Involved Source Files Copyright (c) 2015 Björn Rabenstein
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The code in this package is copy/paste to avoid a dependency. Hence this file
carries the copyright of the original repo.
https://github.com/beorn7/floats Copyright 2022 The Prometheus Authors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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Unless required by applicable law or agreed to in writing, software
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See the License for the specific language governing permissions and
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It provides tools to compare sequences of strings and generate textual diffs.
Maintaining `GetUnifiedDiffString` here because original repository
(https://github.com/pmezard/go-difflib) is no longer maintained.go_collector_options.gogo_runtime_metrics.gometric.go
LabelPairSorter implements sort.Interface. It is used to sort a slice of
dto.LabelPair pointers.( LabelPairSorter) Len() int( LabelPairSorter) Less(i, j int) bool( LabelPairSorter) Swap(i, j int)
LabelPairSorter : sort.Interface
SequenceMatcher compares sequence of strings. The basic
algorithm predates, and is a little fancier than, an algorithm
published in the late 1980's by Ratcliff and Obershelp under the
hyperbolic name "gestalt pattern matching". The basic idea is to find
the longest contiguous matching subsequence that contains no "junk"
elements (R-O doesn't address junk). The same idea is then applied
recursively to the pieces of the sequences to the left and to the right
of the matching subsequence. This does not yield minimal edit
sequences, but does tend to yield matches that "look right" to people.
SequenceMatcher tries to compute a "human-friendly diff" between two
sequences. Unlike e.g. UNIX(tm) diff, the fundamental notion is the
longest *contiguous* & junk-free matching subsequence. That's what
catches peoples' eyes. The Windows(tm) windiff has another interesting
notion, pairing up elements that appear uniquely in each sequence.
That, and the method here, appear to yield more intuitive difference
reports than does diff. This method appears to be the least vulnerable
to synching up on blocks of "junk lines", though (like blank lines in
ordinary text files, or maybe "<P>" lines in HTML files). That may be
because this is the only method of the 3 that has a *concept* of
"junk" <wink>.
Timing: Basic R-O is cubic time worst case and quadratic time expected
case. SequenceMatcher is quadratic time for the worst case and has
expected-case behavior dependent in a complicated way on how many
elements the sequences have in common; best case time is linear.IsJunkfunc(string) bool Isolate change clusters by eliminating ranges with no changes.
Return a generator of groups with up to n lines of context.
Each group is in the same format as returned by GetOpCodes(). Return list of triples describing matching subsequences.
Each triple is of the form (i, j, n), and means that
a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in
i and in j. It's also guaranteed that if (i, j, n) and (i', j', n') are
adjacent triples in the list, and the second is not the last triple in the
list, then i+n != i' or j+n != j'. IOW, adjacent triples never describe
adjacent equal blocks.
The last triple is a dummy, (len(a), len(b), 0), and is the only
triple with n==0. Return list of 5-tuples describing how to turn a into b.
Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple
has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the
tuple preceding it, and likewise for j1 == the previous j2.
The tags are characters, with these meanings:
'r' (replace): a[i1:i2] should be replaced by b[j1:j2]
'd' (delete): a[i1:i2] should be deleted, j1==j2 in this case.
'i' (insert): b[j1:j2] should be inserted at a[i1:i1], i1==i2 in this case.
'e' (equal): a[i1:i2] == b[j1:j2] Return an upper bound on ratio() relatively quickly.
This isn't defined beyond that it is an upper bound on .Ratio(), and
is faster to compute. Return a measure of the sequences' similarity (float in [0,1]).
Where T is the total number of elements in both sequences, and
M is the number of matches, this is 2.0*M / T.
Note that this is 1 if the sequences are identical, and 0 if
they have nothing in common.
.Ratio() is expensive to compute if you haven't already computed
.GetMatchingBlocks() or .GetOpCodes(), in which case you may
want to try .QuickRatio() or .RealQuickRation() first to get an
upper bound. Return an upper bound on ratio() very quickly.
This isn't defined beyond that it is an upper bound on .Ratio(), and
is faster to compute than either .Ratio() or .QuickRatio(). Set the first sequence to be compared. The second sequence to be compared is
not changed.
SequenceMatcher computes and caches detailed information about the second
sequence, so if you want to compare one sequence S against many sequences,
use .SetSeq2(s) once and call .SetSeq1(x) repeatedly for each of the other
sequences.
See also SetSeqs() and SetSeq2(). Set the second sequence to be compared. The first sequence to be compared is
not changed. Set two sequences to be compared.
func NewMatcher(a, b []string) *SequenceMatcher
func NewMatcherWithJunk(a, b []string, autoJunk bool, isJunk func(string) bool) *SequenceMatcher
Unified diff parameters // First sequence lines // Second sequence lines // Number of context lines // Headers end of line, defaults to LF // First file time // First file name // Second file time // Second file name
func GetUnifiedDiffString(diff UnifiedDiff) (string, error)
func WriteUnifiedDiff(writer io.Writer, diff UnifiedDiff) error
NormalizeMetricFamilies returns a MetricFamily slice with empty
MetricFamilies pruned and the remaining MetricFamilies sorted by name within
the slice, with the contained Metrics sorted within each MetricFamily.
RuntimeMetricsBucketsForUnit takes a set of buckets obtained for a runtime/metrics histogram
type (so, lower-bound inclusive) and a unit from a runtime/metrics name, and produces
a reduced set of buckets. This function always removes any -Inf bucket as it's represented
as the bottom-most upper-bound inclusive bucket in Prometheus.
RuntimeMetricsToProm produces a Prometheus metric name from a runtime/metrics
metric description and validates whether the metric is suitable for integration
with Prometheus.
Returns false if a name could not be produced, or if Prometheus does not understand
the runtime/metrics Kind.
Note that the main reason a name couldn't be produced is if the runtime/metrics
package exports a name with characters outside the valid Prometheus metric name
character set. This is theoretically possible, but should never happen in practice.
Still, don't rely on it.
Split a string on "\n" while preserving them. The output can be used
as input for UnifiedDiff and ContextDiff structures.
Compare two sequences of lines; generate the delta as a unified diff.
Unified diffs are a compact way of showing line changes and a few
lines of context. The number of context lines is set by 'n' which
defaults to three.
By default, the diff control lines (those with ---, +++, or @@) are
created with a trailing newline. This is helpful so that inputs
created from file.readlines() result in diffs that are suitable for
file.writelines() since both the inputs and outputs have trailing
newlines.
For inputs that do not have trailing newlines, set the lineterm
argument to "" so that the output will be uniformly newline free.
The unidiff format normally has a header for filenames and modification
times. Any or all of these may be specified using strings for
'fromfile', 'tofile', 'fromfiledate', and 'tofiledate'.
The modification times are normally expressed in the ISO 8601 format.
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