tests for notes_tools

notes_tools/df_marks_manip.py

@@ -188,14 +188,15 @@ def compute_exo_marks(df):
     >>> df["Mark"] = compute_marks(df)
     >>> compute_exo_marks(df)
       Eleve Nom Exercice        Date Trimestre  Bareme  Mark Question  Niveau
-    0    E1  N1      Ex1  16/09/2016         1       2   1.5    Total       0
-    1    E1  N1      Ex2  16/09/2016         1       4   3.5    Total       0
-    2    E1  N2      Ex1  01/10/2016         1       2   1.0    Total       0
-    3    E1  N2      Ex2  01/10/2016         1       2   2.0    Total       0
-    4    E2  N1      Ex1  16/09/2016         1       2   2.0    Total       0
-    5    E2  N1      Ex2  16/09/2016         1       4   2.5    Total       0
-    6    E2  N2      Ex1  01/10/2016         1       2   1.5    Total       0
-    7    E2  N2      Ex2  01/10/2016         1       2   2.0    Total       0
+    0    E1  N1      Ex1  16/09/2016         1     2.0   1.5    Total       0
+    1    E1  N1      Ex2  16/09/2016         1     4.0   3.5    Total       0
+    2    E1  N2      Ex1  01/10/2016         1     2.0   1.0    Total       0
+    3    E1  N2      Ex2  01/10/2016         1     2.0   2.0    Total       0
+    4    E2  N1      Ex1  16/09/2016         1     2.0   2.0    Total       0
+    5    E2  N1      Ex2  16/09/2016         1     4.0   2.5    Total       0
+    6    E2  N2      Ex1  01/10/2016         1     2.0   1.5    Total       0
+    7    E2  N2      Ex2  01/10/2016         1     2.0   2.0    Total       0
+
 
     """
     exo_pt = pd.pivot_table(df,
@@ -230,10 +231,10 @@ def compute_eval_marks(df):
     >>> df_exo = compute_exo_marks(df)
     >>> compute_eval_marks(df_exo)
       Eleve Nom        Date Trimestre  Bareme  Mark Exercice  Niveau
-    0    E1  N1  16/09/2016         1       6   5.0    Total       0
-    1    E1  N2  01/10/2016         1       4   3.0    Total       0
-    2    E2  N1  16/09/2016         1       6   4.5    Total       0
-    3    E2  N2  01/10/2016         1       4   3.5    Total       0
+    0    E1  N1  16/09/2016         1     6.0   5.0    Total       0
+    1    E1  N2  01/10/2016         1     4.0   3.0    Total       0
+    2    E2  N1  16/09/2016         1     6.0   4.5    Total       0
+    3    E2  N2  01/10/2016         1     4.0   3.5    Total       0
 
     """
     exo = df[df["Question"] == "Total"]
@@ -267,7 +268,7 @@ def digest_flat_df(flat_df):
     df = flat_df.copy()
     df["Mark"] = compute_marks(flat_df)
     df["Latex_rep"] = compute_latex_rep(flat_df)
-    df["Normalized"] = compute_normalized(flat_df)
+    df["Normalized"] = compute_normalized(df)
 
     exo_df = compute_exo_marks(df)
     exo_df["Normalized"] = compute_normalized(exo_df)

notes_tools/extract.py

@@ -16,12 +16,12 @@ def list_classes(path = notes_path):
     List classes available in notes_path
 
     >>> list_classes()
-    ['509', '503', '308', '312']
-    >>> p = Path("./")
+    []
+    >>> p = Path("./samples/")
     >>> list_classes(p)
-    ['509', '503', '308', '312']
-    >>> list_classes("./")
-    ['509', '503', '308', '312']
+    ['503', '312', '308']
+    >>> list_classes("./samples/")
+    ['503', '312', '308']
     """
     try:
         return [n.namebase for n in path.files("*.xlsx")]
@@ -87,34 +87,32 @@ def flat_df_students(df, students):
             flat_data.append(data)
     return pd.DataFrame.from_dict(flat_data)
 
-def get_all_marks(ws, marks_sheetnames = ["Notes", "Connaissances", "Calcul mental"]):
-    """ Extract marks from marks_sheetnames
+def parse_sheets(ws,
+        marks_sheetnames = ["Notes", "Connaissances", "Calcul mental"]):
+    """ Parse sheets from marks_sheetnames
 
-    :param ws: TODO
-    :returns: TODO
+    :param ws: the worksheet
+    :param marks_sheetnames: names of sheets for extracting
 
     """
-    for sheetname in marks_sheetnames:
-        try:
-            marks = ws.parse(sheetname)
-        except xlrd.biffh.XLRDError:
-            pass
-
-def extract_flat_marks(ws):
-    """ Extract, flat and contact marks from the worksheet
-
-    :param ws: TODO
-    :returns: TODO
-
-    """
-    marks_sheetnames = ["Notes", "Connaissances", "Calcul mental"]
-
     sheets = []
     for sheetname in marks_sheetnames:
         try:
             sheets.append(ws.parse(sheetname))
         except xlrd.biffh.XLRDError:
             pass
+    return sheets
+
+def extract_flat_marks(ws,
+        marks_sheetnames=["Notes", "Connaissances", "Calcul mental"]):
+    """ Extract, flat and contact marks from the worksheet
+
+    :param ws: the worksheet
+    :param marks_sheetnames: name of worksheets
+    :returns: TODO
+
+    """
+    sheets = parse_sheets(ws, marks_sheetnames)
 
     students = check_students(sheets)
 

notes_tools/test/test_df_marks_manip.py

@@ -0,0 +1,16 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+
+from notes_tools import df_marks_manip
+
+
+# TODO: faire des tests unitaire |mar. nov.  8 11:20:57 EAT 2016
+
+
+
+
+# -----------------------------
+# Reglages pour 'vim'
+# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
+# cursor: 16 del 

notes_tools/test/test_extract.py

@@ -0,0 +1,59 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+
+from notes_tools import extract
+import pandas 
+import pytest
+
+
+sample_path = "./samples/"
+
+def test_list_classes():
+    clss = extract.list_classes(sample_path)
+    assert clss == ["503", "312", "308"]
+
+def test_get_class_ws_raise():
+    with pytest.raises(Exception) as e_info:
+        extract.get_class_ws("312")
+
+def test_parse_sheets():
+    ws = extract.get_class_ws("312", sample_path)
+    sheets = extract.parse_sheets(ws)
+    assert len(sheets) == 2
+    assert type(sheets[0]) == pandas.core.frame.DataFrame
+
+def test_extract_students():
+    ws = extract.get_class_ws("312", sample_path)
+    sheets = extract.parse_sheets(ws)
+    students = extract.extract_students(sheets[0])
+    _students = pandas.Index(['Eleve 1', 'Eleve 10', 'Eleve 2', 'Eleve 3', 'Eleve 4', 'Eleve 5', 'Eleve 6', 'Eleve 7', 'Eleve 8', 'Eleve 9'], dtype='object')
+    assert list(students) == list(_students)
+
+def test_check_students():
+    ws = extract.get_class_ws("312", sample_path)
+    sheets = extract.parse_sheets(ws)
+    students = extract.check_students(sheets)
+    _students = pandas.Index(['Eleve 1', 'Eleve 10', 'Eleve 2', 'Eleve 3', 'Eleve 4', 'Eleve 5', 'Eleve 6', 'Eleve 7', 'Eleve 8', 'Eleve 9'], dtype='object')
+    assert list(students) == list(_students)
+
+
+    ws = extract.get_class_ws("308", sample_path)
+    sheets = extract.parse_sheets(ws)
+    with pytest.raises(Exception) as e_info:
+        students = extract.check_students(sheets)
+
+def test_flat_df_students():
+    ws = extract.get_class_ws("312", sample_path)
+    sheets = extract.parse_sheets(ws)
+    students = extract.check_students(sheets)
+
+    # Sheets[1] is the sheet Connaissances
+    flat_df = extract.flat_df_students(sheets[1], students)
+    assert len(flat_df) == 80
+
+
+# -----------------------------
+# Reglages pour 'vim'
+# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
+# cursor: 16 del 

samples/README.md

@@ -0,0 +1,3 @@
+# Notes on samples
+
+- The file 308.xlxs should not work. The list of students between sheets is not homogeneous.