5086380612

Build Type

github

Committed by GitHub

Commit Message

Merge 369b9ef71 into 4cad7f0d0

Pull Request Pull Request #78: Add f-score

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94 of 127 branches covered (74.02%)

Branch coverage included in aggregate %.

90 of 140 new or added lines in 7 files covered. (64.29%)

38 existing lines in 4 files now uncovered.

395 of 487 relevant lines covered (81.11%)

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95.0

/src/stocktracer/analysis/diluted_eps.py

"""This analysis module determines the trend of EPS over the course of the past 5 years."""
import logging
from typing import Optional

import pandas as pd
from beartype import beartype

from stocktracer.data.sec import Filter as SecFilter
from stocktracer.data.sec import Sec as SecDataSource
from stocktracer.interface import Analysis as AnalysisInterface

logger = logging.getLogger(__name__)


@beartype
class Analysis(AnalysisInterface):
    """Class that calculates the EPS slope."""

    under_development = True
    years_of_analysis = 5

    def analyze(self) -> Optional[pd.DataFrame]:
        # Create the filter we'll use to scrape the results
        sec_filter = SecFilter(
            tags=["EarningsPerShareDiluted"],
            years=self.years_of_analysis,
            last_report=self.options.last_report,
            only_annual=True,  # We only want the 10-K
        )

        # Create an SEC Data Source
        sec = SecDataSource(storage_path=self.options.cache_path)

        # This is an expensive operation
        sec.filter_data(tickers=self.options.tickers, sec_filter=sec_filter)
        return sec_filter.select("slope").data

    # Reuse documentation from parent
    analyze.__doc__ = AnalysisInterface.analyze.__doc__

1	"""This analysis module determines the trend of EPS over the course of the past 5 years."""
2	import logging	2✔
3	from typing import Optional	2✔
4
5	import pandas as pd	2✔
6	from beartype import beartype	2✔
7
8	from stocktracer.data.sec import Filter as SecFilter	2✔
9	from stocktracer.data.sec import Sec as SecDataSource	2✔
10	from stocktracer.interface import Analysis as AnalysisInterface	2✔
11
12	logger = logging.getLogger(__name__)	2✔
13
14
15	@beartype	2✔
16	class Analysis(AnalysisInterface):	2✔
17	"""Class that calculates the EPS slope."""
18
19	under_development = True	2✔
20	years_of_analysis = 5	2✔
21
22	def analyze(self) -> Optional[pd.DataFrame]:	2✔
23	# Create the filter we'll use to scrape the results
24	sec_filter = SecFilter(	2✔
25	tags=["EarningsPerShareDiluted"],
26	years=self.years_of_analysis,
27	last_report=self.options.last_report,
28	only_annual=True, # We only want the 10-K
29	)
30
31	# Create an SEC Data Source
32	sec = SecDataSource(storage_path=self.options.cache_path)	2✔
33
34	# This is an expensive operation
35	sec.filter_data(tickers=self.options.tickers, sec_filter=sec_filter)	2✔
UNCOV 36	return sec_filter.select("slope").data	×
37
38	# Reuse documentation from parent
39	analyze.__doc__ = AnalysisInterface.analyze.__doc__	2✔

gyund / fundamental-analysis / 5086380612

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