 7: 4, 8: 1}

=======
CHANGES
=======
There are several major changes:

- Modules and classes and methods got renamed. see the dictionary at the bottom. There are new classes
- DiceTable.__init__() now takes arguments. The class method DiceTable.new() creates an empty table.
- DiceTable and its parent AdditiveEvents are no longer responsible for obtaining any but the most basic information.
- All the calculations and information are now done by EventsInformation and EventsCalculations
- Aside from the above two classes, every other object is now a child of IntegerEvents.
- Dice classes no longer have "tuple_list()" method. They use the same "get_dict()" method that all IntegerEvents use

The following modules and classes have been renamed.

- longintmath.py: baseevents.py
- dicestats.py: dieevents.py, dicetable.py
- tableinfo.py: eventsinfo.py
- LongIntTable: AdditiveEvents

The following classes have been added:

- baseevents.InvalidEventsError
- dicetable.DiceRecordError
- baseevents.IntegerEvents
- dicetable.DetailedDiceTable
- eventsinfo.EventsInformation
- eventsinfo.EventsCalculations


DiceTable.__init__() now takes two arguments - a dictionary of {event: occurrences}
and a list of [(die, number), ]. to create a new table, call the class method DiceTable.new(). This change allows
easy creation of a new dice table from data. new_table = DiceTable(old_table.get_dict(), old_table.get_list()) or
new_table = DiceTable(stored_dict, stored_dice_list). To create a DiceTable with no dice, use DiceTable.new().

The base class of DiceTable is now called AdditiveEvents and not LongIntTable. If any IntegerEvents events is
instantiated in a way that would cause bugs, it raises an error; the same is true for any dice.

AdditiveEvents.combine/remove take any IntegerEvents as an argument whereas LongIntTable.add/remove took a list of
tuples as an argument. the methods for getting basic information from LongIntTable are now in EventsInformation. mean()
and stddev() are part of EventsCalculations object. These objects work on ANY kind of IntegerEvents, not just DiceTable.

all of tableinfo was rewritten as objects. although they are deprecated, the following still exist as wrapper
functions for those objects:

- events_range
- format_number
- full_table_string
- graph_pts
- graph_pts_overflow
- mean
- percentage_axes
- percentage_points
- safe_true_div
- stats
- stddev

the new objects are:

- NumberFormatter
- EventsInformation
- EventsCalculations

for details, see their headings in the README.

For output:
stats() now shows tiny percentages, and if infinite, shows 'Infinity'.
Any exponent between 10 and -10 has that extraneous zero removed: '1.2e+05' is now '1.2e+5'.

Any subclass of ProtoDie no longer has the .tuple_list() method. It has been replaced by the .get_dict() method
which returns a dictionary and not a list of tuples. The string for StrongDie now puts parentheses around the multiplier.
::

CONVERSIONS = {
'DiceTable()': 'DiceTable.new()',
'LongIntTable.add': 'AdditiveEvents.combine',
'LongIntTable.frequency': 'EventsInformation(event).get_event',
'LongIntTable.frequency_all': 'EventsInformation(event).all_events',
'LongIntTable.frequency_highest': 'EventsInformation(event).biggest_event',
'LongIntTable.frequency_range': 'EventsInformation(event).get_range_of_events',
'LongIntTable.mean': 'EventsCalculations(event).mean',
'LongIntTable.merge': 'GONE',
'LongIntTable.remove': 'AdditiveEvents.remove',
'LongIntTable.stddev': 'EventsCalculations(event).stddev',
'LongIntTable.total_frequency': 'EventsInformation(event).total_occurrences',
'LongIntTable.update_frequency': 'GONE',
'LongIntTable.update_value_add': 'GONE',
'LongIntTable.update_value_ow': 'GONE',
'LongIntTable.values': 'EventsInformation(event).event_keys',
'LongIntTable.values_max': 'EventsInformation(event).event_range[0]',
'LongIntTable.values_min': 'EventsInformation(event).event_range[1]',
'LongIntTable.values_range': 'EventsInformation(event).event_range',
'DiceTable.update_list': 'GONE (DiceTable owns a DiceRecord object that handles this)',
'ProtoDie.tuple_list': ('sorted(ProtoDie.get_dict().items)', 'EventsInformation(ProtoDie).all_events'),
'scinote': ('format_number', 'NumberFormatter.format'),
'full_table_string', 'EventsCalculations(event).full_table_string',
'stats', 'EventsCalculations(event).stats_strings',
'long_int_div': 'safe_true_div',
'graph_pts': ('graph_pts',
'EventsCalculations(event).percentage_points',
'EventsCalculations(event).percentage_points_exact',
'EventsCalculations(event).percentage_axes',
'EventsCalculations(event).percentage_axes_exact',
'EventsInformation(events).all_events',
'EventsInformation(events).all_events_include_zeroes')
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dicetables-1.0.3.tar.gz (31.0 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page