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https://github.com/hellrungj/squatch-watch
Bare-bones application is to display basic data related to cryptozoological findings in a single place that is easy to view and query by researchers.
https://github.com/hellrungj/squatch-watch
bare-bones-application csv django django-admin django-rest-framework pipenv python3
Last synced: 5 days ago
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Bare-bones application is to display basic data related to cryptozoological findings in a single place that is easy to view and query by researchers.
- Host: GitHub
- URL: https://github.com/hellrungj/squatch-watch
- Owner: Hellrungj
- Created: 2018-11-15T04:05:23.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-06-21T21:34:28.000Z (over 4 years ago)
- Last Synced: 2024-10-30T15:35:08.110Z (about 2 months ago)
- Topics: bare-bones-application, csv, django, django-admin, django-rest-framework, pipenv, python3
- Language: Python
- Homepage:
- Size: 4.37 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
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README
# SQUATCH WATCH
*The truth is in here.*
### Introduction
The point of this bare-bones application is to display basic data related to cryptozoological findings in a single place that is easy to view and query by researchers. Sighting data is added to the system in the form of "reports" – CSV files containing rows for individual sightings. The functionality of the app can be broken into two main components:
- An **HTTP endpoint** that handles requests with a CSV file payload and creates objects for the application from the file
- A **front-end table** that displays all sightings created from CSV data and can be filtered by monster, researcher, or specific report
Additionally, in order to submit data to the application, a separate **HTTP client** (`http_client.py`) is provided to look for files in a directory and send them to the HTTP endpoint.
### Data and schema
Each CSV file contains a row per monster sighting being reported by a researcher. The CSV format is as follows:
```
#"timestamp","researcher","monster","latitude","longitude"
"2018-01-01 23:59:59","Jonathan Barker","Dracula","46.8999964","24.1499994"
```
When a file is submitted, it creates objects that correspond with the application's four models:
- `MonsterReport`: refers to a single CSV report that is comprised of many sightings
- `Sighting`: an instance of a researcher spotting a monster at a specific time and location
- `Researcher`: the human credited with finding the monster (unique across all sightings)
- `Monster`: the monster spotted (unique across all sightings)
To test the app's functionality, sample data is provided in the `sample` folder.
#### DQ Schema
### Installation
Note the python version for the project is 3.8, and this is saved in the `.python-version` file in the project root directory.
1. Install pipenv: `pip install pipenv`
2. Activate the virtual environment: `pipenv shell`
3. Install project dependencies: `pipenv install`
4. Migrate the data: `python manage.py migrate`
5. Run the development server: `python manage.py runserver`
6. Open a brower at [http://127.0.0.1:8080](http://127.0.0.1:8080)