# informix-db

Pure-Python driver for IBM Informix IDS, speaking the SQLI wire protocol over raw sockets. **No IBM Client SDK. No JVM. No native libraries.** PEP 249 compliant; sync + async APIs; built-in connection pool; TLS support.

To our knowledge this is the **first pure-socket Informix driver in any language** — every other Informix driver (`IfxPy`, the legacy `informixdb`, ODBC bridges, JPype/JDBC, Perl `DBD::Informix`) wraps either IBM's CSDK or the JDBC JAR.

```bash
pip install informix-db
```

Requires Python ≥ 3.10.

## Status

**Production ready.** Every finding from a system-wide failure-mode audit (data correctness, wire safety, resource leaks, concurrency, async cancellation) has been addressed:

| Severity | Finding | Status |
|---|---|---|
| Critical | Pool returns connections with open transactions | Fixed (Phase 26) |
| Critical | Unsynchronized wire path → PDU interleaving | Fixed (Phase 27) — per-connection wire lock |
| High | Async cancellation leaks running workers onto recycled connections | Fixed (Phase 27) |
| High | `_raise_sq_err` bare-except masks wire desync | Fixed (Phase 28) |
| High | Cursor finalizers — server-side resources leak on mid-fetch raise | Fixed (Phase 28+29) |
| Medium | 5 hardening items | Fixed (Phase 28+30) |

**0 critical, 0 high, 0 medium audit findings remain.** Every architectural change went through a Margaret Hamilton-style review focused on silent-failure modes, recovery paths, and documented invariants. Each documented invariant is paired with either a runtime guard or a CI tripwire test.

**Test coverage:** 300+ tests across unit / integration / benchmark suites. Integration tests run against the official IBM Informix Developer Edition Docker image (15.0.1.0.3DE).

## Quick start

```python
import informix_db

with informix_db.connect(
    host="db.example.com", port=9088,
    user="informix", password="...",
    database="mydb", server="informix",
) as conn:
    cur = conn.cursor()
    cur.execute("SELECT id, name FROM users WHERE id = ?", (42,))
    user_id, name = cur.fetchone()
```

## Async (FastAPI / aiohttp / asyncio)

```python
import asyncio
from informix_db import aio

async def main():
    pool = await aio.create_pool(
        host="db.example.com", user="informix", password="...",
        database="mydb",
        min_size=1, max_size=10,
    )
    async with pool.connection() as conn:
        cur = await conn.cursor()
        await cur.execute("SELECT id, name FROM users WHERE id = ?", (42,))
        row = await cur.fetchone()
    await pool.close()

asyncio.run(main())
```

## Connection pool (sync)

```python
import informix_db

pool = informix_db.create_pool(
    host="db.example.com", user="informix", password="...",
    database="mydb",
    min_size=1, max_size=10, acquire_timeout=5.0,
)

with pool.connection() as conn:
    cur = conn.cursor()
    cur.execute("...")

pool.close()
```

## TLS

```python
import ssl

# Production: bring your own context
ctx = ssl.create_default_context(cafile="/path/to/ca.pem")
informix_db.connect(host="...", port=9089, ..., tls=ctx)

# Dev / self-signed: tls=True disables verification
informix_db.connect(host="127.0.0.1", port=9089, ..., tls=True)
```

Informix uses dedicated TLS-enabled listener ports (configured server-side in `sqlhosts`) rather than STARTTLS upgrade — point `port` at the TLS listener (often `9089`) when `tls` is enabled.

## Type support

| SQL type | Python type |
|---|---|
| `SMALLINT` / `INT` / `BIGINT` / `SERIAL` | `int` |
| `FLOAT` / `SMALLFLOAT` | `float` |
| `DECIMAL(p,s)` / `MONEY` | `decimal.Decimal` |
| `CHAR` / `VARCHAR` / `NCHAR` / `NVCHAR` / `LVARCHAR` | `str` |
| `BOOLEAN` | `bool` |
| `DATE` | `datetime.date` |
| `DATETIME YEAR TO ...` | `datetime.datetime` / `datetime.time` / `datetime.date` |
| `INTERVAL DAY TO FRACTION` | `datetime.timedelta` |
| `INTERVAL YEAR TO MONTH` | `informix_db.IntervalYM` |
| `BYTE` / `TEXT` (legacy in-row blobs) | `bytes` / `str` |
| `BLOB` / `CLOB` (smart-LOBs) | `informix_db.BlobLocator` / `informix_db.ClobLocator` (read via `cursor.read_blob_column`, write via `cursor.write_blob_column`) |
| `ROW(...)` | `informix_db.RowValue` |
| `SET(...)` / `MULTISET(...)` / `LIST(...)` | `informix_db.CollectionValue` |
| `NULL` | `None` |

## Smart-LOB (BLOB / CLOB) read & write

```python
# Read: returns the actual bytes
data = cur.read_blob_column(
    "SELECT data FROM photos WHERE id = ?", (42,)
)

# Write: BLOB_PLACEHOLDER token marks where the BLOB goes
cur.write_blob_column(
    "INSERT INTO photos VALUES (?, BLOB_PLACEHOLDER)",
    blob_data=jpeg_bytes,
    params=(42,),
)
```

Both work end-to-end in pure Python via the `lotofile` / `filetoblob` server functions intercepted at the `SQ_FILE` (98) wire-protocol level — no native machinery anywhere in the thread of execution. See [`docs/DECISION_LOG.md`](docs/DECISION_LOG.md) §10–11 for the architecture pivot that made this possible.

## Direct stored-procedure invocation (fast-path)

```python
# Cleanly close a smart-LOB descriptor opened via SQL
result = conn.fast_path_call(
    "function informix.ifx_lo_close(integer)", lofd
)
# result == [0] on success
```

The fast-path RPC (`SQ_FPROUTINE` / `SQ_EXFPROUTINE`) bypasses PREPARE → EXECUTE → FETCH for direct UDF/SPL calls. Routine handles are cached per-connection, so repeated calls to the same function take a single round-trip.

## Server compatibility

Tested against IBM Informix Dynamic Server **15.0.1.0.3DE** (the official `icr.io/informix/informix-developer-database` Docker image). The wire protocol is stable across modern Informix versions; should work against 12.10+ unmodified.

For features that need server-side configuration (smart-LOBs, logged transactions), see [`docs/DECISION_LOG.md`](docs/DECISION_LOG.md):
- Phase 7 — logged-DB transactions
- Phase 8 — BYTE/TEXT (needs blobspace)
- Phase 10/11 — BLOB/CLOB (needs sbspace + `SBSPACENAME` config + level-0 archive)

## Performance

Single-connection benchmarks against the dev container on loopback:

| Operation | Mean | Throughput |
|---|---:|---:|
| `decode(int)` per cell | 139 ns | 7.2M ops/sec |
| `parse_tuple_payload` per row (5 cols) | 1.4 µs | 715K rows/sec |
| `SELECT 1` round-trip | ~140 µs | ~7K queries/sec |
| 1000-row SELECT | ~1.0 ms | ~990K rows/sec sustained |
| `executemany(1000)` in transaction | 32 ms | **~31,000 rows/sec** |
| Pool acquire + query + release | 295 µs | ~3.4K queries/sec |
| Cold connect (login handshake) | 11 ms | ~90 connections/sec |

**Performance gotcha**: `executemany(...)` under `autocommit=True` is **53× slower** than the same call inside a single transaction (server flushes the transaction log per row). For bulk loads, `autocommit=False` (default) + `conn.commit()` at the end. See [`docs/USAGE.md`](docs/USAGE.md) for the full performance tips section.

### Compared to IfxPy (the C-bound PyPI driver)

Head-to-head benchmarks against [IfxPy](https://pypi.org/project/IfxPy/) on identical workloads, same Informix server, matched conditions. Using **median + IQR over 10+ rounds** to resist outlier-round noise:

| Benchmark | IfxPy 3.0.5 (C-bound) | `informix-db` (pure Python) | Result |
|---|---:|---:|---:|
| Single-row SELECT round-trip | 118 µs | **114 µs** | **`informix-db` 3% faster** |
| ~10-row server-side query | 164 µs | **159 µs** | **`informix-db` 3% faster** |
| 1000-row SELECT (full fetch) | 984 µs | **891 µs** | **`informix-db` 9% faster** |
| **`executemany(1000)` in transaction** | 21.4 ms | **10.4 ms** | **`informix-db` 2.05× faster** |
| Cold connect (login handshake) | 11.0 ms | **10.4 ms** | **`informix-db` 5% faster** |

**`informix-db` wins on all 5 benchmarks against the C-bound driver, including a 2× win on bulk inserts.**

**Why pure-Python wins the round-trip-bound work:** IfxPy's code path is `Python → OneDB ODBC driver → libifdmr.so → wire`. Ours is `Python → wire`. The abstraction-layer overhead IfxPy carries on every call costs more than the C-vs-Python codec gap saves.

**Why we win bulk inserts dramatically:** `executemany` pipelines all N BIND+EXECUTE PDUs to the wire before draining responses (Phase 33), eliminating the per-row round-trip that the older serial loop incurred. IfxPy still does one synchronous round-trip per row.

Full methodology, IQR caveats, install gauntlet, and reproduction in [`tests/benchmarks/compare/README.md`](tests/benchmarks/compare/README.md).

A note on IfxPy's install gauntlet: getting it to run on a modern system requires Python ≤ 3.11, setuptools <58, permissive CFLAGS, manual download of a 92 MB ODBC tarball, four `LD_LIBRARY_PATH` directories, and `libcrypt.so.1` (deprecated 2018, missing on Arch / Fedora 35+ / RHEL 9). `informix-db`'s install: `pip install informix-db`.

## Standards & guarantees

* **PEP 249** (DB-API 2.0): `connect()`, `Connection`, `Cursor`, `description`, `rowcount`, exception hierarchy
* **`paramstyle = "numeric"`** (Informix's native ESQL/C convention; `?` and `:1` both work)
* **Threadsafety = 1**: threads may share the module but not connections; the pool gives per-thread connection access. Phase 27 added a per-connection wire lock that makes accidental sharing safe (interleaved PDUs serialize correctly), but PEP 249 advice still holds — give each thread its own connection.
* **CalVer versioning**: `YYYY.MM.DD` releases. PEP 440 post-releases (`.1`, `.2`) for same-day fixes.

## Development

The full test + lint workflow is in the [Makefile](Makefile). Quick summary:

```bash
make test                     # 77 unit tests (no Docker)
make ifx-up && make test-integration   # 231 integration tests
make bench                    # benchmark suite
make lint                     # ruff
```

For the smart-LOB tests specifically, the dev container needs additional one-time setup (blobspace + sbspace + level-0 archive). See [`docs/DECISION_LOG.md`](docs/DECISION_LOG.md) §10 for the `onspaces` / `onmode` / `ontape` commands.

## Documentation

- [**`docs/USAGE.md`**](docs/USAGE.md) — practical recipes: connections, parameter binding, type mapping, transactions, performance tips, scrollable cursors, BLOBs, async, TLS, locale/Unicode, error handling, known limitations
- [`tests/benchmarks/README.md`](tests/benchmarks/README.md) — performance baselines, headline numbers, how to run regressions
- `CHANGELOG.md` — phase-by-phase release notes

## Project history & design rationale

This driver was built incrementally across 30 phases, each with a focused scope and decision log. The reasoning trail lives in:

- [`docs/PROTOCOL_NOTES.md`](docs/PROTOCOL_NOTES.md) — byte-level SQLI wire-format reference
- [`docs/JDBC_NOTES.md`](docs/JDBC_NOTES.md) — index into the decompiled IBM JDBC driver, used as a clean-room reference
- [`docs/DECISION_LOG.md`](docs/DECISION_LOG.md) — phase-by-phase architectural decisions, with the *why* preserved
- [`docs/CAPTURES/`](docs/CAPTURES/) — annotated socat hex-dump captures

Notable architectural pivots documented in the decision log:
- **Phase 10/11** (smart-LOB read/write): used `lotofile`/`filetoblob` SQL functions + `SQ_FILE` protocol intercept instead of the heavier `SQ_FPROUTINE` + `SQ_LODATA` stack — ~3x smaller than originally projected
- **Phase 7** (logged-DB transactions): discovered Informix requires explicit `SQ_BEGIN` before each transaction in non-ANSI mode, plus `SQ_RBWORK` needs a savepoint short payload
- **Phase 16** (async): shipped thread-pool wrapping (~250 lines) instead of full I/O abstraction refactor (~2000 lines); functionally equivalent for typical FastAPI workloads

## License

MIT.