Source code for usgs

__author__ = 'nicksantos'

	Handles all interfacing with USGS, with the goal of making (parts) of their JSON
	API available to Python as native objects

import urllib
import urllib2
import json

	import pandas
	pass # silently fail - user won't care. Once we add a more robust logging option, we can silently log

[docs]class gage():
[docs] def __init__(self, site_code = None, time_period = "P7D", url_params = {}): """ :param site_code: A USGS Site code for the gage this object represents. See `the USGS documentation <>`_ :param time_period: A compatible period string as specified in `the USGS time period documentation <>`_ - this parameter only accepts "period" values as explained in that documentation. If you would like to specify a time range using startDT and endDT please use the url_params argument. If you specify both, current behavior uses the time period as being more specific. An exception will not be raised. :param url_params: A dictionary of other parameters to pass to the USGS server in key/value format. They will be automatically added to the query. Case sensitive. For a full list of parameters, see `the USGS web service documentation <>`_ """ self.site_code = site_code self.time_series = None self.time_period = time_period self.url_params = url_params # optional dict of params - url key value pairs passed to the api self.data_frame = None self.startDT = None self.endDT = None self._json_string = None self._base_url = ""
[docs] def check_params(self, params = ('site_code',)): """ Makes sure that we have the base level of information necessary to run a query to prevent lazy setup errors """ for param in params: if self.__dict__[param] is None and param not in self.url_params: raise AttributeError("Required attribute %s must be set or provided in url_params before running this method" % param)
[docs] def retrieve(self, return_pandas=False, automerge = True): """ Retrieves data from the server based upon class configuration. Returns the a list of dicts by default, with keys set by the returned data from the server. If return_pandas is True, returns a pandas data frame. :param return_pandas: specifies whether or not to return the pandas object. When True, returns a pandas object. When False, returns the default list of dicts. If True and you have not installed pandas, will raise ValueError :param automerge: Not yet implemented! Warning! Intent is that when returning a pandas table, automerge will allow you to run multiple separate requests for the same gage (different time series with gaps, etc) and merge them into a single result for the gage """ # makes sure that the user didn't forget to set something after init if return_pandas and not pandas: # do this first so we don't find out AFTER doing everything else _pandas_no_exist() self.check_params() self._retrieve_data() self._json_to_dataframe(create_pandas = return_pandas) if return_pandas: return self.data_frame else: return self.time_series
def _retrieve_data(self): """ requests retrieves, and stores the json """ # add the relevant parameters into the dictionary passed by the user (if any self.url_params['format'] = "json" self.url_params['sites'] = self.site_code if self.time_period and not self.startDT and 'startDT' not in self.url_params: # if we have a time period, but not a time range, use the period self.url_params['period'] = self.time_period else: # otherwise, use the time range if it works (doesn't currently valdidate the dates # TODO: Validate the date formats self.check_params(('startDT','endDT')) # it's possible that they won't be defined self.url_params['startDT'] = self.startDT self.url_params['endDT'] = self.endDT # merge parameters into the url request_url = self._base_url + "?" + urllib.urlencode(self.url_params) # open the url and read in the json string to a private variable request = urllib2.Request(request_url) data_stream = urllib2.urlopen(request) self._json_string = self._json_data = json.loads(self._json_string) def _json_to_dataframe(self, create_pandas = False): """ converts the json to a pandas data frame """ self.time_series = self._json_data['value']['timeSeries'][0]['values'][0]['value'] if create_pandas: self.data_frame = pandas.DataFrame(self.time_series) def _merge_with_existing(self): """ if we execute a request when we already have data, this method attempts to merge the two datasets into a single time series so you can effectively execute a partial query and then go further if need be """ pass # TODO: Create shortcut function for getting data from a station - single function
[docs]def retrieve_flow(gage_id=None, return_pandas = False): """ Helper function that initializes the gage for you, runs the necessary methods, and returns the table (list of dicts). Takes no date limiters so default is used. If you need to specify dates, please use the gage class. :param gage_id: The USGS id for the gage :param return_pandas: specifies whether or not to return the pandas object. When True, returns a pandas object. When False, returns the default list of dicts. If True and you have not installed pandas, will raise ValueError """ if return_pandas and not pandas: _pandas_no_exist() if not gage_id: raise ValueError("gage_id must be specified to use this helper function. If you want to initialize a gage" " without specifying an ID, please use the gage class") t_gage = gage(gage_id) return t_gage.retrieve(return_pandas=return_pandas)
def _pandas_no_exist(): raise ValueError("Pandas could not be imported, cannot return pandas object. Try again after checking" " that the pandas module is correctly installed or using return_pandas = False")

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