Get rid of pandas

setup.py

@@ -2,7 +2,7 @@
 
 requirements = [
     "openpyxl",
-    "pandas",
+    "odfpy",
     "pyperclip",
     "numpy",
 ]
@@ -18,7 +18,7 @@
     long_description=long_description,
     long_description_content_type="text/markdown",
     install_requires=requirements,
-    python_requires='>=3',
+    python_requires=">=3",
     entry_points={"console_scripts": ["texel = texel.texel:main"]},
     classifiers=[
         "Programming Language :: Python :: 3",

texel/reader.py

@@ -0,0 +1,109 @@
+import ast
+import csv
+import os
+from numbers import Number
+from typing import Any, Dict, Union
+
+
+import numpy as np
+from openpyxl import load_workbook as load_excel
+from odf.opendocument import load as load_odf
+from odf.table import Table, TableCell, TableRow
+
+
+EXCEL_FORMATS = ("xlsx", "xlsm", "xltx", "xltm")
+ODF_FORMATS = ("odf", "odt", "ods")
+SUPPORTED_FORMATS = ("csv", *ODF_FORMATS, *EXCEL_FORMATS)
+
+
+class InvalidFileException(Exception):
+    pass
+
+
+class SpreadsheetReader:
+    def __init__(self, filename: str, delimiter: str, fillna: Any, encoding: str):
+        self.filename = filename
+        self.delimiter = delimiter
+        self.fillna = fillna
+        self.encoding = encoding
+        self.ft = self.filename.split(".")[-1]
+
+    def read(self) -> Dict[str, np.ndarray]:
+        self._validate()
+        if self.ft in EXCEL_FORMATS:
+            sheetdict = self._read_excel()
+        elif self.ft in ODF_FORMATS:
+            sheetdict = self._read_odf()
+        else:
+            sheetdict = self._read_csv()
+        if self.fillna is not None:
+            for key in sheetdict:
+                sheetdict[key][sheetdict[key] == np.nan] = self.fillna
+        return sheetdict
+
+    def _validate(self):
+        self._check_exists()
+        self._check_format()
+
+    def _check_format(self):
+        if self.ft not in SUPPORTED_FORMATS:
+            raise InvalidFileException(
+                f"Invalid file format ({self.ft})\n"
+                + f"Supported formats are: {', '.join(SUPPORTED_FORMATS)}"
+            )
+
+    def _check_exists(self):
+        if not os.path.exists(self.filename):
+            raise FileNotFoundError()
+
+    def _parse_cell(self, value: Union[str, Number, TableCell]) -> Union[str, Number]:
+        if isinstance(value, Number):
+            return value
+        if value is None:
+            return np.nan
+        value = str(value).strip()
+        if len(value) > 0:
+            try:
+                return ast.literal_eval(value)
+            except (SyntaxError, ValueError):
+                return value
+        return np.nan
+
+    def _parse_odfcell(self, cell: TableCell):
+        if cell.getAttribute("valuetype") != "string":
+            cell = cell.getAttribute("value")
+        return self._parse_cell(cell)
+
+    def _read_csv(self):
+        lines = []
+        with open(self.filename, encoding=self.encoding) as csvfile:
+            for line in csv.reader(csvfile, delimiter=self.delimiter):
+                lines.append(list(map(self._parse_cell, line)))
+        return {self.filename: self._to_array(lines)}
+
+    def _read_excel(self):
+        sheets = {}
+        wb = load_excel(filename=self.filename, data_only=True)
+        for sheet in wb.sheetnames:
+            lines = [[self._parse_cell(e.value) for e in row] for row in wb[sheet].rows]
+            sheets[sheet] = self._to_array(lines)
+        return sheets
+
+    def _read_odf(self):
+        sheets = {}
+        wb = load_odf(self.filename)
+        for sheet in wb.getElementsByType(Table):
+            rows = [
+                list(map(self._parse_odfcell, row.getElementsByType(TableCell)))
+                for row in sheet.getElementsByType(TableRow)
+            ]
+            sheets[sheet.getAttribute("name")] = self._to_array(rows)
+        return sheets
+
+    def _to_array(self, lines):
+        shape = len(lines), max(map(len, lines))
+        arr = np.zeros(shape, dtype=object)
+        arr[:] = np.nan
+        for i, line in enumerate(lines):
+            arr[i, : len(line)] = line
+        return arr

texel/utils.py

@@ -1,23 +1,27 @@
-from itertools import combinations, count
 from functools import lru_cache
-import pyperclip
-import pandas as pd
+from itertools import combinations, count
+from typing import Any, Dict, List, Generator
+
+from .reader import SpreadsheetReader, InvalidFileException
+
 import numpy as np
+import pyperclip
 
-from typing import Any, Dict, List, Generator
+HELP = (
+    "ARROWS / hjkl - Move",
+    "<TAB> <SHIFT-TAB> / n <SHIFT n> - Switch sheet",
+    "v - Visual/selection mode",
+    "<ESC> - Exit visual/selection mode",
+    "c / y - Copy selected cell(s)",
+    "q - Exit",
+    "? - Show this message",
+)
 
 
 def read_spreadsheet(
-    filename: str, delimiter: str, fillna: Any
-) -> Dict[str, pd.DataFrame]:
-    if filename.split(".")[-1] == "csv":
-        sheetdict = {filename: pd.read_csv(filename, delimiter=delimiter, header=None)}
-    else:
-        sheetdict = pd.read_excel(filename, sheet_name=None, header=None)
-    if fillna is not None:
-        for key in sheetdict:
-            sheetdict[key].fillna(fillna, inplace=True)
-    return sheetdict
+    filename: str, delimiter: str, fillna: Any, encoding: str
+) -> Dict[str, np.ndarray]:
+    return SpreadsheetReader(filename, delimiter, fillna, encoding).read()
 
 
 @lru_cache()