sfdupes/README.md

# sfdupes

## Description

`sfdupes` is an MIT-licensed Go CLI tool by
[@sneak](https://sneak.berlin) that quickly identifies *candidate*
duplicate files — and, ultimately, entire duplicate directory trees —
across very large filesystems without reading full file contents. Files
are considered duplicates when they have identical size, identical
SHA-256 of their first 1024 bytes, and identical SHA-256 of their last
1024 bytes. This is a strong candidate signal, not proof of identical
content (the middle of the file is never read); the intended use is
finding duplicate downloads and duplicated directory trees on
multi-terabyte ZFS servers where reading every byte is prohibitively
expensive. `scan` maintains a persistent SQLite database of file
signatures that survives between runs, so it can be run from cron and
the reports can be generated at any time from the most recent scan.

This tool was created by [@sneak](https://sneak.berlin) to scratch an itch,
using Claude Code/Fable.

This README is the complete and authoritative specification.

## Getting Started

```sh
make build
export SFDUPES_DATABASE="$HOME/.local/share/sfdupes/db.sqlite"
./sfdupes scan /srv
./sfdupes report > dupes.tsv
./sfdupes trees > dupetrees.tsv
```

`scan` walks one or more filesystem trees and maintains one database
record per regular file (path, size, mtime, head hash, tail hash). The
database persists between runs; a rescan only hashes files that are new
or changed, and removes records for files that no longer exist.
`report` reads the database and prints the file-level duplicates
report. `trees` reads the same database and prints the duplicate-tree
report. A missing/invalid subcommand — or a `scan` invocation with no
`PATH` operand — prints a usage message and exits 2.

The database defaults to `/var/lib/sfdupes/db.sqlite` and can be placed
anywhere by setting `SFDUPES_DATABASE`. The intended deployment is a
daily `sfdupes scan` cron job, with the reporting commands run
interactively whenever needed; their results are as fresh as the last
completed scan.

## Rationale

Duplicate finders that hash entire files do not scale to the target
environment: ~10 million files and ~150 TB on possibly slow or busy
disks (a ZFS pool under resilver). Reading at most 2 KiB per file — and
only from files whose size at least one other file shares, since a
size-unique file cannot be a duplicate — makes a full-filesystem sweep
tractable, and the signatures are kept in a persistent database, so
the expensive filesystem pass is incremental: a rescan re-hashes only
files whose recorded mtime or size changed, and all analysis happens
offline from the database alone. The end goal is
not individual files but whole duplicated trees — duplicate
extractions, duplicate downloads, copied project trees — which an
operator can consider removing as a unit.

## Design

Goals, in order:

1.  **Find whole duplicate trees, not just files.** The end goal is to
    identify places where the exact same set of files and directories
    exists at two or more paths (duplicate extractions, duplicate
    downloads, copied project trees), so the operator can consider
    removing an entire subtree at once. File-level duplicate detection is
    the foundation; tree-level detection is built on top of it.
2.  **Never read full file contents.** At most 2 KiB is read per file
    (first and last 1024 bytes), and only files whose size at least
    one other file shares are read at all — a size-unique file cannot
    be a duplicate. Scale target: tens of millions of files, ~150 TB
    filesystem, possibly slow or busy disks (ZFS pool under resilver).
    Holding one small record (path, size, mtime) per file in memory
    during a scan is acceptable; holding every file's hashes is not
    (they stay in the database).
3.  **Scan incrementally, analyze offline.** The expensive filesystem
    scan maintains a persistent database; an unchanged file is never
    read again on a rescan. All analysis (`report`, `trees`) works from
    the database alone and must never touch the scanned filesystem
    again. `scan` is designed to be cronned; the reports run at any
    time against the last completed scan.
4.  **Clean stream separation.** Everything on stdout is machine-readable
    data. All progress, warnings, and summaries go to stderr. Never mix
    them.

### Constraints

-   Language: Go (module `sneak.berlin/go/sfdupes`). Binary name:
    `sfdupes`.
-   Dependencies: standard library, `github.com/spf13/cobra` for the
    CLI, **one progress-bar library**
    (`github.com/schollz/progressbar/v3`), and **one SQLite driver**
    (`modernc.org/sqlite`, pure Go, so builds keep cgo disabled).
    `github.com/spf13/viper` is permitted if configuration-file support
    is ever needed, but is not currently used. No other third-party
    deps.
-   Cross-compilation is not a concern. Builds run with cgo disabled (the
    `Makefile` exports `CGO_ENABLED=0`); the code must remain pure Go.
-   Analysis modes (`report`, `trees`) must be deterministic: identical
    database contents, identical output, regardless of the order in
    which records were inserted.

### Subcommands

Three subcommands, all implemented:

1.  `scan` — walk the filesystem and synchronize the database: one
    signature record per regular file.
2.  `report` — file-level duplicate report from the database.
3.  `trees` — tree-level duplicate report: reconstruct the directory
    hierarchy from the database records, compute a Merkle-style digest
    per directory, and report maximal groups of identical trees.

```
sfdupes scan [--workers N] [-x] PATH...
sfdupes report > dupes.tsv
sfdupes trees > dupetrees.tsv
```

### Database

All three subcommands operate on a single SQLite database file:

-   Location: the value of the `SFDUPES_DATABASE` environment variable
    when set and non-empty, otherwise `/var/lib/sfdupes/db.sqlite`.
    There is no command-line flag.
-   `scan` creates the database (and its parent directory) on first
    use. `report` and `trees` require an existing database; a missing
    database file is a fatal error (exit 1) telling the user to run
    `scan` first.
-   The database uses WAL journal mode and a busy timeout, so running a
    report while a cron `scan` is in progress is safe. The filesystem
    is authoritative; the database is an eventually-consistent
    reflection of it. Hashed records are committed in batched
    transactions while the scan is still running (keeping the WAL
    small and letting concurrent reports observe progress), so a
    report may see a scan's changes partially applied, and a scan
    that dies partway leaves a valid database holding everything
    hashed so far; the next scan skips those records and converges
    toward the filesystem.
-   Schema (`PRAGMA user_version` is the schema version, currently 1; a
    database with any other version is a fatal error):

    ```sql
    CREATE TABLE files (
        path  BLOB PRIMARY KEY,  -- absolute path, raw bytes
        size  INTEGER NOT NULL,  -- bytes, from lstat
        mtime INTEGER NOT NULL,  -- Unix seconds, from lstat
        head  TEXT NOT NULL,     -- lowercase-hex SHA-256, first 1 KiB
        tail  TEXT NOT NULL      -- lowercase-hex SHA-256, last 1 KiB
    ) WITHOUT ROWID;
    ```

    Paths are stored as BLOBs because Unix paths are raw bytes, not
    guaranteed UTF-8. `mtime` is used only for change detection; it is
    not part of the duplicate key. `head` and `tail` are empty strings
    when the file has never been hashed because its size was unique as
    of the last scan that covered it; such records still define the
    file for tree reconstruction but never participate in duplicate
    groups.

### `scan` mode

`scan` requires one or more `PATH` operands naming the trees to scan.
There is no default path; invoking `scan` with no operand is a usage
error (usage message on stderr, exit 2). An operand may be a directory
or a regular file; an operand that does not exist is a fatal error
(exit 1). Because database records persist between runs and are keyed
by absolute path, each operand is resolved to an absolute, lexically
cleaned path (symlinks are not resolved) before walking, so results do
not depend on the working directory. All operands belong to a single
scan and are enumerated concurrently: every operand seeds the shared
walk worker pool. Overlapping operands are harmless — an operand that
duplicates another or lies under another is dropped before walking,
so every file is reached exactly once and produces one database
record.

`scan` synchronizes the database with the filesystem state under the
scanned operands:

-   Only a file whose size at least one other file shares is ever
    read: a size-unique file cannot be a duplicate, so it is recorded
    without hashes (`head` and `tail` empty). The size census covers
    every file walked this scan plus every database record outside
    the scanned operands, so a possible duplicate of a separately
    scanned tree is still recognized.
-   A file not yet in the database is inserted: hashed when its size
    is shared, without hashes otherwise.
-   A file already in the database is **skipped without reading its
    contents** when its lstat size equals the recorded size and its
    lstat mtime is not newer than the recorded mtime. This is what
    makes a daily rescan cheap. Exception: an unchanged file whose
    record lacks hashes is hashed — and its record updated — once its
    size becomes shared, so hashing deferred by size-uniqueness
    happens as soon as it could matter.
-   A file whose mtime is newer than recorded, or whose size differs,
    is processed as if new: re-hashed, or recorded without hashes,
    per the shared-size rule.
-   A database record whose path lies under one of the scanned operands
    but was not successfully processed this run is deleted. This
    removes records for deleted files. It also removes records for
    paths that failed to stat or hash this run: the database only ever
    contains signatures verified by the most recent scan that covered
    them (a subsequent successful scan re-adds such files).
-   Database records outside the scanned operands are untouched, so
    disjoint trees can be scanned on different schedules into the same
    database.

`scan` runs **three sequential phases over the whole scan**.
Parallelism lives inside each phase; batched database writes begin
during the hash phase:

1.  **walk + stat** — enumerate the trees under all `PATH` operands
    concurrently with the walk worker pool: every operand seeds the
    shared queue, and each worker reads one directory at a time,
    handing discovered subdirectories back to the queue and running
    `lstat` on each regular file as it is discovered (while the
    directory's metadata is still hot). Sequential directory
    enumeration is metadata-latency-bound and takes hours at tens of
    millions of files; per-directory parallelism is what makes the
    walk tractable on large or busy pools. The walk builds the size
    census and resolves unchanged already-hashed files on the fly;
    every other file is carried to the hash phase as a (path, size,
    mtime) record.
2.  **hash** — with the census complete, each carried file's size
    decides its fate. Size-unique files are never read: new or
    changed ones are recorded without hashes in the update phase,
    unchanged unhashed ones simply keep their records. Every file
    with a shared size is hashed by the worker pool: read the first
    `min(1024, size)` bytes and the last `min(1024, size)` bytes
    (one read when `size <= 1024`, since the two windows coincide;
    for `size == 0` hash the empty input) and compute the SHA-256 of
    each. The phase total is exact, so progress and ETA are
    meaningful. Completed records are committed in batched
    transactions **while hashing runs**, so a scan interrupted after
    hours keeps everything hashed so far and the next scan resumes
    cheaply, skipping records already written.
3.  **update** — commit the final partial batch, the hash-less
    records for size-unique new and changed files, and the deletions
    for records the scan did not verify (vanished files, plus paths
    that failed to stat or hash).

Rules for the walk:

-   Only regular files. Skip directories, symlinks (do not follow,
    including symlink operands), sockets, FIFOs, and device nodes.
-   Never descend into a directory named `.zfs` (ZFS snapshot pseudo-dirs;
    walking them would list every file once per snapshot).
-   Filesystem boundaries are crossed by default. With `-x`
    (long form `--one-file-system`, following the GNU `du`/`rsync`
    convention), never descend into a directory on a different
    filesystem than its `PATH` operand; each operand is bounded by its
    own filesystem.
-   On any per-path error (permission denied, file vanished between
    passes, unreadable): print a one-line warning to stderr, skip the
    path, and continue. Per-file errors never abort the run; the final
    summary reports how many were skipped. As specified above, a
    skipped path that has a database record from an earlier scan loses
    that record; an unreadable directory subtree likewise loses its
    records (accepted: the database mirrors what the latest scan could
    actually verify).

Concurrency: the walk phase (which also stats files) and the hash
phase each use a worker pool of `--workers` workers (default
`runtime.NumCPU()`); the walk parallelizes across directories,
hashing across files. Both phases are seek-bound on spinning disks,
so raising `--workers` well past the core count can help on pools
with many spindles. The main goroutine owns partitioning, database
writes, and progress rendering; progress display must never block
the workers.

`scan` writes nothing to stdout. The summary line on stderr reports the
files seen this run broken down by disposition, plus skips:

```
scan: 123456 files seen (1200 added, 34 updated, 56 removed, 122166 unchanged), 3 skipped
```

(`removed` counts deleted database records, which are not part of the
files-seen total.)

### `report` mode

`report` reads every record from the database and takes no positional
arguments.

**`report` must never touch the filesystem being analyzed.** It does not
stat, open, or otherwise access any path that appears in the records; its
only I/O is reading the database and writing stdout/stderr. It must
produce identical output whether or not the scanned filesystem is still
mounted.

Processing:

-   Records without hashes (size-unique when last scanned) are
    excluded: their content is unknown, so they are never reported as
    duplicates.
-   Group the remaining records by the key
    `(size, head_hash, tail_hash)`.
-   Every group with two or more paths is a duplicate group.
-   Within each group, sort paths lexicographically (byte order). The
    first path is the group's `first`; every other path is a `dupe`.
-   Order groups by size descending (biggest reclaimable space first),
    tie-broken by `first` path ascending. Output must be fully
    deterministic for a given database state.

#### Report output format

TSV on stdout: a header line, then one row per duplicate file (N-1 rows
for a group of N):

```
first	dupe	size
/srv/a/big.iso	/srv/b/big-copy.iso	4294967296
/srv/a/big.iso	/srv/c/big-copy2.iso	4294967296
```

Summary to stderr: records read, number of duplicate groups, number of
dupe files, and total reclaimable bytes (sum of `size` over all dupe
rows) in human units.

### `trees` mode

`trees` reads the same database as `report` (no positional arguments)
and reports **entire duplicate directory trees**: directories under
which the exact same set of relative paths exists with the exact same
file signatures.

**`trees` must never touch the filesystem being analyzed** — the same
rule as `report`. The directory hierarchy is reconstructed purely from
the paths in the records, split on `/`.

Definitions:

-   A file's **signature** is `(size, head_hash, tail_hash)` — mtime is
    informational and excluded. An unhashed record (empty hashes) has
    unknown content: its signature is treated as unique to that file,
    so a tree containing an unhashed file never compares equal to any
    other tree.
-   A directory's **digest** is a SHA-256 Merkle digest computed
    bottom-up: serialize the directory's child entries — for a file
    child, its name and signature; for a subdirectory child, its name
    and that subdirectory's digest — sort the serialized entries
    byte-lexicographically, and hash the concatenation. Names are part
    of the digest: two trees whose files differ only in name are *not*
    duplicates.
-   Two directories are **duplicate trees** when their digests are
    equal. Equal digests imply equal recursive file count and equal
    total byte size.

Known limitation (accepted): only regular files that appear in the
database define a tree. Empty directories are invisible, and a file
skipped during the scan (e.g. permission error) in one copy but not the
other will make otherwise-identical trees compare as different.

Processing:

-   Build the hierarchy, compute every directory's digest, and group
    directories by digest. Every group with two or more directories is a
    duplicate-tree group.
-   **Report only maximal trees.** A group is suppressed when its
    members' parents are pairwise distinct directories that all share a
    single digest — such a group is wholly implied by its parents' (or a
    further ancestor's) group. Groups containing sibling directories, or
    members whose parents differ, are always reported.
-   Within each group, sort paths lexicographically (byte order); the
    first path is `first`, every other path is a `dupe`.
-   Order groups by total tree size descending, tie-broken by `first`
    path ascending. Output must be fully deterministic for a given
    input.

#### Trees output format

TSV on stdout: a header line, then one row per duplicate tree (N-1 rows
for a group of N). `files` is the recursive regular-file count of one
copy of the tree; `size` is the recursive total byte size of one copy:

```
first	dupe	files	size
/srv/a/project	/srv/backup/project	3417	104857600
```

Summary to stderr: records read, number of duplicate-tree groups,
number of dupe trees, and total reclaimable bytes (sum of `size` over
all dupe rows) in human units.

### Progress

Use the progress-bar library for all scan progress; rendering in the
style of `pv` is the model. All progress goes to stderr.

Each phase gets its own display. The walk has no known total while
running: show a live file count, rate, and elapsed time
(spinner-style, no percentage or ETA). The hash and update phases
have exact totals — only files that actually need hashing appear in
the hash total, so its ETA is meaningful. Required elements for the
bars with known totals:

-   elapsed time
-   estimated time remaining
-   a `[m/n] x%` display (items processed / total items, percent)
-   current rate (items/s)

Example shape (exact layout is flexible, content is not):

```
hash: [12345/98765] 12% |████      | 92 files/s elapsed 2:32 eta 17:54
```

Additional requirements:

-   When stderr is not a TTY, do not emit ANSI redraws: print a plain
    one-line progress update no more often than every 5 seconds instead.
-   Progress updates are driven from the main goroutine and must be
    non-blocking with respect to the worker pool.
-   `report` and `trees` modes need no progress display, only their
    stderr summaries.

### Error handling and exit codes

-   `0`: success, even if individual files were skipped with warnings.
-   `1`: fatal error (e.g., a `PATH` operand does not exist, the
    database cannot be created/opened/read/written, a missing database
    for `report`/`trees`, stdout write failure).
-   `2`: usage error (including `scan` with no `PATH` operand and
    `report`/`trees` with any positional argument).

## Build

The `Makefile` is the single source of truth for all operations:

-   `make` / `make build` — build the `sfdupes` binary (cgo
    disabled); building is the default target.
-   `make test` — run the test suite (30-second timeout; reruns with
    `-v` on failure).
-   `make lint` — run `golangci-lint` with the repo config.
-   `make fmt` / `make fmt-check` — format Go sources / verify
    formatting without writing.
-   `make check` — `test`, `lint`, and `fmt-check`; modifies nothing.
-   `make docker` — build the Docker image, which runs `make check` as
    a build stage.
-   `make hooks` — install the pre-commit hook.
-   `make clean` — remove the binary and any legacy local `files.dat`.

### Definition of done

All of the following, run in this directory, must pass:

1.  `make check` passes (tests, lint, `gofmt`).
2.  `make docker` succeeds.
3.  Smoke test — create a throwaway tree in a temp dir (never test
    against real data):

    ```sh
    d=$(mktemp -d)
    export SFDUPES_DATABASE="$d/db.sqlite"
    mkdir -p "$d/a" "$d/b"
    head -c 2000 /dev/urandom > "$d/a/one.bin"
    cp "$d/a/one.bin" "$d/b/copy.bin"
    cp "$d/a/one.bin" "$d/b/copy2.bin"
    head -c 2000 /dev/urandom > "$d/a/unique.bin"     # same size, different content
    printf 'x' > "$d/tiny1"; printf 'x' > "$d/tiny2"  # 1-byte duplicates
    printf 'y' > "$d/tiny3"                           # 1-byte non-duplicate
    : > "$d/empty1"; : > "$d/empty2"                  # empty duplicates
    # duplicate trees: t1 and t2 are identical; t3 differs by one filename
    mkdir -p "$d/t1/sub" "$d/t2/sub" "$d/t3/sub"
    head -c 3000 /dev/urandom > "$d/t1/f1"
    head -c 100  /dev/urandom > "$d/t1/sub/f2"
    cp "$d/t1/f1" "$d/t2/f1"
    cp "$d/t1/sub/f2" "$d/t2/sub/f2"
    cp "$d/t1/f1" "$d/t3/f1"
    cp "$d/t1/sub/f2" "$d/t3/sub/f2renamed"
    ./sfdupes scan "$d"
    ./sfdupes report
    ./sfdupes trees
    # incremental behavior (scan a subtree; records elsewhere persist):
    ./sfdupes scan "$d/a"                  # everything unchanged, nothing hashed
    printf 'z' >> "$d/a/one.bin"           # modify: next scan re-hashes it
    rm "$d/a/unique.bin"                   # delete: next scan removes its record
    ./sfdupes scan "$d/a"                  # 1 updated, 1 removed
    ./sfdupes report
    ```

    (The scan database lives inside `$d` here purely for test hygiene;
    scanning `$d` therefore also records the SQLite file itself, which
    is harmless.)

    Expected from the first `report`: `one.bin`/`copy.bin`/`copy2.bin`
    form one group (two dupe rows, `first` is the lexicographically
    smallest path); `t1/f1`/`t2/f1`/`t3/f1` form one group;
    `t1/sub/f2`/ `t2/sub/f2`/`t3/sub/f2renamed` form one group;
    `tiny1`/`tiny2` pair; `empty1`/`empty2` pair; `unique.bin` and
    `tiny3` appear nowhere; groups ordered by size descending.

    Expected from `trees`: exactly one row — `first` `$d/t1`, `dupe`
    `$d/t2`, 2 files, 3100 bytes. `$d/t1/sub` vs `$d/t2/sub` is
    suppressed as non-maximal (implied by the `t1`/`t2` group), and `t3`
    appears nowhere (its file set differs by name).

    Expected from the second `report` (after the modify/delete rescan):
    `one.bin` has left its group (its content changed), so
    `copy.bin`/`copy2.bin` remain as one pair, and `unique.bin` is
    gone from the database.

    The test suite automates this scenario (see `scan_test.go`), plus a
    negative check: `report` and `trees` operate on the database alone
    and never touch the scanned filesystem.

## TODO

Tracked in [TODO.md](TODO.md).

## Non-goals

-   No full-content verification, no byte-for-byte compare, no deletion
    or linking of duplicates. The reports are advisory; acting on them is
    the user's job.
-   No persistence beyond the SQLite database described above; no
    export/import formats.
-   No daemon or filesystem watcher; scheduling rescans is cron's job.

## License

MIT. See [LICENSE](LICENSE).

## Author

[@sneak](https://sneak.berlin)