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junk.go
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junk.go
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package main
/*
note: these testdata paths are not in the repo, you should gather some of your
own ham/spam emails.
./mox junk train testdata/train/ham testdata/train/spam
./mox junk train -sent-dir testdata/sent testdata/train/ham testdata/train/spam
./mox junk check 'testdata/check/ham/mail1'
./mox junk test testdata/check/ham testdata/check/spam
./mox junk analyze testdata/train/ham testdata/train/spam
./mox junk analyze -top-words 10 -train-ratio 0.5 -spam-threshold 0.85 -max-power 0.01 -sent-dir testdata/sent testdata/train/ham testdata/train/spam
./mox junk play -top-words 10 -train-ratio 0.5 -spam-threshold 0.85 -max-power 0.01 -sent-dir testdata/sent testdata/train/ham testdata/train/spam
*/
import (
"context"
"flag"
"fmt"
"log"
mathrand "math/rand"
"os"
"path/filepath"
"sort"
"time"
"github.com/mjl-/mox/junk"
"github.com/mjl-/mox/message"
"github.com/mjl-/mox/mlog"
"github.com/mjl-/mox/mox-"
)
type junkArgs struct {
params junk.Params
spamThreshold float64
trainRatio float64
seed bool
sentDir string
databasePath, bloomfilterPath string
debug bool
}
func (a junkArgs) SetLogLevel() {
mox.Conf.Log[""] = mlog.LevelInfo
if a.debug {
mox.Conf.Log[""] = mlog.LevelDebug
}
mlog.SetConfig(mox.Conf.Log)
}
func junkFlags(fs *flag.FlagSet) (a junkArgs) {
fs.BoolVar(&a.params.Onegrams, "one-grams", false, "use 1-grams, i.e. single words, for scoring")
fs.BoolVar(&a.params.Twograms, "two-grams", true, "use 2-grams, i.e. word pairs, for scoring")
fs.BoolVar(&a.params.Threegrams, "three-grams", false, "use 3-grams, i.e. word triplets, for scoring")
fs.Float64Var(&a.params.MaxPower, "max-power", 0.05, "maximum word power, e.g. min 0.05/max 0.95")
fs.Float64Var(&a.params.IgnoreWords, "ignore-words", 0.1, "ignore words with ham/spaminess within this distance from 0.5")
fs.IntVar(&a.params.TopWords, "top-words", 10, "number of top spam and number of top ham words from email to use")
fs.IntVar(&a.params.RareWords, "rare-words", 1, "words are rare if encountered this number during training, and skipped for scoring")
fs.BoolVar(&a.debug, "debug", false, "print debug logging when calculating spam probability")
fs.Float64Var(&a.spamThreshold, "spam-threshold", 0.95, "probability where message is seen as spam")
fs.Float64Var(&a.trainRatio, "train-ratio", 0.5, "part of data to use for training versus analyzing (for analyze only)")
fs.StringVar(&a.sentDir, "sent-dir", "", "directory with sent mails, for training")
fs.BoolVar(&a.seed, "seed", false, "seed prng before analysis")
fs.StringVar(&a.databasePath, "dbpath", "filter.db", "database file for ham/spam words")
fs.StringVar(&a.bloomfilterPath, "bloompath", "filter.bloom", "bloom filter for ignoring unique strings")
return
}
func listDir(dir string) (l []string) {
files, err := os.ReadDir(dir)
xcheckf(err, "listing directory %q", dir)
for _, f := range files {
l = append(l, f.Name())
}
return l
}
func must(f *junk.Filter, err error) *junk.Filter {
xcheckf(err, "filter")
return f
}
func cmdJunkTrain(c *cmd) {
c.unlisted = true
c.params = "hamdir spamdir"
c.help = "Train a junk filter with messages from hamdir and spamdir."
a := junkFlags(c.flag)
args := c.Parse()
if len(args) != 2 {
c.Usage()
}
a.SetLogLevel()
f := must(junk.NewFilter(context.Background(), c.log, a.params, a.databasePath, a.bloomfilterPath))
defer func() {
if err := f.Close(); err != nil {
log.Printf("closing junk filter: %v", err)
}
}()
hamFiles := listDir(args[0])
spamFiles := listDir(args[1])
var sentFiles []string
if a.sentDir != "" {
sentFiles = listDir(a.sentDir)
}
err := f.TrainDirs(args[0], a.sentDir, args[1], hamFiles, sentFiles, spamFiles)
xcheckf(err, "train")
}
func cmdJunkCheck(c *cmd) {
c.unlisted = true
c.params = "mailfile"
c.help = "Check an email message against a junk filter, printing the probability of spam on a scale from 0 to 1."
a := junkFlags(c.flag)
args := c.Parse()
if len(args) != 1 {
c.Usage()
}
a.SetLogLevel()
f := must(junk.OpenFilter(context.Background(), c.log, a.params, a.databasePath, a.bloomfilterPath, false))
defer func() {
if err := f.Close(); err != nil {
log.Printf("closing junk filter: %v", err)
}
}()
prob, _, _, _, err := f.ClassifyMessagePath(context.Background(), args[0])
xcheckf(err, "testing mail")
fmt.Printf("%.6f\n", prob)
}
func cmdJunkTest(c *cmd) {
c.unlisted = true
c.params = "hamdir spamdir"
c.help = "Check a directory with hams and one with spams against the junk filter, and report the success ratio."
a := junkFlags(c.flag)
args := c.Parse()
if len(args) != 2 {
c.Usage()
}
a.SetLogLevel()
f := must(junk.OpenFilter(context.Background(), c.log, a.params, a.databasePath, a.bloomfilterPath, false))
defer func() {
if err := f.Close(); err != nil {
log.Printf("closing junk filter: %v", err)
}
}()
testDir := func(dir string, ham bool) (int, int) {
ok, bad := 0, 0
files, err := os.ReadDir(dir)
xcheckf(err, "readdir %q", dir)
for _, fi := range files {
path := filepath.Join(dir, fi.Name())
prob, _, _, _, err := f.ClassifyMessagePath(context.Background(), path)
if err != nil {
log.Printf("classify message %q: %s", path, err)
continue
}
if ham && prob < a.spamThreshold || !ham && prob > a.spamThreshold {
ok++
} else {
bad++
}
if ham && prob > a.spamThreshold {
fmt.Printf("ham %q: %.4f\n", path, prob)
}
if !ham && prob < a.spamThreshold {
fmt.Printf("spam %q: %.4f\n", path, prob)
}
}
return ok, bad
}
nhamok, nhambad := testDir(args[0], true)
nspamok, nspambad := testDir(args[1], false)
fmt.Printf("total ham, ok %d, bad %d\n", nhamok, nhambad)
fmt.Printf("total spam, ok %d, bad %d\n", nspamok, nspambad)
fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
}
func cmdJunkAnalyze(c *cmd) {
c.unlisted = true
c.params = "hamdir spamdir"
c.help = `Analyze a directory with ham messages and one with spam messages.
A part of the messages is used for training, and remaining for testing. The
messages are shuffled, with optional random seed.`
a := junkFlags(c.flag)
args := c.Parse()
if len(args) != 2 {
c.Usage()
}
a.SetLogLevel()
f := must(junk.NewFilter(context.Background(), c.log, a.params, a.databasePath, a.bloomfilterPath))
defer func() {
if err := f.Close(); err != nil {
log.Printf("closing junk filter: %v", err)
}
}()
hamDir := args[0]
spamDir := args[1]
hamFiles := listDir(hamDir)
spamFiles := listDir(spamDir)
var rand *mathrand.Rand
if a.seed {
rand = mathrand.New(mathrand.NewSource(time.Now().UnixMilli()))
} else {
rand = mathrand.New(mathrand.NewSource(0))
}
shuffle := func(l []string) {
count := len(l)
for i := range l {
n := rand.Intn(count)
l[i], l[n] = l[n], l[i]
}
}
shuffle(hamFiles)
shuffle(spamFiles)
ntrainham := int(a.trainRatio * float64(len(hamFiles)))
ntrainspam := int(a.trainRatio * float64(len(spamFiles)))
trainHam := hamFiles[:ntrainham]
trainSpam := spamFiles[:ntrainspam]
testHam := hamFiles[ntrainham:]
testSpam := spamFiles[ntrainspam:]
var trainSent []string
if a.sentDir != "" {
trainSent = listDir(a.sentDir)
}
err := f.TrainDirs(hamDir, a.sentDir, spamDir, trainHam, trainSent, trainSpam)
xcheckf(err, "train")
testDir := func(dir string, files []string, ham bool) (ok, bad, malformed int) {
for _, name := range files {
path := filepath.Join(dir, name)
prob, _, _, _, err := f.ClassifyMessagePath(context.Background(), path)
if err != nil {
// log.Infof("%s: %s", path, err)
malformed++
continue
}
if ham && prob < a.spamThreshold || !ham && prob > a.spamThreshold {
ok++
} else {
bad++
}
if ham && prob > a.spamThreshold {
fmt.Printf("ham %q: %.4f\n", path, prob)
}
if !ham && prob < a.spamThreshold {
fmt.Printf("spam %q: %.4f\n", path, prob)
}
}
return
}
nhamok, nhambad, nmalformedham := testDir(args[0], testHam, true)
nspamok, nspambad, nmalformedspam := testDir(args[1], testSpam, false)
fmt.Printf("training done, nham %d, nsent %d, nspam %d\n", ntrainham, len(trainSent), ntrainspam)
fmt.Printf("total ham, ok %d, bad %d, malformed %d\n", nhamok, nhambad, nmalformedham)
fmt.Printf("total spam, ok %d, bad %d, malformed %d\n", nspamok, nspambad, nmalformedspam)
fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
}
func cmdJunkPlay(c *cmd) {
c.unlisted = true
c.params = "hamdir spamdir"
c.help = "Play messages from ham and spam directory according to their time of arrival and report on junk filter performance."
a := junkFlags(c.flag)
args := c.Parse()
if len(args) != 2 {
c.Usage()
}
a.SetLogLevel()
f := must(junk.NewFilter(context.Background(), c.log, a.params, a.databasePath, a.bloomfilterPath))
defer func() {
if err := f.Close(); err != nil {
log.Printf("closing junk filter: %v", err)
}
}()
// We'll go through all emails to find their dates.
type msg struct {
dir, filename string
ham, sent bool
t time.Time
}
var msgs []msg
var nbad, nnodate, nham, nspam, nsent int
scanDir := func(dir string, ham, sent bool) {
for _, name := range listDir(dir) {
path := filepath.Join(dir, name)
mf, err := os.Open(path)
xcheckf(err, "open %q", path)
fi, err := mf.Stat()
xcheckf(err, "stat %q", path)
p, err := message.EnsurePart(c.log.Logger, false, mf, fi.Size())
if err != nil {
nbad++
if err := mf.Close(); err != nil {
log.Printf("closing message file: %v", err)
}
continue
}
if p.Envelope.Date.IsZero() {
nnodate++
if err := mf.Close(); err != nil {
log.Printf("closing message file: %v", err)
}
continue
}
if err := mf.Close(); err != nil {
log.Printf("closing message file: %v", err)
}
msgs = append(msgs, msg{dir, name, ham, sent, p.Envelope.Date})
if sent {
nsent++
} else if ham {
nham++
} else {
nspam++
}
}
}
hamDir := args[0]
spamDir := args[1]
scanDir(hamDir, true, false)
scanDir(spamDir, false, false)
if a.sentDir != "" {
scanDir(a.sentDir, true, true)
}
// Sort the messages, earliest first.
sort.Slice(msgs, func(i, j int) bool {
return msgs[i].t.Before(msgs[j].t)
})
// Play all messages as if they are coming in. We predict their spaminess, check if
// we are right. And we train the system with the result.
var nhamok, nhambad, nspamok, nspambad int
play := func(msg msg) {
var words map[string]struct{}
path := filepath.Join(msg.dir, msg.filename)
if !msg.sent {
var prob float64
var err error
prob, words, _, _, err = f.ClassifyMessagePath(context.Background(), path)
if err != nil {
nbad++
return
}
if msg.ham {
if prob < a.spamThreshold {
nhamok++
} else {
nhambad++
}
} else {
if prob > a.spamThreshold {
nspamok++
} else {
nspambad++
}
}
} else {
mf, err := os.Open(path)
xcheckf(err, "open %q", path)
defer func() {
if err := mf.Close(); err != nil {
log.Printf("closing message file: %v", err)
}
}()
fi, err := mf.Stat()
xcheckf(err, "stat %q", path)
p, err := message.EnsurePart(c.log.Logger, false, mf, fi.Size())
if err != nil {
log.Printf("bad sent message %q: %s", path, err)
return
}
words, err = f.ParseMessage(p)
if err != nil {
log.Printf("bad sent message %q: %s", path, err)
return
}
}
if err := f.Train(context.Background(), msg.ham, words); err != nil {
log.Printf("train: %s", err)
}
}
for _, m := range msgs {
play(m)
}
err := f.Save()
xcheckf(err, "saving filter")
fmt.Printf("completed, nham %d, nsent %d, nspam %d, nbad %d, nwithoutdate %d\n", nham, nsent, nspam, nbad, nnodate)
fmt.Printf("total ham, ok %d, bad %d\n", nhamok, nhambad)
fmt.Printf("total spam, ok %d, bad %d\n", nspamok, nspambad)
fmt.Printf("specifity (true negatives, hams identified): %.6f\n", float64(nhamok)/(float64(nhamok+nhambad)))
fmt.Printf("sensitivity (true positives, spams identified): %.6f\n", float64(nspamok)/(float64(nspamok+nspambad)))
fmt.Printf("accuracy: %.6f\n", float64(nhamok+nspamok)/float64(nhamok+nhambad+nspamok+nspambad))
}