diff --git a/.containerignore b/.containerignore index ada296cf..2750fe57 100644 --- a/.containerignore +++ b/.containerignore @@ -1,3 +1,4 @@ Containerfile nssp_demo/private_data notebooks +mounts/ diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 00000000..99a798df --- /dev/null +++ b/.dockerignore @@ -0,0 +1,4 @@ +Containerfile +nssp_demo/private_data +notebooks +mounts diff --git a/.github/workflows/update-dagster-code.yaml b/.github/workflows/update-dagster-code.yaml new file mode 100644 index 00000000..202b138d --- /dev/null +++ b/.github/workflows/update-dagster-code.yaml @@ -0,0 +1,24 @@ +name: Deploy Dagster Code + +on: + push: + branches: + - main + workflow_dispatch: + +jobs: + run: + runs-on: ubuntu-latest + environment: production + name: Update Dagster Code Location + steps: + - name: Run update script with cfa runner-action + uses: CDCgov/cfa-actions/runner-action@v1.5.0 + with: + github_app_id: ${{ secrets.REPO_CDCENT_ACTOR_APP_ID }} + github_app_pem: ${{ secrets.REPO_CDCENT_ACTOR_APP_PEM }} + script: | + echo "Running update script" + uv run \ + https://raw.githubusercontent.com/CDCgov/cfa-dagster/refs/heads/main/scripts/update_code_location.py \ + --registry_image cfaprdbatchcr.azurecr.io/pyrenew-hew:dagster_latest diff --git a/.gitignore b/.gitignore index 56cb74ec..d0736e82 100644 --- a/.gitignore +++ b/.gitignore @@ -29,6 +29,8 @@ *.gif *.pdf *.png +# except when in img/ folder +!img/*.png # Compressed archives *.gz @@ -401,8 +403,16 @@ nssp-etl output params nwss-vintages +mounts +prod-param-estimates +pyrenew-hew-config +pyrenew-hew-prod-output +pyrenew-test-output +test-output # Azure configuration files azureconfig.env azureconfig.sh + +# blobfuse config.yaml diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 956d5fb0..360feaa6 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -19,6 +19,7 @@ repos: - id: ruff-check # Run the formatter - id: ruff-format + #####extra - repo: https://github.com/astral-sh/uv-pre-commit rev: 0.9.21 hooks: diff --git a/Containerfile b/Containerfile index 329c6040..baf0b240 100644 --- a/Containerfile +++ b/Containerfile @@ -1,6 +1,7 @@ #syntax=docker/dockerfile:1-labs -FROM rocker/tidyverse +# We pin to a specific version for reproducibility; increment manually as needed +FROM rocker/tidyverse:4.5.1 ARG GIT_COMMIT_SHA ENV GIT_COMMIT_SHA=$GIT_COMMIT_SHA @@ -10,22 +11,50 @@ ENV GIT_BRANCH_NAME=$GIT_BRANCH_NAME ENV XLA_FLAGS=--xla_force_host_platform_device_count=4 +# This makes the /pyrenew-hew/ directory and then copies in the hewr package COPY ./hewr /pyrenew-hew/hewr +# Set the working directory to our pyrenew-hew directory, which represents the repository as a whole WORKDIR /pyrenew-hew +# Install pak and then the hewr package and its dependencies RUN Rscript -e "install.packages('pak')" RUN Rscript -e "pak::local_install('hewr', upgrade = FALSE)" -COPY --exclude=pipelines/priors . . -COPY pipelines/priors pipelines/priors - -# Python from https://docs.astral.sh/uv/guides/integration/docker/ +# Copy in the binaries for UV Python - see https://docs.astral.sh/uv/guides/integration/docker/ COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/ + # Some handy uv environment variables ENV UV_COMPILE_BYTECODE=1 ENV UV_LINK_MODE=copy ENV UV_PYTHON_CACHE_DIR=/root/.cache/uv/python -RUN --mount=type=cache,target=/root/.cache/uv \ - uv sync +# Copy in the pyrenew-hew modeling, pipelining, and testing code +COPY ./pyrenew_hew ./pyrenew_hew +COPY ./pipelines ./pipelines +COPY ./tests ./tests +COPY README.md ./ + +# -- VENV MANAGEMENT AND DEPENDENCY SYNCING -- # + +# Copy in the UV/python dependency management configs +COPY ./pyproject.toml ./ +COPY ./uv.lock ./ +COPY ./.python-version ./ + +# Create the Pyrenew-Hew virtual environment and sync dependencies from pyproject.toml +RUN uv venv .venv +RUN --mount=type=cache,target=/root/.cache/uv + +# Set VIRTUAL_ENV variable at runtime +ENV VIRTUAL_ENV=/pyrenew-hew/.venv +RUN uv sync + +# Copy in the dagster definitions python file. +# All dagster definitions are defined here. +# Dagster Definitions are updated more frequently than other code, +# so it is much quicker for the build cache to worry about it last +COPY ./dagster_defs.py ./ + +# Update PATH to use the selected venv +ENV PATH="${VIRTUAL_ENV}/bin:$PATH" diff --git a/Makefile b/Makefile index 47bca89d..1c8b3a72 100644 --- a/Makefile +++ b/Makefile @@ -1,4 +1,4 @@ -.PHONY: help container_build container_tag ghcr_login container_push run_timeseries run_e_model run_h_models post_process +.PHONY: help container_build container_tag ghcr_login container_push run_timeseries run_e_model run_h_models post_process run_he_model run_hw_model acc mount unmount config dagster dagster_build # Build parameters @@ -6,16 +6,24 @@ ifndef ENGINE ENGINE = docker endif -ifndef CONTAINER_NAME -CONTAINER_NAME = pyrenew-hew +ifndef CONTAINER_REGISTRY +CONTAINER_REGISTRY = ghcr.io/cdcgov endif -ifndef CONTAINERFILE -CONTAINERFILE = Containerfile +ifndef CONTAINER_IMAGE_NAME +CONTAINER_IMAGE_NAME = pyrenew-hew +endif + +ifndef CONTAINER_IMAGE_VERSION +CONTAINER_IMAGE_VERSION = latest endif ifndef CONTAINER_REMOTE_NAME -CONTAINER_REMOTE_NAME = ghcr.io/cdcgov/$(CONTAINER_NAME):latest +CONTAINER_REMOTE_NAME = $(CONTAINER_REGISTRY)/$(CONTAINER_IMAGE_NAME):$(CONTAINER_IMAGE_VERSION) +endif + +ifndef CONTAINERFILE +CONTAINERFILE = Containerfile endif # Model Fit Parameters @@ -47,13 +55,22 @@ endif help: @echo "Usage: make [target] [ARGS]" @echo "" + + @echo "Blobfuse Mount Targets: " + @echo " mount : Mount blob storage containers using blobfuse2" + @echo " unmount : Unmount blob storage containers and clean up" + @echo "" @echo "Container Build Targets: " @echo " container_build : Build the container image" + @echo " dagster : Run dagster definitions locally" + @echo " dagster_build : Build the dagster container image" + @echo " dagster_push : Push the dagster container image to the Azure Container Registry and code location" @echo " container_tag : Tag the container image" @echo " ghcr_login : Log in to the Github Container Registry. Requires GH_USERNAME and GH_PAT env vars" @echo " container_push : Push the container image to the Azure Container Registry" @echo "" @echo "Model Fit Targets: " + @echo " acc : Run the Azure Command Center for routine production jobs" @echo " run_timeseries : Run the timeseries model fit job" @echo " run_e_model : Run an e model fit job" @echo " run_h_models : Run an h model fit job" @@ -73,104 +90,160 @@ help: @echo "" @echo "To run the pyrenew-hew model and output to pyrenew-test-output:" @echo " make run_hew_model TEST=True MODEL_LETTERS=hew" + @echo "To use a custom container registry, image, and tag:" + @echo " make run_hew_model CONTAINER_REGISTRY= CONTAINER_IMAGE_NAME= CONTAINER_IMAGE_VERSION=" @echo "" @echo "Any additional flags can be passed with ARGS, for example:" @echo " make run_hew_model ARGS=\"--locations-include 'NY GA'\"" @echo "" @echo "Passing a flag through ARGS will also override the flags set previously." +#------------------------ # +# Blobfuse Mount Targets +# ----------------------- # + +mount: + sudo bash -c "source ./blobfuse/mount.sh" + +unmount: + sudo bash -c "source ./blobfuse/cleanup.sh" + # ----------------------- # # Container Build Targets # ----------------------- # container_build: ghcr_login - $(ENGINE) build . -t $(CONTAINER_NAME) -f $(CONTAINERFILE) + $(ENGINE) build . -t $(CONTAINER_IMAGE_NAME) -f $(CONTAINERFILE) + +dagster_build: + docker build -t cfaprdbatchcr.azurecr.io/pyrenew-hew:dagster_latest -f Containerfile . + +dagster: + uv run dagster_defs.py container_tag: - $(ENGINE) tag $(CONTAINER_NAME) $(CONTAINER_REMOTE_NAME) + $(ENGINE) tag $(CONTAINER_IMAGE_NAME) $(CONTAINER_REMOTE_NAME) ghcr_login: echo $(GH_PAT) | $(ENGINE) login ghcr.io -u $(GH_USERNAME) --password-stdin -container_push: container_tag ghcr_login +container_push: CONTAINER_IMAGE_VERSION ghcr_login $(ENGINE) push $(CONTAINER_REMOTE_NAME) +config: + bash -c "source ./azureconfig.sh" + # ---------------- # # Model Fit Targets # ---------------- # -run_timeseries: +acc: mount config + uv run pipelines/azure_command_center.py + +# Auto-set TEST/ENVIRONMENT based on each other +ifeq ($(shell echo $(ENVIRONMENT) | tr A-Z a-z),test) +override TEST = True +endif +ifeq ($(shell echo $(TEST) | tr A-Z a-z),true) +override ENVIRONMENT = test +endif + +run_timeseries: config uv run python pipelines/batch/setup_job.py \ --model-family timeseries \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "e" \ - --job-id "pyrenew-e-${ENVIRONMENT}_${FORECAST_DATE}_t" \ + --locations-exclude "WY" \ + --job-id "timeseries-e-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ --pool-id pyrenew-pool \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -run_e_model: +run_e_model: config uv run python pipelines/batch/setup_job.py \ --model-family pyrenew \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "e" \ - --job-id "pyrenew-e-${ENVIRONMENT}_${FORECAST_DATE}" \ + --locations-exclude "WY" \ + --job-id "pyrenew-e-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ --pool-id pyrenew-pool \ --rng-key "$(RNG_KEY)" \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -run_h_model: +run_h_model: config uv run python pipelines/batch/setup_job.py \ --model-family pyrenew \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "h" \ - --job-id "pyrenew-h-${ENVIRONMENT}_${FORECAST_DATE}" \ + --job-id "pyrenew-h-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ --pool-id pyrenew-pool \ --rng-key "$(RNG_KEY)" \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -run_he_model: +run_he_model: config uv run python pipelines/batch/setup_job.py \ --model-family pyrenew \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "he" \ - --job-id "pyrenew-he-${ENVIRONMENT}_${FORECAST_DATE}" \ + --locations-exclude "WY" \ + --job-id "pyrenew-he-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ --pool-id pyrenew-pool \ --rng-key "$(RNG_KEY)" \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -run_hw_model: +run_hw_model: config uv run python pipelines/batch/setup_job.py \ --model-family pyrenew \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "hw" \ - --job-id "pyrenew-hw-${ENVIRONMENT}_${FORECAST_DATE}" \ - --pool-id pyrenew-pool-32gb \ + --diseases "COVID-19" \ + --job-id "pyrenew-hw-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ + --pool-id pyrenew-pool \ --rng-key "$(RNG_KEY)" \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -run_hew_model: +run_hew_model: config uv run python pipelines/batch/setup_job.py \ --model-family pyrenew \ --output-subdir "${FORECAST_DATE}_forecasts" \ --model-letters "hew" \ - --job-id "pyrenew-hew-${ENVIRONMENT}_${FORECAST_DATE}" \ - --pool-id pyrenew-pool-32gb \ + --locations-exclude "WY" \ + --diseases "COVID-19" \ + --job-id "pyrenew-hew-${ENVIRONMENT}_${FORECAST_DATE}_makefile" \ + --pool-id pyrenew-pool \ --rng-key "$(RNG_KEY)" \ --test "$(TEST)" \ --dry-run "$(DRY_RUN)" \ + --container-registry "$(CONTAINER_REGISTRY)" \ + --container-image-name "$(CONTAINER_IMAGE_NAME)" \ + --container-image-version "$(CONTAINER_IMAGE_VERSION)" \ $(ARGS) -post_process: +post_process: config uv run python pipelines/postprocess_forecast_batches.py \ --input "./blobfuse/mounts/pyrenew-hew-prod-output/${FORECAST_DATE}_forecasts" \ --output "./blobfuse/mounts/nssp-etl/gold/${FORECAST_DATE}_forecasts.parquet" \ diff --git a/README.md b/README.md index 2742ac6d..3fc4d66b 100644 --- a/README.md +++ b/README.md @@ -11,10 +11,11 @@ The PyRenew-HEW project aims to create short-term forecasts of respiratory disea This is a work in progress, and not all data sources are currently integrated into the model. -This repository contains code for the [PyRenew-HEW model](https://github.com/CDCgov/pyrenew-hew/blob/main/pyrenew_hew/pyrenew_hew_model.py) itself, as well as [pipelines](https://github.com/CDCgov/pyrenew-hew/tree/main/pyrenew_hew) for running the model in production, and [utilities](https://github.com/CDCgov/pyrenew-hew/tree/main/hewr) for working with model outputs. +This repository contains code for the [PyRenew-HEW model](https://github.com/CDCgov/pyrenew-hew/blob/main/pyrenew_hew/pyrenew_hew_model.py) itself, as well as [pipelines](https://github.com/CDCgov/pyrenew-hew/tree/main/pipelines/) for running the model in production, and [utilities](https://github.com/CDCgov/pyrenew-hew/tree/main/hewr) for working with model outputs. ## Containers +### Standard Container The project uses GitHub Actions for automatically building container images based on the project's [Containerfile](Containerfile). The images are currently hosted on Github Container Registry and are built and pushed via the [containers.yaml](.github/workflows/containers.yaml) GitHub Actions workflow. Images can also be built locally. The [Makefile](Makefile) contains several targets for building and pushing images. Although the Makefile uses Docker as the default engine, the `ENGINE` environment variable can be set to `podman` to use Podman instead, for example: @@ -29,18 +30,80 @@ Container images pushed to the Azure Container Registry are automatically tagged ## Running Model Pipelines > [!NOTE] -> -> Please contact a project maintainer if you believe you need access to pipelines. -> CDC internal users can check regularly scheduled jobs at [PyRenew-Cron](https://github.com/cdcent/pyrenew-cron). - +PyRenew-HEW Azure Batch Modeling Pipelines can only be run by CDC internal users on the CFA Virtual Analyst Platform. + +There are four ways to run PyRenew-HEW Azure Batch Modeling Code: +1. [PyRenew-Cron](#1-pyrenew-cron) - a separate repository on cdcent github (see below) - automated in Github Actions. +2. [Dagster Workflow Orchestration](#2-dagster-workflow-orchestration) - automated, feature rich GUI. +3. [The Azure Command Center](#3-azure-command-center) - interactive/manual. +4. [Makefile targets](#4-makefile-targets) - interactive/manual. + +### 1. PyRenew-Cron + +> [!IMPORTANT] +> - CDC internal users can check regularly scheduled jobs at [PyRenew-Cron](https://github.com/cdcent/pyrenew-cron). +> - Note that these jobs rely upon this repository, so changes to the CLIs here have the potential to break things over there. + +PyRenew-Cron is our first approach to scheduling and automating pipelines in production. +- Pyrenew-Cron checks for data availability, launches jobs based on that availability, and re-polls to check for job completions. +- As of December 2025, this pipeline is production ready and reliably produces production outputs as intended. +- See the `Pyrenew-Cron` [repository](https://github.com/cdcent/pyrenew-cron) for more information. + +### 2. Dagster Workflow Orchestration + +When mature, our dagster implementation is intended to replace the `Azure Command Center` and `PyRenew-Cron`. +Development is ongoing - you can test an early version by following the steps below. + +#### Local Development and Testing +> Prerequisites: `uv`. `docker`, a VAP VM with a registered managed identity in Azure, and rights to the cfaprdbatchcr container registry. Contact cfatoolsteam@cdc.gov for assistance with the latter two. + +The following instructions will set up Dagster on your VAP. However, based on the current configuration, actual execution will still run in the cloud via Azure Batch. You can change the `executor` option in `dagster_defs.py` to test using the local Docker Executor - this will require you to have setup Blobfuse. + +1. Setup your `uv virtual environment`: + - `uv sync` + - `source .venv/bin/activate` +2. Login to Azure and the Batch Container Registry: + - `az login --identity && az acr login -n cfaprdbatchcr` +3. Build and push the `pyrenew-hew:dagster_latest` image: + - `docker build -t cfaprdbatchcr.azurecr.io/pyrenew-hew:dagster_latest -f Containerfile . --push` +3. Start the Dagster UI by running `uv run dagster_defs.py` and clicking the link in your terminal (usually [http://127.0.0.1:3000/]) +4. You should now see the dagster UI for Pyrenew-HEW. This is a local server that will only show PyRenew-HEW asssets as defined in your local git repository. +5. Try materializing an asset by navigating to "Lineage" on the left sidebar. By default, these assets will submit jobs to Azure Batch and write to the `pyrenew-test-output` blob. + - We recommend materializing a few partitions at a time for testing purposes. + ![alt text](img/dagster_lineage.png) + - You will get a pop-up directing you to your asset runs, which provide progress logs. + ![alt text](img/dagster_runs.png) +6. Using the run ID dagster provides, you can also find your jobs in Azure Batch Explorer. + +#### Production Scheduling +> This section is under construction. + +Pushes to main will automatically update the central Dagster Code Location for PyRenew-HEW via a Github Actions Workflow. From the central code server, you can run and schedule Pyrenew-HEW runs and see other projects' pipelines at CFA. You can also manually update the code server with a makefile recipe (see next section). + +To manually update the code location while we evaluate dagster, you can run `make dagster_push`. This manual approach will be deprecated and discouraged once we move to using dagster in production. + +#### Makefile Targets for Dagster +After you've familiarized yourself with the above instructions, feel free to use these convenient `make` targets: +- `make dagster_build`: builds your dagster image. +- `make dagster_push`: builds your dagster image, then pushes it, then uploads the central dagster server's code for pyrenew-hew. +- `make dagster`: runs the dagster UI locally. +- `make mount`: mounts the pyrenew-relevant blobs using blobfuse. +- `make unmount`: gracefully unmounts the pyrenew-relevant blobs. + +### 3. Azure Command Center > Specific environment setup steps required can be found in the [Routine Forecasting Standard Operating Procedure](https://cdcent.github.io/cfa-stf-handbook/routine_forecast_sop.html). -> Additionally, pipelines as written can only be run within CFA's Virtual Analyst Platform. +You can run `uv run pipelines/azure_command_center.py` (or `make acc`) to launch the Azure Command Center. +- The Azure Command Center will check for necessary data before offering to run pipelines. +- You must have previously configured your Azure Credentials and Environment Variables. To do this, run `make config`, or follow the steps in the SOP. +- The Azure Command Center is meant to be a streamlined interface for interactively running in production. + +### 4. Makefile Targets +Run `make help` to see the Makefile targets you can use to run Azure Batch pipelines. +- This method is useful for supplying custom parameters to the batch pipelines, and also lets you perform 'Dry Runs' which will tell you what _would_ happen if you ran the code. +- You will need to check data availability manually or with the Azure Command Center. -Pipelines can be run interactively or non-interactively: -- `pipelines/azure_command_center.py` is now the preferred method of running model fit pipeline jobs interactively. -- The `Makefile` also provides targets that will run pipelines non-interactively. Run `make help` for more information. -- Pipelines are run through the command line python interface when scheduled using [Pyrenew-Cron](https://github.com/cdcent/pyrenew-cron). +---- ## General Disclaimer This repository was created for use by CDC programs to collaborate on public health related projects in support of the [CDC mission](https://www.cdc.gov/about/organization/mission.htm). GitHub is not hosted by the CDC, but is a third party website used by CDC and its partners to share information and collaborate on software. CDC use of GitHub does not imply an endorsement of any one particular service, product, or enterprise. diff --git a/blobfuse/README.md b/blobfuse/README.md new file mode 100644 index 00000000..bf974739 --- /dev/null +++ b/blobfuse/README.md @@ -0,0 +1,17 @@ +# Pyrenew Blobfuse Configuration + +This directory serves as a project-specific fork of the [cfa-blobfuse-tutorial](https://github.com/cdcent). + +> Make sure you have blobfuse2 installed before running this module. + +This directory will mount pyrenew-hew blobs to `/mnt` and then symlink to a directory you specify (or the current directory if you don't supply an argument). + +To run, make sure you're in the top level as your working directory (`pyrenew-hew`, and not `pyrenew-hew/blobfuse`). +1. Run `sudo chmod +x ./blobfuse/mount.sh`. +2. Run `sudo source bash -c "./blobfuse/mount.sh"`. This will mount to the top-level (pyrenew-hew) +3. Check to make sure `/mnt` has pyrenew blobs mounted and that symlinks have been created in your working directory (`pyrenew-hew/`). +4. Before attempting to remount, run the cleanup script `sudo source bash -c "./blobfuse/cleanup.sh"`. + +You can, for convenience, also use make commands: +- `make mount` +- `make unmount` diff --git a/blobfuse/archive/unmount.sh b/blobfuse/archive/unmount.sh new file mode 100755 index 00000000..64d1d2e0 --- /dev/null +++ b/blobfuse/archive/unmount.sh @@ -0,0 +1,28 @@ +#!/bin/bash + +# ensure logged in via Azure CLI. +./blobfuse/verifylogin.sh + +if [[ "$?" -ne 0 ]]; then + exit 1 +fi + +echo "Unmounting containers specified in mounts.txt with blobfuse2..." + +TO_UNMOUNT=( + "nssp-etl" + "nssp-archival-vintages" + "prod-param-estimates" + "pyrenew-hew-prod-output" + "pyrenew-test-output" + "nwss-vintages" + "pyrenew-hew-config" +) + +for dir in "${TO_UNMOUNT[@]}"; do + echo "Unmounting" $dir + blobfuse2 unmount $dir + rmdir $dir +done + +echo "Done." diff --git a/blobfuse/cleanup.sh b/blobfuse/cleanup.sh new file mode 100755 index 00000000..de11bd42 --- /dev/null +++ b/blobfuse/cleanup.sh @@ -0,0 +1,27 @@ +#!/bin/bash + +# ensure logged in via Azure CLI. +./blobfuse/verifylogin.sh + +if [[ "$?" -ne 0 ]]; then + exit 1 +fi + +echo "Cleaning up blobfuse mounts" + +echo "Unmounting any mounted blob storage containers" +blobfuse2 unmount all + +echo "Removing all empty entries in /mnt/" +find /mnt/ -mindepth 1 -type d -empty -delete + +echo "Clearing the cache" +rm -rf .blobfuse_cache/* + +echo "Removing empty directories" +find . -type d -empty -delete + +echo "Removing symlinks" +find . -type l -delete + +echo "Done!" diff --git a/blobfuse/mount.sh b/blobfuse/mount.sh new file mode 100755 index 00000000..ab091e76 --- /dev/null +++ b/blobfuse/mount.sh @@ -0,0 +1,91 @@ +#!/bin/bash + +# ensure logged in via Azure CLI. +./blobfuse/verifylogin.sh + +# pull azure configuration files +./blobfuse/pull_config.sh + +if [[ "$?" -ne 0 ]]; then + exit 1 +fi + +# ensure cache exists +mkdir -p .cache + +echo "Mounting containers specified in mounts.txt using blobfuse2..." +TO_MOUNT=( + "nssp-etl" + "nssp-archival-vintages" + "prod-param-estimates" + "pyrenew-hew-prod-output" + "pyrenew-test-output" + "nwss-vintages" + "pyrenew-hew-config" +) + +for dir in "${TO_MOUNT[@]}"; do + echo "Mounting" $dir + mkdir -p /mnt/$dir + blobfuse2 mount --container-name $dir /mnt/$dir --allow-other +done + +echo "" +echo "Creating symlinks in $(pwd)..." + +# Create symlinks only if they do not already exist, and inform the user +if [[ -L "./params" ]]; then + echo "Symlink './params' already exists, skipping." +else + ln -s "/mnt/prod-param-estimates" "./params" + echo "Created symlink './params' -> '/mnt/prod-param-estimates'" +fi + +if [[ -L "./output" ]]; then + echo "Symlink './output' already exists, skipping." +else + ln -s "/mnt/pyrenew-hew-prod-output" "./output" + echo "Created symlink './output' -> '/mnt/pyrenew-hew-prod-output'" +fi + +if [[ -L "./test-output" ]]; then + echo "Symlink './test-output' already exists, skipping." +else + ln -s "/mnt/pyrenew-test-output" "./test-output" + echo "Created symlink './test-output' -> '/mnt/pyrenew-test-output'" +fi + +if [[ -L "./nwss-vintages" ]]; then + echo "Symlink './nwss-vintages' already exists, skipping." +else + ln -s "/mnt/nwss-vintages" "./nwss-vintages" + echo "Created symlink './nwss-vintages' -> '/mnt/nwss-vintages'" +fi + +if [[ -L "./config" ]]; then + echo "Symlink './config' already exists, skipping." +else + ln -s "/mnt/pyrenew-hew-config" "./config" + echo "Created symlink './config' -> '/mnt/pyrenew-hew-config'" +fi + +if [[ -L "./nssp-etl" ]]; then + echo "Symlink './nssp-etl' already exists, skipping." +else + ln -s "/mnt/nssp-etl" "./nssp-etl" + echo "Created symlink './nssp-etl' -> '/mnt/nssp-etl'" +fi + +if [[ -L "./nssp-archival-vintages" ]]; then + echo "Symlink './nssp-archival-vintages' already exists, skipping." +else + ln -s "/mnt/nssp-archival-vintages" "./nssp-archival-vintages" + echo "Created symlink './nssp-archival-vintages' -> '/mnt/nssp-archival-vintages'" +fi + +echo "Setting environment variables for the Azure Command Center..." +export NSSP_ETL_PATH="$(pwd)/nssp-etl" +export PYRENEW_HEW_PROD_OUTPUT_PATH="$(pwd)/output" +export NWSS_VINTAGES_PATH="$(pwd)/nwss-vintages" + +echo "Done." diff --git a/blobfuse/pull_config.sh b/blobfuse/pull_config.sh new file mode 100755 index 00000000..ef6d5a8d --- /dev/null +++ b/blobfuse/pull_config.sh @@ -0,0 +1,22 @@ +#!/bin/bash +# Execute this script from top level directory: bash -c ./blobfuse/pull_config.sh + +# Download the Azure configuration script from blob storage +az storage blob download \ + --account-name "cfaazurebatchprd" \ + --container-name "pyrenew-hew-config" \ + --name "azureconfig.sh" \ + --file "./azureconfig.sh" \ + --auth-mode login \ + --overwrite + +source ./azureconfig.sh + +# Download the blobfuse config yaml from blob storage +az storage blob download \ + --account-name "cfaazurebatchprd" \ + --container-name "pyrenew-hew-config" \ + --name "blobfuse_config.yaml" \ + --file "./config.yaml" \ + --auth-mode login \ + --overwrite diff --git a/blobfuse/verifylogin.sh b/blobfuse/verifylogin.sh new file mode 100755 index 00000000..7a924952 --- /dev/null +++ b/blobfuse/verifylogin.sh @@ -0,0 +1,20 @@ +#!/bin/bash + +which az &>/dev/null +if [[ "$?" -ne 0 ]]; then + echo "Could not find the Azure CLI 'az'. Check that it is installed and on your PATH." + exit 1 +fi + +az account show &>/dev/null +if [[ "$?" -ne 0 ]]; then + echo "User does not appear to be logged in via the Azure CLI. Attempting to log in with managed identity..." + az login --identity &>/dev/null + if [[ "$?" -ne 0 ]]; then + echo "Failed to log in with managed identity. Please run 'az login' manually and try again." + exit 1 + fi + echo "Logged in with managed identity." +fi + +exit 0 diff --git a/dagster_defs.py b/dagster_defs.py new file mode 100644 index 00000000..a317c88f --- /dev/null +++ b/dagster_defs.py @@ -0,0 +1,515 @@ +import os +import subprocess +from datetime import UTC, datetime +from pathlib import Path + +import dagster as dg +from cfa_dagster import ( + ADLS2PickleIOManager, + azure_batch_executor, + collect_definitions, + docker_executor, + launch_asset_backfill, + start_dev_env, +) +from cfa_dagster import ( + azure_container_app_job_executor as azure_caj_executor, +) +from dagster_azure.blob import ( + AzureBlobStorageDefaultCredential, + AzureBlobStorageResource, +) + +# ---------------------- # +# Dagster Initialization +# ---------------------- # + +# function to start the dev server +start_dev_env(__name__) + +# env variable set by Dagster CLI +is_production = not os.getenv("DAGSTER_IS_DEV_CLI") + +# get the user running the Dagster instance +user = os.getenv("DAGSTER_USER") + +# --------------------------------------------------------------- # +# Partitions: how are the data split and processed in Azure Batch? +# --------------------------------------------------------------- # +# fmt: off +full_state_list = [ + 'US', 'AL', 'AK', 'AZ', 'AR', 'CA', 'CO', + 'CT', 'DE', 'DC', 'FL', 'GA', 'HI', 'ID', + 'IL', 'IN', 'IA', 'KS', 'KY', 'LA', 'ME', + 'MD', 'MA', 'MI', 'MN', 'MS', 'MO', 'MT', + 'NE', 'NV', 'NH', 'NJ', 'NM', 'NY', 'NC', + 'ND', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', + 'SD', 'TN', 'TX', 'UT', 'VT', 'VA', 'WA', + 'WV', 'WI', 'WY', 'AS', 'GU', 'MP', 'PR', + 'UM', 'VI' +] +# fmt: off + +disease_list = [ + "COVID-19", "Influenza", "RSV" +] + +# Disease Partitions +disease_partitions = dg.StaticPartitionsDefinition( + disease_list +) + +# State Partitions +state_partitions = dg.StaticPartitionsDefinition( + full_state_list +) + +# Multi Partitions +pyrenew_multi_partition_def = dg.MultiPartitionsDefinition( + { + "disease": disease_partitions, + "state": state_partitions + } +) + +# ----------------------------------------------------------- # +# Asset Definitions - What are we outputting in our pipeline? +# ----------------------------------------------------------- # + +# --------------- +# Asset Configs +# --------------- + +class PyrenewAssetConfig(dg.Config): + """ + Configuration for the Pyrenew model assets. + These default values can be modified in the Dagster asset materialization launchpad. + We also unpack these for our job run configurations. + """ + n_training_days: int = 150 + n_samples: int = 500 + exclude_last_n_days: int = 1 + n_warmup: int = 1000 + additional_forecast_letters: str = "" + forecast_date: str = datetime.now(UTC).strftime("%Y-%m-%d") + output_dir: str = "output" if is_production else "test-output" + output_subdir: str = f"{forecast_date}_forecasts" + full_dir: str = f"{output_dir}/{output_subdir}" + +# --------------- +# Worker Function +# --------------- + +# This function is NOT an asset itself, but is called by assets to run the pyrenew model +def run_pyrenew_model( + context: dg.AssetExecutionContext, + config: PyrenewAssetConfig, + model_letters: str = "h", + model_family: str = "pyrenew", +): + # Parsing partitions into call parameters for the job + keys_by_dimension: dg.MultiPartitionKey = context.partition_key.keys_by_dimension + DEFAULT_EXCLUDED_LOCATIONS: list[str] = ["AS", "GU", "MP", "PR", "UM", "VI"] + disease = keys_by_dimension["disease"] + state = keys_by_dimension["state"] + + # Exclusions + if state in DEFAULT_EXCLUDED_LOCATIONS: + context.log.info( + f"Location {state} is in the default excluded locations. Skipping model run." + f"Excluded locations: {DEFAULT_EXCLUDED_LOCATIONS}" + "Future logic may be customizable." + ) + return + if "w" in model_letters and disease != "COVID-19": + context.log.info( + f"Model letter 'w' is only applicable for COVID-19. Skipping model run for disease {disease}." + ) + return + if "e" in model_letters and state == "WY": + context.log.info( + "Model letter 'e' is not applicable for location WY. Skipping model run." + ) + return + + # Configuration inherited from PyrenewAssetConfig + context.log.debug(f"config: '{config}'") + n_training_days = config.n_training_days + n_samples = config.n_samples + exclude_last_n_days = config.exclude_last_n_days + n_warmup = config.n_warmup + additional_forecast_letters = config.additional_forecast_letters + full_dir = config.full_dir + + if model_family == "pyrenew": + run_script = "forecast_pyrenew.py" + additional_args = ( + f"--n-warmup {n_warmup} " + "--nwss-data-dir nwss-vintages " + "--priors-path pipelines/priors/prod_priors.py " + f"--additional-forecast-letters {additional_forecast_letters} " + ) + elif model_family == "timeseries": + run_script = "forecast_timeseries.py" + additional_args = "" + else: + raise ValueError( + f"Unsupported model family: {model_family}. " + "Supported values are 'pyrenew' and 'timeseries'." + ) + base_call = ( + "/bin/bash -c '" + f"VIRTUAL_ENV=.venv && " + f"uv run python pipelines/{run_script} " + f"--disease {disease} " + f"--loc {state} " + f"--n-training-days {n_training_days} " + f"--n-samples {n_samples} " + "--facility-level-nssp-data-dir nssp-etl/gold " + "--state-level-nssp-data-dir nssp-archival-vintages/gold " + "--param-data-dir params " + f"--output-dir {full_dir} " + "--credentials-path config/creds.toml " + f"--report-date latest " + f"--exclude-last-n-days {exclude_last_n_days} " + f"--model-letters {model_letters} " + "--eval-data-path " + "nssp-etl/latest_comprehensive.parquet " + f"{additional_args}" + "'" + ) + subprocess.run(base_call, shell=True, check=True) + + +# -------------------------------------------------------------------- +# Assets: these are the core of Dagster - functions that specify data +# -------------------------------------------------------------------- + +# -- Upstream Data -- # + +# NOTE: These are placeholder assets representing data ingestion steps. +# In mature productionimplementation, these would contain logic to ingest and process data, +# or sensors to trigger on new data availability. + +@dg.asset +def nhsn_data(context: dg.AssetExecutionContext): + return "nhsn_data" + + +@dg.asset +def nssp_gold(context: dg.AssetExecutionContext): + return "nssp_gold" + + +@dg.asset +def nssp_latest_comprehensive(context: dg.AssetExecutionContext): + return "nssp_latest_comprehensive" + + +@dg.asset +def nwss_data(context: dg.AssetExecutionContext): + return "nwss_data" + + +# Dependency Definitions # + +nssp_deps = ["nssp_gold", "nssp_latest_comprehensive"] + +# -- Pyrenew Assets -- # + +# TODO: adapt materialize results for asset returns. Currently returning simple strings. +# i.e. +# return dg.MaterializeResult( +# value=output_path, +# metadata={ +# "config": config, +# "output_path": output_path, +# "storage_account": STORAGE_ACCOUNT, +# "storage_container": OUTPUT_CONTAINER, +# "blob_path": job_id, +# } +# ) + + +# Timeseries E +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=nssp_deps, +) +def timeseries_e(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="e", model_family="timeseries") + return "timeseries_e" + + +# Pyrenew E +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=["timeseries_e"] + nssp_deps, +) +def pyrenew_e(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="e", model_family="pyrenew") + return "pyrenew_e" + + +# Pyrenew H +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=["nhsn_data"], +) +def pyrenew_h(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="h", model_family="pyrenew") + return "pyrenew_h" + + +# Pyrenew HE +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=["timeseries_e", "nhsn_data"] + nssp_deps, +) +def pyrenew_he(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="he", model_family="pyrenew") + return "pyrenew_he" + + +# Pyrenew HW +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=["nhsn_data", "nwss_data"], +) +def pyrenew_hw(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="hw", model_family="pyrenew") + return "pyrenew_hw" + + +# Pyrenew HEW +@dg.asset( + partitions_def=pyrenew_multi_partition_def, + deps=["timeseries_e"] + nssp_deps + ["nhsn_data", "nwss_data"], +) +def pyrenew_hew(context: dg.AssetExecutionContext, config: PyrenewAssetConfig): + run_pyrenew_model(context, config, model_letters="hew", model_family="pyrenew") + return "pyrenew_hew" + + +# --------------------------------------------------------- # +# Runtime Configuration: Working Directory, Executors +# - Executors define the runtime-location of an asset job +# - See later on for Asset job definitions +# --------------------------------------------------------- #" + +workdir = "pyrenew-hew" +local_workdir = Path(__file__).parent.resolve() +image = "cfaprdbatchcr.azurecr.io/pyrenew-hew:dagster_latest" + +# add this to a job or the Definitions class to use it +docker_executor_configured = docker_executor.configured( + { + # specify a default image + "image": image, + "env_vars": [f"DAGSTER_USER={user}", "VIRTUAL_ENV=/pyrenew-hew/.venv"], + "container_kwargs": { + "volumes": [ + # bind the ~/.azure folder for optional cli login + f"/home/{user}/.azure:/root/.azure", + # bind current file so we don't have to rebuild + # the container image for workflow changes + f"{__file__}:/{workdir}/{os.path.basename(__file__)}", + # blob container mounts for pyrenew-hew + f"/{local_workdir}/nssp-etl:/pyrenew-hew/nssp-etl", + f"/{local_workdir}/nssp-archival-vintages:/pyrenew-hew/nssp-archival-vintages", + f"/{local_workdir}/nwss-vintages:/pyrenew-hew/nwss-vintages", + f"/{local_workdir}/params:/pyrenew-hew/params", + f"/{local_workdir}/config:/pyrenew-hew/config", + f"/{local_workdir}/output:/pyrenew-hew/output", + f"/{local_workdir}/test-output:/pyrenew-hew/test-output", + ] + }, + } +) + +# configuring an executor to run workflow steps on Azure Container App Jobs +# add this to a job or the Definitions class to use it +# Container app jobs cant have mounted volumes, so we would need to refactor pyrenew-hew to use this +azure_caj_executor_configured = azure_caj_executor.configured( + { + "image": image, + "env_vars": [f"DAGSTER_USER={user}", "VIRTUAL_ENV=/pyrenew-hew/.venv"], + } +) + +# configuring an executor to run workflow steps on Azure Batch 4CPU 16GB RAM pool +# add this to a job or the Definitions class to use it +azure_batch_executor_configured = azure_batch_executor.configured( + { + "pool_name": "pyrenew-pool", + "image": image, + "env_vars": [f"DAGSTER_USER={user}", "VIRTUAL_ENV=/pyrenew-hew/.venv"], + "container_kwargs": { + "volumes": [ + # bind the ~/.azure folder for optional cli login + # f"/home/{user}/.azure:/root/.azure", + # bind current file so we don't have to rebuild + # the container image for workflow changes + # blob container mounts for pyrenew-hew + "nssp-archival-vintages:/pyrenew-hew/nssp-archival-vintages", + "nssp-etl:/pyrenew-hew/nssp-etl", + "nwss-vintages:/pyrenew-hew/nwss-vintages", + "prod-param-estimates:/pyrenew-hew/params", + "pyrenew-hew-config:/pyrenew-hew/config", + "pyrenew-hew-prod-output:/pyrenew-hew/output", + "pyrenew-test-output:/pyrenew-hew/test-output", + ], + "working_dir": "/pyrenew-hew", + }, + } +) + +# ----------------------------------------------------------------------------------- # +# Orchestration of Non-Partitioned Assets - Upstream Data ETL +# +# Note that this basic approach only works for non-partitioned assets, +# the models we'll need to schedule more complexly +# ----------------------------------------------------------------------------------- # + +upstream_asset_job = dg.define_asset_job( + name="upstream_asset_job", + executor_def=dg.in_process_executor, # these are lightweight and do not have partitions + selection=["nhsn_data", "nssp_gold", "nssp_latest_comprehensive", "nwss_data"], + # tag the run with your user to allow for easy filtering in the Dagster UI + tags={"user": user}, +) + +# Every wednesday this will run at hours 11 through 20 UTC (6am-3pm EST) +upstream_every_wednesday = dg.ScheduleDefinition( + name="weekly_upstream_cron", cron_schedule="0 11-20 * * WED", job=upstream_asset_job +) + +# ------------------------------------------------------------------------------------------------- # +# Orchestration of Partitioned Assets - Model Runs +# +# Scheduling full pipeline runs and defining a flexible configuration +# We use dagster ops and jobs here to launch asset backfills with custom configuration +# ------------------------------------------------------------------------------------------------- # + +# This is an op (non-materialized asset function) that launches backfills, as used in scheduled jobs +@dg.op +def launch_pipeline( + context: dg.OpExecutionContext, + config: PyrenewAssetConfig, +) -> dg.Output[str]: + + # We are referencing the global pyrenew_multi_partition_def defined earlier + partition_keys = pyrenew_multi_partition_def.get_partition_keys() + + # We select all the assets we want to "backfill" + asset_selection = ( + "timeseries_e", + "pyrenew_e", + "pyrenew_h", + "pyrenew_he", + "pyrenew_hw", + "pyrenew_hew", + ) + + # Launch the backfill + # Returns: a backfill ID, + # side-effect: launches the backfill run in Dagster via a GraphQL query + backfill_id = launch_asset_backfill( + asset_selection, + partition_keys, + run_config=dg.RunConfig({ + "ops": { + **{asset: config for asset in asset_selection}, + } + }), + tags={ + "run": "pyrenew", + } + ) + + context.log.info( + f"Launched backfill with id: '{backfill_id}'. " + "Click the output metadata url to monitor" + ) + return dg.Output( + value=backfill_id, + metadata={ + "url": dg.MetadataValue.url(f"/runs/b/{backfill_id}") + } + ) + +# This wraps our launch_pipeline op in a job that can be scheduled or manually launched via the GUI +@dg.job( + executor_def=dg.multiprocess_executor, + tags={ + "cfa_dagster/launcher": { + "class": dg.DefaultRunLauncher.__name__ + } + }, + config=dg.RunConfig( + ops={ + "launch_pipeline": PyrenewAssetConfig(), + } + ) +) +def weekly_pyrenew(): + launch_pipeline() + + +schedule_weekly_pyrenew = dg.ScheduleDefinition( + default_status=( + dg.DefaultScheduleStatus.RUNNING + # don't run locally by default + if is_production else dg.DefaultScheduleStatus.STOPPED + ), + job=weekly_pyrenew, + cron_schedule="0 12-21 * * WED", + execution_timezone="America/New_York", +) + +# -------------- Dagster Definitions Object --------------- # +# This code allows us to collect all of the above definitions +# into a single Definitions object for Dagster to read! +# By doing this, we can keep our Dagster code in a single file +# instead of splitting it across multiple files. +# --------------------------------------------------------- # + +# change storage accounts between dev and prod +storage_account = "cfadagster" if is_production else "cfadagsterdev" + +# collect Dagster definitions from the current file +collected_defs = collect_definitions(globals()) + +# Create Definitions object +defs = dg.Definitions( + assets=collected_defs["assets"], + asset_checks=collected_defs["asset_checks"], + jobs=collected_defs["jobs"], + sensors=collected_defs["sensors"], + schedules=collected_defs["schedules"], + resources={ + # This IOManager lets Dagster serialize asset outputs and store them + # in Azure to pass between assets + "io_manager": ADLS2PickleIOManager(), + # an example storage account + "azure_blob_storage": AzureBlobStorageResource( + account_url=f"{storage_account}.blob.core.windows.net", + credential=AzureBlobStorageDefaultCredential(), + ), + }, + # setting Docker as the default executor. comment this out to use + # the default executor that runs directly on your computer + # executor=docker_executor_configured, + # executor=dg.in_process_executor, + # executor=azure_caj_executor_configured, + executor=azure_batch_executor_configured, + # uncomment the below to launch runs on Azure CAJ + # metadata={ + # "cfa_dagster/launcher": { + # "class": AzureContainerAppJobRunLauncher.__name__, + # "config": { + # "image": image, + # }, + # } + # }, +) diff --git a/img/dagster_lineage.png b/img/dagster_lineage.png new file mode 100644 index 00000000..b854276f Binary files /dev/null and b/img/dagster_lineage.png differ diff --git a/img/dagster_runs.png b/img/dagster_runs.png new file mode 100644 index 00000000..676d6651 Binary files /dev/null and b/img/dagster_runs.png differ diff --git a/pipelines/batch/setup_job.py b/pipelines/batch/setup_job.py index 9329f8f8..652673e6 100644 --- a/pipelines/batch/setup_job.py +++ b/pipelines/batch/setup_job.py @@ -38,6 +38,7 @@ def main( diseases: str | list[str], output_subdir: str | Path = "./", additional_forecast_letters: str = "", + container_registry: str = "ghcr.io/cdcgov", container_image_name: str = "pyrenew-hew", container_image_version: str = "latest", n_training_days: int = 150, @@ -182,9 +183,11 @@ def main( # =============== # Container Setup # =============== - container_image = f"ghcr.io/cdcgov/{container_image_name}:{container_image_version}" + container_image_full_string = ( + f"{container_registry}/{container_image_name}:{container_image_version}" + ) container_settings = get_container_settings( - container_image, + container_image_full_string, working_directory="containerImageDefault", mount_pairs=[ { @@ -282,9 +285,9 @@ def main( table.add_row("Model Letters", str(model_letters)) table.add_row("Additional Forecast Letters", str(additional_forecast_letters)) table.add_row("Diseases", ", ".join(disease_list)) + table.add_row("Output Storage Container", str(pyrenew_hew_output_container)) table.add_row("Output Subdirectory", str(output_subdir)) - table.add_row("Container Image", str(container_image)) - table.add_row("Container Version", str(container_image_version)) + table.add_row("Container Image Full String", str(container_image_full_string)) table.add_row("Training Days", str(n_training_days)) table.add_row("Exclude Last N Days", str(exclude_last_n_days)) table.add_row("RNG Key", str(rng_key)) @@ -395,6 +398,12 @@ def style_bool(val): ), default="./", ) + parser.add_argument( + "--container-registry", + type=str, + help=("Container registry URL (e.g. ghcr.io/cdcgov) to use for the job."), + default="ghcr.io/cdcgov", + ) parser.add_argument( "--container-image-name", type=str, diff --git a/pyproject.toml b/pyproject.toml index b76e9565..6f74bcad 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,6 +8,7 @@ authors = [ {name = "Damon Bayer", email = "xum8@cdc.gov"}, {name = "Dylan H. Morris"}, {name = "Subekshya Bidari"}, + {name = "Jon Kislin", email = "qxk3@cdc.gov"} ] @@ -27,6 +28,12 @@ dependencies = [ "rich>=14.0.0", "dotenv>=0.9.9", "polarbayes", + "dagster-azure>=0.27.4", + "dagster-docker>=0.27.4", + "dagster-postgres>=0.27.4", + "dagster-webserver==1.12.2", + "dagster==1.12.2", + "cfa-dagster @ git+https://github.com/cdcgov/cfa-dagster.git", ] [build-system] diff --git a/uv.lock b/uv.lock index 254441c7..67521f0a 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 3 +revision = 2 requires-python = ">=3.13" resolution-markers = [ "python_full_version >= '3.14'", @@ -21,6 +21,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/49/8d/58008a9a86075827f99aa8bb75d8db515bb9c34654f95e647cda31987db7/adal-1.2.7-py2.py3-none-any.whl", hash = "sha256:2a7451ed7441ddbc57703042204a3e30ef747478eea022c70f789fc7f084bc3d", size = 55539, upload-time = "2021-04-05T16:33:39.544Z" }, ] +[[package]] +name = "aiofiles" +version = "25.1.0" 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