Update csv_importer

* rename RowValues to CsvRowValues
* make CsvRowValues into a dataclass
* remove argument in load_csv only used for test mocks; correctly mock test
* update tests
* update csv_to_database with relative imports

Author: dshemetov

src/acquisition/covidcast/csv_importer.py

@@ -1,20 +1,31 @@
 """Collects and reads covidcast data from a set of local CSV files."""
 
 # standard library
+from dataclasses import dataclass
 from datetime import date
 import glob
-import math
 import os
 import re
 
 # third party
-import pandas
+import pandas as pd
 import epiweeks as epi
 
 # first party
 from delphi_utils import Nans
 from delphi.utils.epiweek import delta_epiweeks
-from delphi.epidata.acquisition.covidcast.logger import get_structured_logger
+from .logger import get_structured_logger
+
+@dataclass
+class CsvRowValues:
+  """A container for the values of a single validated covidcast CSV row."""
+  geo_value: str
+  value: float
+  stderr: float
+  sample_size: float
+  missing_value: int
+  missing_stderr: int
+  missing_sample_size: int
 
 class CsvImporter:
   """Finds and parses covidcast CSV files."""
@@ -38,6 +49,7 @@ class CsvImporter:
   MIN_YEAR = 2019
   MAX_YEAR = 2030
 
+  # The datatypes expected by pandas.read_csv. Int64 is like float in that it can handle both numbers and nans.
   DTYPES = {
     "geo_id": str,
     "val": float,
@@ -48,20 +60,6 @@ class CsvImporter:
     "missing_sample_size": "Int64"
   }
 
-  # NOTE: this should be a Python 3.7+ `dataclass`, but the server is on 3.4
-  # See https://docs.python.org/3/library/dataclasses.html
-  class RowValues:
-    """A container for the values of a single covidcast row."""
-
-    def __init__(self, geo_value, value, stderr, sample_size, missing_value, missing_stderr, missing_sample_size):
-      self.geo_value = geo_value
-      self.value = value
-      self.stderr = stderr
-      self.sample_size = sample_size
-      self.missing_value = missing_value
-      self.missing_stderr = missing_stderr
-      self.missing_sample_size = missing_sample_size
-
   @staticmethod
   def is_sane_day(value):
     """Return whether `value` is a sane (maybe not valid) YYYYMMDD date.
@@ -185,7 +183,7 @@ def is_header_valid(columns):
     return set(columns) >= CsvImporter.REQUIRED_COLUMNS
 
   @staticmethod
-  def floaty_int(value):
+  def floaty_int(value: str) -> int:
     """Cast a string to an int, even if it looks like a float.
 
     For example, "-1" and "-1.0" should both result in -1. Non-integer floats
@@ -254,7 +252,7 @@ def validate_missing_code(row, attr_quantity, attr_name, filepath=None, logger=N
 
   @staticmethod
   def extract_and_check_row(row, geo_type, filepath=None):
-    """Extract and return `RowValues` from a CSV row, with sanity checks.
+    """Extract and return `CsvRowValues` from a CSV row, with sanity checks.
 
     Also returns the name of the field which failed sanity check, or None.
 
@@ -331,14 +329,10 @@ def extract_and_check_row(row, geo_type, filepath=None):
     missing_sample_size = CsvImporter.validate_missing_code(row, sample_size, "sample_size", filepath)
 
     # return extracted and validated row values
-    row_values = CsvImporter.RowValues(
-      geo_id, value, stderr, sample_size,
-      missing_value, missing_stderr, missing_sample_size
-    )
-    return (row_values, None)
+    return (CsvRowValues(geo_id, value, stderr, sample_size, missing_value, missing_stderr, missing_sample_size), None)
 
   @staticmethod
-  def load_csv(filepath, geo_type, pandas=pandas):
+  def load_csv(filepath, geo_type):
     """Load, validate, and yield data as `RowValues` from a CSV file.
 
     filepath: the CSV file to be loaded
@@ -350,10 +344,10 @@ def load_csv(filepath, geo_type, pandas=pandas):
     logger = get_structured_logger('load_csv')
 
     try:
-      table = pandas.read_csv(filepath, dtype=CsvImporter.DTYPES)
+      table = pd.read_csv(filepath, dtype=CsvImporter.DTYPES)
     except ValueError as e:
       logger.warning(event='Failed to open CSV with specified dtypes, switching to str', detail=str(e), file=filepath)
-      table = pandas.read_csv(filepath, dtype='str')
+      table = pd.read_csv(filepath, dtype='str')
 
     if not CsvImporter.is_header_valid(table.columns):
       logger.warning(event='invalid header', detail=table.columns, file=filepath)

src/acquisition/covidcast/csv_to_database.py

@@ -6,10 +6,10 @@
 import time
 
 # first party
-from delphi.epidata.acquisition.covidcast.csv_importer import CsvImporter
-from delphi.epidata.acquisition.covidcast.database import Database, CovidcastRow
-from delphi.epidata.acquisition.covidcast.file_archiver import FileArchiver
-from delphi.epidata.acquisition.covidcast.logger import get_structured_logger
+from .csv_importer import CsvImporter
+from .database import Database, CovidcastRow
+from .file_archiver import FileArchiver
+from .logger import get_structured_logger
 
 
 def get_argument_parser():

tests/acquisition/covidcast/test_csv_importer.py

@@ -5,17 +5,15 @@
 from unittest.mock import MagicMock
 from unittest.mock import patch
 from datetime import date
-import math
 import numpy as np
-import os
 
 # third party
-import pandas
+import pandas as pd
 import epiweeks as epi
 
 from delphi_utils import Nans
-from delphi.epidata.acquisition.covidcast.csv_importer import CsvImporter
 from delphi.utils.epiweek import delta_epiweeks
+from ....src.acquisition.covidcast.csv_importer import CsvImporter, CsvRowValues
 
 # py3tester coverage target
 __test_target__ = 'delphi.epidata.acquisition.covidcast.csv_importer'
@@ -208,37 +206,38 @@ def make_row(
       self.assertEqual(error, field)
 
     success_cases = [
-      (make_row(), CsvImporter.RowValues('vi', 1.23, 4.56, 100.5, Nans.NOT_MISSING, Nans.NOT_MISSING, Nans.NOT_MISSING)),
-      (make_row(value=None, stderr=np.nan, sample_size='', missing_value=str(float(Nans.DELETED)), missing_stderr=str(float(Nans.DELETED)), missing_sample_size=str(float(Nans.DELETED))), CsvImporter.RowValues('vi', None, None, None, Nans.DELETED, Nans.DELETED, Nans.DELETED)),
-      (make_row(stderr='', sample_size='NA', missing_stderr=str(float(Nans.OTHER)), missing_sample_size=str(float(Nans.OTHER))), CsvImporter.RowValues('vi', 1.23, None, None, Nans.NOT_MISSING, Nans.OTHER, Nans.OTHER)),
-      (make_row(sample_size=None, missing_value='missing_value', missing_stderr=str(float(Nans.OTHER)), missing_sample_size=str(float(Nans.NOT_MISSING))), CsvImporter.RowValues('vi', 1.23, 4.56, None, Nans.NOT_MISSING, Nans.NOT_MISSING, Nans.OTHER)),
+      (make_row(), CsvRowValues('vi', 1.23, 4.56, 100.5, Nans.NOT_MISSING, Nans.NOT_MISSING, Nans.NOT_MISSING)),
+      (make_row(value=None, stderr=np.nan, sample_size='', missing_value=str(float(Nans.DELETED)), missing_stderr=str(float(Nans.DELETED)), missing_sample_size=str(float(Nans.DELETED))), CsvRowValues('vi', None, None, None, Nans.DELETED, Nans.DELETED, Nans.DELETED)),
+      (make_row(stderr='', sample_size='NA', missing_stderr=str(float(Nans.OTHER)), missing_sample_size=str(float(Nans.OTHER))), CsvRowValues('vi', 1.23, None, None, Nans.NOT_MISSING, Nans.OTHER, Nans.OTHER)),
+      (make_row(sample_size=None, missing_value='missing_value', missing_stderr=str(float(Nans.OTHER)), missing_sample_size=str(float(Nans.NOT_MISSING))), CsvRowValues('vi', 1.23, 4.56, None, Nans.NOT_MISSING, Nans.NOT_MISSING, Nans.OTHER)),
     ]
 
     for ((geo_type, row), field) in success_cases:
       values, error = CsvImporter.extract_and_check_row(row, geo_type)
       self.assertIsNone(error)
-      self.assertIsInstance(values, CsvImporter.RowValues)
+      self.assertIsInstance(values, CsvRowValues)
       self.assertEqual(values.geo_value, field.geo_value)
       self.assertEqual(values.value, field.value)
       self.assertEqual(values.stderr, field.stderr)
       self.assertEqual(values.sample_size, field.sample_size)
 
-  def test_load_csv_with_invalid_header(self):
+  @patch("pandas.read_csv")
+  def test_load_csv_with_invalid_header(self, mock_read_csv):
     """Bail loading a CSV when the header is invalid."""
 
     data = {'foo': [1, 2, 3]}
-    mock_pandas = MagicMock()
-    mock_pandas.read_csv.return_value = pandas.DataFrame(data=data)
     filepath = 'path/name.csv'
     geo_type = 'state'
 
-    rows = list(CsvImporter.load_csv(filepath, geo_type, pandas=mock_pandas))
+    mock_read_csv.return_value = pd.DataFrame(data)
+    rows = list(CsvImporter.load_csv(filepath, geo_type))
 
-    self.assertTrue(mock_pandas.read_csv.called)
-    self.assertTrue(mock_pandas.read_csv.call_args[0][0], filepath)
+    self.assertTrue(mock_read_csv.called)
+    self.assertTrue(mock_read_csv.call_args[0][0], filepath)
     self.assertEqual(rows, [None])
 
-  def test_load_csv_with_valid_header(self):
+  @patch("pandas.read_csv")
+  def test_load_csv_with_valid_header(self, mock_read_csv):
     """Yield sanity checked `RowValues` from a valid CSV file."""
 
     # one invalid geo_id, but otherwise valid
@@ -248,15 +247,14 @@ def test_load_csv_with_valid_header(self):
       'se': ['2.1', '2.2', '2.3', '2.4'],
       'sample_size': ['301', '302', '303', '304'],
     }
-    mock_pandas = MagicMock()
-    mock_pandas.read_csv.return_value = pandas.DataFrame(data=data)
     filepath = 'path/name.csv'
     geo_type = 'state'
 
-    rows = list(CsvImporter.load_csv(filepath, geo_type, pandas=mock_pandas))
+    mock_read_csv.return_value = pd.DataFrame(data=data)
+    rows = list(CsvImporter.load_csv(filepath, geo_type))
 
-    self.assertTrue(mock_pandas.read_csv.called)
-    self.assertTrue(mock_pandas.read_csv.call_args[0][0], filepath)
+    self.assertTrue(mock_read_csv.called)
+    self.assertTrue(mock_read_csv.call_args[0][0], filepath)
     self.assertEqual(len(rows), 4)
 
     self.assertEqual(rows[0].geo_value, 'ca')
@@ -286,15 +284,14 @@ def test_load_csv_with_valid_header(self):
       'missing_stderr': [Nans.NOT_MISSING, Nans.REGION_EXCEPTION, Nans.NOT_MISSING, Nans.NOT_MISSING] + [None],
       'missing_sample_size': [Nans.NOT_MISSING] * 2 + [Nans.REGION_EXCEPTION] * 2 + [None]
     }
-    mock_pandas = MagicMock()
-    mock_pandas.read_csv.return_value = pandas.DataFrame(data=data)
     filepath = 'path/name.csv'
     geo_type = 'state'
 
-    rows = list(CsvImporter.load_csv(filepath, geo_type, pandas=mock_pandas))
+    mock_read_csv.return_value = pd.DataFrame(data)
+    rows = list(CsvImporter.load_csv(filepath, geo_type))
 
-    self.assertTrue(mock_pandas.read_csv.called)
-    self.assertTrue(mock_pandas.read_csv.call_args[0][0], filepath)
+    self.assertTrue(mock_read_csv.called)
+    self.assertTrue(mock_read_csv.call_args[0][0], filepath)
     self.assertEqual(len(rows), 5)
 
     self.assertEqual(rows[0].geo_value, 'ca')

tests/acquisition/covidcast/test_csv_to_database.py

@@ -5,8 +5,7 @@
 import unittest
 from unittest.mock import MagicMock
 
-from delphi.epidata.acquisition.covidcast.csv_to_database import get_argument_parser, main, \
-  collect_files, upload_archive, make_handlers
+from ....src.acquisition.covidcast.csv_to_database import get_argument_parser, main, collect_files, upload_archive, make_handlers
 
 # py3tester coverage target
 __test_target__ = 'delphi.epidata.acquisition.covidcast.csv_to_database'