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# tsfile-cli — TsFile Command-Line Tool

`tsfile-cli` is a single, pipe-friendly C++ command-line tool for inspecting **and**
importing Apache TsFile (`.tsfile`) files from the shell — the TsFile analogue of
`parquet-cli` / `pqrs`. Read commands print data to **stdout** and diagnostics to
**stderr**, so they compose with `awk`, `jq`, `sort`, and friends; the `write` command
imports CSV/TSV into a new `.tsfile`. It is built on the public `storage::TsFileReader`
and `storage::TsFileTableWriter` APIs and does not modify the storage engine.

## Building from source

The CLI is part of the C++ module and is built by default (CMake option `BUILD_TOOLS=ON`).
The CMake target is `tsfile_cli`; the produced executable is named `tsfile-cli`.

**Prerequisites:** a C++11 compiler (GCC / Clang / MSVC) and CMake ≥ 3.11. The third-party
dependencies (ANTLR4, Snappy, LZ4, LZOKAY, Zlib, GoogleTest) are bundled under
`cpp/third_party/` and built automatically — no separate install step needed.

Choose any one of the following.

**1. Build script (recommended).** From `cpp/`:

```bash
bash build.sh -t=Debug      # -> cpp/build/Debug/bin/tsfile-cli
bash build.sh               # Release (default) -> cpp/build/Release/bin/tsfile-cli
bash build.sh install       # Release build, then run make install
```

**2. Maven (builds the whole C++ module).** From the repository root:

```bash
./mvnw clean package -P with-cpp   # -> cpp/target/build/bin/tsfile-cli
```

**3. Plain CMake.** From `cpp/`:

```bash
mkdir -p build/Debug && cd build/Debug
cmake ../.. -DCMAKE_BUILD_TYPE=Debug
make -j tsfile_cli                 # -> build/Debug/bin/tsfile-cli
```

> **CMake 4.x note.** The bundled ANTLR4 runtime sets old CMake policies that CMake 4
> rejects (`Policy CMP00xx may not be set to OLD behavior`). The reader and CLI do not use
> ANTLR4, so disable it — `--disable-antlr4` for the build script, or `-DENABLE_ANTLR4=OFF`
> for plain CMake:
>
> ```bash
> bash build.sh -t=Debug --disable-antlr4
> ```

Verify the binary:

```bash
./build/Debug/bin/tsfile-cli --version    # -> tsfile-cli (Apache TsFile C++) <version>
./build/Debug/bin/tsfile-cli --help
```

The executable links the `tsfile` shared library built alongside it. To run it from
anywhere, either run it in place by its full path, or explicitly install it with
`bash build.sh install`, `cmake --install .`, or `make install`. The install step places
the binary under `<prefix>/bin` and `libtsfile` under `<prefix>/lib`. The build script
does not install by default.

## Usage

```
tsfile-cli <command> [options] <file.tsfile>
tsfile-cli --help | --version | help
```

Exit codes: `0` success, `1` usage/argument error, `2` file open/corrupt,
`3` query/runtime error.

### Reading

| Command | Description |
|---|---|
| `ls` | List devices (tree model) or tables (table model), one name per line |
| `schema` | Per-series `target, measurement, datatype, encoding, compression` |
| `meta` | File summary: model, device/table/series counts, time range, file size |
| `stats` | Per-series `count, start_time, end_time, min, max, first, last, sum` |
| `count` | Per-series row counts plus a `total` row (from statistics, no page scan) |
| `head` | First N rows (default 10; use `-n`) |
| `cat` | All matching rows, streamed (`table` format buffers to align columns) |
| `sample` | Reproducible reservoir sample (default 10; `-n`, `--seed`) |

The metadata commands (`ls` / `schema` / `meta` / `stats` / `count`) answer most questions
without decoding data pages.

Shared options:

| Option | Meaning |
|---|---|
| `-f, --format csv\|tsv\|json\|table` | Output format; defaults to `table` on a TTY, `tsv` when piped |
| `-d, --device <id>` / `-t, --table <name>` | Scope to one device / table (mutually exclusive) |
| `-m, --measurements a,b,c` | Column projection (`schema`, `stats`, `count`, `head`, `cat`, `sample`) |
| `-n, --limit N` / `--offset N` | Max rows / rows to skip (`head`, `cat`; `--offset` not valid for `sample`) |
| `--start <ms>` / `--end <ms>` | Inclusive epoch-millisecond time range (`head`, `cat`, `sample`) |
| `--seed N` | Reproducible sampling seed (`sample` only) |
| `--tag-filter C OP V` / `--tag-between C L U` / `--tag-not-between C L U` | Table TAG predicate for `head`, `cat`, `sample`; `OP` is `eq`, `neq`, `lt`, `lteq`, `gt`, `gteq`, `regexp`, or `not-regexp` |
| `--no-header` | Omit the header row |
| `--model tree\|table` | Force the model (otherwise auto-detected) |

`json` output is NDJSON (one object per line; numbers/booleans bare, other values quoted,
nulls as `null`; non-finite floats — NaN/Inf — become `null`). CSV output follows RFC 4180.
Timestamps are raw epoch milliseconds. The `table` format buffers all rows in memory to
align columns, so prefer `csv`/`tsv`/`json` when dumping large files.

```bash
BIN=cpp/build/Debug/bin/tsfile-cli
$BIN ls -f tsv data.tsfile                          # list tables / devices
$BIN meta data.tsfile                               # quick file overview
$BIN count -t table1 -f tsv data.tsfile             # row counts, no page scan
$BIN cat -t table1 --tag-filter device eq dev_1 -m temp -f tsv data.tsfile
$BIN cat -m temp,humidity --start 1700000000000 -f csv data.tsfile | head
$BIN sample -m temp -n 20 --seed 42 -f json data.tsfile | jq .
```

### Writing (import)

`tsfile-cli write` imports CSV/TSV rows into a **new table-model** `.tsfile` (the output is
overwritten). The first input column is the timestamp (epoch milliseconds); the remaining
columns are declared explicitly with `--columns` — there is no type inference.

Timestamps must be **strictly increasing per device**, where a device is identified by its
`tag` column values (rows that share the same tags form one device's timeline). Rows for
different tag combinations may freely interleave and reuse timestamps. Out-of-order input is
rejected with the offending line number, and a failed import leaves no output file behind.
`--output` must differ from the input file.

```
tsfile-cli write --table <name> --columns <spec> -o <out.tsfile> \
                 [-f csv|tsv] [--no-header] [--header-match] [-v] [<input> | -]
```

`--columns` is a comma-separated list of `name:TYPE:category`, where `category` (case-insensitive)
is `tag` or `field` and `TYPE` (case-insensitive) is one of `BOOLEAN, INT32, INT64, FLOAT, DOUBLE,
STRING, TEXT, TIMESTAMP, DATE, BLOB` — for example `--columns "id1:STRING:tag,s1:INT64:field"`.
`DATE` cells are written as `YYYY-MM-DD`; `TIMESTAMP` cells as epoch milliseconds. Each column is
stored with the engine's default encoding and compression for its type.

| Option | Meaning |
|---|---|
| `--table <name>` | Output table name (lower-cased) |
| `--columns <spec>` | Ordered data columns (excludes the leading timestamp column) |
| `-o, --output <path>` | Output `.tsfile` (required; overwritten) |
| `<input>` / `-` | Input file, or `-` / omitted for stdin |
| `-f csv\|tsv` | Input delimiter (default csv; `json` / `table` are rejected) |
| `--no-header` | Input has no header row (default: first line is a header and is skipped) |
| `--header-match` | Validate header names against `--columns` |
| `-v, --verbose` | Print `wrote N rows to <out>` to stderr (otherwise silent on success) |

An empty cell is written as null. The command is silent on success (Unix-style); pass `-v`
for a one-line summary.

```bash
# round-trip through a pipe
printf 'time,id1,s1\n0,dev,0\n1,dev,10\n' \
  | tsfile-cli write --table t1 --columns "id1:STRING:tag,s1:INT64:field" -o out.tsfile -
tsfile-cli count -f tsv out.tsfile          # -> t1.dev  s1  2
```

For tree-model writes, JSON input, or programmatic use, use the C++ SDK directly — see
`cpp/examples/cpp_examples/demo_write.cpp` (`TsFileTableWriter` / `TsFileWriter` + `Tablet`).

## Using the skill with an AI assistant

`cpp/tools/skills/tsfile-cli/SKILL.md` is a machine-readable reference that teaches AI
coding assistants (e.g. Claude Code) how to drive `tsfile-cli` correctly. Such assistants
auto-discover skills from a `.claude/skills/` directory at session start, so "installing"
the skill just means placing it there — either project-level or user-level:

```bash
# project-level (this repository only)
mkdir -p .claude/skills/tsfile-cli
cp cpp/tools/skills/tsfile-cli/SKILL.md .claude/skills/tsfile-cli/SKILL.md

# or user-level (available in all your projects)
mkdir -p ~/.claude/skills/tsfile-cli
cp cpp/tools/skills/tsfile-cli/SKILL.md ~/.claude/skills/tsfile-cli/SKILL.md
```

> The installed `SKILL.md` must begin with its YAML front-matter (`--- … ---`) for the
> assistant to detect it. The in-repo copy carries an Apache license header comment above
> the front-matter; if discovery fails, delete that leading `<!-- … -->` block from the
> installed copy so `---` is the first line.

Start a new assistant session afterward. The skill then activates automatically when you
ask to inspect or import a `.tsfile`; you can also invoke it explicitly (e.g. "use the
tsfile-cli skill").

## Source layout

```text
cpp/tools/
├── tools_main.cc          # main(): forwards argv to run_cli
├── cli/                   # argument parsing, top-level dispatch, exit codes
├── format/                # csv/tsv/json/table output + CSV/TSV input parsing
├── commands/              # one file per command + shared row-query / statistics helpers
└── skills/tsfile-cli/     # model-facing skill reference (for AI assistants)
```