Feature: Optimize dataframe conversion in JPMaQSDownload()
#1442
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Member
Magnus167
commented
Feb 4, 2024
•
Magnus167
commented
- Reduces API_DELAY_PARAM to 0.2 (200ms) from 0.3
- Removes checks for duplicates. as DQ specifies that only unique date-value pairs will make it into a timeseries. Also removes the test for this
- Uses a new method for converting JSONs to DFs
- Adds progress notifications during dataframe conversion
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## develop #1442 +/- ##
===========================================
+ Coverage 82.05% 82.09% +0.04%
===========================================
Files 59 59
Lines 5906 5909 +3
===========================================
+ Hits 4846 4851 +5
+ Misses 1060 1058 -2
... and 2 files with indirect coverage changes |
Magnus167
commented
Feb 4, 2024
macrosynergy/download/jpmaqs.py
Outdated
Comment on lines
382
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403
| final_df: pd.DataFrame = pd.concat(dfs, ignore_index=True) | ||
| dups_df: pd.DataFrame = final_df.groupby( | ||
| ["real_date", "cid", "xcat", "metric"] | ||
| )["obs"].count() | ||
| if sum(dups_df > 1) > 0: | ||
| dups_df = pd.DataFrame(dups_df[dups_df > 1].index.tolist()) | ||
| err_str: str = "Duplicate data found for the following expressions:\n" | ||
| for i in dups_df.groupby([1, 2, 3]).groups: | ||
| dts_series: pd.Series = dups_df.iloc[ | ||
| dups_df.groupby([1, 2, 3]).groups[i] | ||
| ][0] | ||
| dts: List[str] = dts_series.tolist() | ||
| max_date: str = pd.to_datetime(max(dts)).strftime("%Y-%m-%d") | ||
| min_date: str = pd.to_datetime(min(dts)).strftime("%Y-%m-%d") | ||
| expression: str = self.construct_expressions( | ||
| cids=[i[0]], xcats=[i[1]], metrics=[i[2]] | ||
| )[0] | ||
| err_str += ( | ||
| f"Expression: {expression}, Dates: {min_date} to {max_date}\n" | ||
| final_df: pd.DataFrame = functools.reduce( | ||
| lambda left, right: pd.merge( | ||
| left, | ||
| right, | ||
| on=["real_date", "cid", "xcat"], | ||
| ), | ||
| list( | ||
| map( | ||
| lambda metricx: pd.concat(dfs_dict[metricx], ignore_index=True), | ||
| dfs_dict, | ||
| ) | ||
| ), | ||
| ) | ||
|
|
||
| raise InvalidDataframeError(err_str) |
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Should we drop this check @emhbrine , @sandresen1 ?
sandresen1
approved these changes
Feb 5, 2024
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