def __init__(self, datapackage='http://data.okfn.org/data/cpi/',
country=None):
"""
Initialise a CPI instance. Default data package location is the cpi
data on http://data.okfn.org
"""
# Store datapackage and country as instance variables
self.datapackage = datapackage
self.country = country
# Initialise empty data structures
self.data = MapDict()
# Load the data into the data structures
self.load()
def __init__(self, datapackage="http://data.okfn.org/data/cpi/", country=None):
"""
Initialise a CPI instance. Default data package location is the cpi
data on http://data.okfn.org
"""
# Store datapackage and country as instance variables
self.datapackage = datapackage
self.country = country
# Initialise empty data structures
self.data = MapDict()
# Load the data into the data structures
self.load()
class CPI(object):
"""
Provides a Pythonic interface to Consumer Price Index data packages
"""
def __init__(self, datapackage='http://data.okfn.org/data/cpi/',
country=None):
"""
Initialise a CPI instance. Default data package location is the cpi
data on http://data.okfn.org
"""
# Store datapackage and country as instance variables
self.datapackage = datapackage
self.country = country
# Initialise empty data structures
self.data = MapDict()
# Load the data into the data structures
self.load()
def load(self):
"""
Load data with the data from the datapackage
"""
# Loop through the rows of the datapackage with the help of data
for row in data.get(self.datapackage):
# Get the code and the name and transform to uppercase
# so that it'll match no matter the case
code = row['Country Code'].upper()
name = row['Country Name'].upper()
# Get the date (which is in the field Year) and the CPI value
date = row['Year']
cpi = row['CPI']
# Try to get the data for country
# or initialise an empty dict
country_data = self.data.get(code, {})
# Set the CPI value for the date
country_data[date] = cpi
# Set the code as the default key and name as extra
# key in the mapdict for the country data
self.data[(code, name)] = country_data
def get(self, date=datetime.date.today(), country=None):
"""
Get the CPI value for a specific time. Defaults to today. This uses
the closest method internally but sets limit to one day.
"""
try:
return CPIResult(date=date, value=self.data[country.upper()][date])
except:
raise KeyError('Date {date} not found in data'.format(date=date))
def closest(self, date=datetime.date.today(), country=None,
limit=datetime.timedelta(days=366)):
"""
Get the closest CPI value for a specified date. The date defaults to
today. A limit can be provided to exclude all values for dates further
away than defined by the limit. This defaults to 366 days.
"""
# Try to get the country
country = self.country if country is None else country
# Get the data for the given country (we store it as uppercase)
# import pdb; pdb.set_trace()
country_data = self.data["ESP"]
# Find the closest date
closest_date = min(country_data.keys(),
key=lambda x: abs(date-x))
# We return the CPI value if it's within the limit or raise an error
if abs(date-closest_date) < limit:
return CPIResult(date=closest_date,
value=country_data[closest_date])
else:
raise KeyError('A date close enough was not found in data')
class CPI(object):
"""
Provides a Pythonic interface to Consumer Price Index data packages
"""
def __init__(self, datapackage='http://data.okfn.org/data/cpi/',
country=None):
"""
Initialise a CPI instance. Default data package location is the cpi
data on http://data.okfn.org
"""
# Store datapackage and country as instance variables
self.datapackage = datapackage
self.country = country
# Initialise empty data structures
self.data = MapDict()
# Load the data into the data structures
self.load()
def load(self):
"""
Load data with the data from the datapackage
"""
# Loop through the rows of the datapackage with the help of data
for row in data.get(self.datapackage):
# Get the code and the name and transform to uppercase
# so that it'll match no matter the case
code = row['Country Code'].upper()
name = row['Country Name'].upper()
# Get the date (which is in the field Year) and the CPI value
date = row['Year']
cpi = row['CPI']
# Try to get the data for country
# or initialise an empty dict
country_data = self.data.get(code, {})
# Set the CPI value for the date
country_data[date] = cpi
# Set the code as the default key and name as extra
# key in the mapdict for the country data
self.data[(code, name)] = country_data
def get(self, date=datetime.date.today(), country=None):
"""
Get the CPI value for a specific time. Defaults to today. This uses
the closest method internally but sets limit to one day.
"""
try:
return CPIResult(date=date, value=self.data[country.upper()][date])
except:
raise KeyError('Date {date} not found in data'.format(date=date))
def closest(self, date=datetime.date.today(), country=None,
limit=datetime.timedelta(days=366)):
"""
Get the closest CPI value for a specified date. The date defaults to
today. A limit can be provided to exclude all values for dates further
away than defined by the limit. This defaults to 366 days.
"""
# Try to get the country
country = self.country if country is None else country
# Get the data for the given country (we store it as uppercase)
country_data = self.data[country.upper()]
# Find the closest date
closest_date = min(country_data.keys(),
key=lambda x: abs(date-x))
# We return the CPI value if it's within the limit or raise an error
if abs(date-closest_date) < limit:
return CPIResult(date=closest_date,
value=country_data[closest_date])
else:
raise KeyError('A date close enough was not found in data')
