update script
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README.md
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README.md
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[](https://app.netlify.com/sites/auditorytraining/deploys)
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# Auditory Training Resources
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<p align="center">
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<img src="assets/atr_table.png" width="800" />
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</p>
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## Purpose
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There are many auditory training resources that often have unique requirements. A patient may require an Android application, or help with a specific skill. The patient may also already be at a specific skill level, and want a resource that is more challenging or easier depending on age group. The goal of this application is to provide an accessible website for patients and providers to easily find recommendations for auditory training development resources based on their unique requirements.
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## Production Deployment
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### Docker Method
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Currently this is being deployed through docker on a single VPS. Using the included docker-compose you can start the production server with the following command:
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```sh
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docker-compose up --build -d
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```
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This should deploy the instance on localhost:1234
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I have this hosted behind a reverse proxy (nginx) which routes traffic from the auditorytraining.info URI to localhost:1234. You can of course change this to any port that works best in your configuration!
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@ -20,12 +27,14 @@ I have this hosted behind a reverse proxy (nginx) which routes traffic from the
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A more permanent hosting solution through the University is in the works.
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### Netlify
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As of recently, the project has been migrated to netlify enabling us to automate the deployment process and provide a more reliable experience for the end user.
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## Directory Breakdown
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Many directories have associated README's to provide related directory information.
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- ***src/*** - source directory for nextjs frontend/backend application.
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- ***data/*** - Non-application (application referring to excelProcessor or frontend) specific data such as the ATR data excel sheet which has multiple uses in each application.
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- ***prisma/*** - Prisma schema and seeding of admin account (specified in env).
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- ***excelProcessor/*** - Main excel processing backend server and CLI utility for uploading the ATR data excel sheet to MongoDB.
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- **_src/_** - source directory for nextjs frontend/backend application.
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- **_data/_** - Non-application (application referring to excelProcessor or frontend) specific data such as the ATR data excel sheet which has multiple uses in each application.
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- **_prisma/_** - Prisma schema and seeding of admin account (specified in env).
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- **_excelProcessor/_** - Main excel processing backend server and CLI utility for uploading the ATR data excel sheet to MongoDB.
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# Data
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Backend data is placed in this repository. Currently this consists of the auditory training resources
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Utilize `base_template.xlsx` as your starting point when creating auditory training resource data in excell form. This structure is what the upload script will look for. If your excell sheet is missing any of these required fields the sheet parser will fail and notify you that the upload could not complete.
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# Data
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Backend data is placed in this repository. Currently this consists of the auditory training resources
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Utilize `base_template.xlsx` as your starting point when creating auditory training resource data in excell form. This structure is what the upload script will look for. If your excell sheet is missing any of these required fields the sheet parser will fail and notify you that the upload could not complete.
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version: '3'
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version: "3"
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services:
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uiowa-atr:
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# Importing Data
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The purpose of the import script is to take the formatted excel sheet (found in /data/atr_data.xlsx) and upload it to the remote mongoDB server.
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# Tutorial
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This script is currently in early stages and was initially designed to simplify uploading the assets until a more permanent web UI could be built for the task. Therefore this utility is very low-level and likely requires some tinkering outside its intended use case.
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## Setup
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1. Open import/main.py
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2. Configure the two globals:
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```python
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MONGO_URL = "enter mongo DB URL"
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MONGO_DB = "name of DB"
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```
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3. Make sure dependencies are intalled with `poetry install`
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## Run
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The script takes one parameter which is simply the path of your excel sheet.
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```sh
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poetry run python import/main.py $PATH
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```
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For example; if uploading the data provided in this repository you can run the following:
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```sh
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poetry run python import/main.py ../data/atr_data.xlsx
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```
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You should see output showing the individual objects it extracted from your excel sheet along with a success message at the end.
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# Expected Data Format
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See {project_root}/data/atr_data.xlsx
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# Importing Data
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The purpose of the import script is to take the formatted excel sheet (found in /data/atr_data.xlsx) and upload it to the remote mongoDB server.
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# Tutorial
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This script is currently in early stages and was initially designed to simplify uploading the assets until a more permanent web UI could be built for the task. Therefore this utility is very low-level and likely requires some tinkering outside its intended use case.
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## Setup
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1. Open import/main.py
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2. Configure the two globals:
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```python
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MONGO_URL = "enter mongo DB URL"
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MONGO_DB = "name of DB"
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```
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3. Make sure dependencies are intalled with `poetry install`
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## Run
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The script takes one parameter which is simply the path of your excel sheet.
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```sh
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poetry run python import/main.py $PATH
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```
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For example; if uploading the data provided in this repository you can run the following:
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```sh
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poetry run python import/main.py ../data/atr_data.xlsx
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```
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You should see output showing the individual objects it extracted from your excel sheet along with a success message at the end.
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# Expected Data Format
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See {project_root}/data/atr_data.xlsx
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@ -25,7 +25,7 @@ const MyApp: AppType<{ session: Session | null }> = ({
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<script
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defer
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src="https://analytics.brandonegger.com/script.js"
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data-website-id="121b7ea1-1851-437f-9f3d-4e376487bea0"
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data-website-id="3e1b5a25-9eb9-4dc5-a1d2-259bf73b847f"
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></script>
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) : null}
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</Head>
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@ -5,30 +5,30 @@ const config = {
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extend: {
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keyframes: {
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expand_in_out: {
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'0%, 100%': { transform: 'scale(1)' },
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'50%': { transform: 'scale(1.1)' },
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"0%, 100%": { transform: "scale(1)" },
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"50%": { transform: "scale(1.1)" },
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},
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slide_left_full: {
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'0%': { transform: 'translate(0%)' },
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'100%': { transform: 'translate(-50%)' },
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"0%": { transform: "translate(0%)" },
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"100%": { transform: "translate(-50%)" },
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},
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slide_right_full: {
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'0%': { transform: 'translate(-50%)' },
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'100%': { transform: 'translate(0%)' },
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"0%": { transform: "translate(-50%)" },
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"100%": { transform: "translate(0%)" },
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},
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wiggle_rotate: {
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'0%, 60%, 100%': { transform: 'rotate(0deg)' },
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'42%': { transform: 'rotate(-6deg)' },
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'50%': { transform: 'rotate(4deg)' },
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'6%, 30%': { transform: 'rotate(24deg)' },
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'18%': { transform: 'rotate(-12deg)' },
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"0%, 60%, 100%": { transform: "rotate(0deg)" },
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"42%": { transform: "rotate(-6deg)" },
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"50%": { transform: "rotate(4deg)" },
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"6%, 30%": { transform: "rotate(24deg)" },
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"18%": { transform: "rotate(-12deg)" },
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},
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},
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animation: {
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expand_in_out: 'expand_in_out 2s ease-in-out infinite',
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slide_search_page: 'slide_left_full 0.5s ease-in-out',
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slide_search_page_backwards: 'slide_right_full 0.5s ease-in-out',
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hand_wave: 'wiggle_rotate 1.5s ease-in-out infinite',
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expand_in_out: "expand_in_out 2s ease-in-out infinite",
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slide_search_page: "slide_left_full 0.5s ease-in-out",
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slide_search_page_backwards: "slide_right_full 0.5s ease-in-out",
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hand_wave: "wiggle_rotate 1.5s ease-in-out infinite",
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},
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},
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},
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