delete old files

Dockerfile.code

@@ -14,8 +14,7 @@ RUN curl -LsSf https://astral.sh/uv/install.sh | sh
 WORKDIR /opt/dagster/home
 COPY requirements.txt .
 
-RUN uv pip install -r requirements.txt --system \
+RUN uv pip install -r requirements.txt --system
-    && uv pip install polars-lts-cpu --system
 
 ARG APP
 ENV APP=$APP

Dockerfile.code.playwright

@@ -1,8 +1,5 @@
 FROM mcr.microsoft.com/playwright:v1.54.0-noble
 
-ARG APP
-ENV APP=$APP
-ENV PYTHONPATH=/apps/$APP/src/:/shared/src/:$PYTHONPATH
 ENV PATH="/venv/bin:/root/.local/bin:$PATH"
 
 WORKDIR /opt/dagster/home
@@ -14,14 +11,15 @@ RUN curl -LsSf https://astral.sh/uv/install.sh | sh && \
 COPY requirements.txt .
 
 RUN . /venv/bin/activate && \
-    uv pip install -r requirements.txt && \
+    uv pip install -r requirements.txt
-    uv pip install polars-lts-cpu
 
 RUN . /venv/bin/activate && \
     uv pip install playwright && \
     playwright install
 
-
+ARG APP
+ENV APP=$APP
+ENV PYTHONPATH=/code/apps/$APP/src/:/code/shared/src/:$PYTHONPATH
 
 # Run dagster gRPC server on port 4000
 EXPOSE 4000

Dockerfile.system

@@ -15,22 +15,12 @@ ENV DAGSTER_HOME=/opt/dagster/home/
 WORKDIR $DAGSTER_HOME
 COPY dagster-requirements.txt requirements.txt
 
-RUN uv pip install -r requirements.txt --system \
+RUN uv pip install -r requirements.txt --system
-    && uv pip install polars-lts-cpu --system
 
 RUN mkdir -p $DAGSTER_HOME
 
 # Create entrypoint that renders the dagster.yaml from a template
-RUN cat << 'EOF' > /entrypoint.sh
+COPY entrypoint.sh /entrypoint.sh
-#!/bin/sh
-set -e
-
-echo "Rendering dagster.yaml from template..."
-envsubst < dagster.yaml.template > dagster.yaml
-
-echo "Starting Dagster: $@"
-exec "$@"
-EOF
 RUN chmod +x /entrypoint.sh
 ENTRYPOINT ["/entrypoint.sh"]
 

apps/other/requirements.txt

@@ -6,7 +6,7 @@ annotated-types==0.7.0
     # via pydantic
 antlr4-python3-runtime==4.13.2
     # via dagster
-anyio==4.9.0
+anyio==4.10.0
     # via
     #   gql
     #   starlette
@@ -28,7 +28,7 @@ botocore==1.40.1
     #   boto3
     #   s3fs
     #   s3transfer
-certifi==2025.7.14
+certifi==2025.8.3
     # via requests
 charset-normalizer==3.4.2
     # via requests

apps/stocks/requirements.txt

@@ -6,17 +6,13 @@ annotated-types==0.7.0
     # via pydantic
 antlr4-python3-runtime==4.13.2
     # via dagster
-anyio==4.9.0
+anyio==4.10.0
     # via
     #   gql
     #   starlette
     #   watchfiles
 asttokens==3.0.0
     # via icecream
-attrs==25.3.0
-    # via
-    #   outcome
-    #   trio
 backoff==2.2.1
     # via gql
 beautifulsoup4==4.13.4
@@ -30,10 +26,8 @@ botocore==1.40.1
     #   boto3
     #   s3fs
     #   s3transfer
-certifi==2025.7.14
+certifi==2025.8.3
-    # via
+    # via requests
-    #   requests
-    #   selenium
 charset-normalizer==3.4.2
     # via requests
 click==8.1.8
@@ -132,8 +126,6 @@ graphql-core==3.2.6
     #   graphql-relay
 graphql-relay==3.2.0
     # via graphene
-greenlet==3.2.3
-    # via playwright
 grpcio==1.74.0
     # via
     #   dagster
@@ -141,9 +133,7 @@ grpcio==1.74.0
 grpcio-health-checking==1.71.2
     # via dagster
 h11==0.16.0
-    # via
+    # via uvicorn
-    #   uvicorn
-    #   wsproto
 httptools==0.6.4
     # via uvicorn
 humanfriendly==10.0
@@ -155,7 +145,6 @@ idna==3.10
     #   anyio
     #   email-validator
     #   requests
-    #   trio
     #   yarl
 jinja2==3.1.6
     # via dagster
@@ -190,10 +179,6 @@ numpy==2.3.2
     #   seaborn
 openpyxl==3.1.5
     # via dev (pyproject.toml)
-outcome==1.3.0.post0
-    # via
-    #   trio
-    #   trio-websocket
 packaging==25.0
     # via
     #   dagster-aws
@@ -210,10 +195,10 @@ patito==0.8.3
     # via
     #   dev (pyproject.toml)
     #   dagster-polars
+pendulum==3.1.0
+    # via dev (pyproject.toml)
 pillow==11.3.0
     # via matplotlib
-playwright==1.54.0
-    # via dev (pyproject.toml)
 polars==1.32.0
     # via
     #   dagster-polars
@@ -240,8 +225,6 @@ pydantic-core==2.33.2
     # via pydantic
 pydantic-settings==2.10.1
     # via dev (pyproject.toml)
-pyee==13.0.0
-    # via playwright
 pygments==2.19.2
     # via
     #   icecream
@@ -249,15 +232,14 @@ pygments==2.19.2
 pyparsing==3.2.3
     # via matplotlib
 pysocks==1.7.1
-    # via
+    # via requests
-    #   requests
-    #   urllib3
 python-dateutil==2.9.0.post0
     # via
     #   botocore
     #   graphene
     #   matplotlib
     #   pandas
+    #   pendulum
 python-dotenv==1.1.1
     # via
     #   dagster
@@ -293,8 +275,6 @@ s3transfer==0.13.1
     # via boto3
 seaborn==0.13.2
     # via dev (pyproject.toml)
-selenium==4.34.2
-    # via dev (pyproject.toml)
 setuptools==80.9.0
     # via dagster
 six==1.17.0
@@ -304,11 +284,7 @@ six==1.17.0
 smmap==5.0.2
     # via gitdb
 sniffio==1.3.1
-    # via
+    # via anyio
-    #   anyio
-    #   trio
-sortedcontainers==2.4.0
-    # via trio
 soupsieve==2.7
     # via beautifulsoup4
 sqlalchemy==2.0.42
@@ -333,12 +309,6 @@ toposort==1.10
     # via dagster
 tqdm==4.67.1
     # via dagster
-trio==0.30.0
-    # via
-    #   selenium
-    #   trio-websocket
-trio-websocket==0.12.2
-    # via selenium
 typing-extensions==4.14.1
     # via
     #   alembic
@@ -350,8 +320,6 @@ typing-extensions==4.14.1
     #   patito
     #   pydantic
     #   pydantic-core
-    #   pyee
-    #   selenium
     #   sqlalchemy
     #   starlette
     #   typing-inspection
@@ -360,7 +328,9 @@ typing-inspection==0.4.1
     #   pydantic
     #   pydantic-settings
 tzdata==2025.2
-    # via pandas
+    # via
+    #   pandas
+    #   pendulum
 universal-pathlib==0.2.6
     # via
     #   dagster
@@ -370,7 +340,6 @@ urllib3==2.5.0
     #   botocore
     #   docker
     #   requests
-    #   selenium
 uvicorn==0.35.0
     # via dagster-webserver
 uvloop==0.21.0
@@ -379,12 +348,8 @@ watchdog==5.0.3
     # via dagster
 watchfiles==1.1.0
     # via uvicorn
-websocket-client==1.8.0
-    # via selenium
 websockets==15.0.1
     # via uvicorn
-wsproto==1.2.0
-    # via trio-websocket
 xlsxwriter==3.2.5
     # via dev (pyproject.toml)
 yarl==1.20.1

apps/stocks/src/assets.py

@@ -2,81 +2,30 @@ import asyncio
 from collections.abc import Iterator
 from datetime import datetime, timezone
 from functools import partial
+from pathlib import Path
 
+import structlog
 from config import APP, URL
-from partitions import daily_partitions_def
+from partitions import (
-from playwright.async_api import async_playwright
+    daily_partitions_def,
-from utils import extract_date
+    daily_table_partitions_def,
+    table_partitions_def,
+)
+from utils.extracter import extract_date, extract_tables
+from utils.scraper import scrape
+from utils.text import slugify
 
 import dagster as dg
 
 TAGS = {"app": APP}
 asset = partial(dg.asset, key_prefix=APP, tags=TAGS)
 
-
+logger = structlog.get_logger()
-async def main() -> str:
-    async with async_playwright() as p:
-        browser = await p.chromium.launch(headless=True)
-        context = await browser.new_context(viewport={"width": 1000, "height": 2000})
-        page = await context.new_page()
-
-        await page.goto(URL, timeout=60000)
-
-        # Wait until at least one toggle button is present
-        await page.wait_for_selector(".toggle-btn", timeout=20000)
-
-        # Set zoom
-        await page.evaluate("document.body.style.zoom='50%'")
-
-        # Find all toggle buttons
-        toggle_buttons = await page.query_selector_all(".toggle-btn")
-        print(f"Found {len(toggle_buttons)} toggle buttons")
-
-        for i, btn in enumerate(toggle_buttons):
-            try:
-                # Ensure it's visible and enabled
-                if await btn.is_visible() and await btn.is_enabled():
-                    await btn.click()
-                    await page.wait_for_timeout(1000)
-
-                if i == len(toggle_buttons) - 1:
-                    break
-
-                # Scroll down gradually
-                scroll_step = 500
-                total_height = await page.evaluate("() => document.body.scrollHeight")
-                current_position = 0
-
-                while current_position < total_height:
-                    await page.evaluate(f"window.scrollTo(0, {current_position});")
-                    await page.wait_for_timeout(100)
-                    current_position += scroll_step
-                    total_height = await page.evaluate(
-                        "() => document.body.scrollHeight"
-                    )
-
-            except Exception as e:
-                print(f"Skipped button due to error: {e}")
-
-        # Get the page content
-        page_source = await page.content()
-
-        # Close the browser
-        await browser.close()
-
-        # Continue scraping logic here...
-        print("Scraping done")
-
-        # Save the page content to a file
-        with open("/cache/scraped_page.html", "w") as fp:
-            fp.write(page_source)
-
-    return page_source
 
 
 @asset(io_manager_key="html_io_manager", name="raw")
 def raw_html(context: dg.AssetExecutionContext) -> Iterator[dg.Output[str]]:
-    page_source = asyncio.run(main())
+    page_source = asyncio.run(scrape(url=URL))
 
     now = datetime.now(tz=timezone.utc)
     date_str = now.strftime("%Y-%m-%d")
@@ -94,18 +43,67 @@ def raw_html(context: dg.AssetExecutionContext) -> Iterator[dg.Output[str]]:
         date_str = date_obj.strftime("%Y-%m-%d")
         context.log.info(f"Found date: {date_str}")
         context.log_event(
-            dg.AssetMaterialization(asset_key=daily_html.key, partition=date_str)
+            dg.AssetMaterialization(asset_key=raw_html.key, partition=date_str)
         )
     except Exception as e:
         context.log.error(f"Parsing error: {e}")
 
 
+@asset(deps=[raw_html], partitions_def=daily_table_partitions_def)
+def daily_table() -> None: ...
+
+
 @asset(
-    io_manager_key="html_io_manager",
+    deps=[raw_html],
+    io_manager_key="json_io_manager",
     partitions_def=daily_partitions_def,
+    automation_condition=dg.AutomationCondition.eager(),
+    output_required=False,
 )
-def daily_html() -> str: ...
+def raw_daily(context: dg.AssetExecutionContext) -> None:
+    base = (
+        Path(context.resources.json_io_manager.base_dir).joinpath(*raw_html.key.path)
+        / context.partition_key
+    )
+    if files := list(base.glob("*.html")):
+        logger.info(f"Found {len(files)} html files")
+        page_source = open(files[-1]).read()
 
+        for title, description, df in extract_tables(page_source):
+            # TODO: when scraping click the "View Strategy Criteria" texts and record the
+            #  information
+            if not title:
+                logger.info(
+                    "No title!",
+                    description=description,
+                    num_rows=0 if df is None else len(df),
+                )
+                continue
 
-class MyAssetConfig(dg.Config):
+            if df is None:
-    image: str = "bla"
+                logger.info("No data!", title=title, description=description)
+                continue
+
+            slug = slugify(title)
+            output_context = dg.build_output_context(
+                asset_key=dg.AssetKey(
+                    [APP, "daily", context.partition_key, slug],
+                ),
+                resources=context.resources.original_resource_dict,
+            )
+            context.resources.json_io_manager.handle_output(
+                output_context, df.to_dict(orient="records")
+            )
+            context.log_event(
+                dg.AssetMaterialization(
+                    asset_key=daily_table.key,
+                    partition=f"{context.partition_key}|{slug}",
+                    metadata={
+                        "title": dg.MetadataValue.text(title),
+                        "slug": dg.MetadataValue.text(slug),
+                        "description": dg.MetadataValue.text(description),
+                        "rows": dg.MetadataValue.int(len(df)),
+                    },
+                )
+            )
+            context.instance.add_dynamic_partitions(table_partitions_def.name, [slug])

apps/stocks/src/definitions.py

@@ -4,6 +4,7 @@ import sensors
 from dagster_polars import PolarsParquetIOManager
 from icecream import install
 from shared.config import APP, STORAGE_DIR
+from shared.io_manager import JsonIOManager
 from shared.io_manager.html import HtmlIOManager
 
 import dagster as dg
@@ -20,8 +21,9 @@ definitions = dg.Definitions(
     ],
     resources={
         "html_io_manager": HtmlIOManager(base_dir=STORAGE_DIR),
+        "json_io_manager": JsonIOManager(base_dir=STORAGE_DIR),
         "polars_parquet_io_manager": PolarsParquetIOManager(base_dir=STORAGE_DIR),
     },
     jobs=[jobs.raw_html_job],
-    sensors=[sensors.check_update],
+    sensors=[sensors.check_update, sensors.parse_raw],
 )

apps/stocks/src/jobs.py

@@ -7,3 +7,8 @@ raw_html_job = dg.define_asset_job(
     selection=[assets.raw_html.key],
     tags={"docker/image": "dagster-code-stocks-playwright"},
 )
+
+extract_job = dg.define_asset_job(
+    "extract_job",
+    selection=[assets.raw_daily.key],
+)

apps/stocks/src/partitions.py

@@ -5,3 +5,9 @@ import dagster as dg
 daily_partitions_def = dg.DailyPartitionsDefinition(
     start_date="2025-07-01", end_offset=1, timezone=os.environ.get("TZ", "UTC")
 )
+
+table_partitions_def = dg.DynamicPartitionsDefinition(name="tables")
+
+daily_table_partitions_def = dg.MultiPartitionsDefinition(
+    {"date": daily_partitions_def, "source": table_partitions_def}
+)

apps/stocks/src/sensors.py

@@ -1,13 +1,18 @@
 from collections.abc import Iterator
 from datetime import datetime
 
+import assets
 import jobs
+import pendulum
 import requests
+import structlog
 from config import URL
-from utils import extract_date
+from utils.extracter import extract_date
 
 import dagster as dg
 
+logger = structlog.get_logger()
+
 
 @dg.sensor(job=jobs.raw_html_job, minimum_interval_seconds=4 * 60 * 60)
 def check_update(context: dg.SensorEvaluationContext) -> Iterator[dg.RunRequest]:
@@ -30,5 +35,57 @@ def check_update(context: dg.SensorEvaluationContext) -> Iterator[dg.RunRequest]
     now_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     file = f"{now_str} stocks.html"
     context.log.info(f"Saving file: {file}")
-    with open(f"/cache/{file}") as fp:
+    with open(f"/cache/{file}", "w") as fp:
         fp.write(response.text)
+
+
+@dg.sensor(job=jobs.extract_job, minimum_interval_seconds=2 * 60 * 60)
+def parse_raw(context: dg.SensorEvaluationContext):
+    # TODO: use cursor from sensor to filter materialization events
+
+    # Get the known materialized partitions of daily_tables
+    daily_partitions = context.instance.get_materialized_partitions(
+        assets.daily_table.key
+    )
+    dates = [x.split("|")[0] for x in daily_partitions]
+    ic(daily_partitions, dates)
+
+    # Get metadata for the raw asset (assumes it's tracked or logged with metadata)
+    events = list(
+        context.instance.get_event_records(
+            event_records_filter=dg.EventRecordsFilter(
+                event_type=dg.DagsterEventType.ASSET_MATERIALIZATION,
+                asset_key=assets.raw_html.key,
+            ),
+            limit=100,
+        )
+    )
+
+    # Track unique dates found in raw that are not materialized in daily_tables
+    unknown_dates = set()
+    for event in events:
+        metadata = event.event_log_entry.asset_materialization.metadata
+        date_str = None
+        ic(metadata)
+        for key, entry in metadata.items():
+            # TODO: move this general logic
+            if key.lower() in {"date", "partition", "partition_date"}:
+                date_str = entry.value
+                break
+        if not date_str:
+            continue
+
+        # Normalize and validate the date
+        try:
+            dt = pendulum.from_timestamp(int(date_str))
+            date_str = dt.strftime("%Y-%m-%d")
+        except Exception as e:
+            logger.error(f"Failed to parse date: {date_str}", input=date_str, e=e)
+            continue
+
+        if date_str not in dates:
+            unknown_dates.add(date_str)
+
+    ic(unknown_dates)
+    for date_str in sorted(unknown_dates):
+        yield dg.RunRequest(partition_key=date_str)

apps/stocks/src/utils.py

@@ -1,19 +0,0 @@
-import re
-from collections.abc import Iterator
-from datetime import date, datetime
-
-from bs4 import BeautifulSoup
-
-
-def extract_date(page_source: str) -> Iterator[date]:
-    # Parse with BeautifulSoup
-    soup = BeautifulSoup(page_source, "html.parser")
-
-    # Find the first <div> after </header>
-    if (header := soup.find("header")) and (div := header.find_next_sibling("div")):
-        # Extract date part using regex
-        match = re.search(r"(\d{1,2})(st|nd|rd|th)?\s+([A-Za-z]+)\s+(\d{4})", div.text)
-        if match:
-            day, _, month, year = match.groups()
-            date_obj = datetime.strptime(f"{day} {month} {year}", "%d %B %Y")
-            yield date_obj

apps/stocks/src/utils/extracter.py

@@ -0,0 +1,55 @@
+import re
+from collections.abc import Iterator
+from datetime import date, datetime
+
+import pandas as pd
+from bs4 import BeautifulSoup
+from pandas import DataFrame
+
+
+def extract_date(page_source: str) -> Iterator[date]:
+    # Parse with BeautifulSoup
+    soup = BeautifulSoup(page_source, "html.parser")
+
+    # Find the first <div> after </header>
+    if (header := soup.find("header")) and (div := header.find_next_sibling("div")):
+        # Extract date part using regex
+        match = re.search(r"(\d{1,2})(st|nd|rd|th)?\s+([A-Za-z]+)\s+(\d{4})", div.text)
+        if match:
+            day, _, month, year = match.groups()
+            date_obj = datetime.strptime(f"{day} {month} {year}", "%d %B %Y")
+            yield date_obj
+
+
+def extract_tables(
+    page_source: str,
+) -> Iterator[tuple[str | None, str | None, DataFrame]]:
+    soup = BeautifulSoup(page_source, "html.parser")
+    accordion_items = soup.find_all("div", class_="accordion-item")
+
+    for item in accordion_items:
+        # Extract the title
+        header = item.find("div", class_="accordion-header")
+        title = header.find("h2").get_text(strip=True) if header else None
+
+        # Extract the description
+        description_block = item.find("div", class_="accordion-description")
+        description = (
+            description_block.find("p").get_text(strip=True)
+            if description_block
+            else None
+        )
+
+        # Extract the table
+        table = item.find("table")
+        if table:
+            rows = []
+            for row in table.find_all("tr"):
+                cells = [
+                    cell.get_text(strip=True) for cell in row.find_all(["th", "td"])
+                ]
+                rows.append(cells)
+
+            if rows:
+                df = pd.DataFrame(rows[1:], columns=rows[0])
+                yield title, description, df

apps/stocks/src/utils/scraper.py

@@ -0,0 +1,60 @@
+async def scrape(url: str) -> str:
+    from playwright.async_api import async_playwright
+
+    async with async_playwright() as p:
+        browser = await p.chromium.launch(headless=True)
+        context = await browser.new_context(viewport={"width": 1000, "height": 2000})
+        page = await context.new_page()
+
+        await page.goto(url, timeout=60000)
+
+        # Wait until at least one toggle button is present
+        await page.wait_for_selector(".toggle-btn", timeout=20000)
+
+        # Set zoom
+        await page.evaluate("document.body.style.zoom='50%'")
+
+        # Find all toggle buttons
+        toggle_buttons = await page.query_selector_all(".toggle-btn")
+        print(f"Found {len(toggle_buttons)} toggle buttons")
+
+        for i, btn in enumerate(toggle_buttons):
+            try:
+                # Ensure it's visible and enabled
+                if await btn.is_visible() and await btn.is_enabled():
+                    await btn.click()
+                    await page.wait_for_timeout(1000)
+
+                if i == len(toggle_buttons) - 1:
+                    break
+
+                # Scroll down gradually
+                scroll_step = 500
+                total_height = await page.evaluate("() => document.body.scrollHeight")
+                current_position = 0
+
+                while current_position < total_height:
+                    await page.evaluate(f"window.scrollTo(0, {current_position});")
+                    await page.wait_for_timeout(100)
+                    current_position += scroll_step
+                    total_height = await page.evaluate(
+                        "() => document.body.scrollHeight"
+                    )
+
+            except Exception as e:
+                print(f"Skipped button due to error: {e}")
+
+        # Get the page content
+        page_source = await page.content()
+
+        # Close the browser
+        await browser.close()
+
+        # Continue scraping logic here...
+        print("Scraping done")
+
+        # Save the page content to a file
+        with open("/cache/scraped_page.html", "w") as fp:
+            fp.write(page_source)
+
+    return page_source

apps/stocks/src/utils/text.py

@@ -0,0 +1,11 @@
+import re
+import unicodedata
+
+
+def slugify(text: str) -> str:
+    # Normalize unicode characters
+    text = unicodedata.normalize("NFKD", text).encode("ascii", "ignore").decode("ascii")
+    # Replace non-word characters with hyphens
+    text = re.sub(r"[^\w\s-]", "", text).strip().lower()
+    # Replace spaces and repeated hyphens with a single hyphen
+    return re.sub(r"[-\s]+", "-", text)

apps/tesla/requirements.txt

@@ -6,7 +6,7 @@ annotated-types==0.7.0
     # via pydantic
 antlr4-python3-runtime==4.13.2
     # via dagster
-anyio==4.9.0
+anyio==4.10.0
     # via
     #   gql
     #   starlette
@@ -26,7 +26,7 @@ botocore==1.40.1
     #   boto3
     #   s3fs
     #   s3transfer
-certifi==2025.7.14
+certifi==2025.8.3
     # via requests
 charset-normalizer==3.4.2
     # via requests

apps/test/io.py

@@ -1,22 +0,0 @@
-from typing import Any, Optional
-
-
-class MyIOManager(PolarsParquetIOManager):
-    def _load_partition_from_path(
-        self,
-        context: InputContext,
-        partition_key: str,
-        path: "UPath",
-        backcompat_path: Optional["UPath"] = None,
-    ) -> Any:
-        try:
-            return super()._load_partition_from_path(
-                context, partition_key, path, backcompat_path
-            )
-        except FileNotFoundError:
-            # Handle the case where the partition file does not exist
-            context.log.warning(
-                f"Partition file not found for key {partition_key} at path {path}. "
-                "Returning an empty DataFrame."
-            )
-            return None

apps/test/manual.py

@@ -1,51 +0,0 @@
-import os
-from pathlib import Path
-
-from dotenv import find_dotenv, load_dotenv
-from icecream import ic
-
-from dagster import AssetKey, DagsterInstance
-
-
-def delete_partition(instance, partition_def_name, partition_key):
-    try:
-        # This does not seem to work, perhaps because it is not a dynamic partition?
-        # All materializations can be deleted through the UI, but not one by one
-        instance.delete_dynamic_partition(partition_def_name, partition_key)
-
-    except Exception as e:
-        print(f"Error deleting partition: {e}")
-
-
-def main(instance):
-    print(f"Partition '{partition_key}' deleted successfully.")
-
-
-def detect_previous_partition(instance, name):
-    ic(name)
-    records = instance.get_latest_materialization_events(
-        (AssetKey(name),),
-        # event_type="ASSET_MATERIALIZATION",
-        # asset_key=(partition_key,),
-        # limit=100,
-    )
-    print(records)
-
-
-if __name__ == "__main__":
-    partition_def_name = "asset_single_1"
-    partition_key = "2025-07-20"  # Example partition key
-
-    load_dotenv(find_dotenv())
-    os.environ["DAGSTER_HOME"] = str(Path(__file__).parent.parent.parent)
-
-    for k, v in os.environ.items():
-        if k.startswith("POSTGRES_"):
-            os.environ[f"DAGSTER_{k}"] = v
-
-    os.environ["DAGSTER_POSTGRES_HOST"] = "localhost"
-    instance = DagsterInstance.get()
-
-    # delete_partition(instance, partition_def_name, partition_key)
-
-    detect_previous_partition(instance, partition_def_name)

apps/test/sync.sh

@@ -1,8 +0,0 @@
-#!/usr/bin/env bash
-rsync -av /opt/dagster/src/app/vinyl/ \
-  /Volumes/dagster/src/app/vinyl/ \
-  --include='*.py' \
-  --include='*requirements.txt' \
-  --exclude='__pycache__/' \
-  -progress \
-  --delete $*

apps/test/test.py

@@ -1,34 +0,0 @@
-import time
-
-from dagster import AssetMaterialization, Output, config_mapping, job, op
-
-
-@op(config_schema={"config_param": str})
-def hello(context):
-    time.sleep(1)
-    print("halllo")
-    return Output(123, metadata={"aa": context.op_config["config_param"]})
-
-
-@op
-def goodbye(context, x: int):
-    time.sleep(2)
-    print("doooei", x)
-    context.log_event(
-        AssetMaterialization(
-            asset_key="my_asset",
-            metadata={"my_meta": 444},
-            description="A very useful value!",
-        )
-    )
-    return 2
-
-
-@config_mapping(config_schema={"simplified_param": str})
-def simplified_config(val):
-    return {"ops": {"hello": {"config": {"config_param": val["simplified_param"]}}}}
-
-
-@job
-def my_job():
-    goodbye(hello())

apps/vinyl/requirements.txt

@@ -6,7 +6,7 @@ annotated-types==0.7.0
     # via pydantic
 antlr4-python3-runtime==4.13.2
     # via dagster
-anyio==4.9.0
+anyio==4.10.0
     # via
     #   gql
     #   starlette
@@ -26,7 +26,7 @@ botocore==1.40.1
     #   boto3
     #   s3fs
     #   s3transfer
-certifi==2025.7.14
+certifi==2025.8.3
     # via requests
 charset-normalizer==3.4.2
     # via requests

apps/vinyl/src/assets.py

@@ -170,7 +170,9 @@ def works(context: dg.AssetExecutionContext) -> Iterator[dg.Output[pl.DataFrame]
     },
     output_required=False,
     dagster_type=patito_model_to_dagster_type(Deal),
-    automation_condition=dg.AutomationCondition.eager(),
+    automation_condition=dg.AutomationCondition.on_missing().without(
+        dg.AutomationCondition.in_latest_time_window()
+    ),
 )
 def new_deals(
     context: dg.AssetExecutionContext, partitions: dict[str, pl.LazyFrame | None]

apps/weather/requirements.txt

@@ -6,7 +6,7 @@ annotated-types==0.7.0
     # via pydantic
 antlr4-python3-runtime==4.13.2
     # via dagster
-anyio==4.9.0
+anyio==4.10.0
     # via
     #   gql
     #   starlette
@@ -32,7 +32,7 @@ botocore==1.40.1
     #   s3transfer
 cattrs==25.1.1
     # via requests-cache
-certifi==2025.7.14
+certifi==2025.8.3
     # via requests
 charset-normalizer==3.4.2
     # via

apps/weather/src/definitions.py

@@ -22,10 +22,9 @@ definitions = dg.Definitions(
         "polars_parquet_io_manager": PolarsParquetIOManager(base_dir=STORAGE_DIR),
     },
     sensors=[
-        sensors.list_locations,
+        # sensors.list_locations,
         sensors.list_latitudes,
-        sensors.list_longitudes,
+        # sensors.list_longitudes,
-        sensors.retrieve_weather,
         sensors.retrieve_weather,
     ],
 )

entrypoint.sh

@@ -0,0 +1,8 @@
+#!/bin/sh
+set -e
+
+echo "Rendering dagster.yaml from template..."
+envsubst < dagster.yaml.template > dagster.yaml
+
+echo "Starting Dagster: $@"
+exec "$@"

poetry.lock

@@ -1,19 +0,0 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
-
-[[package]]
-name = "seven"
-version = "1.0.0"
-description = "Python 2.5 compatibility wrapper for Python 2.7 code."
-optional = false
-python-versions = "*"
-files = [
-    {file = "seven-1.0.0.tar.gz", hash = "sha256:e80157857dc378545b0cd8626668bf0e20d7f3608a5587f3fcc71a56d2416814"},
-]
-
-[package.extras]
-tests = ["zope.testing"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "*"
-content-hash = "edfc27fcb4a7dc1b1a11f2224d7b7f3e936c5f624df1dd86207c4dc08e047b5d"