A connector to connect to the Lizard-API (https://demo.lizard.net/api/v2/) with Python.
Project description
lizard-connector
================
Introduction
------------
Connector to Lizard api (e.g. https://demo.lizard.net/api/v3) for python.
Includes:
- Client (experimental / alpha)
- Endpoint (Easy access to Lizard api endpoints)
- Connector (http handling)
- parsers to parse the json obtained from Endpoint queries
- queryfunctions for special cases such as geographical queries and time
related queries other queries can be input as a dictionary
- callbacks for async data handling.
When pandas, numpy are installed the Client returns `pandas.DataFrame`s and/or
`numpy.array`s in a `ScientifResult` object.
Example usage
-------------
An example jupyter notebook can be found `Example_EN.ipynb` or in Dutch:
`Voorbeeld_NL.ipynb`.
Use one endpoints https://demo.lizard.net/api/v2 in Python with the Endpoint
class::
from lizard_connector import Client
import lizard_connector.queries
import datetime
# Fill in your username and password (your password will be prompted)
client = lizard_connector.Client(
username = "example.username"
)
endpoint = 'timeseries'
south_west = [48.0, -6.8]
north_east = [56.2, 18.9]
organisation_id = 'example_organisation_uuid'
start = datetime.datetime(1970, 1, 1)
end = datetime.datetime.now()
relevant_queries = [
lizard_connector.queries.in_bbox(south_west, north_east, endpoint),
lizard_connector.queries.organisation(organisation_id, endpoint),
lizard_connector.queries.datetime_limits(start, end)
]
results = client.timeseries.get(*relevant_queries)
Usage with PyQT (for Qgis plugins)
----------------------------------
You can create a QThread worker like so::
from PyQt4.QtCore import QThread
from PyQt4.QtCore import pyqtSignal
class Worker(QThread):
"""This class creates a worker thread for getting the data."""
output = pyqtSignal(object)
def __init__(self, parent=None, endpoint=None, *querydicts, **queries):
"""Initiate the Worker."""
super(Worker, self).__init__(parent)
self._endpoint = endpoint
self._querydicts = querydicts
self._queries = queries
def run(self):
"""Called indirectly by PyQt if you call start().
This method retrieves the data from Lizard and emits it via the
output signal as dictionary.
"""
data = self._endpoint._synchronous_get_async(
*self._querydicts, **self._queries)
self.output.emit(data)
Credits
=======
- roel.vandenberg@nelen-schuurmans.nl started this library
Changelog of lizard-connector
===================================================
0.7 (2018-04-17)
----------------
- Added Client.
- Added parsers (scientific, json).
- Added callbacks.
- Renamed Endpoint `download...` methods to `get...`.
0.6 (2018-02-07)
----------------
- Add explicit py2/3 imports to mitigate problems with the ``future`` library.
0.5 (2017-10-16)
----------------
- Compatible with python 2.7.
- Refactored pagination.
- Added Async downloads with callback.
- Removes max_result on Endpoint initialisation.
0.4 (2016-06-05)
----------------
- Fixed bug in iteration over paginated results.
- When all_pages is set to False all methods involving get return the object as
an iterator.
0.3 (2016-05-06)
----------------
- Http base urls are not allowed, throws exception when baseurl is not secure
(i.e. does not start with https).
- Fixed a bug that caused a get to run two times.
0.2 (2016-05-04)
----------------
- Added Datatype classes.
- Renamed Endpoint get and post to download and upload.
0.1 (2016-03-29)
----------------
- Basic setup
- Added tests
- Initial project structure created with nensskel 1.37.dev0.
================
Introduction
------------
Connector to Lizard api (e.g. https://demo.lizard.net/api/v3) for python.
Includes:
- Client (experimental / alpha)
- Endpoint (Easy access to Lizard api endpoints)
- Connector (http handling)
- parsers to parse the json obtained from Endpoint queries
- queryfunctions for special cases such as geographical queries and time
related queries other queries can be input as a dictionary
- callbacks for async data handling.
When pandas, numpy are installed the Client returns `pandas.DataFrame`s and/or
`numpy.array`s in a `ScientifResult` object.
Example usage
-------------
An example jupyter notebook can be found `Example_EN.ipynb` or in Dutch:
`Voorbeeld_NL.ipynb`.
Use one endpoints https://demo.lizard.net/api/v2 in Python with the Endpoint
class::
from lizard_connector import Client
import lizard_connector.queries
import datetime
# Fill in your username and password (your password will be prompted)
client = lizard_connector.Client(
username = "example.username"
)
endpoint = 'timeseries'
south_west = [48.0, -6.8]
north_east = [56.2, 18.9]
organisation_id = 'example_organisation_uuid'
start = datetime.datetime(1970, 1, 1)
end = datetime.datetime.now()
relevant_queries = [
lizard_connector.queries.in_bbox(south_west, north_east, endpoint),
lizard_connector.queries.organisation(organisation_id, endpoint),
lizard_connector.queries.datetime_limits(start, end)
]
results = client.timeseries.get(*relevant_queries)
Usage with PyQT (for Qgis plugins)
----------------------------------
You can create a QThread worker like so::
from PyQt4.QtCore import QThread
from PyQt4.QtCore import pyqtSignal
class Worker(QThread):
"""This class creates a worker thread for getting the data."""
output = pyqtSignal(object)
def __init__(self, parent=None, endpoint=None, *querydicts, **queries):
"""Initiate the Worker."""
super(Worker, self).__init__(parent)
self._endpoint = endpoint
self._querydicts = querydicts
self._queries = queries
def run(self):
"""Called indirectly by PyQt if you call start().
This method retrieves the data from Lizard and emits it via the
output signal as dictionary.
"""
data = self._endpoint._synchronous_get_async(
*self._querydicts, **self._queries)
self.output.emit(data)
Credits
=======
- roel.vandenberg@nelen-schuurmans.nl started this library
Changelog of lizard-connector
===================================================
0.7 (2018-04-17)
----------------
- Added Client.
- Added parsers (scientific, json).
- Added callbacks.
- Renamed Endpoint `download...` methods to `get...`.
0.6 (2018-02-07)
----------------
- Add explicit py2/3 imports to mitigate problems with the ``future`` library.
0.5 (2017-10-16)
----------------
- Compatible with python 2.7.
- Refactored pagination.
- Added Async downloads with callback.
- Removes max_result on Endpoint initialisation.
0.4 (2016-06-05)
----------------
- Fixed bug in iteration over paginated results.
- When all_pages is set to False all methods involving get return the object as
an iterator.
0.3 (2016-05-06)
----------------
- Http base urls are not allowed, throws exception when baseurl is not secure
(i.e. does not start with https).
- Fixed a bug that caused a get to run two times.
0.2 (2016-05-04)
----------------
- Added Datatype classes.
- Renamed Endpoint get and post to download and upload.
0.1 (2016-03-29)
----------------
- Basic setup
- Added tests
- Initial project structure created with nensskel 1.37.dev0.
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