MAINT: Convert dictionary .values() to list for python3

This commit is contained in:
Cam Sweeney
2018-01-11 10:34:16 -08:00
parent ff7d7c5256
commit 050fda1bdb
10 changed files with 13 additions and 13 deletions
+2 -2
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@@ -88,11 +88,11 @@ class AssetDispatchBarReader(with_metaclass(ABCMeta)):
if self._last_available_dt is not None:
return self._last_available_dt
else:
return min(r.last_available_dt for r in self._readers.values())
return min(r.last_available_dt for r in list(self._readers.values()))
@lazyval
def first_trading_day(self):
return max(r.first_trading_day for r in self._readers.values())
return max(r.first_trading_day for r in list(self._readers.values()))
def get_value(self, sid, dt, field):
asset = self._asset_finder.retrieve_asset(sid)
+1 -1
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@@ -84,7 +84,7 @@ def handle_data(context, data):
def analyze(context, perf):
# Get the base_currency that was passed as a parameter to the simulation
base_currency = context.exchanges.values()[0].base_currency.upper()
base_currency = list(context.exchanges.values())[0].base_currency.upper()
# First chart: Plot portfolio value using base_currency
ax1 = plt.subplot(411)
+1 -1
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@@ -161,7 +161,7 @@ def analyze(context=None, perf=None):
import matplotlib.pyplot as plt
# The base currency of the algo exchange
base_currency = context.exchanges.values()[0].base_currency.upper()
base_currency = list(context.exchanges.values())[0].base_currency.upper()
# Plot the portfolio value over time.
ax1 = plt.subplot(611)
@@ -161,7 +161,7 @@ def analyze(context=None, perf=None):
import matplotlib.pyplot as plt
# The base currency of the algo exchange
base_currency = context.exchanges.values()[0].base_currency.upper()
base_currency = list(context.exchanges.values())[0].base_currency.upper()
# Plot the portfolio value over time.
ax1 = plt.subplot(611)
+1 -1
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@@ -175,7 +175,7 @@ def handle_data(context, data):
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
base_currency = context.exchanges.values()[0].base_currency.upper()
base_currency = list(context.exchanges.values())[0].base_currency.upper()
# Plot the portfolio and asset data.
ax1 = plt.subplot(611)
results.loc[:, 'portfolio_value'].plot(ax=ax1)
+1 -1
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@@ -57,7 +57,7 @@ def analyze(context, perf):
log.info('the stats: {}'.format(get_pretty_stats(perf)))
# The base currency of the algo exchange
base_currency = context.exchanges.values()[0].base_currency.upper()
base_currency = list(context.exchanges.values())[0].base_currency.upper()
# Plot the portfolio value over time.
ax1 = plt.subplot(611)
+1 -1
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@@ -41,7 +41,7 @@ from catalyst.exchange.utils.exchange_utils import get_exchange_symbols
def initialize(context):
context.i = -1 # minute counter
context.exchange = context.exchanges.values()[0].name.lower()
context.exchange = list(context.exchanges.values())[0].name.lower()
context.base_currency = context.exchanges.values()[0].base_currency.lower()
+1 -1
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@@ -287,7 +287,7 @@ def get_pretty_stats(stats, recorded_cols=None, num_rows=10, show_tail=True):
"""
if isinstance(stats, pd.DataFrame):
stats = stats.T.to_dict().values()
stats = list(stats.T.to_dict().values())
stats.sort(key=itemgetter('period_close'))
if len(stats) > num_rows:
+2 -2
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@@ -142,7 +142,7 @@ class TermGraph(object):
at the end of execution.
"""
refcounts = self.graph.out_degree()
for t in self.outputs.values():
for t in list(self.outputs.values()):
refcounts[t] += 1
for t in initial_terms:
@@ -238,7 +238,7 @@ class ExecutionPlan(TermGraph):
min_extra_rows=0):
super(ExecutionPlan, self).__init__(terms)
for term in terms.values():
for term in list(terms.values()):
self.set_extra_rows(
term,
all_dates,
+2 -2
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@@ -144,7 +144,7 @@ class SpecificEquityTrades(object):
for identifier in self.identifiers:
assets_by_identifier[identifier] = env.asset_finder.\
lookup_generic(identifier, datetime.now())[0]
self.sids = [asset.sid for asset in assets_by_identifier.values()]
self.sids = [asset.sid for asset in list(assets_by_identifier.values())]
for event in self.event_list:
event.sid = assets_by_identifier[event.sid].sid
@@ -167,7 +167,7 @@ class SpecificEquityTrades(object):
for identifier in self.identifiers:
assets_by_identifier[identifier] = env.asset_finder.\
lookup_generic(identifier, datetime.now())[0]
self.sids = [asset.sid for asset in assets_by_identifier.values()]
self.sids = [asset.sid for asset in list(assets_by_identifier.values())]
# Hash_value for downstream sorting.
self.arg_string = hash_args(*args, **kwargs)