adphi/YTSFlix_Go
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

init

Browse Source
This commit is contained in:
Adphi
2018-11-04 15:58:15 +01:00
commit f956bcee28
1178 changed files with 584552 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

24
vendor/github.com/willf/bloom/LICENSE generated vendored Normal file
View File

@ -0,0 +1,24 @@
Copyright (c) 2014 Will Fitzgerald. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following disclaimer
in the documentation and/or other materials provided with the
distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

197
vendor/github.com/willf/bloom/Makefile generated vendored Normal file
View File

@ -0,0 +1,197 @@
# MAKEFILE
#
# @author Nicola Asuni <info@tecnick.com>
# @link https://github.com/willf/bloom
# ------------------------------------------------------------------------------
# List special make targets that are not associated with files
.PHONY: help all test format fmtcheck vet lint coverage cyclo ineffassign misspell structcheck varcheck errcheck gosimple astscan qa deps clean nuke
# Use bash as shell (Note: Ubuntu now uses dash which doesn't support PIPESTATUS).
SHELL=/bin/bash
# CVS path (path to the parent dir containing the project)
CVSPATH=github.com/willf
# Project owner
OWNER=willf
# Project vendor
VENDOR=willf
# Project name
PROJECT=bloom
# Project version
VERSION=$(shell cat VERSION)
# Name of RPM or DEB package
PKGNAME=${VENDOR}-${PROJECT}
# Current directory
CURRENTDIR=$(shell pwd)
# GO lang path
ifneq ($(GOPATH),)
ifeq ($(findstring $(GOPATH),$(CURRENTDIR)),)
# the defined GOPATH is not valid
GOPATH=
endif
endif
ifeq ($(GOPATH),)
# extract the GOPATH
GOPATH=$(firstword $(subst /src/, ,$(CURRENTDIR)))
endif
# --- MAKE TARGETS ---
# Display general help about this command
help:
@echo ""
@echo "$(PROJECT) Makefile."
@echo "GOPATH=$(GOPATH)"
@echo "The following commands are available:"
@echo ""
@echo " make qa : Run all the tests"
@echo " make test : Run the unit tests"
@echo ""
@echo " make format : Format the source code"
@echo " make fmtcheck : Check if the source code has been formatted"
@echo " make vet : Check for suspicious constructs"
@echo " make lint : Check for style errors"
@echo " make coverage : Generate the coverage report"
@echo " make cyclo : Generate the cyclomatic complexity report"
@echo " make ineffassign : Detect ineffectual assignments"
@echo " make misspell : Detect commonly misspelled words in source files"
@echo " make structcheck : Find unused struct fields"
@echo " make varcheck : Find unused global variables and constants"
@echo " make errcheck : Check that error return values are used"
@echo " make gosimple : Suggest code simplifications"
@echo " make astscan : GO AST scanner"
@echo ""
@echo " make docs : Generate source code documentation"
@echo ""
@echo " make deps : Get the dependencies"
@echo " make clean : Remove any build artifact"
@echo " make nuke : Deletes any intermediate file"
@echo ""
# Alias for help target
all: help
# Run the unit tests
test:
@mkdir -p target/test
@mkdir -p target/report
GOPATH=$(GOPATH) \
go test \
-covermode=atomic \
-bench=. \
-race \
-cpuprofile=target/report/cpu.out \
-memprofile=target/report/mem.out \
-mutexprofile=target/report/mutex.out \
-coverprofile=target/report/coverage.out \
-v ./... | \
tee >(PATH=$(GOPATH)/bin:$(PATH) go-junit-report > target/test/report.xml); \
test $${PIPESTATUS[0]} -eq 0
# Format the source code
format:
@find . -type f -name "*.go" -exec gofmt -s -w {} \;
# Check if the source code has been formatted
fmtcheck:
@mkdir -p target
@find . -type f -name "*.go" -exec gofmt -s -d {} \; | tee target/format.diff
@test ! -s target/format.diff || { echo "ERROR: the source code has not been formatted - please use 'make format' or 'gofmt'"; exit 1; }
# Check for syntax errors
vet:
GOPATH=$(GOPATH) go vet .
# Check for style errors
lint:
GOPATH=$(GOPATH) PATH=$(GOPATH)/bin:$(PATH) golint .
# Generate the coverage report
coverage:
@mkdir -p target/report
GOPATH=$(GOPATH) \
go tool cover -html=target/report/coverage.out -o target/report/coverage.html
# Report cyclomatic complexity
cyclo:
@mkdir -p target/report
GOPATH=$(GOPATH) gocyclo -avg ./ | tee target/report/cyclo.txt ; test $${PIPESTATUS[0]} -eq 0
# Detect ineffectual assignments
ineffassign:
@mkdir -p target/report
GOPATH=$(GOPATH) ineffassign ./ | tee target/report/ineffassign.txt ; test $${PIPESTATUS[0]} -eq 0
# Detect commonly misspelled words in source files
misspell:
@mkdir -p target/report
GOPATH=$(GOPATH) misspell -error ./ | tee target/report/misspell.txt ; test $${PIPESTATUS[0]} -eq 0
# Find unused struct fields
structcheck:
@mkdir -p target/report
GOPATH=$(GOPATH) structcheck -a ./ | tee target/report/structcheck.txt
# Find unused global variables and constants
varcheck:
@mkdir -p target/report
GOPATH=$(GOPATH) varcheck -e ./ | tee target/report/varcheck.txt
# Check that error return values are used
errcheck:
@mkdir -p target/report
GOPATH=$(GOPATH) errcheck ./ | tee target/report/errcheck.txt
# Suggest code simplifications
gosimple:
@mkdir -p target/report
GOPATH=$(GOPATH) gosimple ./ | tee target/report/gosimple.txt
# AST scanner
astscan:
@mkdir -p target/report
GOPATH=$(GOPATH) gas .//*.go | tee target/report/astscan.txt ; test $${PIPESTATUS[0]} -eq 0
# Generate source docs
docs:
@mkdir -p target/docs
nohup sh -c 'GOPATH=$(GOPATH) godoc -http=127.0.0.1:6060' > target/godoc_server.log 2>&1 &
wget --directory-prefix=target/docs/ --execute robots=off --retry-connrefused --recursive --no-parent --adjust-extension --page-requisites --convert-links http://127.0.0.1:6060/pkg/github.com/${VENDOR}/${PROJECT}/ ; kill -9 `lsof -ti :6060`
@echo '<html><head><meta http-equiv="refresh" content="0;./127.0.0.1:6060/pkg/'${CVSPATH}'/'${PROJECT}'/index.html"/></head><a href="./127.0.0.1:6060/pkg/'${CVSPATH}'/'${PROJECT}'/index.html">'${PKGNAME}' Documentation ...</a></html>' > target/docs/index.html
# Alias to run all quality-assurance checks
qa: fmtcheck test vet lint coverage cyclo ineffassign misspell structcheck varcheck errcheck gosimple astscan
# --- INSTALL ---
# Get the dependencies
deps:
GOPATH=$(GOPATH) go get ./...
GOPATH=$(GOPATH) go get github.com/golang/lint/golint
GOPATH=$(GOPATH) go get github.com/jstemmer/go-junit-report
GOPATH=$(GOPATH) go get github.com/axw/gocov/gocov
GOPATH=$(GOPATH) go get github.com/fzipp/gocyclo
GOPATH=$(GOPATH) go get github.com/gordonklaus/ineffassign
GOPATH=$(GOPATH) go get github.com/client9/misspell/cmd/misspell
GOPATH=$(GOPATH) go get github.com/opennota/check/cmd/structcheck
GOPATH=$(GOPATH) go get github.com/opennota/check/cmd/varcheck
GOPATH=$(GOPATH) go get github.com/kisielk/errcheck
GOPATH=$(GOPATH) go get honnef.co/go/tools/cmd/gosimple
GOPATH=$(GOPATH) go get github.com/GoASTScanner/gas
# Remove any build artifact
clean:
GOPATH=$(GOPATH) go clean ./...
# Deletes any intermediate file
nuke:
rm -rf ./target
GOPATH=$(GOPATH) go clean -i ./...

69
vendor/github.com/willf/bloom/README.md generated vendored Normal file
View File

@ -0,0 +1,69 @@
Bloom filters
-------------
[![Master Build Status](https://secure.travis-ci.org/willf/bloom.png?branch=master)](https://travis-ci.org/willf/bloom?branch=master)
[![Coverage Status](https://coveralls.io/repos/github/willf/bloom/badge.svg?branch=master)](https://coveralls.io/github/willf/bloom?branch=master)
[![Go Report Card](https://goreportcard.com/badge/github.com/willf/bloom)](https://goreportcard.com/report/github.com/willf/bloom)
[![GoDoc](https://godoc.org/github.com/willf/bloom?status.svg)](http://godoc.org/github.com/willf/bloom)
A Bloom filter is a representation of a set of _n_ items, where the main
requirement is to make membership queries; _i.e._, whether an item is a
member of a set.
A Bloom filter has two parameters: _m_, a maximum size (typically a reasonably large multiple of the cardinality of the set to represent) and _k_, the number of hashing functions on elements of the set. (The actual hashing functions are important, too, but this is not a parameter for this implementation). A Bloom filter is backed by a [BitSet](https://github.com/willf/bitset); a key is represented in the filter by setting the bits at each value of the hashing functions (modulo _m_). Set membership is done by _testing_ whether the bits at each value of the hashing functions (again, modulo _m_) are set. If so, the item is in the set. If the item is actually in the set, a Bloom filter will never fail (the true positive rate is 1.0); but it is susceptible to false positives. The art is to choose _k_ and _m_ correctly.
In this implementation, the hashing functions used is [murmurhash](github.com/spaolacci/murmur3), a non-cryptographic hashing function.
This implementation accepts keys for setting and testing as `[]byte`. Thus, to
add a string item, `"Love"`:
n := uint(1000)
filter := bloom.New(20*n, 5) // load of 20, 5 keys
filter.Add([]byte("Love"))
Similarly, to test if `"Love"` is in bloom:
if filter.Test([]byte("Love"))
For numeric data, I recommend that you look into the encoding/binary library. But, for example, to add a `uint32` to the filter:
i := uint32(100)
n1 := make([]byte, 4)
binary.BigEndian.PutUint32(n1, i)
filter.Add(n1)
Finally, there is a method to estimate the false positive rate of a particular
bloom filter for a set of size _n_:
if filter.EstimateFalsePositiveRate(1000) > 0.001
Given the particular hashing scheme, it's best to be empirical about this. Note
that estimating the FP rate will clear the Bloom filter.
Discussion here: [Bloom filter](https://groups.google.com/d/topic/golang-nuts/6MktecKi1bE/discussion)
Godoc documentation: https://godoc.org/github.com/willf/bloom
## Installation
```bash
go get -u github.com/willf/bloom
```
## Contributing
If you wish to contribute to this project, please branch and issue a pull request against master ("[GitHub Flow](https://guides.github.com/introduction/flow/)")
This project include a Makefile that allows you to test and build the project with simple commands.
To see all available options:
```bash
make help
```
## Running all tests
Before committing the code, please check if it passes all tests using (note: this will install some dependencies):
```bash
make deps
make qa
```

1
vendor/github.com/willf/bloom/VERSION generated vendored Normal file
View File

@ -0,0 +1 @@
2.0.3

362
vendor/github.com/willf/bloom/bloom.go generated vendored Normal file
View File

@ -0,0 +1,362 @@
/*
Package bloom provides data structures and methods for creating Bloom filters.
A Bloom filter is a representation of a set of _n_ items, where the main
requirement is to make membership queries; _i.e._, whether an item is a
member of a set.
A Bloom filter has two parameters: _m_, a maximum size (typically a reasonably large
multiple of the cardinality of the set to represent) and _k_, the number of hashing
functions on elements of the set. (The actual hashing functions are important, too,
but this is not a parameter for this implementation). A Bloom filter is backed by
a BitSet; a key is represented in the filter by setting the bits at each value of the
hashing functions (modulo _m_). Set membership is done by _testing_ whether the
bits at each value of the hashing functions (again, modulo _m_) are set. If so,
the item is in the set. If the item is actually in the set, a Bloom filter will
never fail (the true positive rate is 1.0); but it is susceptible to false
positives. The art is to choose _k_ and _m_ correctly.
In this implementation, the hashing functions used is murmurhash,
a non-cryptographic hashing function.
This implementation accepts keys for setting as testing as []byte. Thus, to
add a string item, "Love":
uint n = 1000
filter := bloom.New(20*n, 5) // load of 20, 5 keys
filter.Add([]byte("Love"))
Similarly, to test if "Love" is in bloom:
if filter.Test([]byte("Love"))
For numeric data, I recommend that you look into the binary/encoding library. But,
for example, to add a uint32 to the filter:
i := uint32(100)
n1 := make([]byte,4)
binary.BigEndian.PutUint32(n1,i)
f.Add(n1)
Finally, there is a method to estimate the false positive rate of a particular
Bloom filter for a set of size _n_:
if filter.EstimateFalsePositiveRate(1000) > 0.001
Given the particular hashing scheme, it's best to be empirical about this. Note
that estimating the FP rate will clear the Bloom filter.
*/
package bloom
import (
"bytes"
"encoding/binary"
"encoding/json"
"fmt"
"io"
"math"
"github.com/spaolacci/murmur3"
"github.com/willf/bitset"
)
// A BloomFilter is a representation of a set of _n_ items, where the main
// requirement is to make membership queries; _i.e._, whether an item is a
// member of a set.
type BloomFilter struct {
m uint
k uint
b *bitset.BitSet
}
func max(x, y uint) uint {
if x > y {
return x
}
return y
}
// New creates a new Bloom filter with _m_ bits and _k_ hashing functions
// We force _m_ and _k_ to be at least one to avoid panics.
func New(m uint, k uint) *BloomFilter {
return &BloomFilter{max(1, m), max(1, k), bitset.New(m)}
}
// From creates a new Bloom filter with len(_data_) * 64 bits and _k_ hashing
// functions. The data slice is not going to be reset.
func From(data []uint64, k uint) *BloomFilter {
m := uint(len(data) * 64)
return &BloomFilter{m, k, bitset.From(data)}
}
// baseHashes returns the four hash values of data that are used to create k
// hashes
func baseHashes(data []byte) [4]uint64 {
a1 := []byte{1} // to grab another bit of data
hasher := murmur3.New128()
hasher.Write(data) // #nosec
v1, v2 := hasher.Sum128()
hasher.Write(a1) // #nosec
v3, v4 := hasher.Sum128()
return [4]uint64{
v1, v2, v3, v4,
}
}
// location returns the ith hashed location using the four base hash values
func location(h [4]uint64, i uint) uint64 {
ii := uint64(i)
return h[ii%2] + ii*h[2+(((ii+(ii%2))%4)/2)]
}
// location returns the ith hashed location using the four base hash values
func (f *BloomFilter) location(h [4]uint64, i uint) uint {
return uint(location(h, i) % uint64(f.m))
}
// EstimateParameters estimates requirements for m and k.
// Based on https://bitbucket.org/ww/bloom/src/829aa19d01d9/bloom.go
// used with permission.
func EstimateParameters(n uint, p float64) (m uint, k uint) {
m = uint(math.Ceil(-1 * float64(n) * math.Log(p) / math.Pow(math.Log(2), 2)))
k = uint(math.Ceil(math.Log(2) * float64(m) / float64(n)))
return
}
// NewWithEstimates creates a new Bloom filter for about n items with fp
// false positive rate
func NewWithEstimates(n uint, fp float64) *BloomFilter {
m, k := EstimateParameters(n, fp)
return New(m, k)
}
// Cap returns the capacity, _m_, of a Bloom filter
func (f *BloomFilter) Cap() uint {
return f.m
}
// K returns the number of hash functions used in the BloomFilter
func (f *BloomFilter) K() uint {
return f.k
}
// Add data to the Bloom Filter. Returns the filter (allows chaining)
func (f *BloomFilter) Add(data []byte) *BloomFilter {
h := baseHashes(data)
for i := uint(0); i < f.k; i++ {
f.b.Set(f.location(h, i))
}
return f
}
// Merge the data from two Bloom Filters.
func (f *BloomFilter) Merge(g *BloomFilter) error {
// Make sure the m's and k's are the same, otherwise merging has no real use.
if f.m != g.m {
return fmt.Errorf("m's don't match: %d != %d", f.m, g.m)
}
if f.k != g.k {
return fmt.Errorf("k's don't match: %d != %d", f.m, g.m)
}
f.b.InPlaceUnion(g.b)
return nil
}
// Copy creates a copy of a Bloom filter.
func (f *BloomFilter) Copy() *BloomFilter {
fc := New(f.m, f.k)
fc.Merge(f) // #nosec
return fc
}
// AddString to the Bloom Filter. Returns the filter (allows chaining)
func (f *BloomFilter) AddString(data string) *BloomFilter {
return f.Add([]byte(data))
}
// Test returns true if the data is in the BloomFilter, false otherwise.
// If true, the result might be a false positive. If false, the data
// is definitely not in the set.
func (f *BloomFilter) Test(data []byte) bool {
h := baseHashes(data)
for i := uint(0); i < f.k; i++ {
if !f.b.Test(f.location(h, i)) {
return false
}
}
return true
}
// TestString returns true if the string is in the BloomFilter, false otherwise.
// If true, the result might be a false positive. If false, the data
// is definitely not in the set.
func (f *BloomFilter) TestString(data string) bool {
return f.Test([]byte(data))
}
// TestLocations returns true if all locations are set in the BloomFilter, false
// otherwise.
func (f *BloomFilter) TestLocations(locs []uint64) bool {
for i := 0; i < len(locs); i++ {
if !f.b.Test(uint(locs[i] % uint64(f.m))) {
return false
}
}
return true
}
// TestAndAdd is the equivalent to calling Test(data) then Add(data).
// Returns the result of Test.
func (f *BloomFilter) TestAndAdd(data []byte) bool {
present := true
h := baseHashes(data)
for i := uint(0); i < f.k; i++ {
l := f.location(h, i)
if !f.b.Test(l) {
present = false
}
f.b.Set(l)
}
return present
}
// TestAndAddString is the equivalent to calling Test(string) then Add(string).
// Returns the result of Test.
func (f *BloomFilter) TestAndAddString(data string) bool {
return f.TestAndAdd([]byte(data))
}
// ClearAll clears all the data in a Bloom filter, removing all keys
func (f *BloomFilter) ClearAll() *BloomFilter {
f.b.ClearAll()
return f
}
// EstimateFalsePositiveRate returns, for a BloomFilter with a estimate of m bits
// and k hash functions, what the false positive rate will be
// while storing n entries; runs 100,000 tests. This is an empirical
// test using integers as keys. As a side-effect, it clears the BloomFilter.
func (f *BloomFilter) EstimateFalsePositiveRate(n uint) (fpRate float64) {
rounds := uint32(100000)
f.ClearAll()
n1 := make([]byte, 4)
for i := uint32(0); i < uint32(n); i++ {
binary.BigEndian.PutUint32(n1, i)
f.Add(n1)
}
fp := 0
// test for number of rounds
for i := uint32(0); i < rounds; i++ {
binary.BigEndian.PutUint32(n1, i+uint32(n)+1)
if f.Test(n1) {
//fmt.Printf("%v failed.\n", i+uint32(n)+1)
fp++
}
}
fpRate = float64(fp) / (float64(rounds))
f.ClearAll()
return
}
// bloomFilterJSON is an unexported type for marshaling/unmarshaling BloomFilter struct.
type bloomFilterJSON struct {
M uint `json:"m"`
K uint `json:"k"`
B *bitset.BitSet `json:"b"`
}
// MarshalJSON implements json.Marshaler interface.
func (f *BloomFilter) MarshalJSON() ([]byte, error) {
return json.Marshal(bloomFilterJSON{f.m, f.k, f.b})
}
// UnmarshalJSON implements json.Unmarshaler interface.
func (f *BloomFilter) UnmarshalJSON(data []byte) error {
var j bloomFilterJSON
err := json.Unmarshal(data, &j)
if err != nil {
return err
}
f.m = j.M
f.k = j.K
f.b = j.B
return nil
}
// WriteTo writes a binary representation of the BloomFilter to an i/o stream.
// It returns the number of bytes written.
func (f *BloomFilter) WriteTo(stream io.Writer) (int64, error) {
err := binary.Write(stream, binary.BigEndian, uint64(f.m))
if err != nil {
return 0, err
}
err = binary.Write(stream, binary.BigEndian, uint64(f.k))
if err != nil {
return 0, err
}
numBytes, err := f.b.WriteTo(stream)
return numBytes + int64(2*binary.Size(uint64(0))), err
}
// ReadFrom reads a binary representation of the BloomFilter (such as might
// have been written by WriteTo()) from an i/o stream. It returns the number
// of bytes read.
func (f *BloomFilter) ReadFrom(stream io.Reader) (int64, error) {
var m, k uint64
err := binary.Read(stream, binary.BigEndian, &m)
if err != nil {
return 0, err
}
err = binary.Read(stream, binary.BigEndian, &k)
if err != nil {
return 0, err
}
b := &bitset.BitSet{}
numBytes, err := b.ReadFrom(stream)
if err != nil {
return 0, err
}
f.m = uint(m)
f.k = uint(k)
f.b = b
return numBytes + int64(2*binary.Size(uint64(0))), nil
}
// GobEncode implements gob.GobEncoder interface.
func (f *BloomFilter) GobEncode() ([]byte, error) {
var buf bytes.Buffer
_, err := f.WriteTo(&buf)
if err != nil {
return nil, err
}
return buf.Bytes(), nil
}
// GobDecode implements gob.GobDecoder interface.
func (f *BloomFilter) GobDecode(data []byte) error {
buf := bytes.NewBuffer(data)
_, err := f.ReadFrom(buf)
return err
}
// Equal tests for the equality of two Bloom filters
func (f *BloomFilter) Equal(g *BloomFilter) bool {
return f.m == g.m && f.k == g.k && f.b.Equal(g.b)
}
// Locations returns a list of hash locations representing a data item.
func Locations(data []byte, k uint) []uint64 {
locs := make([]uint64, k)
// calculate locations
h := baseHashes(data)
for i := uint(0); i < k; i++ {
locs[i] = location(h, i)
}
return locs
}