cnd
v9.3.0
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a grab-bag NodeJS package mainly for functionalities that used to live in coffeenode-trm, coffeenode-bitsnpieces, and coffeenode-types
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cnd
a grab-bag NodeJS package mainly for functionalities that used to live in coffeenode-trm, coffeenode-bitsnpieces, and coffeenode-types
CND Interval Tree
https://www.youtube.com/watch?v=q0QOYtSsTg4
https://www.youtube.com/watch?v=PHlTuCVxJz4
https://github.com/mikolalysenko/functional-red-black-tree
Simplified API (compared to
functional-red-black-tree
)possible to dynamically add nodes
possible to access underlying red/black tree as
tree[ '%self' ]
, root node astree[ '%self' ][ 'root' ]
possible to access
CND = require 'cnd'
ITREE = CND.INTERVALTREE
tree = ITREE.new_tree()
intervals = [
[ 3, 7, 'A', ]
[ 5, 7, 'B', ]
[ 8, 12, 'C', ]
[ 2, 14, 'D', ]
[ 4, 4, 'E', ]
]
ITREE.add_interval tree, interval for interval in intervals
for n in [ 0 .. 15 ]
console.log n
for node in ITREE.find tree, n
console.log node[ 'key' ], node[ 'value' ]
CND Shim
CND now includes https://github.com/es-shims/es6-shim and https://github.com/es-shims/es7-shim; in order to use these, say
CND = require 'cnd'
CND.shim()
which will then polyfill you current runtime to the point where you approximately
reach compatibility with NodeJS v0.12 run with the --harmony
switch. Note
that not everything can be polyfilled; in particular WeakMaps and yield
cannot
be provided this way.
CND TSort
CND TSort implements a simple tool to perform the often-needed requirement of doing a topological sorting over an DAG (directed acyclic graph). It is an adaption of the npm: tsort module.
Here is the basic usage: you instantiate a graph by saying e.g.
CND = require 'cnd'
TS = CND.TSORT
settings =
strict: yes
prefixes: [ 'f|', 'g|', ]
graph = TS.new_graph settings
The settings
object itself and its members are optional. The strict
setting
(true by default) will check for the well-formedness on the graph each time a
relationship is entered; this means you get early errors at the cost of
decreased performance. We come back to the prefixes
later; the default is not
to use prefixes.
Topological sorting is all about finding a total, linear ordering of actions, values, objects or whatever from a series of statements about the relative ordering of pairs of such objects. This is used in many fields, for example in package management, project management, programming language grammars and so on.
So let's say you have a todo list:
'buy books'
'buy food'
'buy food'
'cook'
'do some reading'
'eat'
'fetch money'
'go home'
'go to bank'
'go to exam'
'go to market'
Now you don't have money, foods or books at home right now, but you want to eat, do some reading, and go to the exam after that, so clearly there are certain orderings of events that would make more sense than other orderings. It's perhaps not immediately clear how you can organize all these jobs when you look at the entire list, but given any two jobs, it's often easy to see which one should preced the other one.
Once we have instantiated a graph g
, we can add dual relationships piecemeal,
the convention being that we imagine arrows or links pointing from preconditions
'down' to consequences, which is why the corresponding method is named
link_down
. Calling TS.link_down g, 'buy food', 'cook'
means: 'Add a link to
graph g
to indicate that before I can 'cook'
, I have to 'buy food'
first',
and so on. It is customary to symbolically write 'buy food' > 'cook'
to
indicate the dependency.
In case the graph has been instantiated with a strict: yes
setting, CND TSort
will validate the graph for each single new relationship; as a side effect, a
list of entries is produced and returned that reflects one of the possible
linearizations of the graph which satisfies all requirements so far. For the
purpose of demonstration, we can take advantage of that list and print it out;
we can see that the ordering of jobs will sometimes take a dramatic turn when
new requirements are added. In case you've started the graph with strict: no
,
you'll have to call TS.sort g
yourself to perform a validation and obtain
a serialization.—Let's try that for some obvious dependencies on our list:
console.log ( TS.link_down g, 'buy food', 'cook' ).join ' > '
console.log ( TS.link_down g, 'fetch money', 'buy food' ).join ' > '
console.log ( TS.link_down g, 'do some reading', 'go to exam' ).join ' > '
console.log ( TS.link_down g, 'cook', 'eat' ).join ' > '
console.log ( TS.link_down g, 'go to bank', 'fetch money' ).join ' > '
console.log ( TS.link_down g, 'fetch money', 'buy books' ).join ' > '
console.log ( TS.link_down g, 'buy books', 'do some reading' ).join ' > '
console.log ( TS.link_down g, 'go to market', 'buy food' ).join ' > '
The output from the above will be (re-arranged for readability):
buy food > cook
fetch money > buy food > cook
fetch money > buy food > cook > do some reading > go to exam
fetch money > buy food > cook > do some reading > go to exam > eat
go to bank > fetch money > buy food > cook > do some reading > go to exam > eat
go to bank > fetch money > buy food > cook > do some reading > go to exam > eat > buy books
go to bank > fetch money > buy food > cook > buy books > do some reading > go to exam > eat
go to bank > fetch money > go to market > buy food > cook > buy books > do some reading > go to exam > eat
Observe how the requirement 'fetch money' > 'buy books'
made 'buy books'
appear at the very end of the list, and how only the additonal requirement 'buy
books' > 'do some reading'
managed to put the horse before the cart, as it
were. It still looks as though we're not quite done here yet, as we have to
leave house after cooking and go to the exam with an empty stomach according to
the current linearization, so some dependencies are still missing:
console.log ( TS.link_down g, 'buy food', 'go home' ).join ' > '
console.log ( TS.link_down g, 'buy books', 'go home' ).join ' > '
console.log ( TS.link_down g, 'go home', 'cook' ).join ' > '
console.log ( TS.link_down g, 'eat', 'go to exam' ).join ' > '
This makes the order of events more reasonable with each step:
go to bank > fetch money > go to market > buy food > cook > buy books > do some reading > go to exam > eat > go home
go to bank > fetch money > go to market > buy food > cook > buy books > do some reading > go to exam > eat > go home
go to bank > fetch money > go to market > buy food > buy books > go home > cook > do some reading > go to exam > eat
go to bank > fetch money > go to market > buy food > buy books > go home > cook > do some reading > eat > go to exam
The takeaway up to this point is that although you may have already entered all relevant activities, it may or or may not be the case that the relationships define a unique ordering—TSort will always give you some ordering, but not necessarily the only one. TSort remains silent about that. For this reason and because the precise ordering is dependent upon order of insertion, it may happen that a given result looks satisfying not because the constraints entered were both sufficient and complete, but because they happened to be added to the graph in a fitting sequence. In the same vein, adding more constraints may or may not change the linearization.
Furthermore, each new requirement may introduce an incompatible constraint. It
is by no means unreasonable as such to require that we want to eat before going
to the bank, but should we call TS.link_down g, 'eat', 'go to bank'
at this
point in time, TSort will throw an error (immediately if set to strict
,
otherwise as soon as TS.sort
is called), complaining that it has detected
cycle involving node 'buy food'
. Had we added TS.link_down g, 'eat', 'go to
bank'
first, the error would have resulted upon adding the constraint
TS.link_down g, 'go to bank', 'fetch money'
; in this case the message would've
been detected cycle involving node 'eat'
.
Now for a more CS-ish application of TSort; specifically, we want to implement the 'function table' that Ravindrababu Ravula derives in his lecture on Compiler Design Lecture 9—Operator grammar and Operator precedence parser (one of the few materials about Pratt-style Top-Down Operator Parsing (TDOP) i was able to find on the web).
| . | id
| +
| *
| $
|
| :--: | :---: | :---: | :---: | :---: |
| id
| —
| >
| >
| >
|
| +
| <
| >
| <
| >
|
| *
| <
| >
| >
| >
|
| $
| <
| <
| <
| —
|
operator precedence table
f|id > g|* > f|+ > g|+ > f|$
g|id > f|* > ⤴
| . | id
| +
| *
| $
|
| :--: | :---: | :---: | :---: | :---: |
| f
| 4
| 2
| 4
| 0
|
| g
| 5
| 1
| 3
| 0
|
CND = require 'cnd'
rpr = CND.rpr
badge = 'scratch'
debug = CND.get_logger 'debug', badge
help = CND.get_logger 'help', badge
test_tsort = ->
TS = CND.TSORT
settings =
strict: yes
prefixes: [ 'f|', 'g|', ]
graph = TS.new_graph settings
TS.link graph, 'id', '-', 'id'
TS.link graph, 'id', '>', '+'
TS.link graph, 'id', '>', '*'
TS.link graph, 'id', '>', '$'
TS.link graph, '+', '<', 'id'
TS.link graph, '+', '>', '+'
TS.link graph, '+', '<', '*'
TS.link graph, '+', '>', '$'
TS.link graph, '*', '<', 'id'
TS.link graph, '*', '>', '+'
TS.link graph, '*', '>', '*'
TS.link graph, '*', '>', '$'
TS.link graph, '$', '<', 'id'
TS.link graph, '$', '<', '+'
TS.link graph, '$', '<', '*'
TS.link graph, '$', '-', '$'
help nodes = TS.sort graph
matcher = [ 'f|id', 'g|id', 'f|*', 'g|*', 'f|+', 'g|+', 'g|$', 'f|$' ]
unless CND.equals nodes, matcher
throw new Error """is: #{rpr nodes}
expected: #{rpr matcher}"""
try
TS.link graph, '$', '>', '$'
TS.link graph, '$', '<', '$'
catch error
{ message } = error
if /^detected cycle involving node/.test message
warn error
else
throw error
test_tsort()
console.log '1', ( TS.precedence_of graph, 'f|id' ) > ( TS.precedence_of graph, 'g|+' ) # true
console.log '2', ( TS.precedence_of graph, 'f|id' ) > ( TS.precedence_of graph, 'g|*' ) # true
console.log '3', ( TS.precedence_of graph, 'f|id' ) > ( TS.precedence_of graph, 'g|$' ) # true
console.log '4', ( TS.precedence_of graph, 'f|+' ) < ( TS.precedence_of graph, 'g|id' ) # true
console.log '5', ( TS.precedence_of graph, 'f|+' ) > ( TS.precedence_of graph, 'g|+' ) # true
console.log '6', ( TS.precedence_of graph, 'f|+' ) < ( TS.precedence_of graph, 'g|*' ) # true
console.log '7', ( TS.precedence_of graph, 'f|+' ) > ( TS.precedence_of graph, 'g|$' ) # true
console.log '8', ( TS.precedence_of graph, 'f|*' ) < ( TS.precedence_of graph, 'g|id' ) # true
console.log '9', ( TS.precedence_of graph, 'f|*' ) > ( TS.precedence_of graph, 'g|+' ) # true
console.log '10', ( TS.precedence_of graph, 'f|*' ) > ( TS.precedence_of graph, 'g|*' ) # true
console.log '11', ( TS.precedence_of graph, 'f|*' ) > ( TS.precedence_of graph, 'g|$' ) # true
console.log '12', ( TS.precedence_of graph, 'f|$' ) < ( TS.precedence_of graph, 'g|id' ) # true
console.log '13', ( TS.precedence_of graph, 'f|$' ) < ( TS.precedence_of graph, 'g|+' ) # true
console.log '14', ( TS.precedence_of graph, 'f|$' ) < ( TS.precedence_of graph, 'g|*' ) # true
TSort API
@new_graph = ( settings ) ->
@link = ( me, f, r, g ) ->
@link_down = ( me, precedence, consequence ) ->
@link_up = ( me, consequence, precedence ) -> @link_down me, precedence, consequence
@register = ( me, names... ) ->
@sort = ( me ) ->
@get_precedences = ( me ) ->
@precedence_of = ( me, name ) ->
Some TDOP Links
- Pratt's original paper from 1973: http://hall.org.ua/halls/wizzard/pdf/Vaughan.Pratt.TDOP.pdf
- The same as an HTML page: http://tdop.github.io/
- Simple Top-Down Parsing in Python: http://effbot.org/zone/simple-top-down-parsing.htm
- Douglas Crockford on TDOP: http://javascript.crockford.com/tdop/tdop.html
XJSON
e = new Set 'xy'
e.add new Set 'abc'
d = [ 'A', 'B', e, ]
info CND.XJSON.stringify d
info CND.XJSON.parse CND.XJSON.stringify d
Output:
["A","B",{"~isa":"set","%self":["x","y",{"~isa":"set","%self":["a","b","c"]}]}]
[ 'A', 'B', Set { 'x', 'y', Set { 'a', 'b', 'c' } } ]
CND.TEXT.to_width
2
|北|2
|P |2
|Pe|2
|……|2
|P…|2
|a…|2
|x…|2
|a…|2
|a…|2
|……|2
|……|2
3
|北 |3
|P |3
|Pe |3
|北…|3
|Pe…|3
|a …|3
|xa…|3
|àx…|4
|a⃝b…|4
|北…|3
|北…|3
4
|北 |4
|P |4
|Pe |4
|北京|4
|Pek…|4
|a n…|4
|xàx…|5
|àxa…|5
|a⃝b⃞c…|6
|北……|4
|北……|4
5
|北 |5
|P |5
|Pe |5
|北京 |5
|Peki…|5
|a ni…|5
|xàxa…|6
|àxáx…|7
|a⃝b⃞c⃟a…|8
|北京…|5
|北京…|5
10
|北 |10
|P |10
|Pe |10
|北京 |10
|Peking |10
|a nice te…|10
|xàxáxâxãx…|14
|àxáxâxãxa…|14
|a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c…|18
|北京 (Pek…|10
|北京 (Pek…|10
15
|北 |15
|P |15
|Pe |15
|北京 |15
|Peking |15
|a nice test to…|15
|xàxáxâxãxāxa̅xa…|21
|àxáxâxãxāxa̅xăx…|22
|a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟…|25
|北京 (Peking) …|15
|北京 (Peking) …|15
20
|北 |20
|P |20
|Pe |20
|北京 |20
|Peking |20
|a nice test to see …|20
|xàxáxâxãxāxa̅xăxȧxax…|28
|àxáxâxãxāxa̅xăxȧxaxa…|28
|a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟…|25
|北京 (Peking) 位於……|20
|北京 (Peking) 位於……|20
25
|北 |25
|P |25
|Pe |25
|北京 |25
|Peking |25
|a nice test to see the e…|25
|xàxáxâxãxāxa̅xăxȧxaxa̠xa̡xa…|35
|àxáxâxãxāxa̅xăxȧxaxa̠xa̡xa̢x…|36
|a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟a⃝b⃞c⃟ |25
|北京 (Peking) 位於華北 (…|25
|北京 (Peking) 位於華北 (…|25
0 1 2 3
0123456789012345678901234567890123456789
a nice test to see the effect*
北京 (Peking) 位於華北 (North*
北京 (Peking) 位於華北 (North*
ToDo
- [ ] Add a utility method to enable catch-all listeners on event emitters (as used in kleinbild):
_emit = R.emit.bind R
R.emit = ( event_name, P... ) =>
_emit '*', event_name, P...
_emit event_name, P...
return null
R.on '*', ( event_name, P... ) =>
@U.dump event_name, P...
return null
- [ ] use together with
node-icecream
:ic = ( require 'node-icecream' ) { prefix: '', outputFunction: debug, }