#1342

Committed 25 Apr 2024 10:35AM UTC coverage: 79.909% (-0.06%) from 79.964%

Build # #1342

Build Type

push

coveralls-python

Committed by

dedenbangkit

Commit Message

[#1396] Modify k8s deadline and backoff

Run Details

2583 of 3410 branches covered (75.75%)

Branch coverage included in aggregate %.

6175 of 7550 relevant lines covered (81.79%)

0.82 hits per line

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67.89

backend/utils/export_form.py

import os
import pathlib

import pandas as pd

from api.v1.v1_forms.models import Forms, Questions


meta_columns = ["id", "created_at", "created_by", "updated_at",
                "updated_by", "datapoint_name", "administration",
                "geolocation", "submission_type"]


def get_definition(form: Forms):
    questions = (
        Questions.objects.filter(form=form)
        .order_by("question_group__order", "order")
        .all()
    )
    framed = []
    for i, q in enumerate([qs.to_definition() for qs in questions]):
        rule = ""
        dependency = ""
        if q["rule"]:
            rule = []
            for r in q["rule"]:
                rtext = f"{r}: " + str(q["rule"][r])
                rule.append(rtext)
            rule = " ".join(rule)
        if q["dependency"]:
            dependency = []
            for d in q["dependency"]:
                did = Questions.objects.get(pk=d["id"]).name
                if d.get("options"):
                    options = "|".join(d["options"])
                    dtext = f"{did}: " + options
                    dependency.append(dtext)
                if d.get("min"):
                    dtext = f"{did}: higher than {d['min']}"
                    dependency.append(dtext)
                if d.get("max"):
                    dtext = f"{did}: lower than {d['max']}"
                    dependency.append(dtext)
            dependency = "\n".join(dependency)
        if q["options"]:
            for o in q["options"]:
                framed.append(
                    {
                        "qg_id": q["qg_id"],
                        "order": q["order"],
                        "id": q["id"],
                        "name": q["name"],
                        "label": q["label"],
                        "type": q["type"],
                        "option": o["value"],
                        "option_label": o["label"],
                        "required": "YES" if q["required"] else "NO",
                        "rule": rule,
                        "dependency": dependency,
                        "indexer": i + 1,
                    }
                )
        else:
            framed.append(
                {
                    "qg_id": q["qg_id"],
                    "order": q["order"],
                    "id": q["id"],
                    "name": q["name"],
                    "label": q["label"],
                    "type": q["type"],
                    "option": None,
                    "option_label": None,
                    "required": "YES" if q["required"] else "NO",
                    "rule": rule,
                    "dependency": dependency,
                    "indexer": i + 1,
                }
            )
    return framed


def generate_definition_sheet(form: Forms, writer: pd.ExcelWriter):
    definitions = get_definition(form=form)
    df = pd.DataFrame(definitions)
    question_columns = [
        "name",
        "label",
        "type",
        "required",
        "rule",
        "dependency",
    ]
    df_questions = df[question_columns]
    df_questions = df_questions.drop_duplicates()
    df_questions.to_excel(writer, sheet_name="questions", index=False)
    df_options = df[["name", "option", "option_label"]]
    df_options = df_options.dropna(subset=["option"])
    df_options = df_options.drop_duplicates()
    df_options = df_options.rename(
        columns={
            "name": "question",
            "option": "option",
            "option_label": "label",
        }
    )
    df_options.to_excel(writer, sheet_name="options", index=False)


def rearrange_definition_columns(col_names: list):
    col_question = list(filter(lambda x: x not in meta_columns, col_names))
    if len(col_question) == len(col_names):
        return col_question
    col_names = meta_columns + col_question
    return col_names


def generate_excel(form: Forms):
    questions = questions = (
        Questions.objects.filter(form=form)
        .order_by("question_group__order", "order")
        .all()
    )
    data = pd.DataFrame(
        columns=[q.name for q in questions] + meta_columns,
        index=[0]
    )
    cols = list(data)
    col_names = rearrange_definition_columns(cols)
    data = data[col_names]
    form_name = form.name
    filename = f"{form.id}-{form_name}"
    directory = "tmp"
    pathlib.Path(directory).mkdir(parents=True, exist_ok=True)
    filepath = f"./{directory}/{filename}.xlsx"
    if os.path.exists(filepath):
        os.remove(filepath)
    writer = pd.ExcelWriter(filepath, engine="xlsxwriter")
    data.to_excel(
        writer, sheet_name="data", startrow=1, header=False, index=False
    )
    workbook = writer.book
    worksheet = writer.sheets["data"]
    header_format = workbook.add_format(
        {"bold": True, "text_wrap": True, "valign": "top", "border": 1}
    )
    for col_num, value in enumerate(data.columns.values):
        worksheet.write(0, col_num, value, header_format)
    generate_definition_sheet(form=form, writer=writer)
    writer.save()
    return filepath

1	import os	1✔
2	import pathlib	1✔
3
4	import pandas as pd	1✔
5
6	from api.v1.v1_forms.models import Forms, Questions	1✔
7
8
9	meta_columns = ["id", "created_at", "created_by", "updated_at",	1✔
10	"updated_by", "datapoint_name", "administration",
11	"geolocation", "submission_type"]
12
13
14	def get_definition(form: Forms):	1✔
15	questions = (	1✔
16	Questions.objects.filter(form=form)
17	.order_by("question_group__order", "order")
18	.all()
19	)
20	framed = []	1✔
21	for i, q in enumerate([qs.to_definition() for qs in questions]):	1✔
22	rule = ""	1✔
23	dependency = ""	1✔
24	if q["rule"]:	1!
25	rule = []	×
26	for r in q["rule"]:	×
27	rtext = f"{r}: " + str(q["rule"][r])	×
28	rule.append(rtext)	×
29	rule = " ".join(rule)	×
30	if q["dependency"]:	1!
31	dependency = []	×
32	for d in q["dependency"]:	×
33	did = Questions.objects.get(pk=d["id"]).name	×
34	if d.get("options"):	×
35	options = "\|".join(d["options"])	×
36	dtext = f"{did}: " + options	×
37	dependency.append(dtext)	×
38	if d.get("min"):	×
39	dtext = f"{did}: higher than {d['min']}"	×
40	dependency.append(dtext)	×
41	if d.get("max"):	×
42	dtext = f"{did}: lower than {d['max']}"	×
43	dependency.append(dtext)	×
44	dependency = "\n".join(dependency)	×
45	if q["options"]:	1✔
46	for o in q["options"]:	1✔
47	framed.append(	1✔
48	{
49	"qg_id": q["qg_id"],
50	"order": q["order"],
51	"id": q["id"],
52	"name": q["name"],
53	"label": q["label"],
54	"type": q["type"],
55	"option": o["value"],
56	"option_label": o["label"],
57	"required": "YES" if q["required"] else "NO",
58	"rule": rule,
59	"dependency": dependency,
60	"indexer": i + 1,
61	}
62	)
63	else:
64	framed.append(	1✔
65	{
66	"qg_id": q["qg_id"],
67	"order": q["order"],
68	"id": q["id"],
69	"name": q["name"],
70	"label": q["label"],
71	"type": q["type"],
72	"option": None,
73	"option_label": None,
74	"required": "YES" if q["required"] else "NO",
75	"rule": rule,
76	"dependency": dependency,
77	"indexer": i + 1,
78	}
79	)
80	return framed	1✔
81
82
83	def generate_definition_sheet(form: Forms, writer: pd.ExcelWriter):	1✔
84	definitions = get_definition(form=form)	1✔
85	df = pd.DataFrame(definitions)	1✔
86	question_columns = [	1✔
87	"name",
88	"label",
89	"type",
90	"required",
91	"rule",
92	"dependency",
93	]
94	df_questions = df[question_columns]	1✔
95	df_questions = df_questions.drop_duplicates()	1✔
96	df_questions.to_excel(writer, sheet_name="questions", index=False)	1✔
97	df_options = df[["name", "option", "option_label"]]	1✔
98	df_options = df_options.dropna(subset=["option"])	1✔
99	df_options = df_options.drop_duplicates()	1✔
100	df_options = df_options.rename(	1✔
101	columns={
102	"name": "question",
103	"option": "option",
104	"option_label": "label",
105	}
106	)
107	df_options.to_excel(writer, sheet_name="options", index=False)	1✔
108
109
110	def rearrange_definition_columns(col_names: list):	1✔
111	col_question = list(filter(lambda x: x not in meta_columns, col_names))	1✔
112	if len(col_question) == len(col_names):	1!
113	return col_question	×
114	col_names = meta_columns + col_question	1✔
115	return col_names	1✔
116
117
118	def generate_excel(form: Forms):	1✔
119	questions = questions = (	1✔
120	Questions.objects.filter(form=form)
121	.order_by("question_group__order", "order")
122	.all()
123	)
124	data = pd.DataFrame(	1✔
125	columns=[q.name for q in questions] + meta_columns,
126	index=[0]
127	)
128	cols = list(data)	1✔
129	col_names = rearrange_definition_columns(cols)	1✔
130	data = data[col_names]	1✔
131	form_name = form.name	1✔
132	filename = f"{form.id}-{form_name}"	1✔
133	directory = "tmp"	1✔
134	pathlib.Path(directory).mkdir(parents=True, exist_ok=True)	1✔
135	filepath = f"./{directory}/{filename}.xlsx"	1✔
136	if os.path.exists(filepath):	1!
137	os.remove(filepath)	×
138	writer = pd.ExcelWriter(filepath, engine="xlsxwriter")	1✔
139	data.to_excel(	1✔
140	writer, sheet_name="data", startrow=1, header=False, index=False
141	)
142	workbook = writer.book	1✔
143	worksheet = writer.sheets["data"]	1✔
144	header_format = workbook.add_format(	1✔
145	{"bold": True, "text_wrap": True, "valign": "top", "border": 1}
146	)
147	for col_num, value in enumerate(data.columns.values):	1✔
148	worksheet.write(0, col_num, value, header_format)	1✔
149	generate_definition_sheet(form=form, writer=writer)	1✔
150	writer.save()	1✔
151	return filepath	1✔

akvo / rtmis / #1342

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