use std::{
    collections::{HashMap, HashSet},
    fmt,
    fs::{self, File, OpenOptions},
    io::{BufReader, Read},
    os::unix::fs::MetadataExt,
    path::Path,
};

use anyhow::Context;
use chrono::{DateTime, TimeZone, Utc};
use glob::glob;
use log::{info, warn};
use serde::{Deserialize, Serialize};

use crate::{
    collection::minknow::{parse_pore_activity_from_reader, parse_throughput_from_reader},
    helpers::{find_files, list_directories},
};

use super::minknow::{MinKnowSampleSheet, PoreStateEntry, ThroughputEntry};

/// A collection of `IdInput` records, with utility methods
/// for loading, saving, deduplication, and construction from TSV.
#[derive(Debug, Serialize, Deserialize, Clone)]
pub struct IdsInput {
    /// The list of ID entries.
    pub data: Vec<IdInput>,
}

/// A unique sample identifier from sequencing metadata.
///
/// Uniqueness is defined by the combination of all fields.
#[derive(Debug, Serialize, Deserialize, Clone, PartialEq, Eq, Hash)]
pub struct IdInput {
    /// Case or patient ID.
    pub case_id: String,
    /// Time point or sample type.
    pub sample_type: String,
    /// Barcode number (sequencing index).
    pub barcode: String,
    /// Flow cell identifier.
    pub flow_cell_id: String,
}

impl IdsInput {
    /// Load `IdsInput` from a JSON file.
    pub fn load_json<P: AsRef<Path>>(path: P) -> anyhow::Result<Self> {
        let file = File::open(&path)?;
        Ok(serde_json::from_reader(file)?)
    }

    /// Save `IdsInput` to a JSON file (pretty-printed).
    pub fn save_json<P: AsRef<Path>>(&self, path: P) -> anyhow::Result<()> {
        let file = File::create(&path)?;
        serde_json::to_writer_pretty(file, self)?;
        Ok(())
    }

    /// Remove duplicate `IdInput` entries, retaining the first occurrence.
    pub fn dedup(&mut self) {
        let mut seen = HashSet::new();
        self.data.retain(|item| seen.insert(item.clone()));
    }

    /// Add a new `IdInput` and deduplicate.
    pub fn add_input(&mut self, entry: IdInput) {
        self.data.push(entry);
        self.dedup();
    }
}

/// Container for a deduplicated and enriched collection of flowcells (`FlowCel`).
///
/// `FlowCells` represents the aggregated result of scanning multiple sources:
/// - A cached archive of flowcells (`archive_store_path`)
/// - A live scan of the local run directory (`local_run_dir`)
///
/// Each [`FlowCel`] contains all necessary metadata for downstream processing,
/// including parsed MinKNOW sample sheet data, `.pod5` file statistics, experiment layout,
/// and optional sample/case annotations from an [`IdsInput`] file.
///
/// The [`FlowCells::load`] method performs the following:
/// - Loads existing flowcells from the archive if available
/// - Scans local directories for new or updated flowcells
/// - Deduplicates flowcells using the `flowcell_id`
/// - Retains the most recently modified version of each flowcell
/// - Enriches each flowcell with case-level annotations
///
/// # Fields
/// - `flow_cells`: A deduplicated list of fully parsed [`FlowCel`] instances.
///
/// # Example
/// ```
/// let flow_cells = FlowCells::load(
///     "/mnt/data/runs",
///     "inputs.json",
///     "flowcell_cache.json"
/// )?;
/// println!("Loaded {} unique flowcells", flow_cells.flow_cells.len());
/// ```
///
/// # Deduplication
/// Flowcells are uniquely identified by their `flowcell_id`, a combination of
/// `{experiment_id}/{sample_id}`. If both archived and local versions exist,
/// the one with the latest `.pod5` modification time is retained.
///
/// # Related Types
/// - [`FlowCel`]: Describes a flowcell, its metadata, and files
/// - [`FlowCellExperiment`]: Muxed vs. demuxed layout classification
/// - [`FlowCellLocation`]: Indicates source (local or archive)
/// - [`MinKnowSampleSheet`]: Parsed sample sheet data
/// - [`IdInput`]: Case-level annotation applied to flowcells
#[derive(Debug, Serialize, Deserialize, Clone, Default)]
pub struct FlowCells {
    /// A collection of parsed flowcell metadata records.
    pub flow_cells: Vec<FlowCell>,
}

impl FlowCells {
    /// Load and merge flowcells from archive and local directories, then annotate with `IdsInput`.
    ///
    /// # Arguments
    /// * `local_run_dir` - Root directory containing local flowcell run folders.
    /// * `inputs_path` - Path to a JSON file with [`IdInput`] annotations.
    /// * `archive_store_path` - Path to a cached JSON file of archived flowcells.
    ///
    /// # Returns
    /// A deduplicated and annotated [`FlowCells`] collection.
    ///
    /// # Errors
    /// Returns an error if any input file cannot be read or parsed, or if local scanning fails.
    pub fn load(
        local_run_dir: &str,
        inputs_path: &str,
        archive_store_path: &str,
    ) -> anyhow::Result<Self> {
        let mut instance = Self::default();

        instance.load_from_archive(archive_store_path)?;
        instance.load_from_local(local_run_dir)?;
        instance.annotate_with_inputs(inputs_path)?;
        instance.save_to_archive(archive_store_path)?;

        Ok(instance)
    }

    /// Load flowcells from a cached archive and merge into `self.flow_cells`.
    ///
    /// Retains only the most recently modified entry for each `flowcell_id`.
    ///
    /// # Arguments
    /// * `archive_path` - Path to archive JSON file.
    ///
    /// # Errors
    /// Returns an error if the file cannot be read or parsed.
    pub fn load_from_archive(&mut self, archive_path: &str) -> anyhow::Result<()> {
        if !Path::new(archive_path).exists() {
            return Ok(());
        }

        let file = File::open(archive_path)
            .with_context(|| format!("Failed to open archive file: {archive_path}"))?;
        let archived: Vec<FlowCell> = serde_json::from_reader(BufReader::new(file))
            .with_context(|| format!("Failed to parse FlowCells from: {archive_path}"))?;

        self.insert_flowcells(archived);
        Ok(())
    }

    pub fn save_to_archive(&mut self, archive_path: &str) -> anyhow::Result<()> {
        let file = OpenOptions::new()
            .write(true)
            .create(true)
            .truncate(true)
            .open(archive_path)
            .with_context(|| format!("Failed to open archive file for writing: {archive_path}"))?;

        serde_json::to_writer_pretty(file, &self.flow_cells)
            .with_context(|| format!("Failed to write FlowCells to: {archive_path}"))?;

        Ok(())
    }

    /// Scan local run directories for flowcells and merge into `self.flow_cells`.
    ///
    /// Uses `scan_local()` to parse local metadata and selects the most recently modified
    /// version if duplicates exist.
    ///
    /// # Arguments
    /// * `local_dir` - Root directory containing flowcell runs.
    ///
    /// # Errors
    /// Returns an error if scanning fails or if directory layout is invalid.
    pub fn load_from_local(&mut self, local_dir: &str) -> anyhow::Result<()> {
        let sample_sheets = find_files(&format!("{local_dir}/**/sample_sheet*"))?;

        for path in sample_sheets {
            let dir = path
                .parent()
                .ok_or_else(|| anyhow::anyhow!("Invalid sample_sheet path: {}", path.display()))?;
            let dir_str = dir.to_string_lossy();

            let (sheet, pore, throughput, files) = scan_local(&dir_str)
                .with_context(|| format!("Failed to scan local dir: {dir_str}"))?;

            let fc = FlowCell::new(
                sheet,
                pore,
                throughput,
                FlowCellLocation::Local(dir_str.to_string()),
                files,
            )
            .with_context(|| format!("Failed to create FlowCell from dir: {dir_str}"))?;

            self.insert_flowcells(vec![fc]);
        }

        Ok(())
    }

    /// Annotate flowcells with matching `IdInput` records from JSON.
    ///
    /// Assigns to `FlowCell.cases` all matching `IdInput`s by `flow_cell_id`.
    ///
    /// # Arguments
    /// * `inputs_path` - Path to JSON file containing a list of `IdInput` records.
    ///
    /// # Errors
    /// Returns an error if the file is unreadable or malformed.
    pub fn annotate_with_inputs(&mut self, inputs_path: &str) -> anyhow::Result<()> {
        if !Path::new(inputs_path).exists() {
            warn!("IdsInput file not found at {}", inputs_path);
            return Ok(());
        }

        let inputs = IdsInput::load_json(inputs_path)
            .with_context(|| format!("Failed to load IdsInput from: {inputs_path}"))?;

        self.cross_cases(&inputs)
            .with_context(|| format!("Failed to cross with IdsInput from: {inputs_path}"))?;

        Ok(())
    }

    pub fn cross_cases(&mut self, inputs: &IdsInput) -> anyhow::Result<()> {
        for fc in &mut self.flow_cells {
            fc.cases = inputs
                .data
                .iter()
                .filter(|id| id.flow_cell_id == fc.sample_sheet.flow_cell_id)
                .cloned()
                .collect();
        }

        Ok(())
    }

    /// Insert new flowcells into the current collection, deduplicating by `flowcell_id`.
    ///
    /// For duplicates, retains the flowcell with the newer `.modified` timestamp.
    ///
    /// # Arguments
    /// * `new_cells` - A vector of parsed `FlowCell` instances.
    pub fn insert_flowcells(&mut self, new_cells: Vec<FlowCell>) {
        let mut map: HashMap<String, FlowCell> = self
            .flow_cells
            .drain(..)
            .map(|fc| (fc.sample_sheet.flow_cell_id.clone(), fc))
            .collect();

        for fc in new_cells {
            map.entry(fc.sample_sheet.flow_cell_id.clone())
                .and_modify(|existing| {
                    if fc.modified > existing.modified {
                        *existing = fc.clone();
                    }
                })
                .or_insert(fc);
        }

        self.flow_cells = map.into_values().collect();
    }

    /// Updates a JSON archive of `FlowCel` objects by scanning `.tar` archives in a directory.
    ///
    /// This function is used to **discover new archived flowcells** by scanning all `.tar` files
    /// in a given directory, parsing their contents using [`scan_archive`] and [`FlowCel::new`],
    /// and then appending the results to an existing JSON file (if present).
    /// Flowcells are **deduplicated** by `flowcell_id`, and the updated result is saved back to disk.
    ///
    /// # Arguments
    /// - `archive_path`: Path to a directory containing `.tar` archives produced by MinKNOW.
    /// - `save_path`: Path to a JSON file where the deduplicated list of `FlowCel` objects will be saved.
    ///
    /// # Behavior
    /// - If `save_path` exists, the function loads existing flowcells from it.
    /// - Then it scans all `.tar` files in `archive_path`, one by one:
    ///     - Extracts `sample_sheet` and `.pod5` file metadata using [`scan_archive`]
    ///     - Builds a new [`FlowCel`] using [`FlowCel::new`] with location `FlowCellLocation::Archived(...)`
    ///     - Logs and skips entries that fail to parse
    /// - All new flowcells are added to the existing list and deduplicated.
    /// - The updated list is sorted and written back to `save_path`.
    ///
    /// # Deduplication
    /// - Flowcells are deduplicated using `.dedup_by_key(|fc| fc.flowcell_id.clone())`.
    /// - The last encountered entry is kept if duplicates exist.
    ///
    /// # Returns
    /// - `Ok(())` if scanning and update succeeds.
    /// - `Err` if the archive directory, `.tar` files, or save path cannot be processed.
    ///
    /// # Example
    /// ```
    /// update_archive_from_scan("archives/", "flowcell_cache.json")?;
    /// ```
    ///
    /// # See Also
    /// - [`scan_archive`]
    /// - [`FlowCell`]
    /// - [`FlowCellLocation::Archived`]
    pub fn update_archive_from_scan(archive_path: &str, save_path: &str) -> anyhow::Result<()> {
        // Load existing archive, if any
        let mut all: Vec<FlowCell> = if Path::new(save_path).exists() {
            let file = File::open(save_path)?;
            serde_json::from_reader(BufReader::new(file))?
        } else {
            Vec::new()
        };

        let n_before = all.len();
        let pattern = format!("{archive_path}/*.tar");

        // Scan all .tar archives
        let res: Vec<FlowCell> = glob(&pattern)?
            .filter_map(Result::ok)
            .filter_map(|path| {
                let archive_str = path.to_string_lossy();
                let (sample_sheet, pore_activity, throughput, files) =
                    match scan_archive(&archive_str) {
                        Ok(r) => r,
                        Err(e) => {
                            warn!("Failed to scan archive {}: {e}", archive_str);
                            return None;
                        }
                    };
                match FlowCell::new(
                    sample_sheet,
                    pore_activity,
                    throughput,
                    FlowCellLocation::Archived(archive_path.to_string()),
                    files,
                ) {
                    Ok(fc) => Some(fc),
                    Err(e) => {
                        warn!("Failed to create FlowCel from {}: {e}", archive_str);
                        None
                    }
                }
            })
            .collect();

        // Merge, deduplicate, and write updated archive
        all.extend(res);
        all.sort_by(|a, b| {
            a.sample_sheet
                .flow_cell_id
                .cmp(&b.sample_sheet.flow_cell_id)
        });
        all.dedup_by_key(|v| v.sample_sheet.flow_cell_id.clone());

        let n_final = all.len();
        info!(
            "{} new archive(s) discovered.",
            n_final.saturating_sub(n_before)
        );

        let json = serde_json::to_string_pretty(&all)
            .map_err(|e| anyhow::anyhow!("Can't convert into json.\n{e}"))?;

        fs::write(save_path, json)
            .map_err(|e| anyhow::anyhow!("Can't write file: {save_path}.\n{e}"))?;

        Ok(())
    }
}

/// Represents a fully described flowcell unit, including experimental metadata,
/// physical location (local or archived), sample sheet data, and associated pod5 files.
///
/// A `FlowCell` object serves as the central unit in the data model for sample aggregation
/// and downstream processing.
///
/// # Fields
/// - `sample_sheet`: The original MinKNOW sample sheet metadata (`MinKnowSampleSheet`).
/// - `experiment`: Experiment type inferred from `.pod5` files (see `FlowCellExperiment`).
/// - `location`: Whether the flowcell was loaded from a local directory or archive store.
/// - `modified`: Last modification timestamp among `.pod5` files.
/// - `pod5_size`: Total size (in bytes) of `.pod5` files.
/// - `n_pod5`: Number of `.pod5` files found.
/// - `cases`: List of sample/case-level annotations associated with this flowcell (from `IdsInput`).
#[derive(Debug, Serialize, Deserialize, Clone)]
pub struct FlowCell {
    pub sample_sheet: MinKnowSampleSheet,
    pub experiment: FlowCellExperiment,
    pub location: FlowCellLocation,
    pub modified: DateTime<Utc>,
    pub pod5_size: usize,
    pub n_pod5: usize,
    pub cases: Vec<IdInput>,
    pub pore_activity: Option<Vec<PoreStateEntry>>,
    pub throughput: Option<Vec<ThroughputEntry>>,
}

/// Describes the physical origin of a flowcell when loaded.
///
/// This is used to differentiate flowcells discovered during a local scan
/// versus those restored from an archived store.
#[derive(Debug, Serialize, Deserialize, Clone)]
pub enum FlowCellLocation {
    /// Flowcell discovered in a local filesystem path.
    Local(String),

    /// Flowcell restored from a `.tar` archive or a serialized cache.
    Archived(String),
}

impl fmt::Display for FlowCellLocation {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        write!(
            f,
            "{}",
            match self {
                FlowCellLocation::Local(_) => "local",
                FlowCellLocation::Archived(_) => "archived",
            }
        )
    }
}

impl FlowCell {
    /// Constructs a new `FlowCell` from a sample sheet and associated file list.
    ///
    /// This method aggregates information from a parsed `MinKnowSampleSheet` and the
    /// corresponding `.pod5` file metadata, and infers the experiment type from
    /// file paths using `FlowCellExperiment::from_pod5_paths`.
    ///
    /// # Arguments
    /// - `sample_sheet`: Parsed sample sheet metadata.
    /// - `location`: Origin of the flowcell (local or archived).
    /// - `files`: List of files associated with the flowcell, each with:
    ///   - `String`: file path
    ///   - `u64`: size in bytes
    ///   - `DateTime<Utc>`: modification time
    ///
    /// # Returns
    /// - `Ok(FlowCell)` if experiment type and file metadata are successfully resolved.
    /// - `Err` if the experiment type cannot be determined.
    ///
    /// # Errors
    /// - If `FlowCellExperiment::from_pod5_paths` fails (e.g., unknown layout).
    ///
    /// # Example
    /// ```
    /// let fc = FlowCell::new(sample_sheet, FlowCellLocation::Local(dir), files)?;
    /// println!("Flowcell ID: {}", fc.flowcell_id);
    /// ```
    pub fn new(
        sample_sheet: MinKnowSampleSheet,
        pore_activity: Option<Vec<PoreStateEntry>>,
        throughput: Option<Vec<ThroughputEntry>>,
        location: FlowCellLocation,
        files: Vec<(String, u64, DateTime<Utc>)>,
    ) -> anyhow::Result<Self> {
        let flowcell_id = sample_sheet.flow_cell_id.clone();

        // Filter .pod5 files
        let pod5s: Vec<_> = files
            .iter()
            .filter(|(path, _, _)| path.ends_with(".pod5"))
            .cloned()
            .collect();
        let n_pod5 = pod5s.len();

        // Infer experiment type from pod5 paths
        let experiment = FlowCellExperiment::from_pod5_paths(
            &files.iter().map(|(p, _, _)| p.to_string()).collect(),
        )
        .ok_or_else(|| anyhow::anyhow!("Can't find experiment type for {flowcell_id}"))?;

        // Aggregate pod5 size and latest modification time
        let (pod5_size, modified): (usize, DateTime<Utc>) = files
            .into_iter()
            .filter(|(path, _, _)| path.ends_with(".pod5"))
            .fold(
                (0, DateTime::<Utc>::MIN_UTC),
                |(acc_size, acc_time), (_, size, time)| {
                    (
                        acc_size + size as usize,
                        if acc_time < time { time } else { acc_time },
                    )
                },
            );

        Ok(Self {
            experiment,
            location,
            modified,
            sample_sheet,
            pod5_size,
            n_pod5,
            cases: Vec::new(),
            pore_activity,
            throughput,
        })
    }
}

/// Describes the type of experiment layout based on `.pod5` file structure.
///
/// Used to distinguish between whole-genome sequencing (WGS) `.pod5` files
/// organized in a single (muxed) directory or demultiplexed (`pod5_pass`) structure.
#[derive(Debug, Serialize, Deserialize, Clone)]
pub enum FlowCellExperiment {
    /// `.pod5` files are stored in a single unbarcoded directory, typically `/pod5/`.
    WGSPod5Mux(String),

    /// `.pod5` files are organized by barcode in subdirectories, typically `/pod5_pass/`.
    WGSPod5Demux(String),
}

impl fmt::Display for FlowCellExperiment {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        write!(
            f,
            "{}",
            match self {
                FlowCellExperiment::WGSPod5Mux(_) => "WGS Pod5 Muxed",
                FlowCellExperiment::WGSPod5Demux(_) => "WGS Pod5 Demuxed",
            }
        )
    }
}

impl FlowCellExperiment {
    /// Attempts to infer the experiment type from the immediate subdirectories of the given path.
    ///
    /// This is useful when scanning a flowcell directory directly and checking
    /// whether it contains a `pod5/` or `pod5_pass/` structure.
    ///
    /// # Arguments
    /// - `flowcell_path`: Path to the root of a flowcell directory.
    ///
    /// # Returns
    /// - `Some(FlowCellExperiment)` if a known subdirectory is found.
    /// - `None` if no match is detected.
    pub fn from_path(flowcell_path: &str) -> Option<Self> {
        for dir in list_directories(flowcell_path).ok().unwrap_or_default() {
            if dir == "pod5" {
                return Some(FlowCellExperiment::WGSPod5Mux(dir.to_string()));
            }
            if dir == "pod5_pass" {
                return Some(FlowCellExperiment::WGSPod5Demux(dir.to_string()));
            }
        }
        None
    }

    /// Attempts to infer the experiment type from a list of `.pod5` file paths.
    ///
    /// This is typically used when files have already been collected and their
    /// parent directories can be checked for naming conventions.
    ///
    /// # Arguments
    /// - `all_paths`: Vector of paths (as strings) to `.pod5` files or directories.
    ///
    /// # Returns
    /// - `Some(FlowCellExperiment)` if a known suffix is detected.
    /// - `None` if no matching pattern is found.
    pub fn from_pod5_paths(all_paths: &Vec<String>) -> Option<Self> {
        for path in all_paths {
            if path.ends_with("/pod5/") || path.ends_with("/pod5") {
                return Some(FlowCellExperiment::WGSPod5Mux(path.to_string()));
            }

            if path.ends_with("/pod5_pass/") || path.ends_with("/pod5_pass") {
                return Some(FlowCellExperiment::WGSPod5Demux(path.to_string()));
            }
        }
        None
    }

    /// Returns the underlying string (directory path) for the experiment.
    ///
    /// This is useful when you need access to the directory path used to classify the experiment.
    pub fn inner(&self) -> &str {
        match self {
            FlowCellExperiment::WGSPod5Mux(v) => v,
            FlowCellExperiment::WGSPod5Demux(v) => v,
        }
    }
}

/// Represents the result of scanning a MinKNOW experiment source.
///
/// This tuple includes:
/// - `MinKnowSampleSheet`: Parsed metadata describing the experiment/sample.
/// - `Vec<(String, u64, DateTime<Utc>)>`: A list of files with:
///   - `String`: file path
///   - `u64`: file size in bytes
///   - `DateTime<Utc>`: last modification time (UTC)
type ExperimentData = (
    MinKnowSampleSheet,
    Option<Vec<PoreStateEntry>>,
    Option<Vec<ThroughputEntry>>,
    Vec<(String, u64, DateTime<Utc>)>,
);

/// Scans a local directory for MinKNOW experiment files and metadata.
///
/// This function recursively walks a directory using globbing,
/// collects file paths, sizes, and modification timestamps,
/// and identifies a `sample_sheet` file to parse as `MinKnowSampleSheet`.
///
/// # Arguments
/// - `dir`: Root directory to scan (absolute or relative).
///
/// # Returns
/// - `Ok(ExperimentData)` containing the sample sheet and a list of file records.
/// - `Err` if the directory can't be accessed, no sample sheet is found, or parsing fails.
///
/// # Requirements
/// - A file path containing `"sample_sheet"` must be present and readable.
/// - The sample sheet must be formatted according to MinKNOW expectations
///   (1 header + 1 data row).
///
/// # Errors
/// - If reading files or metadata fails.
/// - If the sample sheet is missing or invalid.
///
/// # Example
/// ```
/// let (sheet, files) = scan_local("/data/run001")?;
/// println!("Kit used: {}", sheet.kit);
/// println!("Number of files found: {}", files.len());
/// ```
pub fn scan_local(dir: &str) -> anyhow::Result<ExperimentData> {
    let mut result = Vec::new();
    let mut sample_sheet: Option<String> = None;
    let mut pore_activity = None;
    let mut throughput = None;

    for entry in glob(&format!("{}/**/*", dir))? {
        let file = entry.context("Failed to read an entry from the tar archive")?;

        // Extract file properties safely
        let metadata = file.metadata().context(format!(
            "Failed to access file metadata: {}",
            file.display()
        ))?;
        let size = metadata.size();
        let modified = metadata.mtime();
        let modified_utc: DateTime<Utc> = Utc.timestamp_opt(modified as i64, 0).unwrap();

        let path = file.to_string_lossy().into_owned();

        if path.contains("pore_activity") {
            let mut reader =
                File::open(&file).with_context(|| format!("Failed to open: {}", file.display()))?;
            pore_activity = Some(parse_pore_activity_from_reader(&mut reader).with_context(
                || {
                    format!(
                        "Failed to parse pore activity date from: {}",
                        file.display()
                    )
                },
            )?);
        } else if path.contains("sample_sheet") {
            sample_sheet = Some(path.clone());
        } else if path.contains("throughput") {
            let mut reader =
                File::open(&file).with_context(|| format!("Failed to open: {}", file.display()))?;
            throughput = Some(parse_throughput_from_reader(&mut reader).with_context(|| {
                format!("Failed to parse throughput date from: {}", file.display())
            })?);
        }

        result.push((path, size, modified_utc));
    }

    let sample_sheet = sample_sheet.ok_or(anyhow::anyhow!("No sample sheet detected in: {dir}"))?;
    let sample_sheet = MinKnowSampleSheet::from_path(&sample_sheet)
        .context(anyhow::anyhow!("Can't parse sample sheet data"))?;

    Ok((sample_sheet, pore_activity, throughput, result))
}

/// Scans a `.tar` archive containing a MinKNOW sequencing experiment.
///
/// This function opens a TAR archive, searches for the `sample_sheet` CSV file,
/// extracts its metadata, and parses it into a `MinKnowSampleSheet`.
/// All other entries in the archive are collected with their path, size, and modification time.
///
/// # Arguments
/// - `tar_path`: Path to the `.tar` archive file.
///
/// # Returns
/// - `Ok(ExperimentData)`: A tuple containing the parsed sample sheet and the list of file metadata.
/// - `Err`: If the archive is unreadable, malformed, or missing the `sample_sheet`.
///
/// # Archive Requirements
/// - Must contain exactly one file matching `"sample_sheet"` in its path.
/// - The sample sheet must contain a valid CSV header and a single data row.
///
/// # Errors
/// - Fails if the archive can't be opened or read.
/// - Fails if any entry is malformed (e.g., missing timestamp).
/// - Fails if no sample sheet is found or if it is malformed.
///
/// # Example
/// ```no_run
/// let (sample_sheet, files) = scan_archive("archive.tar")?;
/// println!("Sample ID: {}", sample_sheet.sample_id);
/// println!("Total files in archive: {}", files.len());
/// ```
pub fn scan_archive(tar_path: &str) -> anyhow::Result<ExperimentData> {
    info!("Scanning archive: {tar_path}");

    let file = File::open(tar_path)
        .with_context(|| format!("Failed to open tar file at path: {}", tar_path))?;

    let mut archive = tar::Archive::new(file);
    let mut result = Vec::new();

    let mut sample_sheet: Option<String> = None;

    let mut throughput = None;
    let mut pore_activity = None;

    // Iterate through the entries in the archive
    for entry in archive.entries_with_seek()? {
        let mut file = entry.context("Failed to read an entry from the tar archive")?;

        // Extract file properties safely
        let size = file.size();
        let modified = file
            .header()
            .mtime()
            .context("Failed to get modification time")?;
        let modified_utc: DateTime<Utc> = Utc.timestamp_opt(modified as i64, 0).unwrap();

        let path = file
            .path()
            .context("Failed to get file path from tar entry")?
            .to_string_lossy()
            .into_owned();

        if path.contains("pore_activity") {
            pore_activity = Some(
                parse_pore_activity_from_reader(&mut file)
                    .context("Failed to read pore_activity data: {path}")?,
            );
        } else if path.contains("sample_sheet") {
            let mut buffer = String::new();
            file.read_to_string(&mut buffer)
                .context("Failed to read file contents as string")?;
            sample_sheet = Some(buffer);
        } else if path.contains("throughput") {
            throughput = Some(
                parse_throughput_from_reader(&mut file)
                    .context("Failed to read throughput data: {path}")?,
            );
        }

        result.push((path, size, modified_utc));
    }

    let sample_sheet = sample_sheet.ok_or(anyhow::anyhow!(
        "No sample sheet detected in archive: {tar_path}"
    ))?;
    let (_, data) = sample_sheet
        .split_once("\n")
        .ok_or(anyhow::anyhow!("Can't parse sample sheet data"))?;
    let sample_sheet: MinKnowSampleSheet = data
        .try_into()
        .map_err(|e| anyhow::anyhow!("Can't parse sample sheet.\n{e}"))?;
    Ok((sample_sheet, pore_activity, throughput, result))
}