semvec/pypi-packages huggingface dataset:
django-geohashing 0.2.1
Django app for working with XKCD geohashing data
License: MIT License
Keywords: geohashing xkcd django

# django-geohashing

A Django application for calculating geohashes and exposing them 
via RESTful interface. Requires Django 1.8.x+ (takes advantage of
updated argument parsing for custom management commands, see: 
[Django 1.8 Release Notes][1] for more information).

## Installation

Install with pip:

```bash
pip install django-geohashing
```

## Quick Start

1. Add "geohashing"  and "rest_framework" to your INSTALLED_APPS:

    ```python
    INSTALLED_APPS = (
       ...
       'geohashing',
       'rest_framework',
    )
    ```

2. Create the geohashing tables by resyncing your models:

    ```bash
    python manage.py migrate
    ```

3. Populate the table using the `get_historical_djia` management command:

    ```bash
    python manage.py get_historical_djia --start <date> --end <date>
    ```

   The `get_historical_djia` command takes two optional parameters:
   `--start` and `--end`. These parameters accept date strings of the format
   `YYYY-MM-DD`. They may be used to limit the set of results from
   which to database is populated (so for instance to only retrieve and process 
   only the 30 most recent DJIA openings instead of every opening since 1928).

   The parameters are optional but their use is very much encouraged; otherwise 
   tens of thousands of records will be retrieved and imported individually.

4. To expose the geohashing offsets via REST API, include `geohashing.urls` in
   your `urls.py`. Though not strictly required, as a best practice a namespace 
   for the urls should be provided:

    ```python
    from django.conf.urls import url

    urlpatterns = [
        url(r'^geohashing/', include('geohashing.urls', namespace='geohashing')),
    ]
    ```

## TODO

This project is still in an extremely early alpha stage. Tasks that still need 
to be tackled:

- Update the importer to:

    - Handle the creation of new Day objects and the update of existing Day 
      objects seperately so that we can use `bulk_create` to improve 
      performance.
    - Extrapolate data points beyond the maximum date when enough information
      is available to do so.
    - Add a `get_current_djia` management command to be used for retrieving
      today's opening value. Occasionally the various sources for the opening 
      value are initially inconsistent with one another. The management command 
      should handle this gracefully by waiting for consensus.

- Add unit tests and docs
- Run Flake8 against the codebase and fix any glaring PEP-8 violations
- Set up Continuous Integration...integration

[1]: https://docs.djangoproject.com/en/1.8/releases/1.8/#extending-management-command-arguments-through-command-option-list