informix-db/CHANGELOG.md

Changelog

All notable changes to informix-db. Versioning is CalVer — YYYY.MM.DD for date-based releases, YYYY.MM.DD.N for same-day post-releases per PEP 440.

2026.05.04.6 — executemany perf finding: it was the autocommit cliff

Investigation of the Phase 21 finding that executemany(N) cost scaled linearly per-row (1.74 ms × N) regardless of batch size. Root cause: every autocommit-True INSERT forces a server-side transaction-log flush. Not a wire-protocol bug.

Added

• test_executemany_1000_rows_in_txn benchmark — same workload, but inside a single transaction with one COMMIT at the end. Isolates pure protocol cost from server-storage cost.
• New module-scoped txn_conn fixture in tests/benchmarks/test_insert_perf.py for autocommit-False benchmarks.

Findings

Mode	Total	Per row
executemany(1000) autocommit=True	1.72 s	1.72 ms
executemany(1000) in single txn	32 ms	32 µs

53× speedup from changing the transaction boundary, not the driver. Pure protocol overhead is ~32 µs/row → ~31,000 rows/sec sustained throughput on a single connection. Comparable to mature pure-Python drivers (pg8000).

Changed

• tests/benchmarks/README.md — updated headline numbers to show both modes, added a "Performance gotchas" section explaining when to use autocommit=False for bulk loads.
• tests/benchmarks/baseline.json — refreshed to include the new txn-mode measurement (now 29 entries, was 28).

Decision: don't pipeline

Pipelining BIND+EXECUTE PDUs (writing N without waiting for responses between them) could potentially halve the 32 µs/row figure on loopback. Decided against:

• The remaining 32 µs is already excellent — single-connection bulk-load performance is not where users hit limits.
• Pipelining adds complexity around TCP send-buffer management, partial-failure semantics, and error reporting (which row failed when 50 are in flight).
• The autocommit gotcha is the real user-facing footgun. Better docs > more code.

If someone reports needing >31K rows/sec single-connection, this becomes Phase 22 work.

2026.05.04.5 — Performance benchmarks (Phase 21)

Adds tests/benchmarks/ — a pytest-benchmark driven suite covering codec micro-benchmarks (no server required) and end-to-end SELECT/INSERT/pool/async benchmarks. Establishes a committed baseline.json so future PRs can be compared against the floor and regressions caught at review.

Added

• tests/benchmarks/test_codec_perf.py — 16 micro-benchmarks for the hot codec paths (decode, encode_param, parse_tuple_payload). Run without an Informix container; suitable for pre-merge CI.
• tests/benchmarks/test_select_perf.py — 4 SELECT round-trip benchmarks: 1-row latency floor, ~10 rows, full 1k-row table, parameterized.
• tests/benchmarks/test_insert_perf.py — 3 INSERT benchmarks: single-row, executemany(100), executemany(1000).
• tests/benchmarks/test_pool_perf.py — 3 pool benchmarks: cold connect (login handshake cost), pool acquire/release, pool acquire + tiny query + release.
• tests/benchmarks/test_async_perf.py — 2 async benchmarks: single async round-trip overhead, 10 concurrent SELECTs through an async pool.
• tests/benchmarks/conftest.py — bench_conn (long-lived autocommit connection) and bench_table (pre-populated 1k-row table) fixtures, both session-scoped.
• tests/benchmarks/baseline.json — committed baseline (28 measurements) for --benchmark-compare regression checks.
• tests/benchmarks/README.md — headline numbers, regression policy, how to update baseline, what each benchmark measures.
• make bench / make bench-codec / make bench-save Makefile targets.
• benchmark pytest marker — gated, off by default. pytest -m benchmark to opt in.

Changed

• make test-integration now uses -m "integration and not benchmark" so the integration suite stays fast (~6s) — benchmarks (~27s) are gated behind make bench.
• pytest default -m now excludes both integration and benchmark. Default run is unit-only.

Headline numbers (dev container, x86_64 Linux, loopback)

Operation	Mean
decode(int) (per cell)	181 ns
parse_tuple_payload(5 cols) (per row)	2.87 µs
SELECT 1 round-trip	177 µs
Pool acquire + tiny query + release	295 µs
Cold connect + close	11.2 ms

Pool-vs-cold delta is 72×. UTF-8 decode carries no measurable cost over iso-8859-1 (Phase 20 didn't slow anything down).

Tests

28 new benchmark tests. Total: 69 unit + 211 integration + 28 benchmark = 308.

2026.05.04.4 — UTF-8 / multibyte locale support

Threads the connection's CLIENT_LOCALE through to user-data string codecs so multibyte locales (UTF-8, etc.) round-trip correctly. The driver previously hardcoded iso-8859-1 for every string conversion — fine for Western European text, broken-by-design for CJK, Cyrillic, Arabic, emoji.

Added

• Connection.encoding property — reports the Python codec name derived from CLIENT_LOCALE (e.g., iso-8859-1, utf-8, iso-8859-15). Default for a connection without client_locale= is iso-8859-1 (compatible with the legacy default).

• informix_db.connections._python_encoding_from_locale(locale: str) — maps Informix locale strings (en_US.utf8, en_US.8859-1, en_US.819) to Python codec names. Falls back to iso-8859-1 for unknown / unsuffixed forms.

Changed

• encode_param(value, encoding=...) and _encode_str(value, encoding=...) honor the connection's encoding instead of hardcoded iso-8859-1. Cursor's _emit_bind_params forwards self._conn.encoding per parameter.

• decode(type_code, raw, encoding=...) and parse_tuple_payload(reader, columns, encoding=...) thread the encoding to string column decoders (CHAR, VARCHAR, NCHAR, NVCHAR, LVARCHAR). Cursor's _read_fetch_response forwards self._conn.encoding.

• Smart-LOB CLOB encode/decode (write_blob_column, simple-LOB TEXT fetch) honor self._conn.encoding.

• Fast-path RPC (Connection.fast_path_call) honors self._encoding for its bound parameters.

Boundary discipline

Protocol-level strings stay iso-8859-1 (always ASCII, never user-controlled): cursor names, function signatures, server-fabricated SQ_FILE virtual filenames, error "near tokens", SQL keywords/identifiers. Only user-data strings (column values, parameter binds) follow CLIENT_LOCALE.

Error handling

Encoding-can't-represent-this-value (e.g., "你好" on an 8859-1 connection) now raises informix_db.DataError instead of letting Python's UnicodeEncodeError leak. The cursor releases the prepared statement before propagating, so the connection survives cleanly for the next query.

Tests

9 new integration tests in tests/test_unicode.py:

• ASCII round-trip (regression)
• Latin-1 high-bit chars round-trip on default locale
• Full byte range 0x20-0xFE round-trip via VARCHAR
• Locale → Python codec mapping for common forms
• Connection.encoding exposes the resolved codec
• UTF-8 locale negotiation (server transcodes for ASCII even with 8859-1 DB)
• UTF-8 multibyte round-trip (skipped without IFX_UTF8_DATABASE env var pointing to a UTF-8 database)
• Non-representable char raises DataError cleanly; connection survives
• CLOB column round-trips Latin-1 text honoring connection encoding

Total: 69 unit + 212 integration = 281 tests.

Limitations

• Multibyte UTF-8 storage requires both client_locale='en_US.utf8' AND a database whose DB_LOCALE is UTF-8. The dev container's testdb is 8859-1, so storing CJK chars there will continue to fail server-side regardless of the client codec. The test_utf8_multibyte_round_trip test is gated on the IFX_UTF8_DATABASE env var pointing to a UTF-8 database.

2026.05.04.3 — Resilience tests (fault injection)

Added

• tests/_proxy.py — ControlledProxy helper: a thread-based TCP forwarder between the test client and Informix, with a kill() method that sends TCP RST (via SO_LINGER=0) to simulate a network drop or server crash. Used as a context manager.

• tests/test_resilience.py — 12 integration tests filling the resilience gap identified in the test-coverage audit:

  • Network drop mid-SELECT raises OperationalError cleanly (not hang)
  • Network drop after describe but before fetch
  • Network drop during fetch iteration (already-materialized rows still readable, fresh execute fails)
  • Local socket close (yank-the-rug from client side)
  • I/O error marks connection unusable
  • Pool evicts a connection that died mid-with block
  • Pool revives after all idle connections died (health-check on acquire mints fresh)
  • Async cancellation via asyncio.wait_for — pool stays usable for subsequent queries
  • Cursor reusable after SQL error
  • Connection survives cursor close after error
  • Pool sustained-load smoke (50 acquire/release cycles, no leak)
  • read_timeout fires on a hung connection

What this catches

• Hangs (waiting forever on a dead socket)
• Silent data corruption (treating EOF as a valid tuple)
• Double-fault (one error → cleanup raises a different error)
• Pool poisoning (returning a broken connection to the pool)
• Stale cursor reuse (same cursor reused across an error boundary)

Tests

12 new integration tests. Total: 69 unit + 203 integration = 272 tests.

The Phase 19 work fills the highest-priority gap from the test-adequacy audit. Remaining gaps from that audit (UTF-8 locale, server-version matrix, performance benchmarks) are real but lower-severity.

2026.05.04.2 — Server-side scrollable cursors

Added

• Server-side scrollable cursors (Phase 18): opt in via conn.cursor(scrollable=True). The cursor opens with SQ_SCROLL (24) before SQ_OPEN (6), the result set stays materialized server-side, and each scroll method sends SQ_SFETCH (23) to fetch one row at a time. Use this for huge result sets where in-memory materialization would be wasteful.

  The user-facing API is identical to Phase 17's in-memory scroll (fetch_first, fetch_last, fetch_prior, fetch_absolute, fetch_relative, scroll, rownumber); only the internal mechanism differs:

  	Default cursor	scrollable=True
  Memory	All rows materialized	One row at a time
  Network round-trips per fetch	0 (after initial NFETCH)	1 (one SFETCH per call)
  Cursor lifetime	Closed after execute()	Open until close()
  Best for	Moderate result sets, sequential iteration	Huge result sets, random access

  Implementation discovers total row count lazily via SFETCH(LAST=4) when negative absolute indexing requires it; result is cached in _scroll_total_rows. Position tracking is authoritative from the server's SQ_TUPID (25) tag, not client-computed.

Wire-protocol details

• SQ_SFETCH (23): [short SQ_ID=4][int 23][short scrolltype][int target][int bufSize=4096][short SQ_EOT]. scrolltype values: 1=NEXT, 4=LAST, 6=ABSOLUTE.
• SQ_SCROLL (24): emitted between CURNAME and SQ_OPEN to mark the cursor as scrollable.
• SQ_TUPID (25): server response carrying the 1-indexed row position the server just delivered. [short 25][int rowID].

The trap on the way: I initially used SHORT for bufSize and the server hung silently — same SHORT-vs-INT diagnostic pattern as Phase 4.x's CURNAME+NFETCH. Captured a JDBC trace, byte-diffed against ours, found the mismatch.

Tests

14 new integration tests in test_scroll_cursor_server.py. Total: 69 unit + 191 integration = 260 tests.

2026.05.04.1 — Scroll cursors

Added

• Scroll cursor API on Cursor (Phase 17):

  • cur.scroll(value, mode='relative'|'absolute') — PEP 249 compatible
  • cur.fetch_first() / cur.fetch_last() — jump to ends
  • cur.fetch_prior() — backward step (SQL-standard semantics: from past-end yields the last row)
  • cur.fetch_absolute(n) — 0-indexed jump; negative n indexes from the end
  • cur.fetch_relative(n) — n-step from current position
  • cur.rownumber — current 0-indexed position (None if before-first or no result set)

  In-memory implementation — no new wire-protocol; the existing materialized result set in cur._rows is now indexed rather than iterated. For server-side scroll over huge result sets, SQ_SFETCH (tag 23) would be needed — Phase 18 if anyone hits the in-memory ceiling.

Tests

14 new integration tests in test_scroll_cursor.py. Total: 69 unit + 177 integration = 246 tests.

2026.05.04 — Library completion

The Phase 0 ambition — first pure-Python Informix SQLI driver — reaches feature completeness. Adds async, TLS, connection pool, smart-LOBs, fast-path RPC, composite UDTs.

Added

• Async API (informix_db.aio) — AsyncConnection, AsyncCursor, AsyncConnectionPool for FastAPI / aiohttp / asyncio. Each blocking I/O call is offloaded to a worker thread via asyncio.to_thread; event loop never blocks.
• Connection pool (informix_db.create_pool) — thread-safe with min/max sizing, lazy growth, health-check on acquire, error-aware eviction.
• TLS — tls=True for self-signed dev servers, tls=ssl.SSLContext for production. Wrapping happens in IfxSocket so the rest of the protocol layer is unaware.
• Smart-LOBs (BLOB / CLOB) — full read/write end-to-end via cursor.read_blob_column() / cursor.write_blob_column() using the server's lotofile / filetoblob SQL functions intercepted at the SQ_FILE (98) protocol level.
• Legacy in-row blobs (BYTE / TEXT) — bind + read via the SQ_BBIND / SQ_BLOB / SQ_FETCHBLOB protocol family.
• Fast-path RPC (Connection.fast_path_call) — direct stored-procedure invocation bypassing PREPARE/EXECUTE; routine handles cached per-connection.
• Composite UDT recognition — ROW, SET, MULTISET, LIST columns return typed RowValue / CollectionValue wrappers exposing schema and raw bytes.
• Type codecs — INTERVAL (both DAY-TO-FRACTION and YEAR-TO-MONTH families), DATETIME (all qualifier ranges), DECIMAL / MONEY (BCD with sign+exp head byte and asymmetric base-100 complement for negatives), DATE, BOOL, all integer / float widths, CHAR / VARCHAR / LVARCHAR.
• Transactions — implicit SQ_BEGIN before each transaction in non-ANSI logged DBs; transparent no-ops on unlogged DBs.
• PEP 249 exception hierarchy — server SQLCODE mapped to the right exception class (IntegrityError for duplicate-key violations, ProgrammingError for syntax errors, etc.).

Documentation

• README.md — overview and quick-start
• docs/USAGE.md — practical recipes and migration guide
• docs/PROTOCOL_NOTES.md — byte-level wire-format reference
• docs/DECISION_LOG.md — phase-by-phase architectural decisions, with the why preserved
• docs/JDBC_NOTES.md — index into the decompiled IBM JDBC reference
• docs/CAPTURES/ — annotated socat hex-dump captures

Test coverage

232 tests total: 69 unit + 163 integration. Unit tests run with no external dependencies; integration tests run against the IBM Informix Developer Edition Docker image.

Known gaps (deferred)

• Full ROW/COLLECTION recursive parsing: Phase 12 ships type recognition + raw-bytes wrapper. Parsing the textual representation into typed Python tuples/sets/lists is deferred — most workloads can use SQL projections (SELECT row_col.fieldname FROM tbl) instead.
• UDT parameter encoding for fast-path: scalar params/returns work; passing a 72-byte BLOB locator as a UDT param requires extending the SQ_BIND encoder with the extended_owner/extended_name preamble for type > 18.
• Native async I/O: Phase 16 ships a thread-pool wrapper that's functionally equivalent for typical FastAPI workloads. Native async (asyncpg-style transport abstraction) would be Phase 17 if a real workload needs it.

2026.05.02 — Phase 1: connection lifecycle

Initial release. connect() / close() works end-to-end. Cursor / execute / fetch arrived in Phase 2 (subsequent commits within the same session).