Fix: save csv with nice column order

recopytex/config.py

@@ -2,16 +2,16 @@
 # encoding: utf-8
 
 NO_ST_COLUMNS = {
-    "term": "Trimestre",
     "assessment": "Nom",
+    "term": "Trimestre",
     "date": "Date",
     "exercise": "Exercice",
     "question": "Question",
     "competence": "Competence",
     "theme": "Domaine",
     "comment": "Commentaire",
-    "score_rate": "Bareme",
     "is_leveled": "Est_nivele",
+    "score_rate": "Bareme",
 }
 
 COLUMNS = {

recopytex/dashboard/exam_analysis/app.py

@@ -192,7 +192,7 @@ def update_final_scores(data):
 
     scores = pd.DataFrame.from_records(data)
     try:
-        if scores.iloc[0]["Commentaire"] == "commentaire":
+        if scores.iloc[0]["Commentaire"] == "commentaire" or scores.iloc[0].str.contains("PPRE").any():
             scores.drop([0], inplace=True)
     except KeyError:
         pass
@@ -280,7 +280,7 @@ def update_final_scores_hist(data):
 def update_competence_fig(data):
     scores = pd.DataFrame.from_records(data)
     try:
-        if scores.iloc[0]["Commentaire"] == "commentaire":
+        if scores.iloc[0]["Commentaire"] == "commentaire" or scores.iloc[0].str.contains("PPRE").any():
             scores.drop([0], inplace=True)
     except KeyError:
         pass
@@ -343,6 +343,7 @@ def update_competence_fig(data):
 def save_scores(data, csv):
     try:
         scores = pd.DataFrame.from_records(data)
+        scores = scores_table_column_order(scores)
         scores.to_csv(csv, index=False)
     except:
         return [f"Soucis pour sauvegarder à  {datetime.today()} dans {csv}"]
@@ -365,6 +366,11 @@ def highlight_value(df):
         ]
     return hight
 
+def scores_table_column_order(df):
+    df_student_columns = [c for c in df.columns if c not in NO_ST_COLUMNS.values()]
+    order = list(NO_ST_COLUMNS.values())+df_student_columns
+    return df.loc[:, order]
+    
 
 @app.callback(
     [
@@ -388,6 +394,7 @@ def update_scores_table(csv, add_element, data):
             [{k: stack.iloc[-1][k] for k in NO_ST_COLUMNS.values()}]
         )
         stack = stack.append(infos)
+    stack = scores_table_column_order(stack)
     return (
         [
             {"id": c, "name": c}

recopytex/dashboard/student_analysis/app.py

@@ -191,11 +191,8 @@ def update_student_scores(tribe, student, term):
         except pd.errors.ParserError:
             pass
         else:
-            try:
-                if scores.iloc[0]["Commentaire"] == "commentaire":
+            if scores.iloc[0]["Commentaire"] == "commentaire" or scores.iloc[0].str.contains("PPRE").any():
                 scores.drop([0], inplace=True)
-            except KeyError:
-                pass
             scores = flat_df_students(scores).dropna(subset=["Score"])
             scores = scores[scores["Eleve"] == student]
             scores = scores[scores["Trimestre"] == term]

recopytex/df_marks_manip.py

@@ -50,7 +50,6 @@ def score_to_mark(x):
                 f"The evaluation is out of range: {x[COLUMNS['score']]} at {x}"
             )
         return round(x[COLUMNS["score"]] * x[COLUMNS["score_rate"]] / 3, 2)
-        #return round_half_point(x[COLUMNS["score"]] * x[COLUMNS["score_rate"]] / 3)
 
     if x[COLUMNS["score"]] > x[COLUMNS["score_rate"]]:
         raise ValueError(

recopytex/scripts/config.py

@@ -0,0 +1,10 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+import yaml
+
+CONFIGPATH = "recoconfig.yml"
+
+with open(CONFIGPATH, "r") as configfile:
+    config = yaml.load(configfile, Loader=yaml.FullLoader)
+

recopytex/scripts/exam.py

@@ -3,7 +3,8 @@
 
 from datetime import datetime
 from pathlib import Path
-from prompt_toolkit import HTML
+
+# from prompt_toolkit import HTML
 from ..config import NO_ST_COLUMNS
 import pandas as pd
 import yaml
@@ -61,7 +62,9 @@ class Exam:
         try:
             self._exercises[name]
         except KeyError:
-            self._exercises[name] = format_question(questions)
+            self._exercises[name] = [
+                format_question(question) for question in questions
+            ]
         else:
             raise KeyError("The exercise already exsists. Use modify_exercise")
 
@@ -153,6 +156,7 @@ class Exam:
     def write_csv(self):
         rows = self.to_row()
 
+        print(rows)
         base_df = pd.DataFrame.from_dict(rows)[NO_ST_COLUMNS.keys()]
         base_df.rename(columns=NO_ST_COLUMNS, inplace=True)
 

recopytex/scripts/prepare_csv.py

@@ -0,0 +1,160 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+import click
+from pathlib import Path
+from datetime import datetime
+from PyInquirer import prompt, print_json
+import pandas as pd
+import numpy as np
+
+from .config import config
+from ..config import NO_ST_COLUMNS
+
+
+class PromptAbortException(EOFError):
+    def __init__(self, message, errors=None):
+
+        # Call the base class constructor with the parameters it needs
+        super(PromptAbortException, self).__init__("Abort questionnary", errors)
+
+
+def get_tribes(answers):
+    """ List tribes based on subdirectory of config["source"] which have an "eleves.csv" file inside """
+    return [
+        p.name for p in Path(config["source"]).iterdir() if (p / "eleves.csv").exists()
+    ]
+
+
+def prepare_csv():
+    items = new_eval()
+
+    item = items[0]
+    # item = {"tribe": "308", "date": datetime.today(), "assessment": "plop"}
+    csv_output = (
+        Path(config["source"])
+        / item["tribe"]
+        / f"{item['date']:%y%m%d}_{item['assessment']}.csv"
+    )
+
+    students = pd.read_csv(Path(config["source"]) / item["tribe"] / "eleves.csv")["Nom"]
+
+    columns = list(NO_ST_COLUMNS.keys())
+    items = [[it[c] for c in columns] for it in items]
+    columns = list(NO_ST_COLUMNS.values())
+    items_df = pd.DataFrame.from_records(items, columns=columns)
+    for s in students:
+        items_df[s] = np.nan
+
+    items_df.to_csv(csv_output, index=False, date_format="%d/%m/%Y")
+    click.echo(f"Saving csv file to {csv_output}")
+
+
+def new_eval(answers={}):
+    click.echo(f"Préparation d'un nouveau devoir")
+
+    eval_questions = [
+        {"type": "input", "name": "assessment", "message": "Nom de l'évaluation",},
+        {
+            "type": "list",
+            "name": "tribe",
+            "message": "Classe concernée",
+            "choices": get_tribes,
+        },
+        {
+            "type": "input",
+            "name": "date",
+            "message": "Date du devoir (%y%m%d)",
+            "default": datetime.today().strftime("%y%m%d"),
+            "filter": lambda val: datetime.strptime(val, "%y%m%d"),
+        },
+        {
+            "type": "list",
+            "name": "term",
+            "message": "Trimestre",
+            "choices": ["1", "2", "3"],
+        },
+    ]
+
+    eval_ans = prompt(eval_questions)
+
+    items = []
+    add_exo = True
+    while add_exo:
+        ex_items = new_exercice(eval_ans)
+        items += ex_items
+        add_exo = prompt(
+            [
+                {
+                    "type": "confirm",
+                    "name": "add_exo",
+                    "message": "Ajouter un autre exercice",
+                    "default": True,
+                }
+            ]
+        )["add_exo"]
+    return items
+
+
+def new_exercice(answers={}):
+    exercise_questions = [
+        {"type": "input", "name": "exercise", "message": "Nom de l'exercice"},
+    ]
+
+    click.echo(f"Nouvel exercice")
+    exercise_ans = prompt(exercise_questions, answers=answers)
+
+    items = []
+
+    add_item = True
+    while add_item:
+        try:
+            item_ans = new_item(exercise_ans)
+        except PromptAbortException:
+            click.echo("Création de l'item annulée")
+        else:
+            items.append(item_ans)
+        add_item = prompt(
+            [
+                {
+                    "type": "confirm",
+                    "name": "add_item",
+                    "message": f"Ajouter un autre item pour l'exercice {exercise_ans['exercise']}",
+                    "default": True,
+                }
+            ]
+        )["add_item"]
+
+    return items
+
+
+def new_item(answers={}):
+    item_questions = [
+        {"type": "input", "name": "question", "message": "Nom de l'item",},
+        {"type": "input", "name": "comment", "message": "Commentaire",},
+        {
+            "type": "list",
+            "name": "competence",
+            "message": "Competence",
+            "choices": ["Cher", "Rep", "Mod", "Rai", "Cal", "Com"],
+        },
+        {"type": "input", "name": "theme", "message": "Domaine",},
+        {
+            "type": "confirm",
+            "name": "is_leveled",
+            "message": "Évaluation par niveau",
+            "default": True,
+        },
+        {"type": "input", "name": "score_rate", "message": "Bareme"},
+        {
+            "type": "confirm",
+            "name": "correct",
+            "message": "Tout est correct?",
+            "default": True,
+        },
+    ]
+    click.echo(f"Nouvelle question pour l'exercice {answers['exercise']}")
+    item_ans = prompt(item_questions, answers=answers)
+    if item_ans["correct"]:
+        return item_ans
+    raise PromptAbortException("Abort item creation")

recopytex/scripts/recopytex.py

@@ -10,7 +10,6 @@ from datetime import datetime
 import yaml
 
 from .getconfig import config, CONFIGPATH
-from .prompts import prompt_exam, prompt_exercise, prompt_validate
 from ..config import NO_ST_COLUMNS
 from .exam import Exam
 from ..dashboard.index import app as dash
@@ -37,55 +36,6 @@ def setup():
             print(f"The file {tribe['students']} does not exists")
 
 
-@cli.command()
-def new_exam():
-    """ Create new exam csv file """
-    exam = Exam(**prompt_exam())
-
-    if exam.path(".yml").exists():
-        print(f"Fichier sauvegarde trouvé à {exam.path('.yml')} -- importation")
-        with open(exam.path(".yml"), "r") as f:
-            for name, questions in yaml.load(f, Loader=yaml.SafeLoader)[
-                "exercices"
-            ].items():
-                exam.add_exercise(name, questions)
-
-        print(exam.themes)
-        # print(yaml.dump(exam.to_dict()))
-
-    exam.write()
-
-    for name, questions in exam.exercices.items():
-        exam.modify_exercise(
-            **prompt_exercise(
-                name=name, completer={"theme": exam.themes}, questions=questions
-            )
-        )
-        exam.write()
-
-    new_exercise = prompt_validate("Ajouter un exercice? ")
-    while new_exercise:
-        exam.add_exercise(
-            **prompt_exercise(len(exam.exercices) + 1, completer={"theme": exam.themes})
-        )
-        exam.write()
-        new_exercise = prompt_validate("Ajouter un exercice? ")
-
-    rows = exam.to_row()
-
-    base_df = pd.DataFrame.from_dict(rows)[NO_ST_COLUMNS.keys()]
-    base_df.rename(columns=NO_ST_COLUMNS, inplace=True)
-
-    students = pd.read_csv(exam.tribe_student_path)["Nom"]
-    for student in students:
-        base_df[student] = ""
-
-    exam.tribe_path.mkdir(exist_ok=True)
-
-    base_df.to_csv(exam.path(".csv"), index=False)
-    print(f"Le fichier note a été enregistré à {exam.path('.csv')}")
-
-
 @cli.command()
 @click.option("--debug", default=0, help="Debug mode for dash")
 def dashboard(debug):
@@ -112,7 +62,7 @@ def report(csv_file):
     try:
         date = datetime.strptime(date, "%y%m%d")
     except ValueError:
-        date = None
+        date = datetime.today().strptime(date, "%y%m%d")
 
     tribe = str(tribe_dir).split("/")[-1]
 

requirements.txt

@@ -1,4 +1,77 @@
-pandas
-click
-papermill
 prompt_toolkit
+ansiwrap==0.8.4
+appdirs==1.4.3
+attrs==19.1.0
+backcall==0.1.0
+black==19.10b0
+bleach==3.1.0
+certifi==2019.6.16
+chardet==3.0.4
+Click==7.0
+colorama==0.4.1
+cycler==0.10.0
+decorator==4.4.0
+defusedxml==0.6.0
+entrypoints==0.3
+future==0.17.1
+idna==2.8
+importlib-resources==1.0.2
+ipykernel==5.1.3
+ipython==7.11.1
+ipython-genutils==0.2.0
+ipywidgets==7.5.1
+jedi==0.15.2
+Jinja2==2.10.3
+jsonschema==3.2.0
+jupyter==1.0.0
+jupyter-client==5.3.4
+jupyter-console==6.1.0
+jupyter-core==4.6.1
+jupytex==0.0.3
+kiwisolver==1.1.0
+Markdown==3.1.1
+MarkupSafe==1.1.1
+matplotlib==3.1.2
+mistune==0.8.4
+nbconvert==5.6.1
+nbformat==5.0.3
+notebook==6.0.3
+numpy==1.18.1
+pandas==0.25.3
+pandocfilters==1.4.2
+papermill==1.2.1
+parso==0.5.2
+pathspec==0.7.0
+pexpect==4.8.0
+pickleshare==0.7.5
+prometheus-client==0.7.1
+prompt-toolkit==1.0.14
+ptyprocess==0.6.0
+Pygments==2.5.2
+PyInquirer==1.0.3
+pyparsing==2.4.6
+pyrsistent==0.15.7
+python-dateutil==2.8.0
+pytz==2019.3
+PyYAML==5.3
+pyzmq==18.1.1
+qtconsole==4.6.0
+-e git+git_opytex:/lafrite/recopytex.git@7e026bedb24c1ca8bef3b71b3d63f8b0d6916e81#egg=Recopytex
+regex==2020.1.8
+requests==2.22.0
+scipy==1.4.1
+Send2Trash==1.5.0
+six==1.12.0
+tenacity==6.0.0
+terminado==0.8.3
+testpath==0.4.4
+textwrap3==0.9.2
+toml==0.10.0
+tornado==6.0.3
+tqdm==4.41.1
+traitlets==4.3.2
+typed-ast==1.4.1
+urllib3==1.25.8
+wcwidth==0.1.8
+webencodings==0.5.1
+widgetsnbextension==3.5.1

setup.py

@@ -5,7 +5,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='Recopytex',
-    version='0.1',
+    version='1.1.1',
     description='Assessment analysis',
     author='Benjamin Bertrand',
     author_email='',
@@ -13,6 +13,10 @@ setup(
     include_package_data=True,
     install_requires=[
         'Click',
+        'pandas',
+        'numpy',
+        'papermill',
+        'pyyaml',
     ],
     entry_points='''
             [console_scripts]