def test_respond_frame_csv(nav):
x = nav.to_frame(name="Maffay")
response = respond_pandas(x, "csv")
f = pd.read_csv(StringIO(response.data.decode("utf-8")),
index_col=0,
header=0,
parse_dates=True)
pt.assert_frame_equal(f, x, check_names=False)
def volatility():
return respond_pandas(object=to_json(__series().ewm_volatility()),
format="json")
def drawdown():
return respond_pandas(object=to_json(__series().drawdown), format="json")
def month():
# return a frame...
return respond_pandas(
object=__series().monthlytable.applymap(__percentage), format="json")
def performance():
perf = __series().summary_format().apply(str)
return respond_pandas(object=perf.to_dict(), format="json")
def test_respond_json():
x = ["A", "B"]
assert json.loads(respond_pandas(x, "json").data) == x
def test_respond_frame_json(nav):
x = nav.to_frame(name="Maffay")
response = respond_pandas(x, "json")
pt.assert_frame_equal(
pd.read_json(response.data, typ="frame", orient="table"), x)
def json():
return respond_pandas(object=frame, format="json")
def csv():
return respond_pandas(object=frame, format="csv")
def search(fmt):
if fmt.lower().strip() == "html":
return render_template("results.html")
return respond_pandas(Whoosh.frame(), format=fmt)
