291 lines
12 KiB
Python
291 lines
12 KiB
Python
import logging
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import operator
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from numbers import Number
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from typing import Any, Union, cast, Callable
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from typing import Dict, List, Tuple
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import os.path
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import itertools
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import functools
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import openpyxl
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import pandas as pd
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from openpyxl import Workbook
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from openpyxl.worksheet.worksheet import Worksheet
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#from openpyxl.worksheet.cell_range import MultiCellRange
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from openpyxl.worksheet.datavalidation import DataValidation
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from .utils import load_charts, load_sparklines, _match_value_to_rule
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logger = logging.getLogger("desktopenv.metric.table")
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BOOK = Union[pd.ExcelFile, Workbook, str]
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def _parse_sheet_idx( sheet_idx: Union[int, str]
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, result: BOOK, expected: BOOK
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, result_sheet_names: List[str]
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, expected_sheet_names: List[str]
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) -> Tuple[BOOK, str]:
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# function _parse_sheet_idx {{{ #
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if isinstance(sheet_idx, int):
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index: str = result_sheet_names[sheet_idx]
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book: BOOK = result
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elif sheet_idx.startswith("RI"):
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index: str = result_sheet_names[int(sheet_idx[2:])]
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book: BOOK = result
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elif sheet_idx.startswith("RN"):
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index: str = sheet_idx[2:]
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book: BOOK = result
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elif sheet_idx.startswith("EI"):
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index: str = expected_sheet_names[int(sheet_idx[2:])]
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book: BOOK = expected
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elif sheet_idx.startswith("EN"):
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index: str = sheet_idx[2:]
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book: BOOK = expected
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else:
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logger.error("Unrecognized sheet index")
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raise ValueError("Unrecognized sheet index")
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return book, index
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# }}} function _parse_sheet_idx #
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SHEET = Union[pd.DataFrame, Worksheet, List[str]]
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def _load_sheet(book: BOOK, index: str) -> SHEET:
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# function _load_sheet {{{ #
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if isinstance(book, str):
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book: str = cast(str, book)
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csv_name: str = "{:}-{:}.csv".format(os.path.splitext(book)[0], index)
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with open(csv_name) as f:
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csv_lines: List[str] = list( itertools.dropwhile( lambda l: len(l)==0
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, map( lambda l: l.strip()
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, reversed(f.read().splitlines())
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)
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)
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)
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return csv_lines
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if isinstance(book, pd.ExcelFile):
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return pd.read_excel(book, index)
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if isinstance(book, Workbook):
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return book[index]
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logger.error("Not supported workbook format")
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raise NotImplementedError("Not supported workbook format")
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# }}} function _load_sheet #
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def compare_table(result: str, expected: str, **options) -> float:
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# function compare_table {{{ #
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"""
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Args:
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result (str): path to result xlsx
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expected (str): path to golden xlsx
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rules (List[Dict[str, Any]]): list of dict like
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{
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"type": str,
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<str as parameters>: anything
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}
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as sequential rules
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Returns:
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float: the score
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"""
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if result is None:
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return 0.
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xlworkbookr: Workbook = openpyxl.load_workbook(filename=result)
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pdworkbookr = pd.ExcelFile(xlworkbookr, engine="openpyxl")
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worksheetr_names: List[str] = pdworkbookr.sheet_names
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xlworkbooke: Workbook = openpyxl.load_workbook(filename=expected)
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pdworkbooke = pd.ExcelFile(xlworkbooke, engine="openpyxl")
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worksheete_names: List[str] = pdworkbooke.sheet_names
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parse_idx: Callable[[Union[str, int], BOOK, BOOK], BOOK] =\
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functools.partial( _parse_sheet_idx
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, result_sheet_names=worksheetr_names
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, expected_sheet_names=worksheete_names
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)
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passes = True
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for r in options["rules"]:
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if r["type"] == "sheet_name":
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# Compare Sheet Names {{{ #
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metric: bool = worksheetr_names==worksheete_names
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logger.debug("Assertion: %s.sheet_names == %s.sheet_names - %s", result, expected, metric)
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# }}} Compare Sheet Names #
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elif r["type"] == "sheet_data":
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# Compare Sheet Data by Internal Value {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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sheet1: pd.DataFrame = _load_sheet(*parse_idx(r["sheet_idx0"], pdworkbookr, pdworkbooke))
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sheet2: pd.DataFrame = _load_sheet(*parse_idx(r["sheet_idx1"], pdworkbookr, pdworkbooke))
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metric: bool = sheet1.equals(sheet2)
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logger.debug("Assertion: %s =v= %s - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Sheet Data by Internal Value #
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elif r["type"] == "sheet_print":
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# Compare Sheet Data by Printed Value {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# ignore_case: optional, defaults to False
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sheet1: List[str] = _load_sheet(*parse_idx(r["sheet_idx0"], result, expected))
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sheet2: List[str] = _load_sheet(*parse_idx(r["sheet_idx1"], result, expected))
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if r.get("ignore_case", False):
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sheet1 = [l.lower() for l in sheet1]
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sheet2 = [l.lower() for l in sheet2]
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metric: bool = sheet1 == sheet2
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logger.debug("Assertion: %s =p= %s - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Sheet Data by Printed Value #
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elif r["type"] == "sparkline":
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# Compare Sparklines {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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sparkline1: Dict[str, str] = load_sparklines(*parse_idx(r["sheet_idx0"], result, expected))
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sparkline2: Dict[str, str] = load_sparklines(*parse_idx(r["sheet_idx1"], result, expected))
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metric: bool = sparkline1 == sparkline2
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logger.debug("Assertion: %s.sp == %.sp - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Sparklines #
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elif r["type"] == "chart":
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# Compare Charts {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# chart_props: list of str, see utils.load_charts
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charts1: Dict[str, Any] = load_charts(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke), **r)
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charts2: Dict[str, Any] = load_charts(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke), **r)
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metric: bool = charts1 == charts2
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logger.debug("Assertion: %s[chart] == %s[chart] - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Charts #
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elif r["type"] == "number_format":
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# Compare Number Formats {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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sheet1: Worksheet = _load_sheet(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke))
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sheet2: Worksheet = _load_sheet(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke))
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number_formats1: List[str] = [c.number_format.lower() for col in sheet1.iter_cols() for c in col if c.data_type=="n"]
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number_formats2: List[str] = [c.number_format.lower() for col in sheet2.iter_cols() for c in col if c.data_type=="n"]
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metric: bool = number_formats1 == number_formats2
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logger.debug("Assertion: %s.nf == %s.nf - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Number Formats #
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elif r["type"] == "freeze":
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# Compare Freezing {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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sheet1: Worksheet = _load_sheet(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke))
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sheet2: Worksheet = _load_sheet(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke))
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metric: bool = sheet1.freeze_panes == sheet2.freeze_panes
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logger.debug( "Assertion: %s.freeze(%s) == %s.freeze(%s) - %s"
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, r["sheet_idx0"], sheet1.freeze_panes
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, r["sheet_idx1"], sheet2.freeze_panes
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, metric
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)
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# }}} Compare Freezing #
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elif r["type"] == "zoom":
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# Check Zooming {{{ #
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# sheet_idx: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# method: str
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# ref: value
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sheet: Worksheet = _load_sheet(*parse_idx(r["sheet_idx"], xlworkbookr, xlworkbooke))
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zoom_scale: Number = sheet.sheet_view.zoomScale or 100.
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metric: bool = _match_value_to_rule(zoom_scale, r)
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logger.debug("Assertion: %s.zoom(%.1f) %s %.1f - %s", r["sheet_idx"], zoom_scale, r["method"], r["ref"], metric)
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# }}} Check Zooming #
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elif r["type"] == "data_validation":
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# Check Data Validation {{{ #
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# sheet_idx: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# dv_props: list of dict like {attribute: "method": str, "ref": anythin}
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# available attributes:
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# * ranges
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# * type
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# * formula1
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# * formula2
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# * operator
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# * allowBlank
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# * showDropDown
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# * showInputMessage
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# * showErrorMessage
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# * error
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# * errorTitle
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# * errorStyle
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# * prompt
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# * promptTitle
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# * imeMode
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sheet: Worksheet = _load_sheet(*parse_idx(r["sheet_idx"], xlworkbookr, xlworkbooke))
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data_validators: List[DataValidation] = sheet.data_validations.dataValidation
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total_metric = True
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for dat_vldt in data_validators:
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metric = False
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for r in r["dv_props"]:
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metric = metric or all( _match_value_to_rule( getattr(dat_vldt, attrbt)
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, mr
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)\
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for attrbt, mr in r.items()
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)
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if metric:
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break
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total_metric = total_metric and metric
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if not total_metric:
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break
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logger.debug("Assertion: %s.data_validation - %s", r["sheet_idx"], total_metric)
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metric: bool = total_metric
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# }}} Check Data Validation #
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else:
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raise NotImplementedError("Unimplemented sheet check: {:}".format(r["type"]))
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passes = passes and metric
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if not passes:
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break
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return float(passes)
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# }}} function compare_table #
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if __name__ == '__main__':
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path1 = "../../任务数据/LibreOffice Calc/Freeze_row_column.xlsx"
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path2 = "../../任务数据/LibreOffice Calc/Freeze_row_column_gold.xlsx"
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rules = [ { "type": "sheet_data"
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, "sheet_idx0": 0
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, "sheet_idx1": "EI0"
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}
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, { "type": "freeze"
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, "sheet_idx0": 0
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, "sheet_idx1": "EI0"
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}
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]
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print( compare_table( path1, path2
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, rules=rules
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)
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)
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print( compare_table( path2, path2
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, rules=rules
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)
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)
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#path = "../../任务数据/LibreOffice Calc/Order_Id_Mark_Pass_Fail_gold.xlsx"
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#print( check_data_validations( path, [ { "ranges": { "method": "spreadsheet_range"
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#, "ref": ["D2:D29", "D2:D1048576"]
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#}
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#, "type": { "method": "eq"
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#, "ref": "list"
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#}
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#, "formula1": { "method": "str_set_eq"
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#, "ref": ["Pass", "Fail", "Held"]
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#}
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#}
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#]
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#)
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#)
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