Metadata-Version: 2.4
Name: a5_client
Version: 0.1.19
Summary: a5 api client for python
Home-page: https://github.com/jbianchi81/a5_client
Author: Juan F. Bianchi
Author-email: SSIyAH-INA <jbianchi@ina.gob.ar>
License: MIT License
        
        Copyright (c) 2023 jbianchi81
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, http://github.com/jbianchi81/a5client
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: jsonschema
Requires-Dist: requests
Requires-Dist: datetime
Requires-Dist: pyyaml
Dynamic: author
Dynamic: home-page

# a5 api client library
This is a Python client library to work against a [alerta5DBIO API](https://github.com/jbianchi81/alerta5DBIO.git) instance developed by [Instituto Nacional del Agua](https://www.ina.gob.ar), such as the one deployed [here](https://alerta.ina.gob.ar/a5).
## Installation
```bash
# set environment
python3 -m venv .
source bin/activate
## Install from pip
pip install a5-client
## Or clone git repo
clone https://github.com/jbianchi81/a5client.git
cd a5client
pip install .
```
#### Config file location
- **Linux**: $HOME/.a5client.ini
- **Windows**: %USERPROFILE%/.a5client.ini 
- **MacOS**: $HOME/.a5client.ini
#### Default log file location (may be changed in config file)
- **Linux**: $HOME/.local/share/a5client/logs/a5client.log
- **Windows**: %LOCALAPPDATA%/a5client/logs/a5client.log
- **MacOS**: $HOME/Library/Logs/a5client/a5client.log
### Config file example
```
[log]
  filename = /var/log/a5client.log
[server]
  url = http://localhost:3005
  token = my.access.token
```
## Use
```python
from datetime import datetime, timedelta
from a5client import Crud
# Instantiate client
client = Crud(url="A5_API_ENDPOINT_URL", token="YOUR_PERSONAL_TOKEN")
```
### Methods
```python
# READ actions
# Retrieve observations metadata
series = client.readSeries(
    var_id=2
)

# retrieve stations metadata
stations = client.readEstaciones()

# retrieve area metadata
area = client.readArea(1)

# retrieve variable metadata
var = client.readVar(2)

# retrieve observations data
serie = client.readSerie(
    series_id=29, 
    timestart="2020-01-01T03:00:00.000Z", 
    timeend="2021-01-01T03:00:00.000Z"
)

# retrieve simulation configuration
calibrado = client.readCalibrado(289)

# retrieve forecast metadata
corridas = client.readCorridas(289)

# retrieve forecast data, only last run
serie_forecast = client.readSerieProno(
    cal_id=289,
    series_id=3526
)

# retrieve forecast data, concatenate runs
serie_forecast = client.readSeriePronoConcat(
    cal_id=289,
    series_id=3526,
    forecast_timestart = datetime.now() - timedelta(days=20)
)

# WRITE actions
# create sites (stations, areas, scenes)
created_sites = client.createSites(
    [
        {
            "nombre": "my_station_name",
            "id": 11111111,
            "geom": {
                "type": "Point",
                "coordinates": [ -55.55, -33.33 ]
            },
            "tabla": "alturas_varios"   
        }
    ],
    tipo="estaciones",
    format="json"
)

# create series
created_series = client.createSeries(
    [
        {
            "tipo": "puntual",
            "id": 22222222,
            "estacion": created_sites[0],
            "var": {"id": 2},
            "procedimiento": {"id": 1},
            "unidades": {"id": 11}
        }
    ]
)

# create observations
import pandas as pd 
observations = pd.DataFrame({
        "valor": [1.11, 2.22, 3.33]
    },
    index = pd.date_range(start="2024-01-01 00:00", periods=3, freq='h', tz="UTC")
)
created_observations = client.createObservaciones(
    observations,
    series_id = created_series[0]["id"],
    tipo="puntual"
)

# Create simulation run
from a5client import observacionesDataFrameToList
forecasts = pd.DataFrame({
        "valor": [1.21, 2.32, 3.43]
    },
    index = pd.date_range(start="2024-01-01 00:00", periods=3, freq='h', tz="UTC")
)
forecast_run = {
    "forecast_date": "2024-01-01 00:00",
    "series": [
        {
            "series_table": "series",
            "series_id": created_series[0]["id"],
            "pronosticos": observacionesDataFrameToList(forecasts, series_id=created_series[0]["id"])
        }
    ]
}
created_run = client.createCorrida(
    forecast_run,
    cal_id = 507
)
```
### Auxiliary functions
```python
from a5client import observacionesDataFrameToList, observacionesListToDataFrame, geojsonToList
from datetime import datetime
# DataFrame to list of dict (a5 schema)
observaciones = pd.DataFrame({
        "valor": [1.21, 2.32, 3.43]
    },
    index = pd.date_range(start="2024-01-01 00:00", periods=3, freq='h', tz="UTC")
)
df = observacionesDataFrameToList(observaciones, series_id = 3333333)

# list of dict (a5 schema) to DataFrame
df = observacionesListToDataFrame([
    {
        "timestart": datetime(2024,1,1,0),
        "valor": 5.55
    },
    {
        "timestart": datetime(2024,1,1,1),
        "valor": 4.44
    },
    {
        "timestart": datetime(2024,1,1,2),
        "valor": 3.33
    }
])

# GeoJSON dict to list of sites dict (a5 schema)
sites = geojsonToList({
    "type": "FeatureCollection",
    "features": [
        {
            "geometry": {
                "type": "Point",
                "coordinates": [-55.55, -33.33]
            },
            "properties": {
                "nombre": "my_station_name",
                "id": 555555,
                "tabla": "my_provider_name"
            }
        }
    ]
})
```
## TO DO
- Update methods
- Delete methods
