def get_teachers_report_file_path(from_date,to_date,std):
syjc = std == "SYJC"
query = Lecture.objects(date__gte=from_date,date__lte=to_date,syjc=syjc).only("division","lecturer","subject")
df = pd.DataFrame(json.loads(query.to_json()))
if len(df) == 0:
return "NA"
df.drop("_id",axis=1,inplace=True)
df = df.rename({"subject":"Subject","lecturer":"Lecturer","division":"Division"},axis=1)
# Use mongoDB framework aggregation for this
a = df.groupby(["Division","Subject","Lecturer"]).size()
b = pd.DataFrame(a,columns=["Count"])
subjects_mapper = get_subjects_mapper()
lecturers_mapper = get_lecturers_mapper()
b.index = b.index.map(lambda x: index_mapper(x,subjects_mapper,lecturers_mapper))
fd = from_date.strftime("%d_%m_%y")
td = to_date.strftime("%d_%m_%y")
in_memory_fp = BytesIO()
b.to_excel(in_memory_fp)
in_memory_fp.seek(0,0)
file = in_memory_fp
file_path = f"teachers_reports/{std}__{fd}__{td}.xlsx"
default_storage.delete(file_path)
file_name = default_storage.save(file_path, file)
return "media/" + file_path
def get_lectures_data(date,std):
syjc = std == "SYJC"
query = Lecture.objects(date=date,syjc=syjc).only("division","subject","lecturer","date","start_time","end_time","num_students")
data = []
for lec in query:
obj = {}
obj["division"] = lec.division
obj["subject"] = lec.subject
obj["lecturer"] = lec.lecturer
obj["date"] = lec.date
obj["start_time"] = lec.start_time
obj["end_time"] = lec.end_time
obj["num_students"] = lec.num_students
data.append(obj)
df = pd.DataFrame(data)
if len(df) == 0:
return None
df["date"] = df["date"].map(lambda x: x.strftime("%d/%m/%y"))
df["start_time"] = df["start_time"].map(lambda x: str(x)[:2] + ":" + str(x)[2:])
df["end_time"] = df["end_time"].map(lambda x: str(x)[:2] + ":" + str(x)[2:])
df = df.rename(columns={"division":"Division","subject":"Subject","lecturer":"Lecturer","date":"Date","start_time":"From","end_time":"To","num_students":"Students"})
df = df[["Division","Subject","Lecturer","Date","From","To","Students"]]
df["Subject"] = df["Subject"].map(get_subjects_mapper())
df["Lecturer"] = df["Lecturer"].map(get_lecturers_mapper())
df = df.to_html(classes=["mystyle table table-bordered table-striped"],index=False,table_id="mytable")
df = re.sub('<tbody>', '<tbody id="log">',df)
replace = """
<thead>
<tr class="filters" style="text-align: right;">
<th><input type="text" class="form-control" placeholder="Division" disabled></th>
<th><input type="text" class="form-control" placeholder="Subject" disabled></th>
<th><input type="text" class="form-control" placeholder="Lecturer" disabled></th>
<th><input type="text" class="form-control" placeholder="Date" disabled></th>
<th><input type="text" class="form-control" placeholder="From" disabled></th>
<th><input type="text" class="form-control" placeholder="To" disabled></th>
<th><input type="text" class="form-control" placeholder="Students" disabled></th>
</tr>
</thead>
"""
df = re.sub(r"<thead>.+<\/thead>",replace,df,flags=re.S)
df = df.replace("\\n","<br>")
return df
def get_students_report_file_path(from_date,to_date,division,std):
syjc = std == "SYJC"
filtered = Lecture.objects(Q(date__lte=to_date) & Q(date__gte=from_date) & Q(division=division.name) & Q(syjc=syjc)).only("present")
pipeline = [
{
"$project":{
"record": {
"$objectToArray":"$present"
}
}
},
{
"$unwind" : "$record"
},
{
"$group" :{
"_id":"$record.k",
"count":{"$sum":1},
"present":{
"$sum": {"$cond" : [ "$record.v", 1, 0 ] }
}
}
}
]
ans = filtered.aggregate(pipeline)
data = [i for i in ans]
df = pd.DataFrame(data)
if len(df) == 0:
return "NA"
df = df.rename(columns={"_id":"Roll","count":"Total","present":"Present"})
df = df.sort_values("Roll")
fd = from_date.strftime("%d_%m_%y")
td = to_date.strftime("%d_%m_%y")
in_memory_fp = BytesIO()
df.to_excel(in_memory_fp,index=False)
in_memory_fp.seek(0,0)
file = in_memory_fp
file_path = f"students_reports/{division}/{fd}__{td}.xlsx"
default_storage.delete(file_path)
file_name = default_storage.save(file_path, file)
return "media/" + file_path