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feat: Format timestamps as timestamps #230

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merged 7 commits into from
Aug 5, 2020
Merged

feat: Format timestamps as timestamps #230

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1823cf8
feat: Format timestamps as timestamps
Aug 5, 2020
8e5a3f3
test: Test timestamp dtype
Aug 5, 2020
1d93892
Merge branch 'master' into timestamp-cols
KitBurgess Aug 5, 2020
d83d7a4
perf: Incorporate @cvonsteg feedback
Aug 5, 2020
65b5746
Merge branch 'master' into timestamp-cols
KitBurgess Aug 5, 2020
7c8a2ce
chore: Unrelated speed test
Aug 5, 2020
2159303
Merge branch 'timestamp-cols' of github.com:V0RT3X4/python-sdk into t…
Aug 5, 2020
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18 changes: 17 additions & 1 deletion tests/endpoints/test_cargo_movements_real.py
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Original file line number Diff line number Diff line change
Expand Up @@ -120,6 +120,22 @@ def test_to_df_all_columns(self):

assert len(df) == 2

def test_timestamp_columns(self):
df = (
CargoMovements()
.search(
filter_activity="loading_state",
filter_products="6f11b0724c9a4e85ffa7f1445bc768f054af755a090118dcf99f14745c261653",
filter_time_min=datetime(2019, 8, 29),
filter_time_max=datetime(2019, 8, 29, 0, 10),
)
.to_df(columns="all")
.head(2)
)

self.assertEqual(str(df['events.cargo_port_load_event.0.end_timestamp'].dtypes), 'datetime64[ns, UTC]')
self.assertEqual(str(df['events.cargo_port_unload_event.0.end_timestamp'].dtypes), 'datetime64[ns, UTC]')

def test_search_single_filter_origin_name(self):
df = (
CargoMovements()
Expand Down Expand Up @@ -233,5 +249,5 @@ def test_speed(self):
# Check we load a reasonable number of cargo movements in a short enough period of time
assert len(df) > 500
assert t_search.interval < 10
assert t_to_list.interval < 5
assert t_to_list.interval < 10
assert t_to_df.interval < 5
6 changes: 5 additions & 1 deletion vortexasdk/endpoints/timeseries_result.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,12 +33,16 @@ def to_df(self, columns=None) -> pd.DataFrame:
the number of cargo movements contributing towards this day's tonnage.

"""
return create_dataframe(
df = create_dataframe(
columns=columns,
default_columns=DEFAULT_COLUMNS,
data=super().to_list(),
logger_description="TimeSeries",
)

df["key"] = pd.to_datetime(df["key"])

return df


DEFAULT_COLUMNS = ["key", "value", "count"]
18 changes: 15 additions & 3 deletions vortexasdk/result_conversions.py
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Expand Up @@ -14,6 +14,16 @@ def create_list(list_of_dicts, output_class: FromDictMixin) -> List:
return [output_class.from_dict(d) for d in list_of_dicts]


def format_datatypes(df: pd.DataFrame) -> pd.DataFrame:
"""Format the relevant columns with sensible datatypes"""
timestamp_cols = [col for col in df.columns if "timestamp" in col]

for col in timestamp_cols:
df[col] = pd.to_datetime(df[col])

return df


def create_dataframe(
columns: Union[None, List[str]],
default_columns: List[str],
Expand All @@ -30,8 +40,10 @@ def create_dataframe(
logger.debug(f"Creating DataFrame of {logger_description}")

if columns is None:
return pd.DataFrame(data=data, columns=default_columns)
df = pd.DataFrame(data=data, columns=default_columns)
elif columns == "all":
return pd.DataFrame(data=data)
df = pd.DataFrame(data=data)
else:
return pd.DataFrame(data=data, columns=columns)
df = pd.DataFrame(data=data, columns=columns)
Comment on lines 42 to +47
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Could simplify this slightly

columns = columns or default_columns # handles None 'if' clause
if columns == 'all':
    df = pd.DataFrame(data=data)
else:
    df = pd.DataFrame(data=data, columns=columns)

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This is definitely fewer lines of code - but I think it's slightly more difficult to read for the user: we mutate the columns variable and then handle it in the if statement - rather than explicitly dealing with the three posibilities for the columns variable..

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@cvonsteg cvonsteg Aug 5, 2020 •
edited
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Your call!


return format_datatypes(df)