https://github.com/elhanarinc/housedata-challenge
Challenge written with Django Framework
https://github.com/elhanarinc/housedata-challenge
django pip postgresql python3 virtualenv
Last synced: about 1 month ago
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Challenge written with Django Framework
- Host: GitHub
- URL: https://github.com/elhanarinc/housedata-challenge
- Owner: elhanarinc
- License: gpl-3.0
- Created: 2018-12-22T15:28:03.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-01-26T11:30:12.000Z (over 6 years ago)
- Last Synced: 2025-01-29T22:27:41.360Z (3 months ago)
- Topics: django, pip, postgresql, python3, virtualenv
- Language: Python
- Homepage:
- Size: 34.2 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Django Challenge
Coding challenge written with Django Framework.
This project assumes you had already installed these tools:
1. [python 3](https://realpython.com/installing-python/)
2. [pip](https://www.makeuseof.com/tag/install-pip-for-python/)
3. [postgresql](http://postgresguide.com/setup/install.html)
After necessary tools, you need to install the `sold house pricing` dataset from [here](https://data.gov.uk/dataset/4c9b7641-cf73-4fd9-869a-4bfeed6d440e/hm-land-registry-price-paid-data).
Then you need to add header row for this raw data by using command below on terminal:
* `echo 'transaction_unique_identifier,price,date_of_transfer,postcode,property_type,old_or_new,duration,paon,saon,street,locality,town,district,country,ppd_category_type,record_status' | cat - latest.csv > temp && mv temp latest.csv`
In order to use django with postgresql, you need to follow this [link](https://www.digitalocean.com/community/tutorials/how-to-use-postgresql-with-your-django-application-on-ubuntu-14-04).
First we need to create a `virtualenv` by using below commands:
* `virtualenv venv -p [python3 location like /usr/local/bin/python3]`
* `source venv/bin/activate`
* Go to the project directory like `cd /home/challenge-directory/`
* `pip install -r requirements.txt`
Below are the commands that is need for populating the empty postgresql table, then running the API:
* `python manage.py makemigrations`
* `python manage.py migrate`
* `python manage.py populate_db [file-location]`
* `python manage.py runserver`
There are two endpoints for timeseries and histogram:
1. `/timeseries`:
This endpoint only accepts *GET* request and params are:
```
{
"postcode": required,
"from_date": optional (format: [Month Year]),
"to_date": optional (example: September 2018)
}
```
2. `/histogram`:
This endpoint only accepts *GET* request and params are:
```
{
"postcode": required,
"date": optional (format: [Month Year], example: September 2018)
}
```
Tools used for deploying and serving endpoints:
1. [Microsoft Azure VM](https://azure.microsoft.com/tr-tr/services/virtual-machines/)
2. [gunicorn](https://gunicorn.org/)
3. [nginx](https://www.nginx.com/)
4. [supervisor](http://supervisord.org/introduction.html)