add line counter tool and update README with code stats

https://claude.ai/code/session_01Gt1RfK8m2hxciLMMMYG8xg

README.md

@@ -1 +1,26 @@
 # dotfiles
+
+<!-- LINE-COUNT-START -->
+This repo has **20,055** lines of technical debt.
+
+| File Type | Lines | Percentage |
+|-----------|------:|-----------:|
+| .py | 11,441 | 57.0% |
+| .nix | 4,471 | 22.3% |
+| .yaml | 1,121 | 5.6% |
+| .html | 1,009 | 5.0% |
+| .json | 555 | 2.8% |
+| .yml | 479 | 2.4% |
+| .toml | 290 | 1.4% |
+| .css | 212 | 1.1% |
+| .gitignore | 199 | 1.0% |
+| .md | 75 | 0.4% |
+| .cfg | 73 | 0.4% |
+| .sh | 48 | 0.2% |
+| .mako | 36 | 0.2% |
+| .LICENSE | 21 | 0.1% |
+| .conf | 17 | 0.1% |
+| .Gemfile | 4 | 0.0% |
+| .svg | 3 | 0.0% |
+| .new | 1 | 0.0% |
+<!-- LINE-COUNT-END -->

overlays/default.nix

@@ -21,12 +21,10 @@
         alembic
         apprise
         apscheduler
-        confluent-kafka
         fastapi
         fastapi-cli
         httpx
         mypy
-        orjson
         polars
         psycopg
         pydantic

python/alembic/data_science_dev/versions/2026_03_24-adding_failedingestion_2f43120e3ffc.py

@@ -1,50 +0,0 @@
-"""adding FailedIngestion.
-
-Revision ID: 2f43120e3ffc
-Revises: f99be864fe69
-Create Date: 2026-03-24 23:46:17.277897
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-import sqlalchemy as sa
-from alembic import op
-
-from python.orm import DataScienceDevBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "2f43120e3ffc"
-down_revision: str | None = "f99be864fe69"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = DataScienceDevBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table(
-        "failed_ingestion",
-        sa.Column("raw_line", sa.Text(), nullable=False),
-        sa.Column("error", sa.Text(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_failed_ingestion")),
-        schema=schema,
-    )
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_table("failed_ingestion", schema=schema)
-    # ### end Alembic commands ###

python/alembic/data_science_dev/versions/2026_03_25-attach_partitions_to_posts.py

@@ -1,80 +0,0 @@
-"""Attach all partition tables to the posts parent table.
-
-Alembic autogenerate creates partition tables as standalone tables but does not
-emit the ALTER TABLE ... ATTACH PARTITION statements needed for PostgreSQL to
-route inserts to the correct partition.
-
-Revision ID: a1b2c3d4e5f6
-Revises: 605b1794838f
-Create Date: 2026-03-25 10:00:00.000000
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-from alembic import op
-from sqlalchemy import text
-
-from python.orm import DataScienceDevBase
-from python.orm.data_science_dev.posts.partitions import (
-    PARTITION_END_YEAR,
-    PARTITION_START_YEAR,
-    iso_weeks_in_year,
-    week_bounds,
-)
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "a1b2c3d4e5f6"
-down_revision: str | None = "605b1794838f"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = DataScienceDevBase.schema_name
-
-ALREADY_ATTACHED_QUERY = text("""
-    SELECT inhrelid::regclass::text
-    FROM pg_inherits
-    WHERE inhparent = :parent::regclass
-""")
-
-
-def upgrade() -> None:
-    """Attach all weekly partition tables to the posts parent table."""
-    connection = op.get_bind()
-    already_attached = {
-        row[0]
-        for row in connection.execute(
-            ALREADY_ATTACHED_QUERY, {"parent": f"{schema}.posts"}
-        )
-    }
-
-    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
-        for week in range(1, iso_weeks_in_year(year) + 1):
-            table_name = f"posts_{year}_{week:02d}"
-            qualified_name = f"{schema}.{table_name}"
-            if qualified_name in already_attached:
-                continue
-            start, end = week_bounds(year, week)
-            start_str = start.strftime("%Y-%m-%d %H:%M:%S")
-            end_str = end.strftime("%Y-%m-%d %H:%M:%S")
-            op.execute(
-                f"ALTER TABLE {schema}.posts "
-                f"ATTACH PARTITION {qualified_name} "
-                f"FOR VALUES FROM ('{start_str}') TO ('{end_str}')"
-            )
-
-
-def downgrade() -> None:
-    """Detach all weekly partition tables from the posts parent table."""
-    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
-        for week in range(1, iso_weeks_in_year(year) + 1):
-            table_name = f"posts_{year}_{week:02d}"
-            op.execute(
-                f"ALTER TABLE {schema}.posts "
-                f"DETACH PARTITION {schema}.{table_name}"
-            )

python/alembic/env.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import logging
-import re
 import sys
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Literal
@@ -82,7 +81,6 @@ def include_name(
 
     """
     if type_ == "schema":
-        # allows a database with multiple schemas to have separate alembic revisions
         return name == target_metadata.schema
     return True
 

python/data_science/__init__.py

@@ -1,3 +0,0 @@
-"""Data science CLI tools."""
-
-from __future__ import annotations

python/data_science/bluesky_ids.py

@@ -1,104 +0,0 @@
-"""Utilities for converting Bluesky identifiers to numeric database IDs.
-
-Handles DID-to-user_id hashing, TID-to-post_id decoding, and AT-URI parsing.
-"""
-
-from __future__ import annotations
-
-import hashlib
-
-TID_CHARSET = "234567abcdefghijklmnopqrstuvwxyz"
-_TID_LENGTH = 13
-_BIGINT_MASK = 0x7FFFFFFFFFFFFFFF
-_AT_URI_SEGMENT_COUNT = 3
-
-
-def did_to_user_id(did: str) -> int:
-    """Convert a DID string to a deterministic 63-bit integer for user_id.
-
-    Uses SHA-256, truncated to 63 bits (positive signed BigInteger range).
-    Collision probability is negligible at Bluesky's scale (~tens of millions of users).
-
-    Args:
-        did: A Bluesky DID string, e.g. "did:plc:abc123".
-
-    Returns:
-        A positive 63-bit integer suitable for BigInteger storage.
-    """
-    digest = hashlib.sha256(did.encode()).digest()
-    return int.from_bytes(digest[:8], "big") & _BIGINT_MASK
-
-
-def tid_to_integer(tid: str) -> int:
-    """Decode a Bluesky TID (base32-sortbase) into a 64-bit integer for post_id.
-
-    TIDs are 13-character, base32-sortbase encoded identifiers that encode a
-    microsecond timestamp plus a clock ID. They are globally unique by construction.
-
-    Args:
-        tid: A 13-character TID string, e.g. "3abc2defghijk".
-
-    Returns:
-        A positive integer suitable for BigInteger storage.
-
-    Raises:
-        ValueError: If the TID is malformed (wrong length or invalid characters).
-    """
-    if len(tid) != _TID_LENGTH:
-        message = f"TID must be {_TID_LENGTH} characters, got {len(tid)}: {tid!r}"
-        raise ValueError(message)
-
-    result = 0
-    for char in tid:
-        index = TID_CHARSET.find(char)
-        if index == -1:
-            message = f"Invalid character {char!r} in TID {tid!r}"
-            raise ValueError(message)
-        result = result * 32 + index
-    return result
-
-
-def parse_at_uri(uri: str) -> tuple[str, str, str]:
-    """Parse an AT-URI into its components.
-
-    Args:
-        uri: An AT-URI string, e.g. "at://did:plc:abc123/app.bsky.feed.post/3abc2defghijk".
-
-    Returns:
-        A tuple of (did, collection, rkey).
-
-    Raises:
-        ValueError: If the URI doesn't have the expected format.
-    """
-    stripped = uri.removeprefix("at://")
-    parts = stripped.split("/", maxsplit=2)
-    if len(parts) != _AT_URI_SEGMENT_COUNT:
-        message = f"Expected {_AT_URI_SEGMENT_COUNT} path segments in AT-URI, got {len(parts)}: {uri!r}"
-        raise ValueError(message)
-    return parts[0], parts[1], parts[2]
-
-
-def post_id_from_uri(uri: str) -> int:
-    """Extract and decode the post_id (TID) from an AT-URI.
-
-    Args:
-        uri: An AT-URI pointing to a post.
-
-    Returns:
-        The post_id as an integer.
-    """
-    _did, _collection, rkey = parse_at_uri(uri)
-    return tid_to_integer(rkey)
-
-
-def user_id_from_uri(uri: str) -> int:
-    """Extract and hash the user_id (DID) from an AT-URI.
-
-    Args:
-        uri: An AT-URI pointing to a post.
-
-    Returns:
-        The user_id as an integer.
-    """
-    did, _collection, _rkey = parse_at_uri(uri)
-    return did_to_user_id(did)

python/data_science/bluesky_transform.py

@@ -1,143 +0,0 @@
-"""Transform Bluesky Jetstream messages into rows matching the Posts table schema."""
-
-from __future__ import annotations
-
-import json
-import logging
-from datetime import datetime
-
-from python.data_science.bluesky_ids import (
-    did_to_user_id,
-    post_id_from_uri,
-    tid_to_integer,
-    user_id_from_uri,
-)
-
-logger = logging.getLogger(__name__)
-
-INSTANCE = "bsky"
-POST_COLLECTION = "app.bsky.feed.post"
-EMBED_RECORD_TYPE = "app.bsky.embed.record"
-EMBED_RECORD_WITH_MEDIA_TYPE = "app.bsky.embed.recordWithMedia"
-
-
-def transform_jetstream_post(message: dict) -> dict:
-    """Transform a Jetstream commit message into a dict matching Posts table columns.
-
-    Expects a Jetstream message with kind=commit, operation=create,
-    collection=app.bsky.feed.post.
-
-    Args:
-        message: The full Jetstream JSON message.
-
-    Returns:
-        A dict with keys matching the Posts table columns.
-    """
-    did = message["did"]
-    commit = message["commit"]
-    record = commit["record"]
-
-    row: dict = {
-        "post_id": tid_to_integer(commit["rkey"]),
-        "user_id": did_to_user_id(did),
-        "instance": INSTANCE,
-        "date": datetime.fromisoformat(record["createdAt"]),
-        "text": record.get("text", ""),
-        "langs": _extract_langs(record),
-        "like_count": 0,
-        "reply_count": 0,
-        "repost_count": 0,
-        "reply_to": None,
-        "replied_author": None,
-        "thread_root": None,
-        "thread_root_author": None,
-        "repost_from": None,
-        "reposted_author": None,
-        "quotes": None,
-        "quoted_author": None,
-        "labels": _extract_labels(record),
-        "sent_label": None,
-        "sent_score": None,
-    }
-
-    _extract_reply_refs(record, row)
-    _extract_quote_refs(record, row)
-
-    return row
-
-
-def is_post_create(message: dict) -> bool:
-    """Check if a Jetstream message is a post creation event.
-
-    Args:
-        message: The full Jetstream JSON message.
-
-    Returns:
-        True if this is a create commit for app.bsky.feed.post.
-    """
-    if message.get("kind") != "commit":
-        return False
-    commit = message.get("commit", {})
-    return commit.get("operation") == "create" and commit.get("collection") == POST_COLLECTION
-
-
-def _extract_langs(record: dict) -> str | None:
-    """Extract langs array as a JSON string, or None if absent."""
-    langs = record.get("langs")
-    if langs is None:
-        return None
-    return json.dumps(langs)
-
-
-def _extract_labels(record: dict) -> str | None:
-    """Extract self-labels as a JSON string, or None if absent."""
-    labels_obj = record.get("labels")
-    if labels_obj is None:
-        return None
-    values = labels_obj.get("values", [])
-    if not values:
-        return None
-    label_strings = [label.get("val", "") for label in values]
-    return json.dumps(label_strings)
-
-
-def _extract_reply_refs(record: dict, row: dict) -> None:
-    """Populate reply_to, replied_author, thread_root, thread_root_author from record.reply."""
-    reply = record.get("reply")
-    if reply is None:
-        return
-
-    parent = reply.get("parent", {})
-    parent_uri = parent.get("uri")
-    if parent_uri:
-        row["reply_to"] = post_id_from_uri(parent_uri)
-        row["replied_author"] = user_id_from_uri(parent_uri)
-
-    root = reply.get("root", {})
-    root_uri = root.get("uri")
-    if root_uri:
-        row["thread_root"] = post_id_from_uri(root_uri)
-        row["thread_root_author"] = user_id_from_uri(root_uri)
-
-
-def _extract_quote_refs(record: dict, row: dict) -> None:
-    """Populate quotes and quoted_author from embed record references."""
-    embed = record.get("embed")
-    if embed is None:
-        return
-
-    embed_type = embed.get("$type", "")
-
-    if embed_type == EMBED_RECORD_TYPE:
-        _set_quote_from_record(embed.get("record", {}), row)
-    elif embed_type == EMBED_RECORD_WITH_MEDIA_TYPE:
-        inner_record = embed.get("record", {}).get("record", {})
-        _set_quote_from_record(inner_record, row)
-
-
-def _set_quote_from_record(record_ref: dict, row: dict) -> None:
-    """Set quotes and quoted_author from a record reference object."""
-    uri = record_ref.get("uri")
-    if uri and POST_COLLECTION in uri:
-        row["quotes"] = post_id_from_uri(uri)
-        row["quoted_author"] = user_id_from_uri(uri)

python/data_science/firehose_consumer.py

@@ -1,203 +0,0 @@
-"""Kafka consumer that ingests Bluesky posts into the partitioned Posts table.
-
-Consumes Jetstream messages from Kafka, transforms them into Posts rows,
-and batch-inserts them into PostgreSQL with manual offset commits.
-
-Usage:
-    firehose-consumer
-    firehose-consumer --kafka-servers kafka:9092 --batch-size 500
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import signal
-from os import getenv
-from threading import Event
-from typing import Annotated
-
-import typer
-from confluent_kafka import Consumer, KafkaError, KafkaException
-from sqlalchemy.orm import Session
-
-from python.data_science.bluesky_transform import is_post_create, transform_jetstream_post
-from python.data_science.ingest_posts import ingest_batch
-from python.orm.common import get_postgres_engine
-from python.orm.data_science_dev.posts.failed_ingestion import FailedIngestion
-
-logger = logging.getLogger(__name__)
-
-DEFAULT_TOPIC = "bluesky.firehose.posts"
-DEFAULT_KAFKA_SERVERS = "localhost:9092"
-DEFAULT_GROUP_ID = "bluesky-posts-ingestor"
-DEFAULT_BATCH_SIZE = 500
-POLL_TIMEOUT_SECONDS = 5.0
-
-shutdown_event = Event()
-
-app = typer.Typer(help="Consume Bluesky posts from Kafka and ingest into PostgreSQL.")
-
-
-@app.command()
-def main(
-    kafka_servers: Annotated[str, typer.Option(help="Kafka bootstrap servers")] = "",
-    topic: Annotated[str, typer.Option(help="Kafka topic to consume from")] = "",
-    group_id: Annotated[str, typer.Option(help="Kafka consumer group ID")] = "",
-    batch_size: Annotated[int, typer.Option(help="Messages per DB insert batch")] = DEFAULT_BATCH_SIZE,
-) -> None:
-    """Consume Bluesky posts from Kafka and ingest into the partitioned posts table."""
-    logging.basicConfig(
-        level=logging.INFO,
-        format="%(asctime)s %(levelname)s %(message)s",
-        datefmt="%H:%M:%S",
-    )
-
-    servers = kafka_servers or getenv("KAFKA_BOOTSTRAP_SERVERS", DEFAULT_KAFKA_SERVERS)
-    topic_name = topic or getenv("BLUESKY_FIREHOSE_TOPIC", DEFAULT_TOPIC)
-    group = group_id or getenv("KAFKA_GROUP_ID", DEFAULT_GROUP_ID)
-
-    signal.signal(signal.SIGTERM, _handle_shutdown)
-    signal.signal(signal.SIGINT, _handle_shutdown)
-
-    consumer = _create_consumer(servers, group)
-    consumer.subscribe([topic_name])
-
-    engine = get_postgres_engine(name="DATA_SCIENCE_DEV")
-    total_inserted = 0
-
-    logger.info("Starting firehose consumer: topic=%s group=%s batch_size=%d", topic_name, group, batch_size)
-
-    try:
-        with Session(engine) as session:
-            while not shutdown_event.is_set():
-                inserted = _consume_batch(consumer, session, batch_size)
-                total_inserted += inserted
-                if inserted > 0:
-                    logger.info("Batch inserted %d rows (total: %d)", inserted, total_inserted)
-    except KafkaException:
-        logger.exception("Fatal Kafka error")
-    finally:
-        logger.info("Closing consumer (total inserted: %d)", total_inserted)
-        consumer.close()
-
-
-def _consume_batch(consumer: Consumer, session: Session, batch_size: int) -> int:
-    """Poll a batch of messages, transform, and insert into the database.
-
-    Args:
-        consumer: The Kafka consumer instance.
-        session: SQLAlchemy database session.
-        batch_size: Maximum number of messages to consume per batch.
-
-    Returns:
-        Number of rows successfully inserted.
-    """
-    messages = consumer.consume(num_messages=batch_size, timeout=POLL_TIMEOUT_SECONDS)
-    if not messages:
-        return 0
-
-    rows: list[dict] = []
-    for message in messages:
-        error = message.error()
-        if error is not None:
-            if error.code() == KafkaError._PARTITION_EOF:  # noqa: SLF001 — confluent-kafka exposes this as a pseudo-private constant; no public alternative exists
-                continue
-            logger.error("Consumer error: %s", error)
-            continue
-
-        row = _safe_transform(message.value(), session)
-        if row is not None:
-            rows.append(row)
-
-    if not rows:
-        consumer.commit(asynchronous=False)
-        return 0
-
-    inserted = ingest_batch(session, rows)
-    consumer.commit(asynchronous=False)
-    return inserted
-
-
-def _safe_transform(raw_value: bytes | None, session: Session) -> dict | None:
-    """Transform a Kafka message value into a Posts row, logging failures.
-
-    Args:
-        raw_value: Raw message bytes from Kafka.
-        session: SQLAlchemy session for logging failures.
-
-    Returns:
-        A transformed row dict, or None if transformation failed.
-    """
-    if raw_value is None:
-        return None
-
-    try:
-        message = json.loads(raw_value)
-    except (json.JSONDecodeError, UnicodeDecodeError):
-        logger.exception("Failed to decode Kafka message")
-        _log_failed_ingestion(session, raw_value, "JSON decode error")
-        return None
-
-    if not is_post_create(message):
-        return None
-
-    try:
-        return transform_jetstream_post(message)
-    except (KeyError, ValueError, TypeError):
-        logger.exception("Failed to transform Jetstream message")
-        _log_failed_ingestion(session, raw_value, "Transform error")
-        return None
-
-
-def _log_failed_ingestion(session: Session, raw_value: bytes, error: str) -> None:
-    """Log a failed ingestion to the FailedIngestion table.
-
-    Args:
-        session: SQLAlchemy session.
-        raw_value: The raw message bytes.
-        error: Description of the error.
-    """
-    try:
-        session.add(
-            FailedIngestion(
-                raw_line=raw_value.decode(errors="replace")[:10000],
-                error=error,
-            )
-        )
-        session.commit()
-    except Exception:
-        session.rollback()
-        logger.exception("Failed to log ingestion failure")
-
-
-def _create_consumer(servers: str, group: str) -> Consumer:
-    """Create a configured Kafka consumer.
-
-    Args:
-        servers: Kafka bootstrap servers string.
-        group: Consumer group ID.
-
-    Returns:
-        A configured confluent_kafka.Consumer.
-    """
-    config = {
-        "bootstrap.servers": servers,
-        "group.id": group,
-        "auto.offset.reset": "earliest",
-        "enable.auto.commit": False,
-        "max.poll.interval.ms": 300000,
-        "fetch.min.bytes": 1024,
-        "session.timeout.ms": 30000,
-    }
-    return Consumer(config)
-
-
-def _handle_shutdown(_signum: int, _frame: object) -> None:
-    """Signal handler to trigger graceful shutdown."""
-    logger.info("Shutdown signal received")
-    shutdown_event.set()
-
-
-if __name__ == "__main__":
-    app()

python/data_science/firehose_producer.py

@@ -1,230 +0,0 @@
-"""Bluesky Jetstream firehose to Kafka producer.
-
-Connects to the Bluesky Jetstream WebSocket API with zstd compression,
-filters for post creation events, and produces them to a Kafka topic.
-
-Usage:
-    firehose-producer
-    firehose-producer --kafka-servers kafka:9092 --topic bluesky.firehose.posts
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import signal
-from os import getenv
-from threading import Event
-from typing import Annotated
-
-import typer
-from compression import zstd
-from confluent_kafka import KafkaError, KafkaException, Producer
-from websockets.exceptions import ConnectionClosed
-from websockets.sync.client import connect
-
-logger = logging.getLogger(__name__)
-
-JETSTREAM_URL = "wss://jetstream2.us-east.bsky.network/subscribe"
-DEFAULT_TOPIC = "bluesky.firehose.posts"
-DEFAULT_KAFKA_SERVERS = "localhost:9092"
-POLL_INTERVAL = 100
-POST_COLLECTION = "app.bsky.feed.post"
-
-shutdown_event = Event()
-
-app = typer.Typer(help="Stream Bluesky firehose posts into Kafka.")
-
-
-@app.command()
-def main(
-    kafka_servers: Annotated[str, typer.Option(help="Kafka bootstrap servers")] = "",
-    topic: Annotated[str, typer.Option(help="Kafka topic to produce to")] = "",
-    collections: Annotated[str, typer.Option(help="Comma-separated collections to subscribe to")] = POST_COLLECTION,
-) -> None:
-    """Connect to Bluesky Jetstream and produce post events to Kafka."""
-    logging.basicConfig(
-        level=logging.INFO,
-        format="%(asctime)s %(levelname)s %(message)s",
-        datefmt="%H:%M:%S",
-    )
-
-    servers = kafka_servers or getenv("KAFKA_BOOTSTRAP_SERVERS", DEFAULT_KAFKA_SERVERS)
-    topic_name = topic or getenv("BLUESKY_FIREHOSE_TOPIC", DEFAULT_TOPIC)
-
-    signal.signal(signal.SIGTERM, _handle_shutdown)
-    signal.signal(signal.SIGINT, _handle_shutdown)
-
-    producer = _create_producer(servers)
-    cursor: int | None = None
-
-    logger.info("Starting firehose producer → %s on %s", topic_name, servers)
-
-    while not shutdown_event.is_set():
-        try:
-            cursor = _stream_loop(producer, topic_name, collections, cursor)
-        except (ConnectionClosed, OSError):
-            logger.exception("WebSocket disconnected, reconnecting")
-        except KafkaException:
-            logger.exception("Kafka error, reconnecting")
-
-        if not shutdown_event.is_set():
-            logger.info("Reconnecting in 5 seconds (cursor=%s)", cursor)
-            shutdown_event.wait(timeout=5)
-
-    logger.info("Shutting down, flushing producer")
-    producer.flush(timeout=30)
-    logger.info("Producer shutdown complete")
-
-
-def _stream_loop(
-    producer: Producer,
-    topic: str,
-    collections: str,
-    cursor: int | None,
-) -> int | None:
-    """Connect to Jetstream and stream messages to Kafka until disconnected.
-
-    Args:
-        producer: The Kafka producer instance.
-        topic: Kafka topic name.
-        collections: Comma-separated AT Protocol collections to subscribe to.
-        cursor: Optional microsecond timestamp to resume from.
-
-    Returns:
-        The last processed time_us cursor value.
-    """
-    url = _build_jetstream_url(collections, cursor)
-    logger.info("Connecting to %s", url)
-
-    message_count = 0
-    last_cursor = cursor
-
-    with connect(url, additional_headers={"Accept-Encoding": "zstd"}) as websocket:
-        logger.info("Connected to Jetstream")
-
-        while not shutdown_event.is_set():
-            try:
-                raw_frame = websocket.recv(timeout=10)
-            except TimeoutError:
-                producer.poll(0)
-                continue
-
-            text = _decode_frame(raw_frame)
-            message = json.loads(text)
-
-            time_us = message.get("time_us")
-            if time_us is not None:
-                last_cursor = time_us
-
-            if not _is_post_create(message):
-                continue
-
-            did = message.get("did", "")
-
-            try:
-                producer.produce(
-                    topic,
-                    key=did.encode(),
-                    value=text.encode() if isinstance(text, str) else text,
-                    callback=_delivery_callback,
-                )
-            except BufferError:
-                logger.warning("Producer buffer full, flushing")
-                producer.flush(timeout=10)
-                producer.produce(
-                    topic,
-                    key=did.encode(),
-                    value=text.encode() if isinstance(text, str) else text,
-                    callback=_delivery_callback,
-                )
-
-            message_count += 1
-            if message_count % POLL_INTERVAL == 0:
-                producer.poll(0)
-
-            if message_count % 10000 == 0:
-                logger.info("Produced %d messages (cursor=%s)", message_count, last_cursor)
-
-    return last_cursor
-
-
-def _build_jetstream_url(collections: str, cursor: int | None) -> str:
-    """Build the Jetstream WebSocket URL with query parameters.
-
-    Args:
-        collections: Comma-separated collection names.
-        cursor: Optional microsecond timestamp for resumption.
-
-    Returns:
-        The full WebSocket URL.
-    """
-    params = ["compress=true"]
-    for raw_collection in collections.split(","):
-        cleaned = raw_collection.strip()
-        if cleaned:
-            params.append(f"wantedCollections={cleaned}")
-    if cursor is not None:
-        params.append(f"cursor={cursor}")
-    return f"{JETSTREAM_URL}?{'&'.join(params)}"
-
-
-def _decode_frame(frame: str | bytes) -> str:
-    """Decode a WebSocket frame, decompressing zstd if binary.
-
-    Jetstream with compress=true sends zstd-compressed binary frames.
-
-    Args:
-        frame: Raw WebSocket frame data.
-
-    Returns:
-        The decoded JSON string.
-    """
-    if isinstance(frame, bytes):
-        return zstd.decompress(frame).decode()
-    return frame
-
-
-def _is_post_create(message: dict) -> bool:
-    """Check if a Jetstream message is a post creation commit."""
-    if message.get("kind") != "commit":
-        return False
-    commit = message.get("commit", {})
-    return commit.get("operation") == "create" and commit.get("collection") == POST_COLLECTION
-
-
-def _create_producer(servers: str) -> Producer:
-    """Create a configured Kafka producer.
-
-    Args:
-        servers: Kafka bootstrap servers string.
-
-    Returns:
-        A configured confluent_kafka.Producer.
-    """
-    config = {
-        "bootstrap.servers": servers,
-        "linger.ms": 50,
-        "batch.size": 65536,
-        "compression.type": "zstd",
-        "acks": "all",
-        "retries": 5,
-        "retry.backoff.ms": 500,
-    }
-    return Producer(config)
-
-
-def _delivery_callback(error: KafkaError | None, _message: object) -> None:
-    """Log delivery failures from the Kafka producer."""
-    if error is not None:
-        logger.error("Kafka delivery failed: %s", error)
-
-
-def _handle_shutdown(_signum: int, _frame: object) -> None:
-    """Signal handler to trigger graceful shutdown."""
-    logger.info("Shutdown signal received")
-    shutdown_event.set()
-
-
-if __name__ == "__main__":
-    app()

python/data_science/ingest_posts.py

@@ -1,247 +0,0 @@
-"""Ingestion pipeline for loading JSONL post files into the weekly-partitioned posts table.
-
-Usage:
-    ingest-posts /path/to/files/
-    ingest-posts /path/to/single_file.jsonl
-    ingest-posts /data/dir/ --workers 4 --batch-size 5000
-"""
-
-from __future__ import annotations
-
-import logging
-from datetime import UTC, datetime
-from pathlib import Path  # noqa: TC003 this is needed for typer
-from typing import TYPE_CHECKING, Annotated
-
-import orjson
-import psycopg
-import typer
-
-from python.common import configure_logger
-from python.orm.common import get_connection_info
-from python.parallelize import parallelize_process
-
-if TYPE_CHECKING:
-    from collections.abc import Iterator
-
-logger = logging.getLogger(__name__)
-
-
-app = typer.Typer(help="Ingest JSONL post files into the partitioned posts table.")
-
-
-@app.command()
-def main(
-    path: Annotated[Path, typer.Argument(help="Directory containing JSONL files, or a single JSONL file")],
-    batch_size: Annotated[int, typer.Option(help="Rows per INSERT batch")] = 10000,
-    workers: Annotated[int, typer.Option(help="Parallel workers for multi-file ingestion")] = 4,
-    pattern: Annotated[str, typer.Option(help="Glob pattern for JSONL files")] = "*.jsonl",
-) -> None:
-    """Ingest JSONL post files into the weekly-partitioned posts table."""
-    configure_logger(level="INFO")
-
-    logger.info("starting ingest-posts")
-    logger.info("path=%s batch_size=%d workers=%d pattern=%s", path, batch_size, workers, pattern)
-    if path.is_file():
-        ingest_file(path, batch_size=batch_size)
-    elif path.is_dir():
-        ingest_directory(path, batch_size=batch_size, max_workers=workers, pattern=pattern)
-    else:
-        typer.echo(f"Path does not exist: {path}", err=True)
-        raise typer.Exit(code=1)
-
-    logger.info("ingest-posts done")
-
-
-def ingest_directory(
-    directory: Path,
-    *,
-    batch_size: int,
-    max_workers: int,
-    pattern: str = "*.jsonl",
-) -> None:
-    """Ingest all JSONL files in a directory using parallel workers."""
-    files = sorted(directory.glob(pattern))
-    if not files:
-        logger.warning("No JSONL files found in %s", directory)
-        return
-
-    logger.info("Found %d JSONL files to ingest", len(files))
-
-    kwargs_list = [{"path": fp, "batch_size": batch_size} for fp in files]
-    parallelize_process(ingest_file, kwargs_list, max_workers=max_workers)
-
-
-SCHEMA = "main"
-
-COLUMNS = (
-    "post_id",
-    "user_id",
-    "instance",
-    "date",
-    "text",
-    "langs",
-    "like_count",
-    "reply_count",
-    "repost_count",
-    "reply_to",
-    "replied_author",
-    "thread_root",
-    "thread_root_author",
-    "repost_from",
-    "reposted_author",
-    "quotes",
-    "quoted_author",
-    "labels",
-    "sent_label",
-    "sent_score",
-)
-
-INSERT_FROM_STAGING = f"""
-    INSERT INTO {SCHEMA}.posts ({", ".join(COLUMNS)})
-    SELECT {", ".join(COLUMNS)} FROM pg_temp.staging
-    ON CONFLICT (post_id, date) DO NOTHING
-"""  # noqa: S608
-
-FAILED_INSERT = f"""
-    INSERT INTO {SCHEMA}.failed_ingestion (raw_line, error)
-    VALUES (%(raw_line)s, %(error)s)
-"""  # noqa: S608
-
-
-def get_psycopg_connection() -> psycopg.Connection:
-    """Create a raw psycopg3 connection from environment variables."""
-    database, host, port, username, password = get_connection_info("DATA_SCIENCE_DEV")
-    return psycopg.connect(
-        dbname=database,
-        host=host,
-        port=int(port),
-        user=username,
-        password=password,
-        autocommit=False,
-    )
-
-
-def ingest_file(path: Path, *, batch_size: int) -> None:
-    """Ingest a single JSONL file into the posts table."""
-    log_trigger = max(100_000 // batch_size, 1)
-    failed_lines: list[dict] = []
-    try:
-        with get_psycopg_connection() as connection:
-            for index, batch in enumerate(read_jsonl_batches(path, batch_size, failed_lines), 1):
-                ingest_batch(connection, batch)
-                if index % log_trigger == 0:
-                    logger.info("Ingested %d batches (%d rows) from %s", index, index * batch_size, path)
-
-            if failed_lines:
-                logger.warning("Recording %d malformed lines from %s", len(failed_lines), path.name)
-                with connection.cursor() as cursor:
-                    cursor.executemany(FAILED_INSERT, failed_lines)
-                connection.commit()
-    except Exception:
-        logger.exception("Failed to ingest file: %s", path)
-        raise
-
-
-def ingest_batch(connection: psycopg.Connection, batch: list[dict]) -> None:
-    """COPY batch into a temp staging table, then INSERT ... ON CONFLICT into posts."""
-    if not batch:
-        return
-
-    try:
-        with connection.cursor() as cursor:
-            cursor.execute(f"""
-                CREATE TEMP TABLE IF NOT EXISTS staging
-                (LIKE {SCHEMA}.posts INCLUDING DEFAULTS)
-                ON COMMIT DELETE ROWS
-            """)
-            cursor.execute("TRUNCATE pg_temp.staging")
-
-            with cursor.copy(f"COPY pg_temp.staging ({', '.join(COLUMNS)}) FROM STDIN") as copy:
-                for row in batch:
-                    copy.write_row(tuple(row.get(column) for column in COLUMNS))
-
-            cursor.execute(INSERT_FROM_STAGING)
-        connection.commit()
-    except Exception as error:
-        connection.rollback()
-
-        if len(batch) == 1:
-            logger.exception("Skipping bad row post_id=%s", batch[0].get("post_id"))
-            with connection.cursor() as cursor:
-                cursor.execute(
-                    FAILED_INSERT,
-                    {
-                        "raw_line": orjson.dumps(batch[0], default=str).decode(),
-                        "error": str(error),
-                    },
-                )
-            connection.commit()
-            return
-
-        midpoint = len(batch) // 2
-        ingest_batch(connection, batch[:midpoint])
-        ingest_batch(connection, batch[midpoint:])
-
-
-def read_jsonl_batches(file_path: Path, batch_size: int, failed_lines: list[dict]) -> Iterator[list[dict]]:
-    """Stream a JSONL file and yield batches of transformed rows."""
-    batch: list[dict] = []
-    with file_path.open("r", encoding="utf-8") as handle:
-        for raw_line in handle:
-            line = raw_line.strip()
-            if not line:
-                continue
-            batch.extend(parse_line(line, file_path, failed_lines))
-            if len(batch) >= batch_size:
-                yield batch
-                batch = []
-    if batch:
-        yield batch
-
-
-def parse_line(line: str, file_path: Path, failed_lines: list[dict]) -> Iterator[dict]:
-    """Parse a JSONL line, handling concatenated JSON objects."""
-    try:
-        yield transform_row(orjson.loads(line))
-    except orjson.JSONDecodeError:
-        if "}{" not in line:
-            logger.warning("Skipping malformed line in %s: %s", file_path.name, line[:120])
-            failed_lines.append({"raw_line": line, "error": "malformed JSON"})
-            return
-        fragments = line.replace("}{", "}\n{").split("\n")
-        for fragment in fragments:
-            try:
-                yield transform_row(orjson.loads(fragment))
-            except (orjson.JSONDecodeError, KeyError, ValueError) as error:
-                logger.warning("Skipping malformed fragment in %s: %s", file_path.name, fragment[:120])
-                failed_lines.append({"raw_line": fragment, "error": str(error)})
-    except Exception as error:
-        logger.exception("Skipping bad row in %s: %s", file_path.name, line[:120])
-        failed_lines.append({"raw_line": line, "error": str(error)})
-
-
-def transform_row(raw: dict) -> dict:
-    """Transform a raw JSONL row into a dict matching the Posts table columns."""
-    raw["date"] = parse_date(raw["date"])
-    if raw.get("langs") is not None:
-        raw["langs"] = orjson.dumps(raw["langs"])
-    if raw.get("text") is not None:
-        raw["text"] = raw["text"].replace("\x00", "")
-    return raw
-
-
-def parse_date(raw_date: int) -> datetime:
-    """Parse compact YYYYMMDDHHmm integer into a naive datetime (input is UTC by spec)."""
-    return datetime(
-        raw_date // 100000000,
-        (raw_date // 1000000) % 100,
-        (raw_date // 10000) % 100,
-        (raw_date // 100) % 100,
-        raw_date % 100,
-        tzinfo=UTC,
-    )
-
-
-if __name__ == "__main__":
-    app()

python/database_cli.py

@@ -90,13 +90,6 @@ DATABASES: dict[str, DatabaseConfig] = {
         base_class_name="SignalBotBase",
         models_module="python.orm.signal_bot.models",
     ),
-    "data_science_dev": DatabaseConfig(
-        env_prefix="DATA_SCIENCE_DEV",
-        version_location="python/alembic/data_science_dev/versions",
-        base_module="python.orm.data_science_dev.base",
-        base_class_name="DataScienceDevBase",
-        models_module="python.orm.data_science_dev.models",
-    ),
 }
 
 

python/orm/__init__.py

@@ -1,12 +1,10 @@
 """ORM package exports."""
 
-from python.orm.data_science_dev.base import DataScienceDevBase
 from python.orm.richie.base import RichieBase
 from python.orm.signal_bot.base import SignalBotBase
 from python.orm.van_inventory.base import VanInventoryBase
 
 __all__ = [
-    "DataScienceDevBase",
     "RichieBase",
     "SignalBotBase",
     "VanInventoryBase",

python/orm/data_science_dev/__init__.py

@@ -1,11 +0,0 @@
-"""Data science dev database ORM exports."""
-
-from __future__ import annotations
-
-from python.orm.data_science_dev.base import DataScienceDevBase, DataScienceDevTableBase, DataScienceDevTableBaseBig
-
-__all__ = [
-    "DataScienceDevBase",
-    "DataScienceDevTableBase",
-    "DataScienceDevTableBaseBig",
-]

python/orm/data_science_dev/base.py

@@ -1,52 +0,0 @@
-"""Data science dev database ORM base."""
-
-from __future__ import annotations
-
-from datetime import datetime
-
-from sqlalchemy import BigInteger, DateTime, MetaData, func
-from sqlalchemy.ext.declarative import AbstractConcreteBase
-from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
-
-from python.orm.common import NAMING_CONVENTION
-
-
-class DataScienceDevBase(DeclarativeBase):
-    """Base class for data_science_dev database ORM models."""
-
-    schema_name = "main"
-
-    metadata = MetaData(
-        schema=schema_name,
-        naming_convention=NAMING_CONVENTION,
-    )
-
-
-class _TableMixin:
-    """Shared timestamp columns for all table bases."""
-
-    created: Mapped[datetime] = mapped_column(
-        DateTime(timezone=True),
-        server_default=func.now(),
-    )
-    updated: Mapped[datetime] = mapped_column(
-        DateTime(timezone=True),
-        server_default=func.now(),
-        onupdate=func.now(),
-    )
-
-
-class DataScienceDevTableBase(_TableMixin, AbstractConcreteBase, DataScienceDevBase):
-    """Table with Integer primary key."""
-
-    __abstract__ = True
-
-    id: Mapped[int] = mapped_column(primary_key=True)
-
-
-class DataScienceDevTableBaseBig(_TableMixin, AbstractConcreteBase, DataScienceDevBase):
-    """Table with BigInteger primary key."""
-
-    __abstract__ = True
-
-    id: Mapped[int] = mapped_column(BigInteger, primary_key=True)

python/orm/data_science_dev/models.py

@@ -1,10 +0,0 @@
-"""Data science dev database ORM models."""
-
-from __future__ import annotations
-
-from python.orm.data_science_dev.posts import partitions  # noqa: F401 — registers partition classes in metadata
-from python.orm.data_science_dev.posts.tables import Posts
-
-__all__ = [
-    "Posts",
-]

python/orm/data_science_dev/posts/__init__.py

@@ -1,11 +0,0 @@
-"""Posts module — weekly-partitioned posts table and partition ORM models."""
-
-from __future__ import annotations
-
-from python.orm.data_science_dev.posts.failed_ingestion import FailedIngestion
-from python.orm.data_science_dev.posts.tables import Posts
-
-__all__ = [
-    "FailedIngestion",
-    "Posts",
-]

python/orm/data_science_dev/posts/columns.py

@@ -1,33 +0,0 @@
-"""Shared column definitions for the posts partitioned table family."""
-
-from __future__ import annotations
-
-from datetime import datetime
-
-from sqlalchemy import BigInteger, SmallInteger, Text
-from sqlalchemy.orm import Mapped, mapped_column
-
-
-class PostsColumns:
-    """Mixin providing all posts columns. Used by both the parent table and partitions."""
-
-    post_id: Mapped[int] = mapped_column(BigInteger, primary_key=True)
-    user_id: Mapped[int] = mapped_column(BigInteger)
-    instance: Mapped[str]
-    date: Mapped[datetime] = mapped_column(primary_key=True)
-    text: Mapped[str] = mapped_column(Text)
-    langs: Mapped[str | None]
-    like_count: Mapped[int]
-    reply_count: Mapped[int]
-    repost_count: Mapped[int]
-    reply_to: Mapped[int | None] = mapped_column(BigInteger)
-    replied_author: Mapped[int | None] = mapped_column(BigInteger)
-    thread_root: Mapped[int | None] = mapped_column(BigInteger)
-    thread_root_author: Mapped[int | None] = mapped_column(BigInteger)
-    repost_from: Mapped[int | None] = mapped_column(BigInteger)
-    reposted_author: Mapped[int | None] = mapped_column(BigInteger)
-    quotes: Mapped[int | None] = mapped_column(BigInteger)
-    quoted_author: Mapped[int | None] = mapped_column(BigInteger)
-    labels: Mapped[str | None]
-    sent_label: Mapped[int | None] = mapped_column(SmallInteger)
-    sent_score: Mapped[float | None]

python/orm/data_science_dev/posts/failed_ingestion.py

@@ -1,17 +0,0 @@
-"""Table for storing JSONL lines that failed during post ingestion."""
-
-from __future__ import annotations
-
-from sqlalchemy import Text
-from sqlalchemy.orm import Mapped, mapped_column
-
-from python.orm.data_science_dev.base import DataScienceDevTableBase
-
-
-class FailedIngestion(DataScienceDevTableBase):
-    """Stores raw JSONL lines and their error messages when ingestion fails."""
-
-    __tablename__ = "failed_ingestion"
-
-    raw_line: Mapped[str] = mapped_column(Text)
-    error: Mapped[str] = mapped_column(Text)

python/orm/data_science_dev/posts/partitions.py

@@ -1,71 +0,0 @@
-"""Dynamically generated ORM classes for each weekly partition of the posts table.
-
-Each class maps to a PostgreSQL partition table (e.g. posts_2024_01).
-These are real ORM models tracked by Alembic autogenerate.
-
-Uses ISO week numbering (datetime.isocalendar().week). ISO years can have
-52 or 53 weeks, and week boundaries are always Monday to Monday.
-"""
-
-from __future__ import annotations
-
-import sys
-from datetime import UTC, datetime
-
-from python.orm.data_science_dev.base import DataScienceDevBase
-from python.orm.data_science_dev.posts.columns import PostsColumns
-
-PARTITION_START_YEAR = 2023
-PARTITION_END_YEAR = 2026
-
-_current_module = sys.modules[__name__]
-
-
-def iso_weeks_in_year(year: int) -> int:
-    """Return the number of ISO weeks in a given year (52 or 53)."""
-    dec_28 = datetime(year, 12, 28, tzinfo=UTC)
-    return dec_28.isocalendar().week
-
-
-def week_bounds(year: int, week: int) -> tuple[datetime, datetime]:
-    """Return (start, end) datetimes for an ISO week.
-
-    Start = Monday 00:00:00 UTC of the given ISO week.
-    End   = Monday 00:00:00 UTC of the following ISO week.
-    """
-    start = datetime.fromisocalendar(year, week, 1).replace(tzinfo=UTC)
-    if week < iso_weeks_in_year(year):
-        end = datetime.fromisocalendar(year, week + 1, 1).replace(tzinfo=UTC)
-    else:
-        end = datetime.fromisocalendar(year + 1, 1, 1).replace(tzinfo=UTC)
-    return start, end
-
-
-def _build_partition_classes() -> dict[str, type]:
-    """Generate one ORM class per ISO week partition."""
-    classes: dict[str, type] = {}
-
-    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
-        for week in range(1, iso_weeks_in_year(year) + 1):
-            class_name = f"PostsWeek{year}W{week:02d}"
-            table_name = f"posts_{year}_{week:02d}"
-
-            partition_class = type(
-                class_name,
-                (PostsColumns, DataScienceDevBase),
-                {
-                    "__tablename__": table_name,
-                    "__table_args__": ({"implicit_returning": False},),
-                },
-            )
-
-            classes[class_name] = partition_class
-
-    return classes
-
-
-# Generate all partition classes and register them on this module
-_partition_classes = _build_partition_classes()
-for _name, _cls in _partition_classes.items():
-    setattr(_current_module, _name, _cls)
-__all__ = list(_partition_classes.keys())

python/orm/data_science_dev/posts/tables.py

@@ -1,13 +0,0 @@
-"""Posts parent table with PostgreSQL weekly range partitioning on date column."""
-
-from __future__ import annotations
-
-from python.orm.data_science_dev.base import DataScienceDevBase
-from python.orm.data_science_dev.posts.columns import PostsColumns
-
-
-class Posts(PostsColumns, DataScienceDevBase):
-    """Parent partitioned table for posts, partitioned by week on `date`."""
-
-    __tablename__ = "posts"
-    __table_args__ = ({"postgresql_partition_by": "RANGE (date)"},)

systems/jeeves/scripts/zfs.sh

@@ -15,7 +15,6 @@ sudo zpool add storage -o ashift=12 logs mirror
 sudo zpool create scratch -o ashift=12 -O acltype=posixacl -O atime=off -O dnodesize=auto -O xattr=sa -O compression=zstd -O encryption=aes-256-gcm -O keyformat=hex -O keylocation=file:///key -m /zfs/scratch
 
 # media datasets
-sudo zfs create media/temp -o sync=disabled -o redundant_metadata=none
 sudo zfs create media/secure -o encryption=aes-256-gcm -o keyformat=hex -o keylocation=file:///root/zfs.key
 sudo zfs create media/secure/docker -o compression=zstd-9
 sudo zfs create media/secure/github-runners -o compression=zstd-9 -o sync=disabled
@@ -27,7 +26,7 @@ sudo zfs create media/secure/share -o mountpoint=/zfs/media/share -o exec=off
 
 # scratch datasets
 sudo zfs create scratch/kafka -o mountpoint=/zfs/scratch/kafka -o recordsize=1M
-sudo zfs create scratch/transmission -o mountpoint=/zfs/scratch/transmission -o recordsize=16k -o sync=disabled -o redundant_metadata=none
+sudo zfs create scratch/transmission -o mountpoint=/zfs/scratch/transmission -o recordsize=16k -o sync=disabled
 
 # storage datasets
 sudo zfs create storage/ollama -o recordsize=1M -o compression=zstd-19 -o sync=disabled

systems/jeeves/services/bluesky_firehose.nix

@@ -1,96 +0,0 @@
-{
-  pkgs,
-  inputs,
-  ...
-}:
-let
-  commonEnv = {
-    PYTHONPATH = "${inputs.self}";
-    KAFKA_BOOTSTRAP_SERVERS = "localhost:9092";
-    BLUESKY_FIREHOSE_TOPIC = "bluesky.firehose.posts";
-  };
-  commonServiceConfig = {
-    Type = "simple";
-    WorkingDirectory = "${inputs.self}";
-    User = "richie";
-    Group = "users";
-    Restart = "on-failure";
-    RestartSec = "10s";
-    StandardOutput = "journal";
-    StandardError = "journal";
-    NoNewPrivileges = true;
-    ProtectSystem = "strict";
-    ProtectHome = "read-only";
-    PrivateTmp = true;
-    ReadOnlyPaths = [ "${inputs.self}" ];
-  };
-in
-{
-  systemd.services.bluesky-firehose-topic-init = {
-    description = "Create Kafka topic for Bluesky firehose";
-    after = [ "apache-kafka.service" ];
-    requires = [ "apache-kafka.service" ];
-    wantedBy = [ "multi-user.target" ];
-
-    serviceConfig = {
-      Type = "oneshot";
-      RemainAfterExit = true;
-      ExecStart = pkgs.writeShellScript "create-bluesky-topic" ''
-        ${pkgs.apacheKafka}/bin/kafka-topics.sh \
-          --bootstrap-server localhost:9092 \
-          --create \
-          --if-not-exists \
-          --topic bluesky.firehose.posts \
-          --partitions 6 \
-          --replication-factor 1
-      '';
-    };
-  };
-
-  systemd.services.bluesky-firehose-producer = {
-    description = "Bluesky Jetstream to Kafka producer";
-    after = [
-      "network.target"
-      "apache-kafka.service"
-      "bluesky-firehose-topic-init.service"
-    ];
-    requires = [
-      "apache-kafka.service"
-      "bluesky-firehose-topic-init.service"
-    ];
-    wantedBy = [ "multi-user.target" ];
-
-    environment = commonEnv;
-
-    serviceConfig = commonServiceConfig // {
-      ExecStart = "${pkgs.my_python}/bin/python -m python.data_science.firehose_producer";
-    };
-  };
-
-  systemd.services.bluesky-firehose-consumer = {
-    description = "Bluesky Kafka to PostgreSQL consumer";
-    after = [
-      "network.target"
-      "apache-kafka.service"
-      "bluesky-firehose-topic-init.service"
-      "postgresql.service"
-    ];
-    requires = [
-      "apache-kafka.service"
-      "bluesky-firehose-topic-init.service"
-      "postgresql.service"
-    ];
-    wantedBy = [ "multi-user.target" ];
-
-    environment = commonEnv // {
-      DATA_SCIENCE_DEV_DB = "data_science_dev";
-      DATA_SCIENCE_DEV_USER = "richie";
-      DATA_SCIENCE_DEV_HOST = "/run/postgresql";
-      DATA_SCIENCE_DEV_PORT = "5432";
-    };
-
-    serviceConfig = commonServiceConfig // {
-      ExecStart = "${pkgs.my_python}/bin/python -m python.data_science.firehose_consumer";
-    };
-  };
-}

systems/jeeves/services/kafka.nix

@@ -3,10 +3,17 @@ let
 in
 {
   services.apache-kafka = {
-    enable = false;
+    enable = true;
     settings = {
       listeners = [ "PLAINTEXT://localhost:9092" ];
       "log.dirs" = [ vars.kafka ];
+      "num.partitions" = 6;
+      "default.replication.factor" = 1;
+      "log.retention.hours" = 168;
+      "log.retention.bytes" = 10737418240;
+      "log.segment.bytes" = 1073741824;
+      "log.cleanup.policy" = "delete";
+      "auto.create.topics.enable" = false;
     };
   };
 }

systems/jeeves/services/postgress.nix

@@ -39,10 +39,6 @@ in
       host  postgres  math   ::1/128         trust
       host  postgres  math   192.168.90.1/24 trust
 
-      local data_science_dev  math   trust
-      host  data_science_dev  math   127.0.0.1/32    trust
-      host  data_science_dev  math   ::1/128         trust
-      host  data_science_dev  math   192.168.90.1/24 trust
     '';
 
     identMap = ''
@@ -114,7 +110,6 @@ in
       }
     ];
     ensureDatabases = [
-      "data_science_dev"
       "hass"
       "gitea"
       "math"

tools/line_counter.py

@@ -0,0 +1,86 @@
+"""Count lines of code in the repository, grouped by file type."""
+
+from __future__ import annotations
+
+import subprocess
+from collections import defaultdict
+from pathlib import Path
+
+
+def get_tracked_files() -> list[str]:
+    """Get all git-tracked files."""
+    result = subprocess.run(
+        ["git", "ls-files"],  # noqa: S603, S607
+        capture_output=True,
+        text=True,
+        check=True,
+    )
+    return [f for f in result.stdout.strip().splitlines() if f]
+
+
+def count_lines(filepath: str) -> int:
+    """Count lines in a file, returning 0 for binary files."""
+    try:
+        return len(Path(filepath).read_text(encoding="utf-8").splitlines())
+    except (UnicodeDecodeError, OSError):
+        return 0
+
+
+def count_lines_by_type() -> dict[str, int]:
+    """Count lines grouped by file extension."""
+    lines_by_type: dict[str, int] = defaultdict(int)
+    for filepath in get_tracked_files():
+        ext = Path(filepath).suffix.lstrip(".")
+        if not ext:
+            ext = Path(filepath).name
+        lines_by_type[ext] += count_lines(filepath)
+    # Exclude binary/non-code files
+    for key in ("png", "lock"):
+        lines_by_type.pop(key, None)
+    return dict(sorted(lines_by_type.items(), key=lambda x: x[1], reverse=True))
+
+
+def format_report() -> str:
+    """Generate a formatted line count report."""
+    lines_by_type = count_lines_by_type()
+    total = sum(lines_by_type.values())
+
+    lines = [
+        f"This repo has **{total:,}** lines of technical debt.",
+        "",
+        "| File Type | Lines | Percentage |",
+        "|-----------|------:|-----------:|",
+    ]
+    for ext, count in lines_by_type.items():
+        if count > 0:
+            pct = count / total * 100
+            prefix = "." if not ext.startswith(".") else ""
+            lines.append(f"| {prefix}{ext} | {count:,} | {pct:.1f}% |")
+
+    return "\n".join(lines)
+
+
+def update_readme() -> None:
+    """Update README.md with the line count report."""
+    readme_path = Path("README.md")
+    report = format_report()
+
+    start_marker = "<!-- LINE-COUNT-START -->"
+    end_marker = "<!-- LINE-COUNT-END -->"
+
+    content = readme_path.read_text(encoding="utf-8")
+
+    section = f"{start_marker}\n{report}\n{end_marker}"
+
+    if start_marker in content:
+        start = content.index(start_marker)
+        end = content.index(end_marker) + len(end_marker)
+        content = content[:start] + section + content[end:]
+    else:
+        content = content.rstrip() + "\n\n" + section + "\n"
+
+    readme_path.write_text(content, encoding="utf-8")
+
+
+if __name__ == "__main__":
+    update_readme()