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bicidata-0.0.4
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bicidata is a framework to work with the General Bikeshare Feed Specification (GBFS)
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | bicidata-0.0.4 |
| نام | bicidata |
| نسخه کتابخانه | 0.0.4 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Ismael Benito Altamirano |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://github.com/bicidata/bicidata |
| آدرس اینترنتی | https://pypi.org/project/bicidata/ |
| مجوز | - |
# bicidata
`bicidata` from `bici` the equivalent of `bike` in Spanish, Catalan, Portuguese or Galician.
`bici` is pronounced in two syllables `bi-ci`, which can be pronounced as something similar to
`be-cy` or `be-thy` for a English speaker. The first one approximates better to Catalan,
Portuguese and Latin Spanish, the second one to Spanish and Galician.
`bicidata` is a framework to work with the [General Bikeshare Feed Specification](https://github.com/NABSA/gbfs/blob/master/gbfs.md#gbfsjson)
(GBFS) data and aims to develop several services to collect, process and publish data from GBFS
feeds different front-ends, such as, social media bots, etc.
It is based upon Python 3, with a very unstable package API until v1.0.0 is reached. You may
use the code here, but I must warn you we are in the early stage of development.
## Installation
You can use a deployed PyPI version of `bicidata`:
```
pip install bicidata
```
However, that version may be outdated, so I recommend to install directly from GitHub:
```
pip install git+https://github.com/bicidata/bicidata.git
```
Or, if you want to have access to the code to develop new features (PRs are welcome!):
```
git clone https://github.com/bicidata/bicidata.git & cd bicidata
pip install -e .
```
## Services
`bicidata` it is thought as a framework to provide services to work with GBFS data. These
services could run together as a Python app or be launched alone (i.e. dockerized).
Thus, scalability will be one of the main goals of `bicidata`. Some services have already profiled:
- **Snapshots:** as GBFS data is updated in "real-time" and it is not stored we need to do it
for ourselves.
- **Archivers:** assuming GBFS data is stored in raw JSON format, and a snapshot is taken
every minute, the amount of data per day reaches around ~200MB for the city of Barcelona. So,
some kind of data preprocessing is needed, it could be something as zipper, or something more
powerful, as data bases.
- **Reporters:** we want data with swag, so we will create _reports_ with the available data.
- **Publishers:** and finally we want the data to become available to the public.
### Snapshots
This is the first service that is being implemented, it creates snapshots of a given GBFS API
at the current timestamp.
Run
```
python -m bicidata.services.snapshot
```
and it will create a snapshot of a live GBFS API in you filesystem to acquire its data. If
you want to loop it, you perfectly can do something like this from inside Python:
```python
import time
from bicidata.services.snapshot import Snapshot, GBFSOnlineResource, FileStorageSaver
num_snapshots = 60
snapshot_sample_time = 60 # time in seconds
snapshot = Snapshot(
GBFSOnlineResource("https://barcelona.publicbikesystem.net/ube/gbfs/v1/gbfs.json"),
FileStorageSaver(),
)
for _ in range(60):
snapshot.run()
time.sleep(snapshot_sample_time)
```
To consume the acquired data, you will find some examples at the `scripts/` folder. To
check for an advanced snap-shooter, consider run the `server` app.
### Archivers
For the moment, there are any services to compress the data to more advanced structures
than JSON, but I'm playing with pandas and xarray at `scripts/create_dataset.py`,
so take a look if you want!
### Reporters
Same here, there is a compiled dataset in the repo, so, if you want to play with it, feel
free, at `scripts/scripts.py` you will find this to start playing with:
```python
import pandas as pd
import xarray as xr
dataset = xr.open_dataset("data/gbfs_bcn_dump_20200925.dat")
capacity = int(dataset.capacity.sum())
print(f"'Bicing' total capacity: {capacity}")
max_bikes_available = int(dataset.num_bikes_available.sum("station_id").max())
print(f"'Bicing' max bikes available: {max_bikes_available}")
when_max_bikes_available = pd.to_datetime(
dataset.times[dataset.num_bikes_available.sum("station_id").argmax()].values
)
print(f"When max bikes are available in UTC+0: {when_max_bikes_available}")
```
With should produce something like:
```
'Bicing' total capacity: 13328
'Bicing' max bikes available: 4116
When max bikes are available in UTC+0: 2020-09-25 01:35:09
```
## Server
All services are planed to run in a server instance, this server first will be implemented
in python, but the idea is to run it using docker-compose or kubernetes, at some point...
Now, it is implemented as a 24h snap-shooter,this will change soon with
a more elegant way to run it. For the moment:
```
python -m bicidata.apps.server
```
You can configure the server changing the `.env.template` to `.env` and placing there your
desired configuration.
نحوه نصب
نصب پکیج whl bicidata-0.0.4:
pip install bicidata-0.0.4.whl
نصب پکیج tar.gz bicidata-0.0.4:
pip install bicidata-0.0.4.tar.gz