diff --git a/src/caosadvancedtools/table_importer.py b/src/caosadvancedtools/table_importer.py
new file mode 100755
index 0000000000000000000000000000000000000000..c859f67524d9ec60962d88dbc904def81acbfd37
--- /dev/null
+++ b/src/caosadvancedtools/table_importer.py
@@ -0,0 +1,148 @@
+#!/usr/bin/env python
+# encoding: utf-8
+#
+# Copyright (C) 2020 Henrik tom Wörden
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Affero General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Affero General Public License for more details.
+#
+# You should have received a copy of the GNU Affero General Public License
+# along with this program. If not, see <https://www.gnu.org/licenses/>.
+
+
+import logging
+
+import numpy as np
+import pandas as pd
+
+from caosadvancedtools.suppressable import Suppressable
+
+logger = logging.getLogger("caosadvancedtools")
+
+
+def name_converter(name):
+ name = str(name)
+
+ if len(name.split(",")) != 2:
+ raise ValueError("Name field should be 'LastName, FirstName'."
+ "The supplied value was '{}'.".format(name))
+
+ return name
+
+
+def yes_no_converter(val):
+ if str(val).lower() == "yes":
+ return True
+ elif str(val).lower() == "no":
+ return False
+ else:
+ raise ValueError(
+ "Field should be 'Yes' or 'No', but is '{}'.".format(val))
+
+
+class XLS_Importer(object):
+ def __init__(self, converters, obligatory_columns=[], unique_columns=[]):
+ """
+
+ converters: dict with column names as keys and converter functions as
+ values
+ This dict also defines what columns are required to exist
+ throught the existing keys. The converter functions are
+ applied to the cell values. They should also check for
+ ValueErrors, such that a separate value check is not
+ necessary.
+ obligatory_columns: list of column names, optional
+ each listed column must not have missing values
+ """
+ self.sup = Suppressable(logger=logger)
+ self.required_columns = list(converters.keys())
+ self.obligatory_columns = obligatory_columns
+ self.unique_columns = unique_columns
+ self.converters = converters
+
+ def read_xls(self, filename):
+ xls_file = pd.io.excel.ExcelFile(filename)
+
+ if len(xls_file .sheet_names) > 1:
+ # Multiple sheets is the default now. Only show in debug
+ logger.debug("Excel file {} contains multiple sheets. "
+ "All but the first are being ignored.".format(
+ filename
+ ))
+
+ df = xls_file.parse(converters=self.converters)
+ self.check_columns(df, filename=filename)
+ df = self.check_missing(df, filename=filename)
+
+ if len(self.unique_columns) > 0:
+ df = self.check_unique(df, filename=filename)
+
+ return df
+
+ def check_columns(self, df, filename=None):
+ for col in self.required_columns:
+ if col not in df.columns:
+ errmssg = "Column '{}' missing in ".format(col)
+ errmssg += "{}.".format(filename) if filename else "the file."
+ raise ValueError(errmssg)
+
+ def check_unique(self, df, filename=None):
+ df = df.copy()
+ uniques = []
+
+ for index, row in df.iterrows():
+ element = tuple(row.loc[key] for key in self.unique_columns)
+
+ if element in uniques:
+ errmssg = (
+ "The {}. row contains the values '{}'.\nThis value "
+ "combination should be unique, but was used in a previous "
+ "row in\n").format(index+1, element)
+ errmssg += "{}.".format(filename) if filename else "the file."
+ errmssg += "\nThis row will be ignored!"
+
+ self.sup.warning(errmssg, identifier=filename,
+ category="inconsistency")
+ df = df.drop(index)
+ else:
+ uniques.append(element)
+
+ return df
+
+ def check_missing(self, df, filename=None):
+ df = df.copy()
+
+ for index, row in df.iterrows():
+ # if none of the relevant information is given, skip
+
+ if np.array([pd.isnull(row.loc[key]) for key in
+ self.obligatory_columns]).all():
+
+ df = df.drop(index)
+
+ continue
+
+ # if any of the relevant information is missing, report it
+
+ for key in self.obligatory_columns:
+
+ if pd.isnull(row.loc[key]):
+ errmssg = (
+ "Required information is missing ({}) in {}. row"
+ " (without header) of "
+ "file:\n{}".format(key, index+1, filename))
+
+ self.sup.warning(errmssg, identifier=filename,
+ category="inconsistency")
+ df = df.drop(index)
+
+ continue
+
+ return df
diff --git a/tox.ini b/tox.ini
index 57cda000e9853362917c1e8830d9ebc589d0e9e4..e40e0ad367fb7d909363b6f376734e3c923b9f11 100644
--- a/tox.ini
+++ b/tox.ini
@@ -7,4 +7,6 @@ deps=nose
caosdb
pytest
pytest-cov
+ openpyxl
+ xlrd
commands=py.test --cov=caosadvancedtools -vv {posargs}
diff --git a/unittests/test_table_importer.py b/unittests/test_table_importer.py
new file mode 100644
index 0000000000000000000000000000000000000000..49debb43f20704c301a77cf2386307c9d3de7d1b
--- /dev/null
+++ b/unittests/test_table_importer.py
@@ -0,0 +1,83 @@
+#!/usr/bin/env python
+# encoding: utf-8
+#
+# Copyright (C) 2020 Henrik tom Wörden
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU Affero General Public License as
+# published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU Affero General Public License for more details.
+#
+# You should have received a copy of the GNU Affero General Public License
+# along with this program. If not, see <https://www.gnu.org/licenses/>.
+
+
+import unittest
+from tempfile import NamedTemporaryFile
+
+import numpy as np
+import pandas as pd
+from caosadvancedtools.table_importer import (XLS_Importer, name_converter,
+ yes_no_converter)
+
+
+class ConverterTest(unittest.TestCase):
+ def test_yes_no(self):
+ self.assertTrue(yes_no_converter("YES"))
+ self.assertTrue(yes_no_converter("Yes"))
+ self.assertTrue(yes_no_converter("yes"))
+ self.assertTrue(not yes_no_converter("No"))
+ self.assertTrue(not yes_no_converter("no"))
+ self.assertRaises(ValueError, yes_no_converter, "nope")
+ self.assertRaises(ValueError, yes_no_converter, "FALSE")
+ self.assertRaises(ValueError, yes_no_converter, "TRUE")
+ self.assertRaises(ValueError, yes_no_converter, "True")
+ self.assertRaises(ValueError, yes_no_converter, "true")
+
+ def test_name_converter(self):
+ self.assertEqual(name_converter("Müstermann, Max"), "Müstermann, Max")
+ self.assertRaises(ValueError, name_converter, "Max Mustermann")
+
+
+class XLS_ImporterTest(unittest.TestCase):
+ def setUp(self):
+ self.importer = XLS_Importer(
+ converters={'a': str, 'b': int, 'c': float, 'd': yes_no_converter},
+ obligatory_columns=['a', 'b'], unique_columns=['a', 'b'])
+ self.valid_df = pd.DataFrame(
+ [['a', 1, 2.0, 'yes']], columns=['a', 'b', 'c', 'd'])
+
+ def test_missing_col(self):
+ df = pd.DataFrame(columns=['a', 'b'])
+ self.assertRaises(ValueError, self.importer.check_columns, df)
+ self.importer.check_columns(self.valid_df)
+
+ def test_missing_val(self):
+ self.importer.check_missing(self.valid_df)
+ df = pd.DataFrame([[None, np.nan, 2.0, 'yes'],
+ [None, 1, 2.0, 'yes'],
+ ['a', np.nan, 2.0, 'yes'],
+ ['b', 5, 3.0, 'no']],
+ columns=['a', 'b', 'c', 'd'])
+ df_new = self.importer.check_missing(df)
+ self.assertEqual(df_new.shape[0], 1)
+ self.assertEqual(df_new.shape[1], 4)
+ self.assertEqual(df_new.iloc[0].b, 5)
+
+ def test_full(self):
+ tmp = NamedTemporaryFile(delete=False, suffix=".xlsx")
+ tmp.close()
+ self.valid_df.to_excel(tmp.name)
+ self.importer.read_xls(tmp.name)
+
+ def test_unique(self):
+ self.importer.check_missing(self.valid_df)
+ df = pd.DataFrame([['b', 5, 3.0, 'no'], ['b', 5, 3.0, 'no']],
+ columns=['a', 'b', 'c', 'd'])
+ df_new = self.importer.check_unique(df)
+ self.assertEqual(df_new.shape[0], 1)