def generate_package():
package_flow = Flow(
add_metadata(
name="unicode-emojis",
title="UTS #51 Unicode Emoji",
descriptor=(
"List of emojis available from the Unicode Consortium. "
"More information can be found in the Unicode® Technical Standard #51."
),
sources=[
{
"name": "unicode-emoji",
"path": "https://unicode.org/Public/emoji/latest/emoji-test.txt",
"title": "UTS #51 Unicode Emoji",
},
],
licenses=[
{
"name": "ODC-PDDL-1.0",
"path": "http://opendatacommons.org/licenses/pddl/",
"title": "Open Data Commons Public Domain Dedication and License v1.0",
}
],
keywords=["unicode", "emojis", "emoji", "51", "standard", "uts"],
),
load(load_source="data/emojis.csv", format="csv",),
validate(),
dump_to_path(),
)
package_flow.process()
def test_add_metadata():
from dataflows import add_metadata
f = Flow(
data,
add_metadata(author='Adam Kariv')
)
_, dp, _ = f.results()
assert dp.descriptor['author'] == 'Adam Kariv'
def conference_csv():
flow = Flow(
# Load inputs
load(
od19_base + od19_feedback,
name='feedback',
format='csv',
),
load(
od19_base + od19_analysis,
name='analysis',
format='csv',
),
# Process them
set_type("Anzahl.*", type='integer', resources='analysis'),
delete_fields([
"Anzahl Auflistung",
".*\\(Formel\\)",
".*Duplikate",
],
resources='analysis'),
not_empty_groupcol,
# Save the results
add_metadata(
name='opendatach19',
title='''Opendata.ch/2019 Forum''',
licenses=[{
"name":
"ODC-PDDL-1.0",
"path":
"http://opendatacommons.org/licenses/pddl/",
"title":
"Open Data Commons Public Domain Dedication and License v1.0"
}],
maintainers=[{
"name": "Oleg Lavrovsky",
"web": "https://datalets.ch/"
}],
views=[{
"name": "Groups",
"resources": ["analysis"],
"spec": {
"group": "Alle "
"Bedürfnisse"
"",
"series": ["Anzahl Auflistung (Zahl)"],
"type": "bar"
},
"specType": "simple",
"title": "Topic counts"
}]),
printer(),
validate(),
dump_to_path('data/opendatach19'),
)
flow.process()
def AFRR_Data():
unpivoting_fields = [{
'name': 'aFRR_DownActivated',
'keys': {
'product': 'aFRR_DownActivated'
}
}, {
'name': 'aFRR_UpActivated',
'keys': {
'product': 'aFRR_UpActivated'
}
}]
extra_keys = [{'name': 'product', 'type': 'string'}]
extra_value = {'name': 'amount', 'type': 'number'}
flow = Flow(
# Load inputs - using 'datastore_search_sql' API load last 10k rows:
load(
'https://api.energidataservice.dk/datastore_search_sql?sql=select%20*%20from%20afrrreservesdk1%20order%20by%20"HourUTC"%20desc%20limit%201000',
format="json",
property="result.records",
name="fact_afrr"),
# Remove extra fields:
delete_fields(fields=['_id', '_full_text', 'HourDK']),
# Save the results
checkpoint('afrr'),
# Normalize/unpivot:
unpivot(unpivoting_fields, extra_keys, extra_value),
add_computed_field([
dict(target=dict(name='PriceArea', type='string'),
operation='constant',
with_='DK1'),
dict(target=dict(name='PriceDKK', type='number'),
operation='constant',
with_='dummy'),
dict(target=dict(name='PriceEUR', type='number'),
operation='constant',
with_='dummy')
]),
add_price,
delete_fields(fields=[
'aFRR_DownPriceDKK', 'aFRR_DownPriceEUR', 'aFRR_UpPriceDKK',
'aFRR_UpPriceEUR'
]),
add_metadata(name='marketdata', title='Marketdata prototype'),
update_resource(resources=None, mediatype='text/csv'),
update_resource(
resources='fact_afrr',
title='Automatic Frequency Restoration Reserves',
source=
'https://www.energidataservice.dk/dataset/afrrreservesdk1/resource_extract/0694e216-6713-4f84-9b98-7bb5bc11d80c'
),
printer(),
dump_to_path('afrr_data'))
flow.process()
def flow(parameters, datapackage, resources, source_stats):
def download_messages(package: PackageWrapper):
if 'allowed-senders' in package.pkg.resource_names:
package.pkg.remove_resource('allowed-senders')
package.pkg.add_resource({
'dpp:streaming': True,
'name': 'messages',
'path': 'messages.csv',
'schema': {
'fields': [{
'name': 'id',
'type': 'string'
}, {
'name': 'snippet',
'type': 'string'
}, {
'name': 'from',
'type': 'string'
}, {
'name': 'to',
'type': 'string'
}, {
'name': 'date',
'type': 'string'
}, {
'name': 'subject',
'type': 'string'
}, {
'name': 'part_ids',
'type': 'array'
}, {
'name': 'organization_id',
'type': 'string'
}]
}
})
yield package.pkg
allowed_senders = []
for resource in package:
if resource.res.name == 'allowed-senders':
allowed_senders = list(get_allowed_senders(resource))
else:
yield resource
yield get_messages(source_stats, allowed_senders)
load_args = parameters.get("load_args")
if not load_args:
load_args = [(datapackage, resources)]
return Flow(add_metadata(name='_'), load(*load_args), download_messages)
def flow(parameters, datapackage, resources, stats):
meta = get_league_meta(parameters)
processors = get_processors(meta)
processors.append(set_type('Date', type='date', format='%d/%m/%y')),
processors = [
add_metadata(name=parameters['dataset-name'],
title=parameters['dataset-title'],
licenses=licenses,
sources=sources,
related=related_datasets,
readme=readme %
parameters['dataset-title'].replace(' (football)', ''))
] + processors
return Flow(*processors)
def update_dataset():
flow = Flow(
# Load inputs
load(f'{BASE_URL}{CONFIRMED}'),
load(f'{BASE_URL}{RECOVERED}'),
load(f'{BASE_URL}{DEATH}'),
checkpoint('load_data'),
# Process them (if necessary)
# Save the results
add_metadata(name='csse_covid_19_time_series', title='''csse_covid_19_time_series'''),
printer(),
dump_to_path(),
)
flow.process()
def flow(*args):
return Flow(
# Load inputs
load(
"https://www.data.gouv.fr/fr/datasets/r/41b9bd2a-b5b6-4271-8878-e45a8902ef00",
name='donnees-etab',
format='csv',
),
# necessary for dpp integration
# https://github.com/frictionlessdata/datapackage-pipelines/issues/150#issuecomment-432152302
update_resource('donnees-etab', **{'dpp:streaming': True}),
# Save the results
add_metadata(name='donnees_test', title='''donnees-test'''),
)
def WERKVERZEICHNIS_csv():
flow = Flow(
# Load inputs
# load('input/WERKVERZEICHNIS_ohne W.xlsx', format='xlsx', ),
load(
'input/WERKVERZEICHNIS.csv',
format='csv',
),
# Process them (if necessary)
# ...
# Save the results
add_metadata(name='Werkverzeichnis-JStraumann',
title='''Werkverzeichnis Jürg Straumann'''),
# printer(),
dump_to_path('data'),
)
flow.process()
def flow(parameters, datapackage, resources, stats):
stats['foo_values'] = 0
def add_foo_field(package: PackageWrapper):
package.pkg.descriptor['resources'][0]['schema']['fields'] += [
{'name': parameters['attr'], 'type': 'string'}]
yield package.pkg
yield from package
def add_foo_value(row):
row[parameters['attr']] = 'foo'
stats['foo_values'] += 1
return Flow(add_metadata(name='_'),
hello_dataflows,
load((datapackage, resources)),
add_foo_field,
add_foo_value)
def Elspot_Prices_Data():
# field_metadata = get_metadata('c86859d2-942e-4029-aec1-32d56f1a2e5d')
flow = Flow(
# Load inputs - using 'datastore_search_sql' API load last 10k rows:
load(
'https://api.energidataservice.dk/datastore_search_sql?sql=select%20*%20from%20elspotprices%20order%20by%20"HourUTC"%20desc%20limit%20100',
format="json",
property="result.records",
name="fact_elspot_prices"),
# Remove extra fields:
delete_fields(fields=['_id', '_full_text', 'HourDK']),
# Save the results
checkpoint('load_data'),
# Add product:
add_computed_field([
dict(target=dict(name='product', type='string'),
operation='constant',
with_='Elspot'),
dict(target=dict(name='amount', type='number'),
operation='constant',
with_=1),
dict(target=dict(name='PriceDKK', type='number'),
operation='constant',
with_=-1),
dict(target=dict(name='PriceEUR', type='number'),
operation='constant',
with_=-1)
]),
add_price,
delete_fields(fields=['SpotPriceDKK', 'SpotPriceEUR']),
add_metadata(name='marketdata', title='Marketdata prototype'),
update_resource(resources=None, mediatype='text/csv'),
update_resource(
resources='fact_elspot_prices',
title='Elspot Prices Data',
source=
'https://www.energidataservice.dk/dataset/elspotprices/resource_extract/c86859d2-942e-4029-aec1-32d56f1a2e5d'
),
printer(),
dump_to_path('elspot_prices_data'),
# dump_to_sql(tables={'elspot': {'resource-name': 'Elspot_Prices_Data', 'mode': 'append'}}, engine='postgresql://*****:*****@localhost/cubes')
)
flow.process()
def flow(*args):
return Flow(
# Load inputs
*[
load(f"https://www.data.gouv.fr/fr/datasets/r/{resource['id']}",
name=resource['name'],
format='csv',
override_schema=get_schema(resource['name']))
for resource in RESOURCES
],
# necessary for dpp integration
# https://github.com/frictionlessdata/datapackage-pipelines/issues/150#issuecomment-432152302
*[
update_resource(resource['name'], **{'dpp:streaming': True})
for resource in RESOURCES
],
# Save the results
add_metadata(name='donnees_hospitalieres_covid19',
title='''donnees-hospitalieres-covid19'''),
)
{% if 'delete_fields' in processing %}
delete_fields(['field_name']), # Pass a list of field names to delete from the data
{% endif %}
{% if 'set_type' in processing %}
set_type('field_name', type='number', constraints=dict(minimum=3)), # There are quite a few options you can use here
# Take a look at https://frictionlessdata.io/specs/table-schema/
# Or you can simply use validate() here instead
{% endif %}
{% if 'unpivot' in processing %}
unpivot(unpivot_fields, extra_keys, extra_value), # See documentation on the meaning of each of these parameters
{% endif %}
{% if 'custom' in processing %}
my_custom_processing,
{% endif %}
# Save the results
add_metadata(name='{{slug}}', title='''{{title}}'''),
{% if output in ('print', 'print_n_pkg') %}
printer(),
{% endif %}
{% if output == 'list' %}
{% endif %}
{% if output in ('dp_csv', 'print_n_pkg') %}
dump_to_path('{{slug}}'),
{% endif %}
{% if output == 'dp_csv_zip' %}
dump_to_zip('{{slug}}.zip'),
{% endif %}
{% if output == 'dp_json' %}
dump_to_path('{{slug}}', force_format=True, format='json'),
{% endif %}
{% if output == 'dp_json_zip' %}
bond_uk = Flow(
add_metadata(
name="bond-yields-uk-10y",
title="10y UK Government Bond Yields (long-term interest rate)",
sources=[{
"name": "Bank of England",
"path":
"http://www.bankofengland.co.uk/boeapps/iadb/index.asp?Travel=NIxIRx&levels=1&XNotes=Y&C=DUS&G0Xtop.x=51&G0Xtop.y=7&XNotes2=Y&Nodes=X41514X41515X41516X41517X55047X76909X4051X4052X4128X33880X4053X4058&SectionRequired=I&HideNums=-1&ExtraInfo=true#BM",
"title": "Bank of England"
}],
licenses=[{
"id": "odc-pddl",
"path": "http://opendatacommons.org/licenses/pddl/",
"name": "public_domain_dedication_and_license"
}],
views=[{
"name": "graph",
"title":
"Average yield from British Government Securities, 10 year Nominal Par Yield",
"specType": "simple",
"spec": {
"type": "line",
"group": "Date",
"series": ["Rate"]
}
}],
readme=readme()),
load(
load_source=
'http://www.bankofengland.co.uk/boeapps/iadb/fromshowcolumns.asp?csv.x=yes&SeriesCodes=IUQAMNPY&UsingCodes=Y&CSVF=TN&Datefrom=01/Jan/1963',
add_metadata(
name="oil-prices",
title= "Brent and WTI Spot Prices",
descriptor="A variety of temporal granularities for Europe Brent and WTI (West Texas Intermediate) Spot Prices.",
sources=[
{
"name": "Daily Europe Brent Spot Price",
"path": "https://www.eia.gov/dnav/pet/hist_xls/RBRTEd.xls",
"title": "Daily Europe Brent Spot Price"
},
{
"name": "Daily Cushing, OK WTI Spot Price",
"path": "http://www.eia.gov/dnav/pet/hist_xls/RWTCd.xls",
"title": "Daily Cushing, OK WTI Spot Price"
},
{
"name": "OPEC: Monthly Oil Market Report",
"path": "https://www.opec.org/opec_web/static_files_project/media/downloads/publications/MOMR%20Appendix%20Tables%20(April%202020).xlsx",
"title": "OPEC: Monthly Oil Market Report"
},
],
licenses=[
{
"name": "ODC-PDDL-1.0",
"path": "http://opendatacommons.org/licenses/pddl/",
"title": "Open Data Commons Public Domain Dedication and License v1.0"
}
],
keywords=["Oil","Brent","WTI","Oil Prices","eia","oil eia"],
views=[
{
"name": "graph",
"title": "Europe Brent Spot Price FOB (Dollars per Barrel)",
"resourceName": "brent-day",
"specType": "simple",
"spec": {
"type": "line",
"group": "Date",
"series": ["Brent Spot Price"]
}
}
]
),
yield package.pkg
res_iter = iter(package)
for res in res_iter:
yield res.it
yield from package
oil_prices = Flow(
add_metadata(
name="Opec_data",
title="A source of Opec Data",
descriptor=
"A variety of temporal granularities for Europe Brent and WTI (West Texas Intermediate) Spot Prices.",
sources=[
{
"name": "OPEC: Monthly Oil Market Report",
"path":
"https://www.opec.org/opec_web/static_files_project/media/downloads/publications/MOMR%20Appendix%20Tables%20(April%202020).xlsx",
"title": "OPEC: Monthly Oil Market Report"
},
]),
load(
load_source=
'https://www.opec.org/opec_web/static_files_project/media/downloads/publications/MOMR%20Appendix%20Tables%20(April%202020).xlsx',
format='xls',
sheet=2,
skip_rows=[1, 2, 3, 4, 5],
headers=[
' ', 'Country', '2016', '2017', '2018', '1Q19', '2Q19', '3Q19',
'4Q19', '2019', '1Q20', '2Q20', '3Q20', '4Q20', '2020'
'name': 'serie-a',
'path': 'italym.php',
'key': 'I1',
'links': [],
'dataset-name': 'italian-serie-a',
'dataset-title': 'Italian Serie A (football)'
}, {
'name': 'ligue-1',
'path': 'francem.php',
'key': 'F1',
'links': [],
'dataset-name': 'french-ligue-1',
'dataset-title': 'French Ligue 1 (football)'
}]
for league in leagues:
meta = get_league_meta(league)
processors = get_processors(meta)
processors.append(set_type('Date', type='date', format='%d/%m/%y')),
processors.append(dump_to_path(out_path='datasets/' + league['name']))
processors.append(printer())
processors = [
add_metadata(name=league['dataset-name'],
title=league['dataset-title'],
licenses=licenses,
sources=sources,
related=related_datasets,
readme=readme %
league['dataset-title'].replace(' (football)', ''))
] + processors
Flow(*processors).process()
bond_us = Flow(
add_metadata(
name="bond-yields-us-10y",
title="10 year US Government Bond Yields (long-term interest rate)",
version="0.2.0",
sources=[
{
"name": "Federal Reserve (Release H.15)",
"path": "http://www.federalreserve.gov/releases/h15/data.htm",
"title": "Federal Reserve (Release H.15)"
}
],
licenses=[
{
"id": "odc-pddl",
"path": "http://opendatacommons.org/licenses/pddl/",
"title": "Open Data Commons Public Domain Dedication and License v1.0",
'name': "open_data_commons_public_domain_dedication_and_license_v1.0"
}
],
views=[
{
"name": "graph",
"title": "10 year US Government Bond Yields (Monthly granuarlity)",
"specType": "simple",
"spec": {"type": "line","group": "Date","series": ["Rate"]}
}
],
readme=readme()
),
load(
add_metadata(
name="population-growth-estimates-and-projections",
title= "Population Growth",
descriptor="Total Population - Both Sexes. De facto population in a country, area or region",
views=[
{
"name": "population-growth-estimates",
"resources": [
{
"name": "population-estimates",
"transform": [{"expression": "data['Region'] === 'WORLD'","type": "filter"}]
}
],
"spec": {"group": "year","series": ["population"],"type": "line"},
"specType": "simple",
"title": "Population Growth - World Estimates"
},
{
"name": "population-growth-projections",
"resources": [
{
"name": "population-no-change",
"transform": [{"expression": "data['Region'] === 'WORLD'", "type": "filter"}]
}
],
"spec": {"group": "year","series": ["population"],"type": "line"},
"specType": "simple",
"title": "Population Growth - World Projections (No change)"
},
{
"name": "population-growth-projections-low",
"resources": [
{
"name": "population-low-fertility",
"transform": [{"expression": "data['Region'] === 'WORLD'","type": "filter"}]
}
],
"spec": {"group": "year","series": ["population"],"type": "line"},
"specType": "simple",
"title": "Population Growth - World Projections (Low Fertility)"
},
{
"name": "population-growth-projections-medium",
"resources": [
{
"name": "population-medium-fertility",
"transform": [{"expression": "data['Region'] === 'WORLD'","type": "filter"}]
}
],
"spec": {"group": "year","series": ["population"],"type": "line"},
"specType": "simple",
"title": "Population Growth - World Projections (Medium Fertility)"
},
{
"name": "population-growth-projections-high",
"resources": [
{
"name": "population-high-fertility",
"transform": [
{"expression": "data['Region'] === 'WORLD'","type": "filter"}]
}
],
"spec": {"group": "year","series": ["population"],"type": "line"},
"specType": "simple",
"title": "Population Growth - World Projections (High Fertility)"
}
],
readme=readme()
),
add_metadata(
name="gold-prices",
title="Gold Prices",
homepage='http://www.bundesbank.de',
licenses=[
{
"id": "odc-pddl",
"name": "public_domain_dedication_and_license",
"version": "1.0",
"url": "http://opendatacommons.org/licenses/pddl/1.0/"
}
],
sources=[
{
"name": "bundesbank-gold-prices",
"path": "'http://www.bundesbank.de/cae/servlet/StatisticDownload?tsId=BBEX3.M.XAU.USD.EA.AC.C06&its_csvFormat=en&its_fileFormat=csv&mode=its'",
"title": "Bundesbank gold prices"
}
],
views=[
{
"name": "graph",
"title": "Gold Prices (Monthly in USD)",
"specType": "simple",
"spec": {
"type": "lines-and-points",
"group": "Date",
"series": [
"Price"
]
}
}
],
related=[
{
"title": "Oil prices",
"path": "/core/oil-prices",
"publisher": "core",
"formats": ["CSV", "JSON"]
},
{
"title": "Natural gas",
"path": "/core/natural-gas",
"publisher": "core",
"formats": ["CSV", "JSON"]
}
],
version="0.2.0"
),
finance_vix = Flow(
add_metadata(
name="finance-vix",
title= "VIX - CBOE Volatility Index",
homepage= 'http://www.cboe.com/micro/VIX/',
sources=[
{
"name": "CBOE VIX Page",
"path": "http://www.cboe.com/micro/vix/historical.aspx",
"title": "CBOE VIX Page"
}
],
licenses=[
{
"id": "odc-pddl",
"path": "http://opendatacommons.org/licenses/pddl/",
"title": "Open Data Commons Public Domain Dedication and License v1.0",
'name': "open_data_commons_public_domain_dedication_and_license_v1.0"
}
],
version="0.2.0",
views=[
{
"name": "graph",
"title": "VIX - CBOE Volatility Index",
"specType": "simple",
"spec": {"type": "line","group": "Date","series": ["VIX Close"]}
}
],
readme=readme()
),
load(
return open(fpath).read()
dialing_info_cldr = Flow(
load('http://ourairports.com/data/airports.csv', name='airport-codes'),
add_metadata(
name="airport-codes",
title="Airport Codes",
homepage="http://www.ourairports.com/",
version="0.2.0",
licenses=[{
"id":
"odc-pddl",
"path":
"http://opendatacommons.org/licenses/pddl/",
"title":
"Open Data Commons Public Domain Dedication and License v1.0",
'name':
"open_data_commons_public_domain_dedication_and_license_v1.0"
}],
sources=[{
"name": "Our Airports",
"path": "http://ourairports.com/data/",
"title": "Our Airports"
}],
readme=readme()),
add_computed_field([{
"operation": "format",
"target": "coordinates",
"with": "{latitude_deg}, {longitude_deg}"
}]),
add_metadata(
name="us-euro-foreign-exchange-rate",
title="USA / EUR Foreign Exchange Rate since 1999",
homepage='https://fred.stlouisfed.org',
sources=[
{
"name": "federal-reserve-bank-st-louis",
"title": "Federal Reserve Bank of St. Louis",
"path": "https://fred.stlouisfed.org/categories/158"
}
],
licenses=[
{
"id": "odc-pddl",
"name": "public_domain_dedication_and_license",
"version": "1.0",
"url": "http://opendatacommons.org/licenses/pddl/1.0/"
}
],
views=[
{
"name": "us-to-uk-foreign-exchange-rate",
"title": "USA / GBP Foreign Exchange Rate since 1971",
"resources": [
{
"name": "daily",
"transform": [
{
"type": "filter",
"expression": "data['Country'] === 'United Kingdom'"
}
]
}
],
"specType": "simple",
"spec": {
"type": "line",
"group": "Date",
"series": [
"Exchange Rate"
]
}
},
{
"name": "us-euro-foreign-exchange-rate",
"title": "USA / EUR Foreign Exchange Rate since 1999",
"resources": [
{
"name": "daily",
"transform": [
{
"type": "filter",
"expression": "data['Country'] === 'Euro'"
}
]
}
],
"specType": "simple",
"spec": {
"type": "line",
"group": "Date",
"series": [
"Exchange Rate"
]
}
}
],
version="0.2.0",
readme=readme()
),
add_metadata(
name="household-income-us-historical",
title=
"Income Limits for Each Fifth and Top 5 Percent of All Households: 1967 to 2016",
description=
"Households as of March of the following year. Income in current and 2016 CPI-U-RS adjusted dollars.",
sources=[{
"path": "https://www2.census.gov",
"title": "United States Census Bureau"
}],
licenses=[{
"id":
"odc-pddl",
"path":
"http://opendatacommons.org/licenses/pddl/",
"title":
"Open Data Commons Public Domain Dedication and License v1.0",
'name':
"open_data_commons_public_domain_dedication_and_license_v1.0"
}],
version="0.3.0",
views=[{
"name":
"comparison-of-upper-limit-of-each-fifth-and-lower-limit-of-top-5-percent",
"title":
"Comparison of upper limit of each fifth and lower limit of top 5 percent (2016 dollars)",
"resources": ["household-income-us-historical"],
"specType": "simple",
"spec": {
"type": "line",
"group": "Year",
"series":
["Lowest", "Second", "Third", "Fourth", "Top 5 percent"]
}
}, {
"name":
"lowest-fifth-vs-top-5-percent",
"title":
"Ratio of lower limit of top 5 percent to upper limit of lowest fifth (2016 dollars)",
"resources": [{
"name":
"household-income-us-historical",
"transform": [{
"type":
"formula",
"expressions": ["data['Top 5 percent']/data['Lowest']"],
"asFields": ["Ratio"]
}]
}],
"specType":
"simple",
"spec": {
"type": "line",
"group": "Year",
"series": ["Ratio"]
}
}],
readme=readme()),
add_metadata(
name="oil-prices",
title="Brent and WTI Spot Prices",
descriptor=
"A variety of temporal granularities for Europe Brent and WTI (West Texas Intermediate) Spot Prices.",
sources=[{
"name": "Daily Europe Brent Spot Price",
"path": "https://www.eia.gov/dnav/pet/hist_xls/RBRTEd.xls",
"title": "Daily Europe Brent Spot Price"
}, {
"name": "Weekly Europe Brent Spot Price",
"path": "https://www.eia.gov/dnav/pet/hist_xls/RBRTEw.xls",
"title": "Weekly Europe Brent Spot Price"
}, {
"name": "Monthly Europe Brent Spot Price",
"path": "https://www.eia.gov/dnav/pet/hist_xls/RBRTEm.xls",
"title": "Monthly Europe Brent Spot Price"
}, {
"name": "Annual Europe Brent Spot Price",
"path": "https://www.eia.gov/dnav/pet/hist_xls/RBRTEa.xls",
"title": "Annual Europe Brent Spot Price"
}, {
"name": "Daily Cushing, OK WTI Spot Price",
"path": "http://www.eia.gov/dnav/pet/hist_xls/RWTCd.xls",
"title": "Daily Cushing, OK WTI Spot Price"
}, {
"name": "Weekly Cushing, OK WTI Spot Price",
"path": "http://www.eia.gov/dnav/pet/hist_xls/RWTCw.xls",
"title": "Weekly Cushing, OK WTI Spot Price"
}, {
"name": "Monthly Cushing, OK WTI Spot Price",
"path": "http://www.eia.gov/dnav/pet/hist_xls/RWTCm.xls",
"title": "Monthly Cushing, OK WTI Spot Price"
}, {
"name": "Annual Cushing, OK WTI Spot Price",
"path": "http://www.eia.gov/dnav/pet/hist_xls/RWTCa.xls",
"title": "Annual Cushing, OK WTI Spot Price"
}],
licenses=[{
"name":
"ODC-PDDL-1.0",
"path":
"http://opendatacommons.org/licenses/pddl/",
"title":
"Open Data Commons Public Domain Dedication and License v1.0"
}],
keywords=["Oil", "Brent", "WTI", "Oil Prices", "eia", "oil eia"],
views=[{
"name": "graph",
"title": "Europe Brent Spot Price FOB (Dollars per Barrel)",
"resourceName": "brent-day",
"specType": "simple",
"spec": {
"type": "line",
"group": "Date",
"series": ["Brent Spot Price"]
}
}]),
bond_uk = Flow(
add_metadata(
name="bond-yields-uk-10y",
title= "10y UK Government Bond Yields (long-term interest rate)",
sources=[
{
"name": "Bank of England",
"path": "http://www.bankofengland.co.uk/boeapps/iadb/index.asp?Travel=NIxIRx&levels=1&XNotes=Y&C=DUS&G0Xtop.x=51&G0Xtop.y=7&XNotes2=Y&Nodes=X41514X41515X41516X41517X55047X76909X4051X4052X4128X33880X4053X4058&SectionRequired=I&HideNums=-1&ExtraInfo=true#BM",
"title": "Bank of England"
}
],
licenses=[
{
"id": "odc-pddl",
"path": "http://opendatacommons.org/licenses/pddl/",
"name": "public_domain_dedication_and_license"
}
],
views=[
{
"name": "graph",
"title": "Average yield from British Government Securities, 10 year Nominal Par Yield",
"specType": "simple",
"spec": {"type": "line","group": "Date","series": ["Rate"]}
}
],
readme=readme()
),
load(
load_source='http://www.bankofengland.co.uk/boeapps/iadb/fromshowcolumns.asp?csv.x=yes&SeriesCodes=IUQAMNPY&UsingCodes=Y&CSVF=TN&Datefrom=01/Jan/1963',
