X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Ftools%2Fdash%2Fapp%2Fpal%2Fdata%2Fdata.py;h=3d9b8b166417cc03a3ae220a07e70319b623d925;hb=cd417be7f836eb9346fad4f87bd4f75dc1d9a429;hp=859c7d3458f67636e7a983754f626d88ec20fa86;hpb=9c10745ce84d74ff5752aa3a19508cc731bba8b9;p=csit.git diff --git a/resources/tools/dash/app/pal/data/data.py b/resources/tools/dash/app/pal/data/data.py index 859c7d3458..3d9b8b1664 100644 --- a/resources/tools/dash/app/pal/data/data.py +++ b/resources/tools/dash/app/pal/data/data.py @@ -13,10 +13,12 @@ """Prepare data for Plotly Dash.""" +from datetime import datetime, timedelta import logging from time import time import awswrangler as wr +from pytz import UTC from yaml import load, FullLoader, YAMLError from awswrangler.exceptions import EmptyDataFrame, NoFilesFound @@ -82,7 +84,7 @@ class Data: def _create_dataframe_from_parquet(self, path, partition_filter=None, columns=None, validate_schema=False, last_modified_begin=None, - last_modified_end=None): + last_modified_end=None, days=None): """Read parquet stored in S3 compatible storage and returns Pandas Dataframe. @@ -116,6 +118,8 @@ class Data: """ df = None start = time() + if days: + last_modified_begin = datetime.now(tz=UTC) - timedelta(days=days) try: df = wr.s3.read_parquet( path=path, @@ -144,18 +148,35 @@ class Data: self._data = df return df - def read_stats(self): + def read_stats(self, days=None): """Read Suite Result Analysis data partition from parquet. """ - lambda_f = lambda part: True if part["stats_type"] == "sra" else False - - return self._create_dataframe_from_parquet( - path=self._get_path("statistics"), - partition_filter=lambda_f, - columns=None # Get all columns. + l_stats = lambda part: True if part["stats_type"] == "sra" else False + l_mrr = lambda part: True if part["test_type"] == "mrr" else False + l_ndrpdr = lambda part: True if part["test_type"] == "ndrpdr" else False + + return ( + self._create_dataframe_from_parquet( + path=self._get_path("statistics"), + partition_filter=l_stats, + columns=self._get_columns("statistics"), + days=days + ), + self._create_dataframe_from_parquet( + path=self._get_path("statistics-trending"), + partition_filter=l_mrr, + columns=self._get_columns("statistics-trending"), + days=days + ), + self._create_dataframe_from_parquet( + path=self._get_path("statistics-trending"), + partition_filter=l_ndrpdr, + columns=self._get_columns("statistics-trending"), + days=days + ) ) - def read_trending_mrr(self): + def read_trending_mrr(self, days=None): """Read MRR data partition from parquet. """ lambda_f = lambda part: True if part["test_type"] == "mrr" else False @@ -163,10 +184,11 @@ class Data: return self._create_dataframe_from_parquet( path=self._get_path("trending-mrr"), partition_filter=lambda_f, - columns=self._get_columns("trending-mrr") + columns=self._get_columns("trending-mrr"), + days=days ) - def read_trending_ndrpdr(self): + def read_trending_ndrpdr(self, days=None): """Read NDRPDR data partition from iterative parquet. """ lambda_f = lambda part: True if part["test_type"] == "ndrpdr" else False @@ -174,10 +196,11 @@ class Data: return self._create_dataframe_from_parquet( path=self._get_path("trending-ndrpdr"), partition_filter=lambda_f, - columns=self._get_columns("trending-ndrpdr") + columns=self._get_columns("trending-ndrpdr"), + days=days ) - def read_iterative_mrr(self): + def read_iterative_mrr(self, days=None): """Read MRR data partition from iterative parquet. """ lambda_f = lambda part: True if part["test_type"] == "mrr" else False @@ -185,10 +208,11 @@ class Data: return self._create_dataframe_from_parquet( path=self._get_path("iterative-mrr"), partition_filter=lambda_f, - columns=self._get_columns("iterative-mrr") + columns=self._get_columns("iterative-mrr"), + days=days ) - def read_iterative_ndrpdr(self): + def read_iterative_ndrpdr(self, days=None): """Read NDRPDR data partition from parquet. """ lambda_f = lambda part: True if part["test_type"] == "ndrpdr" else False @@ -196,5 +220,6 @@ class Data: return self._create_dataframe_from_parquet( path=self._get_path("iterative-ndrpdr"), partition_filter=lambda_f, - columns=self._get_columns("iterative-ndrpdr") + columns=self._get_columns("iterative-ndrpdr"), + days=days )