Linux premium71.web-hosting.com 4.18.0-513.11.1.lve.el8.x86_64 #1 SMP Thu Jan 18 16:21:02 UTC 2024 x86_64
LiteSpeed
Server IP : 198.187.29.8 & Your IP : 13.58.228.206
Domains :
Cant Read [ /etc/named.conf ]
User : cleahvkv
Terminal
Auto Root
Create File
Create Folder
Localroot Suggester
Backdoor Destroyer
Readme
/
opt /
alt /
ruby33 /
share /
ruby /
Delete
Unzip
Name
Size
Permission
Date
Action
bigdecimal
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
cgi
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
csv
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
did_you_mean
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
digest
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
drb
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
erb
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
error_highlight
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
fiddle
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
forwardable
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
io
[ DIR ]
drwxr-xr-x
2025-01-26 18:06
json
[ DIR ]
drwxr-xr-x
2025-02-06 11:33
logger
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
net
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
objspace
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
open3
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
openssl
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
optparse
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
prism
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
psych
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
random
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
reline
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
rinda
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
ripper
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
ruby_vm
[ DIR ]
drwxr-xr-x
2024-06-12 10:36
set
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
syntax_suggest
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
syslog
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
unicode_normalize
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
uri
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
vendor_ruby
[ DIR ]
drwxr-xr-x
2025-01-26 18:06
yaml
[ DIR ]
drwxr-xr-x
2025-02-06 11:32
English.rb
5.54
KB
-rw-r--r--
2025-01-26 18:06
abbrev.rb
3.47
KB
-rw-r--r--
2025-01-26 18:06
base64.rb
13.22
KB
-rw-r--r--
2025-01-26 18:06
benchmark.rb
18.42
KB
-rw-r--r--
2025-01-26 18:06
bigdecimal.rb
130
B
-rw-r--r--
2025-01-26 18:06
bundled_gems.rb
6.86
KB
-rw-r--r--
2025-01-26 18:06
cgi.rb
9.83
KB
-rw-r--r--
2025-01-26 18:06
coverage.rb
368
B
-rw-r--r--
2025-01-26 18:06
csv.rb
92.46
KB
-rw-r--r--
2025-01-26 18:06
date.rb
1.17
KB
-rw-r--r--
2025-01-26 18:06
delegate.rb
11.68
KB
-rw-r--r--
2025-01-26 18:06
did_you_mean.rb
5.36
KB
-rw-r--r--
2025-01-26 18:06
digest.rb
3.3
KB
-rw-r--r--
2025-01-26 18:06
drb.rb
50
B
-rw-r--r--
2025-01-26 18:06
erb.rb
14.53
KB
-rw-r--r--
2025-01-26 18:06
error_highlight.rb
84
B
-rw-r--r--
2025-01-26 18:06
expect.rb
2.19
KB
-rw-r--r--
2025-01-26 18:06
fiddle.rb
2.88
KB
-rw-r--r--
2025-01-26 18:06
fileutils.rb
78.69
KB
-rw-r--r--
2025-01-26 18:06
find.rb
2.52
KB
-rw-r--r--
2025-01-26 18:06
forwardable.rb
9.03
KB
-rw-r--r--
2025-01-26 18:06
getoptlong.rb
20.26
KB
-rw-r--r--
2025-01-26 18:06
ipaddr.rb
20.93
KB
-rw-r--r--
2025-01-26 18:06
json.rb
19.62
KB
-rw-r--r--
2025-01-26 18:06
kconv.rb
5.72
KB
-rw-r--r--
2025-01-26 18:06
logger.rb
22.03
KB
-rw-r--r--
2025-01-26 18:06
mkmf.rb
88.69
KB
-rw-r--r--
2025-01-26 18:06
monitor.rb
6.75
KB
-rw-r--r--
2025-01-26 18:06
mutex_m.rb
2.36
KB
-rw-r--r--
2025-01-26 18:06
objspace.rb
4.14
KB
-rw-r--r--
2025-01-26 18:06
observer.rb
6.38
KB
-rw-r--r--
2025-01-26 18:06
open-uri.rb
25.84
KB
-rw-r--r--
2025-01-26 18:06
open3.rb
47.51
KB
-rw-r--r--
2025-01-26 18:06
openssl.rb
1.03
KB
-rw-r--r--
2025-01-26 18:06
optionparser.rb
59
B
-rw-r--r--
2025-01-26 18:06
optparse.rb
61.82
KB
-rw-r--r--
2025-01-26 18:06
ostruct.rb
14.22
KB
-rw-r--r--
2025-01-26 18:06
pathname.rb
16.85
KB
-rw-r--r--
2025-01-26 18:06
pp.rb
17.24
KB
-rw-r--r--
2025-01-26 18:06
prettyprint.rb
15.93
KB
-rw-r--r--
2025-01-26 18:06
prism.rb
3.17
KB
-rw-r--r--
2025-01-26 18:06
pstore.rb
20.36
KB
-rw-r--r--
2025-01-26 18:06
psych.rb
24.44
KB
-rw-r--r--
2025-01-26 18:06
readline.rb
215
B
-rw-r--r--
2025-01-26 18:06
reline.rb
14.7
KB
-rw-r--r--
2025-01-26 18:06
resolv-replace.rb
1.76
KB
-rw-r--r--
2025-01-26 18:06
resolv.rb
85.03
KB
-rw-r--r--
2025-01-26 18:06
ripper.rb
2.44
KB
-rw-r--r--
2025-01-26 18:06
securerandom.rb
2.06
KB
-rw-r--r--
2025-01-26 18:06
set.rb
24.94
KB
-rw-r--r--
2025-01-26 18:06
shellwords.rb
7.11
KB
-rw-r--r--
2025-01-26 18:06
singleton.rb
3.94
KB
-rw-r--r--
2025-01-26 18:06
socket.rb
44.04
KB
-rw-r--r--
2025-01-26 18:06
syntax_suggest.rb
74
B
-rw-r--r--
2025-01-26 18:06
tempfile.rb
14.73
KB
-rw-r--r--
2025-01-26 18:06
time.rb
23.74
KB
-rw-r--r--
2025-01-26 18:06
timeout.rb
5.69
KB
-rw-r--r--
2025-01-26 18:06
tmpdir.rb
4.93
KB
-rw-r--r--
2025-01-26 18:06
tsort.rb
14.29
KB
-rw-r--r--
2025-01-26 18:06
un.rb
11.17
KB
-rw-r--r--
2025-01-26 18:06
uri.rb
3.06
KB
-rw-r--r--
2025-01-26 18:06
weakref.rb
1.36
KB
-rw-r--r--
2025-01-26 18:06
yaml.rb
2.13
KB
-rw-r--r--
2025-01-26 18:06
Save
Rename
# frozen_string_literal: true #-- # tsort.rb - provides a module for topological sorting and strongly connected components. #++ # # # TSort implements topological sorting using Tarjan's algorithm for # strongly connected components. # # TSort is designed to be able to be used with any object which can be # interpreted as a directed graph. # # TSort requires two methods to interpret an object as a graph, # tsort_each_node and tsort_each_child. # # * tsort_each_node is used to iterate for all nodes over a graph. # * tsort_each_child is used to iterate for child nodes of a given node. # # The equality of nodes are defined by eql? and hash since # TSort uses Hash internally. # # == A Simple Example # # The following example demonstrates how to mix the TSort module into an # existing class (in this case, Hash). Here, we're treating each key in # the hash as a node in the graph, and so we simply alias the required # #tsort_each_node method to Hash's #each_key method. For each key in the # hash, the associated value is an array of the node's child nodes. This # choice in turn leads to our implementation of the required #tsort_each_child # method, which fetches the array of child nodes and then iterates over that # array using the user-supplied block. # # require 'tsort' # # class Hash # include TSort # alias tsort_each_node each_key # def tsort_each_child(node, &block) # fetch(node).each(&block) # end # end # # {1=>[2, 3], 2=>[3], 3=>[], 4=>[]}.tsort # #=> [3, 2, 1, 4] # # {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}.strongly_connected_components # #=> [[4], [2, 3], [1]] # # == A More Realistic Example # # A very simple `make' like tool can be implemented as follows: # # require 'tsort' # # class Make # def initialize # @dep = {} # @dep.default = [] # end # # def rule(outputs, inputs=[], &block) # triple = [outputs, inputs, block] # outputs.each {|f| @dep[f] = [triple]} # @dep[triple] = inputs # end # # def build(target) # each_strongly_connected_component_from(target) {|ns| # if ns.length != 1 # fs = ns.delete_if {|n| Array === n} # raise TSort::Cyclic.new("cyclic dependencies: #{fs.join ', '}") # end # n = ns.first # if Array === n # outputs, inputs, block = n # inputs_time = inputs.map {|f| File.mtime f}.max # begin # outputs_time = outputs.map {|f| File.mtime f}.min # rescue Errno::ENOENT # outputs_time = nil # end # if outputs_time == nil || # inputs_time != nil && outputs_time <= inputs_time # sleep 1 if inputs_time != nil && inputs_time.to_i == Time.now.to_i # block.call # end # end # } # end # # def tsort_each_child(node, &block) # @dep[node].each(&block) # end # include TSort # end # # def command(arg) # print arg, "\n" # system arg # end # # m = Make.new # m.rule(%w[t1]) { command 'date > t1' } # m.rule(%w[t2]) { command 'date > t2' } # m.rule(%w[t3]) { command 'date > t3' } # m.rule(%w[t4], %w[t1 t3]) { command 'cat t1 t3 > t4' } # m.rule(%w[t5], %w[t4 t2]) { command 'cat t4 t2 > t5' } # m.build('t5') # # == Bugs # # * 'tsort.rb' is wrong name because this library uses # Tarjan's algorithm for strongly connected components. # Although 'strongly_connected_components.rb' is correct but too long. # # == References # # R. E. Tarjan, "Depth First Search and Linear Graph Algorithms", # <em>SIAM Journal on Computing</em>, Vol. 1, No. 2, pp. 146-160, June 1972. # module TSort VERSION = "0.2.0" class Cyclic < StandardError end # Returns a topologically sorted array of nodes. # The array is sorted from children to parents, i.e. # the first element has no child and the last node has no parent. # # If there is a cycle, TSort::Cyclic is raised. # # class G # include TSort # def initialize(g) # @g = g # end # def tsort_each_child(n, &b) @g[n].each(&b) end # def tsort_each_node(&b) @g.each_key(&b) end # end # # graph = G.new({1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]}) # p graph.tsort #=> [4, 2, 3, 1] # # graph = G.new({1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}) # p graph.tsort # raises TSort::Cyclic # def tsort each_node = method(:tsort_each_node) each_child = method(:tsort_each_child) TSort.tsort(each_node, each_child) end # Returns a topologically sorted array of nodes. # The array is sorted from children to parents, i.e. # the first element has no child and the last node has no parent. # # The graph is represented by _each_node_ and _each_child_. # _each_node_ should have +call+ method which yields for each node in the graph. # _each_child_ should have +call+ method which takes a node argument and yields for each child node. # # If there is a cycle, TSort::Cyclic is raised. # # g = {1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # p TSort.tsort(each_node, each_child) #=> [4, 2, 3, 1] # # g = {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # p TSort.tsort(each_node, each_child) # raises TSort::Cyclic # def self.tsort(each_node, each_child) tsort_each(each_node, each_child).to_a end # The iterator version of the #tsort method. # <tt><em>obj</em>.tsort_each</tt> is similar to <tt><em>obj</em>.tsort.each</tt>, but # modification of _obj_ during the iteration may lead to unexpected results. # # #tsort_each returns +nil+. # If there is a cycle, TSort::Cyclic is raised. # # class G # include TSort # def initialize(g) # @g = g # end # def tsort_each_child(n, &b) @g[n].each(&b) end # def tsort_each_node(&b) @g.each_key(&b) end # end # # graph = G.new({1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]}) # graph.tsort_each {|n| p n } # #=> 4 # # 2 # # 3 # # 1 # def tsort_each(&block) # :yields: node each_node = method(:tsort_each_node) each_child = method(:tsort_each_child) TSort.tsort_each(each_node, each_child, &block) end # The iterator version of the TSort.tsort method. # # The graph is represented by _each_node_ and _each_child_. # _each_node_ should have +call+ method which yields for each node in the graph. # _each_child_ should have +call+ method which takes a node argument and yields for each child node. # # g = {1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # TSort.tsort_each(each_node, each_child) {|n| p n } # #=> 4 # # 2 # # 3 # # 1 # def self.tsort_each(each_node, each_child) # :yields: node return to_enum(__method__, each_node, each_child) unless block_given? each_strongly_connected_component(each_node, each_child) {|component| if component.size == 1 yield component.first else raise Cyclic.new("topological sort failed: #{component.inspect}") end } end # Returns strongly connected components as an array of arrays of nodes. # The array is sorted from children to parents. # Each elements of the array represents a strongly connected component. # # class G # include TSort # def initialize(g) # @g = g # end # def tsort_each_child(n, &b) @g[n].each(&b) end # def tsort_each_node(&b) @g.each_key(&b) end # end # # graph = G.new({1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]}) # p graph.strongly_connected_components #=> [[4], [2], [3], [1]] # # graph = G.new({1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}) # p graph.strongly_connected_components #=> [[4], [2, 3], [1]] # def strongly_connected_components each_node = method(:tsort_each_node) each_child = method(:tsort_each_child) TSort.strongly_connected_components(each_node, each_child) end # Returns strongly connected components as an array of arrays of nodes. # The array is sorted from children to parents. # Each elements of the array represents a strongly connected component. # # The graph is represented by _each_node_ and _each_child_. # _each_node_ should have +call+ method which yields for each node in the graph. # _each_child_ should have +call+ method which takes a node argument and yields for each child node. # # g = {1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # p TSort.strongly_connected_components(each_node, each_child) # #=> [[4], [2], [3], [1]] # # g = {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # p TSort.strongly_connected_components(each_node, each_child) # #=> [[4], [2, 3], [1]] # def self.strongly_connected_components(each_node, each_child) each_strongly_connected_component(each_node, each_child).to_a end # The iterator version of the #strongly_connected_components method. # <tt><em>obj</em>.each_strongly_connected_component</tt> is similar to # <tt><em>obj</em>.strongly_connected_components.each</tt>, but # modification of _obj_ during the iteration may lead to unexpected results. # # #each_strongly_connected_component returns +nil+. # # class G # include TSort # def initialize(g) # @g = g # end # def tsort_each_child(n, &b) @g[n].each(&b) end # def tsort_each_node(&b) @g.each_key(&b) end # end # # graph = G.new({1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]}) # graph.each_strongly_connected_component {|scc| p scc } # #=> [4] # # [2] # # [3] # # [1] # # graph = G.new({1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}) # graph.each_strongly_connected_component {|scc| p scc } # #=> [4] # # [2, 3] # # [1] # def each_strongly_connected_component(&block) # :yields: nodes each_node = method(:tsort_each_node) each_child = method(:tsort_each_child) TSort.each_strongly_connected_component(each_node, each_child, &block) end # The iterator version of the TSort.strongly_connected_components method. # # The graph is represented by _each_node_ and _each_child_. # _each_node_ should have +call+ method which yields for each node in the graph. # _each_child_ should have +call+ method which takes a node argument and yields for each child node. # # g = {1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # TSort.each_strongly_connected_component(each_node, each_child) {|scc| p scc } # #=> [4] # # [2] # # [3] # # [1] # # g = {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]} # each_node = lambda {|&b| g.each_key(&b) } # each_child = lambda {|n, &b| g[n].each(&b) } # TSort.each_strongly_connected_component(each_node, each_child) {|scc| p scc } # #=> [4] # # [2, 3] # # [1] # def self.each_strongly_connected_component(each_node, each_child) # :yields: nodes return to_enum(__method__, each_node, each_child) unless block_given? id_map = {} stack = [] each_node.call {|node| unless id_map.include? node each_strongly_connected_component_from(node, each_child, id_map, stack) {|c| yield c } end } nil end # Iterates over strongly connected component in the subgraph reachable from # _node_. # # Return value is unspecified. # # #each_strongly_connected_component_from doesn't call #tsort_each_node. # # class G # include TSort # def initialize(g) # @g = g # end # def tsort_each_child(n, &b) @g[n].each(&b) end # def tsort_each_node(&b) @g.each_key(&b) end # end # # graph = G.new({1=>[2, 3], 2=>[4], 3=>[2, 4], 4=>[]}) # graph.each_strongly_connected_component_from(2) {|scc| p scc } # #=> [4] # # [2] # # graph = G.new({1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}) # graph.each_strongly_connected_component_from(2) {|scc| p scc } # #=> [4] # # [2, 3] # def each_strongly_connected_component_from(node, id_map={}, stack=[], &block) # :yields: nodes TSort.each_strongly_connected_component_from(node, method(:tsort_each_child), id_map, stack, &block) end # Iterates over strongly connected components in a graph. # The graph is represented by _node_ and _each_child_. # # _node_ is the first node. # _each_child_ should have +call+ method which takes a node argument # and yields for each child node. # # Return value is unspecified. # # #TSort.each_strongly_connected_component_from is a class method and # it doesn't need a class to represent a graph which includes TSort. # # graph = {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]} # each_child = lambda {|n, &b| graph[n].each(&b) } # TSort.each_strongly_connected_component_from(1, each_child) {|scc| # p scc # } # #=> [4] # # [2, 3] # # [1] # def self.each_strongly_connected_component_from(node, each_child, id_map={}, stack=[]) # :yields: nodes return to_enum(__method__, node, each_child, id_map, stack) unless block_given? minimum_id = node_id = id_map[node] = id_map.size stack_length = stack.length stack << node each_child.call(node) {|child| if id_map.include? child child_id = id_map[child] minimum_id = child_id if child_id && child_id < minimum_id else sub_minimum_id = each_strongly_connected_component_from(child, each_child, id_map, stack) {|c| yield c } minimum_id = sub_minimum_id if sub_minimum_id < minimum_id end } if node_id == minimum_id component = stack.slice!(stack_length .. -1) component.each {|n| id_map[n] = nil} yield component end minimum_id end # Should be implemented by a extended class. # # #tsort_each_node is used to iterate for all nodes over a graph. # def tsort_each_node # :yields: node raise NotImplementedError.new end # Should be implemented by a extended class. # # #tsort_each_child is used to iterate for child nodes of _node_. # def tsort_each_child(node) # :yields: child raise NotImplementedError.new end end