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add integration test
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‎.github/workflows/integration-test.yml‎

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name: integration-test
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on:
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push:
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jobs:
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docker-build-and-test:
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name: Build Docker and Test Server
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runs-on: ubuntu-latest
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env:
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GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
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NOAA_TOKEN: ${{ secrets.NOAA_TOKEN }}
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steps:
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- name: Checkout Code
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uses: actions/checkout@v3
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- name: Set up Docker
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uses: docker/setup-buildx-action@v2
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- name: Build Docker Image
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run: |
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docker build -t bsyncr-server .
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- name: Run Docker Container
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run: |
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docker run -p 8080:5000 bsyncr-server
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echo "Docker container started successfully"
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- name: Extra wait
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run: |
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sleep 10
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- name: Health check
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run: |
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curl -f http://localhost:8080/health || exit 1
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- name: Post BuildingSync file
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run: |
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curl -X POST "http://localhost:8080/?model_type=SLR" \
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-F "file=@tests/data/ex_bsync.xml" \
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--max-time 120 \
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--output ./tests/slr_results.zip
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# check if the slr_results.zip file exists, error if not
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if [ ! -f ./tests/slr_results.zip ]; then
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echo "Error: slr_results.zip not found!"
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exit 1
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fi
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echo "slr_results.zip file exists, proceeding with next steps."
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- name: Cleanup Docker Container
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run: |
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docker stop bsyncr-server
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docker rm bsyncr-server

‎.gitignore‎

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.DS_Store
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.python-version
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.vscode
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.ruff_cache
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node_modules
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tests/*.zip

‎README.md‎

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# bsyncr server
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3-
A light HTTP wrapper around the bsyncr R package.
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A light HTTP wrapper around the `bsyncr` R package.
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## Setup
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```bash
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# run the server on localhost:5000
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docker run -p 5000:5000 -v $(pwd):/usr/src/app -e NOAA_TOKEN=YOUR_TOKEN_HERE bsyncr_server:latest
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export NOAA_TOKEN=<YOUR_TOKEN>
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docker run -p 5000:5000 -v $(pwd):/usr/src/app -e NOAA_TOKEN bsyncr_server:latest
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# run the server along with SEED (assuming SEED is being run with docker-compose)
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docker run \
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--network="seed_default" \
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--name="bsyncr-server" \
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-e NOAA_TOKEN=$NOAA_TOKEN \
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-e NOAA_TOKEN \
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seedplatform/bsyncr-server:latest
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```
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## Running Example with Curl
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To post via CURL for easy testing:
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```bash
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curl -X POST "http://localhost:8080/?model_type=SLR" \
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-F "file=@tests/data/ex_bsync.xml" \
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--max-time 120 \
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--output ./tests/slr_results.zip
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curl -X POST "http://localhost:8080/?model_type=3PH" \
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-F "file=@tests/data/ex_bsync.xml" \
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--max-time 120 \
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--output ./tests/3ph_results.zip
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```
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## Running Example with Python
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To post via python using requests:
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```python
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import requests
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with open("tests/data/ex_bsync.xml", "rb") as file_:
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response = requests.request(
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method="POST",
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url="http://localhost:8080/",
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files=[("file", file_)],
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params={"model_type": "4P"}, # can be SLR, 3PC, 3PH, 4P
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timeout=60 * 2, # timeout after two minutes
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)
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print(response.status_code)
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print(response.text)
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```

‎bsyncr_server/__init__.py‎

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from io import BytesIO
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import json
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from os import path
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import subprocess
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import tempfile
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import zipfile
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from testsuite.validate_sch import validate_schematron
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from flask import Flask, jsonify, send_file, request
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app = Flask(__name__)
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R_SCRIPT_PATH = "/usr/src/app/bsyncr_server/lib/bsyncRunner.r"
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SCHEMATRON_FILE_PATH = "/usr/src/schematron/bsyncr_schematron.sch"
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INPUT_FILE_PATH = "/tmp/input.xml"
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OUTPUT_FILENAMES = ["result.xml", "plot.png"]
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ERROR_FILENAME = "error.json"
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MODEL_CHOICES = ["SLR", "3PC", "3PH", "4P"]
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def json_error(status_code, detail):
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return {"errors": [{"status": str(status_code), "detail": detail}]}, status_code
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@app.route("/", methods=["POST"])
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def root():
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if "file" not in request.files:
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return json_error(400, "No file in request")
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uploaded_file = request.files["file"]
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uploaded_file.save(INPUT_FILE_PATH)
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try:
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errors = validate_schematron(SCHEMATRON_FILE_PATH, INPUT_FILE_PATH)
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except Exception as e:
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print(e)
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return json_error(400, "Failed to run schematron. Is your XML well-formed?")
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if errors:
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def format_failure(failure):
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return f"line {failure.line}: element {failure.element}: {failure.message}"
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json_errors = [
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{"detail": format_failure(error), "status": "400"} for error in errors
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]
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return {"errors": json_errors}, 400
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model_type = request.args.get("model_type")
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if model_type is None:
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return json_error(
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400,
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f"Invalid value for `model_type` query parameter. "
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f"Must provide one of the following: {', '.join(MODEL_CHOICES)}",
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)
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with tempfile.TemporaryDirectory() as tmpdirname:
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completed_process = subprocess.run(
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["Rscript", R_SCRIPT_PATH, INPUT_FILE_PATH, model_type, tmpdirname],
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)
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if completed_process.returncode != 0:
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error_filepath = f"{tmpdirname}/{ERROR_FILENAME}"
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if not path.exists(error_filepath):
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raise Exception(f'Expected to find error json at "{error_filepath}"')
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with open(error_filepath, "r") as f:
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r_error = json.load(f)
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return json_error(
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500, f"Unexpected error from bsyncr script: {r_error['message']}"
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)
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zip_file = BytesIO()
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with zipfile.ZipFile(zip_file, "w") as zf:
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for filename in OUTPUT_FILENAMES:
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zf.write(f"{tmpdirname}/{filename}", arcname=filename)
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zip_file.seek(0)
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return send_file(zip_file, attachment_filename="bsyncr.zip")
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@app.route("/health", methods=["GET"])
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def health_check():
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return jsonify({"status": "healthy"}), 200

bsyncr_server/lib/bsyncRunner.r renamed to bsyncr_server/lib/bsync_runner.r

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library("nmecr")
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library("bsyncr")
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library("rjson")
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library("dplyr")
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library("ggplot2")
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run_analysis <- function(bsync_filepath, model_type) {
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baseline_scenario_id <- "Scenario-bsyncr"
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args <- commandArgs(trailingOnly=TRUE)
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if (length(args) != 3) {
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print('USAGE:')
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print('Rscript bsyncRunner.r bsync_input model_type output_directory')
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print('Rscript bsync_runner.r bsync_input model_type output_directory')
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print(' bsync_input: path to input file')
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print(' model_type: type of model to fit')
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print(' output_directory: directory to output files')

‎bsyncr_server/main.py‎

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app = Flask(__name__)
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R_SCRIPT_PATH = "/usr/src/app/bsyncr_server/lib/bsyncRunner.r"
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R_SCRIPT_PATH = "/usr/src/app/bsyncr_server/lib/bsync_runner.r"
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SCHEMATRON_FILE_PATH = "/usr/src/schematron/bsyncr_schematron.sch"
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INPUT_FILE_PATH = "/tmp/input.xml"
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OUTPUT_FILENAMES = ["result.xml", "plot.png"]
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zf.write(f"{tmpdirname}/{filename}", arcname=filename)
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zip_file.seek(0)
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return send_file(zip_file, attachment_filename="bsyncr.zip")
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return send_file(zip_file, download_name="bsyncr.zip", as_attachment=True)
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@app.route("/health", methods=["GET"])

‎cspell.json‎

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{
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"version": "0.2",
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"ignorePaths": [],
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"dictionaryDefinitions": [],
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"dictionaries": [],
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"words": [
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"Arvada",
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"balancepoint",
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"bsync",
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"bsyncr",
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"crul",
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"dataframe",
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"datatypeid",
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"dplyr",
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"Drybulb",
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"elec",
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"NMEC",
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"nmecr",
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"NOAA",
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"noaakey",
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"rnoaa",
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"testthat",
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"tidyr"
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],
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"ignoreWords": [],
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"import": []
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}

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