/*
	Timelinize
	Copyright (c) 2013 Matthew Holt

	This program is free software: you can redistribute it and/or modify
	it under the terms of the GNU Affero General Public License as published
	by the Free Software Foundation, either version 3 of the License, or
	(at your option) any later version.

	This program is distributed in the hope that it will be useful,
	but WITHOUT ANY WARRANTY; without even the implied warranty of
	MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
	GNU Affero General Public License for more details.

	You should have received a copy of the GNU Affero General Public License
	along with this program.  If not, see <https://www.gnu.org/licenses/>.
*/

// Package genericcsv implements a data source that imports simple CSV files.
// Files must be named SHOULD_IMPORT_GENERIC.csv to be recognized.
//
// If the first row's first cell cannot be parsed as a timestamp it is treated
// as a header row and columns are mapped by name (case-insensitive):
//
//	timestamp / time / date         – item timestamp (required)
//	description / desc              – item text content (required)
//	type                            – item classification (message, email, note,
//	                                  social, location, media, event, document,
//	                                  bookmark; defaults to note)
//	sender                          – entity credited as the item's owner/sender
//	receiver / recipient            – entity the item was sent to
//	latitude / lat                  – decimal latitude
//	longitude / lon / lng           – decimal longitude
//	tags                            – comma-separated tag strings
//
// Without a header row, columns are positional: timestamp, description,
// latitude, longitude.
package genericcsv

import (
	"context"
	"encoding/csv"
	"errors"
	"fmt"
	"io"
	"strconv"
	"strings"
	"time"

	"github.com/timelinize/timelinize/timeline"
	"go.uber.org/zap"
)

func init() {
	err := timeline.RegisterDataSource(timeline.DataSource{
		Name:            "generic_csv",
		Title:           "Generic CSV",
		Description:     "A CSV file with timestamp, description, and optional type, sender, receiver, latitude, longitude, and tags columns. File must be named SHOULD_IMPORT_GENERIC.csv.",
		NewFileImporter: func() timeline.FileImporter { return new(Importer) },
	})
	if err != nil {
		timeline.Log.Fatal("registering data source", zap.Error(err))
	}
}

// Importer imports data from a generic CSV file.
type Importer struct{}

const targetFilename = "SHOULD_IMPORT_GENERIC.csv"

// Recognize returns whether the input is a recognized generic CSV file.
func (Importer) Recognize(_ context.Context, dirEntry timeline.DirEntry, _ timeline.RecognizeParams) (timeline.Recognition, error) {
	if strings.EqualFold(dirEntry.Name(), targetFilename) {
		return timeline.Recognition{Confidence: 1}, nil
	}
	return timeline.Recognition{}, nil
}

// noCol is the sentinel value for a column that is absent from the file.
const noCol = -1

// columnMap holds the index of each known column, or noCol if absent.
type columnMap struct {
	timestamp   int
	description int
	itemType    int
	sender      int
	receiver    int
	latitude    int
	longitude   int
	tags        int
}

// buildColumnMap maps header names to column indices.
func buildColumnMap(headers []string) columnMap {
	m := columnMap{
		timestamp: noCol, description: noCol, itemType: noCol,
		sender: noCol, receiver: noCol, latitude: noCol, longitude: noCol, tags: noCol,
	}
	for i, h := range headers {
		switch strings.ToLower(strings.TrimSpace(h)) {
		case "timestamp", "time", "date":
			m.timestamp = i
		case "description", "desc":
			m.description = i
		case "type":
			m.itemType = i
		case "sender":
			m.sender = i
		case "receiver", "recipient":
			m.receiver = i
		case "latitude", "lat":
			m.latitude = i
		case "longitude", "lon", "lng":
			m.longitude = i
		case "tags":
			m.tags = i
		}
	}
	return m
}

// positionalColumnMap returns a column map for files without a header row,
// preserving the original column ordering.
func positionalColumnMap() columnMap {
	return columnMap{
		timestamp: 0, description: 1, latitude: 2, longitude: 3,
		itemType: noCol, sender: noCol, receiver: noCol, tags: noCol,
	}
}

// col safely returns rec[idx] trimmed, or "" if idx is noCol or out of bounds.
func col(rec []string, idx int) string {
	if idx == noCol || idx >= len(rec) {
		return ""
	}
	return strings.TrimSpace(rec[idx])
}

// FileImport imports items from the CSV file, one item per row.
func (imp *Importer) FileImport(ctx context.Context, dirEntry timeline.DirEntry, params timeline.ImportParams) error {
	f, err := dirEntry.FS.Open(dirEntry.Filename)
	if err != nil {
		return fmt.Errorf("opening file: %w", err)
	}
	defer f.Close()

	r := csv.NewReader(f)
	r.FieldsPerRecord = -1

	// Read the first row to decide whether it is a header or a data row.
	firstRow, err := r.Read()
	if errors.Is(err, io.EOF) {
		return nil
	}
	if err != nil {
		return fmt.Errorf("reading first row: %w", err)
	}

	var cols columnMap
	firstRowIsData := false

	if len(firstRow) > 0 {
		if _, tsErr := parseTimestamp(strings.TrimSpace(firstRow[0])); tsErr != nil {
			// First cell is not a timestamp — treat the row as a header.
			cols = buildColumnMap(firstRow)
		} else {
			// First cell is a valid timestamp — no header row.
			cols = positionalColumnMap()
			firstRowIsData = true
		}
	} else {
		cols = positionalColumnMap()
	}

	if cols.timestamp == noCol {
		return fmt.Errorf("no timestamp column found in header")
	}
	if cols.description == noCol {
		return fmt.Errorf("no description column found in header")
	}

	lineNum := 1

	// If the first row was data, process it before entering the main loop.
	if firstRowIsData {
		if g := buildGraph(firstRow, cols, lineNum, params.Log); g != nil {
			params.Pipeline <- g
		}
	}

	for {
		if err := ctx.Err(); err != nil {
			return err
		}

		lineNum++
		rec, err := r.Read()
		if errors.Is(err, io.EOF) {
			break
		}
		if err != nil {
			return fmt.Errorf("reading CSV at line %d: %w", lineNum, err)
		}

		if g := buildGraph(rec, cols, lineNum, params.Log); g != nil {
			params.Pipeline <- g
		}
	}

	return nil
}

// buildGraph converts a CSV row into a timeline Graph, or returns nil if the
// row should be skipped (e.g. unparseable timestamp).
func buildGraph(rec []string, cols columnMap, lineNum int, log *zap.Logger) *timeline.Graph {
	tsStr := col(rec, cols.timestamp)
	ts, err := parseTimestamp(tsStr)
	if err != nil {
		log.Warn("skipping row with unparseable timestamp",
			zap.Int("line", lineNum),
			zap.String("value", tsStr),
			zap.Error(err),
		)
		return nil
	}

	item := &timeline.Item{
		Classification: classificationFromString(col(rec, cols.itemType)),
		Timestamp:      ts,
		Content: timeline.ItemData{
			Data:      timeline.StringData(col(rec, cols.description)),
			MediaType: "text/plain",
		},
	}

	// Sender → Item.Owner
	if senderVal := col(rec, cols.sender); senderVal != "" {
		item.Owner = entityFromName(senderVal)
	}

	// Latitude + Longitude
	latStr := col(rec, cols.latitude)
	lonStr := col(rec, cols.longitude)
	if latStr != "" && lonStr != "" {
		lat, latErr := strconv.ParseFloat(latStr, 64)
		lon, lonErr := strconv.ParseFloat(lonStr, 64)
		if latErr == nil && lonErr == nil {
			item.Location = timeline.Location{
				Latitude:  &lat,
				Longitude: &lon,
			}
		} else if latErr != nil {
			log.Warn("ignoring unparseable latitude",
				zap.Int("line", lineNum),
				zap.String("value", latStr),
				zap.Error(latErr),
			)
		} else {
			log.Warn("ignoring unparseable longitude",
				zap.Int("line", lineNum),
				zap.String("value", lonStr),
				zap.Error(lonErr),
			)
		}
	}

	// Tags → "Tags" metadata key (comma-separated string as-is from the column)
	if tagsVal := col(rec, cols.tags); tagsVal != "" {
		item.Metadata = timeline.Metadata{"Tags": tagsVal}
	}

	g := &timeline.Graph{Item: item}

	// Receiver → RelSent relationship
	if receiverVal := col(rec, cols.receiver); receiverVal != "" {
		receiver := entityFromName(receiverVal)
		g.ToEntity(timeline.RelSent, &receiver)
	}

	return g
}

// classificationFromString maps a type string to the corresponding
// Classification. Defaults to ClassNote for unknown or empty values.
func classificationFromString(s string) timeline.Classification {
	switch strings.ToLower(s) {
	case "message":
		return timeline.ClassMessage
	case "email":
		return timeline.ClassEmail
	case "social":
		return timeline.ClassSocial
	case "location":
		return timeline.ClassLocation
	case "media":
		return timeline.ClassMedia
	case "event":
		return timeline.ClassEvent
	case "document":
		return timeline.ClassDocument
	case "bookmark":
		return timeline.ClassBookmark
	default:
		return timeline.ClassNote
	}
}

// entityFromName creates an Entity identified by name, suitable for use as a
// sender or receiver in a generic CSV import.
func entityFromName(name string) timeline.Entity {
	return timeline.Entity{
		Name: name,
		Attributes: []timeline.Attribute{
			{
				Name:     "generic_csv_name",
				Value:    name,
				Identity: true,
			},
		},
	}
}

// timestampFormats lists the timestamp formats tried in order of specificity.
var timestampFormats = []string{
	time.RFC3339Nano,
	time.RFC3339,
	"2006-01-02T15:04:05",
	"2006-01-02 15:04:05",
	"2006-01-02T15:04",
	"2006-01-02 15:04",
	"2006-01-02",
	"01/02/2006 15:04:05",
	"01/02/2006",
}

func parseTimestamp(s string) (time.Time, error) {
	for _, format := range timestampFormats {
		if t, err := time.Parse(format, s); err == nil {
			return t, nil
		}
	}
	return time.Time{}, fmt.Errorf("unrecognized timestamp format: %q", s)
}