96e2c6ee34
fixed server/main.py fixed several sheetcopilot tasks fixed several calc metrics, including float difference of sheet_data and conditional formatting recognition
473 lines
21 KiB
Python
473 lines
21 KiB
Python
import functools
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import itertools
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import logging
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import os.path
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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, Iterable
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from typing import Dict, List, Tuple
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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.cell.cell import Cell
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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 openpyxl.worksheet.worksheet import Worksheet
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from .utils import _match_value_to_rule, _read_cell_style, read_cell_value
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from .utils import load_charts, load_sparklines, load_rows_or_cols, load_xlsx_styles\
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, load_filters, load_pivot_tables
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# from openpyxl.utils import coordinate_to_tuple
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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 = None, **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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try:
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xlworkbookr: Workbook = openpyxl.load_workbook(filename=result)
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pdworkbookr = pd.ExcelFile(result)
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except:
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return 0.
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worksheetr_names: List[str] = pdworkbookr.sheet_names
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if expected is not None:
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xlworkbooke: Workbook = openpyxl.load_workbook(filename=expected)
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pdworkbooke = pd.ExcelFile(expected)
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worksheete_names: List[str] = pdworkbooke.sheet_names
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else:
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xlworkbooke: Workbook = None
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pdworkbooke = None
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worksheete_names: List[str] = None
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parse_idx: Callable[[Union[str, int], BOOK, BOOK], Tuple[BOOK, str]] = \
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functools.partial(
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_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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# precision: int as number of decimal digits, default to 4
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error_limit: int = r.get("precision", 4)
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sheet1: pd.DataFrame = _load_sheet(*parse_idx(r["sheet_idx0"], pdworkbookr, pdworkbooke)).round(error_limit)
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sheet2: pd.DataFrame = _load_sheet(*parse_idx(r["sheet_idx1"], pdworkbookr, pdworkbooke)).round(error_limit)
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metric: bool = sheet1.equals(sheet2)
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logger.debug("Sheet1: \n%s", str(sheet1))
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logger.debug("Sheet2: \n%s", str(sheet2))
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logger.debug("Sheet1 =v= Sheet2: \n%s", str(sheet1==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"] == "style":
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# Compare Style (Also Conditional Formatiing) {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# props: list of str indicating concerned styles, see utils._read_cell_style
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sheet_idx1: Tuple[Book, str] = parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke)
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book_name1: str = parse_idx(r["sheet_idx0"], result, expected)[0]
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styles1: Dict[str, List[Any]] = load_xlsx_styles(*sheet_idx1, book_name1, **r)
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sheet_idx2: Tuple[Book, str] = parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke)
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book_name2: str = parse_idx(r["sheet_idx1"], result, expected)[0]
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styles2: Dict[str, List[Any]] = load_xlsx_styles(*sheet_idx2, book_name2, **r)
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# number_formats1: List[str] = [c.number_format.lower() for col in sheet1.iter_cols() for c in col if c.value is not None and 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.value is not None and c.data_type=="n"]
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metric: bool = styles1 == styles2
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logger.debug("Assertion: %s.style == %s.style - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Style (Also Conditional Formatiing) #
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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"],
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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": anything}}
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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 = len(data_validators) >= len(r["dv_props"])
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for dat_vldt in data_validators:
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metric = False
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for prpt 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 prpt.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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elif r["type"] == "row_props":
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# Check Row Properties {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# props: list of str, see utils.load_rows_or_cols
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rows1: Dict[str, Any] = load_rows_or_cols(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke)
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, obj="row"
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, **r
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)
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rows2: Dict[str, Any] = load_rows_or_cols(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke)
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, obj="row"
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, **r
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)
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logger.debug("Rows1: %s", repr(rows1))
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logger.debug("Rows2: %s", repr(rows2))
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metric: bool = rows1 == rows2
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logger.debug("Assertion: %s[rows] == %s[rows] - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Check Row Properties #
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elif r["type"] == "col_props":
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# Check Row Properties {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# props: list of str, see utils.load_rows_or_cols
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cols1: Dict[str, Any] = load_rows_or_cols(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke)
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, obj="column"
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, **r
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)
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cols2: Dict[str, Any] = load_rows_or_cols(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke)
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, obj="column"
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, **r
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)
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metric: bool = cols1 == cols2
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logger.debug("Assertion: %s[cols] == %s[cols] - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Check Row Properties #
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elif r["type"] == "filter":
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# Compare Filters {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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filters1: Dict[str, Any] = load_filters(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke), **r)
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filters2: Dict[str, Any] = load_filters(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke), **r)
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metric: bool = filters1==filters2
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logger.debug("Assertion: %s[filter] == %s[filter] - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Filters #
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elif r["type"] == "pivot_table":
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# Compare Pivot Tables {{{ #
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# sheet_idx0: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# sheet_idx1: as sheet_idx0
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# pivot_props: list of str, see utils.load_pivot_tables
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pivots1: Dict[str, Any] = load_pivot_tables(*parse_idx(r["sheet_idx0"], xlworkbookr, xlworkbooke), **r)
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pivots2: Dict[str, Any] = load_pivot_tables(*parse_idx(r["sheet_idx1"], xlworkbookr, xlworkbooke), **r)
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metric: bool = pivots1==pivots2
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logger.debug("Assertion: %s[pivot]==%s[pivot] - %s", r["sheet_idx0"], r["sheet_idx1"], metric)
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# }}} Compare Pivot Tables #
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elif r["type"] == "check_cell":
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# Check Cell Properties {{{ #
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# sheet_idx: 0 == "RI0" == "RNSheet1" | "EI0" == "ENSheet1"
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# coordinate: str, "E3"
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# props: dict like {attribute: {"method": str, "ref": anything}}
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# supported attributes: value & those supported by utils._read_cell_style
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sheet: Worksheet = _load_sheet(*parse_idx(r["sheet_idx"], xlworkbookr, xlworkbooke))
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# data_frame: pd.DataFrame = _load_sheet(*parse_idx(r["sheet_idx"], pdworkbookr, pdworkbooke))
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cell: Cell = sheet[r["coordinate"]]
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metric: bool = True
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for prpt, rule in r["props"].items():
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if prpt == "value":
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val = read_cell_value(*parse_idx(r["sheet_idx"], result, expected), r["coordinate"])
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else:
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val = _read_cell_style(prpt, cell)
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metric = metric and _match_value_to_rule(val, rule)
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logger.debug("Assertion: %s[%s] :%s - %s"
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, r["sheet_idx"], r["coordinate"]
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, repr(r["props"]), metric
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)
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# }}} Check Cell Properties #
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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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def compare_csv(result: str, expected: str, **options) -> float:
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if result is None:
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return 0.
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with open(result) as f:
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result_lines: Iterable[str] = f.read().splitlines()
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with open(expected) as f:
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expected_lines: Iterable[str] = f.read().splitlines()
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if not options.get("strict", True):
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result_lines = map(str.strip, result_lines)
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expected_lines = map(str.strip, expected_lines)
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if options.get("ignore_case", False):
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result_lines = map(str.lower, result_lines)
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expected_lines = map(str.lower, expected_lines)
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metric: bool = list(result_lines) == list(expected_lines)
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return float(metric)
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if __name__ == '__main__':
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import datetime
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import sys
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logger = logging.getLogger()
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logger.setLevel(logging.DEBUG)
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datetime_str: str = datetime.datetime.now().strftime("%Y%m%d@%H%M%S")
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file_handler = logging.FileHandler(os.path.join("logs", "normal-{:}.log".format(datetime_str)))
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debug_handler = logging.FileHandler(os.path.join("logs", "debug-{:}.log".format(datetime_str)))
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stdout_handler = logging.StreamHandler(sys.stdout)
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sdebug_handler = logging.FileHandler(os.path.join("logs", "sdebug-{:}.log".format(datetime_str)))
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file_handler.setLevel(logging.INFO)
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debug_handler.setLevel(logging.DEBUG)
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stdout_handler.setLevel(logging.INFO)
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sdebug_handler.setLevel(logging.DEBUG)
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formatter = logging.Formatter(
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fmt="\x1b[1;33m[%(asctime)s \x1b[31m%(levelname)s \x1b[32m%(module)s/%(lineno)d-%(processName)s\x1b[1;33m] \x1b[0m%(message)s")
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file_handler.setFormatter(formatter)
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debug_handler.setFormatter(formatter)
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stdout_handler.setFormatter(formatter)
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|
sdebug_handler.setFormatter(formatter)
|
|
|
|
stdout_handler.addFilter(logging.Filter("desktopenv"))
|
|
sdebug_handler.addFilter(logging.Filter("desktopenv"))
|
|
|
|
logger.addHandler(file_handler)
|
|
logger.addHandler(debug_handler)
|
|
logger.addHandler(stdout_handler)
|
|
logger.addHandler(sdebug_handler)
|
|
|
|
path1 = "snapshots/test/cache/4e6fcf72-daf3-439f-a232-c434ce416af6/Employee_Age_By_Birthday.xlsx"
|
|
path2 = "snapshots/test/cache/4e6fcf72-daf3-439f-a232-c434ce416af6/Employee_Age_By_Birthday_gold.xlsx"
|
|
rules = [ { "type": "sheet_data"
|
|
, "sheet_idx0": 0
|
|
, "sheet_idx1": "EI0"
|
|
}
|
|
]
|
|
print(compare_table(path1, path2
|
|
, rules=rules
|
|
)
|
|
)
|
|
print(compare_table(path2, path2
|
|
, rules=rules
|
|
)
|
|
)
|
|
|
|
# Row Properties
|
|
# path1 = "../../任务数据/LibreOffice Calc/Date_Budget_Variance_HideNA.xlsx"
|
|
# path2 = "../../任务数据/LibreOffice Calc/Date_Budget_Variance_HideNA_gold.xlsx"
|
|
# workbook: Workbook = openpyxl.load_workbook(filename=path1)
|
|
# worksheet: Worksheet = workbook.active
|
|
# for r_no, dms in worksheet.column_dimensions.items():
|
|
# print(r_no, type(r_no), type(dms), dms.hidden)
|
|
|
|
# Conditional Formats
|
|
# import formulas
|
|
# path1 = "../../任务数据/LibreOffice Calc/Calendar_Highlight_Weekend_Days.xlsx"
|
|
# path2 = "../../任务数据/LibreOffice Calc/Calendar_Highlight_Weekend_Days_gold.xlsx"
|
|
# path3 = "../../任务数据/LibreOffice Calc/Calendar_Highlight_Weekend_Days_gold_test.xlsx"
|
|
# workbook: Workbook = openpyxl.load_workbook(filename=path2)
|
|
# worksheet: Worksheet = workbook.active
|
|
# print(worksheet.conditional_formatting)
|
|
# for itm in worksheet.conditional_formatting:
|
|
# print(itm.cells)
|
|
# for r in itm.rules:
|
|
# print( r.type, r.formula, r.dxf.font.color.rgb
|
|
# , r.dxf.fill.fgColor.rgb, r.dxf.fill.bgColor.rgb
|
|
# )
|
|
# condition = formulas.Parser().ast("=" + r.formula[0])[1].compile()
|
|
##print(r.type, r.operator, r.dxfId, r.dxf)
|
|
# for r in itm.cells:
|
|
# for c in r.cells:
|
|
# value = worksheet.cell(row=c[0], column=c[1]).value
|
|
# print(value, condition(str(value)))
|