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mid refactor for improved rebustness and readability

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This commit is contained in:
Landon Wark
2023-03-15 15:38:02 -05:00
parent fc334155ff
commit c645d3a9cf
15 changed files with 337 additions and 468 deletions
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93
src/submissions/backend/excel/reports.py
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@@ -1,8 +1,6 @@
from pandas import DataFrame, concat
from operator import itemgetter
from pandas import DataFrame
# from backend.db import models
import json
import logging
from jinja2 import Environment, FileSystemLoader
from datetime import date, timedelta
@@ -38,13 +36,8 @@ def make_report_xlsx(records:list[dict]) -> DataFrame:
df2 = df.groupby(["Submitting Lab", "Extraction Kit"]).agg({'Extraction Kit':'count', 'Cost': 'sum', 'Sample Count':'sum'})
df2 = df2.rename(columns={"Extraction Kit": 'Kit Count'})
logger.debug(f"Output daftaframe for xlsx: {df2.columns}")
# apply formating to cost column
# df2.iloc[:, (df2.columns.get_level_values(1)=='sum') & (df2.columns.get_level_values(0)=='Cost')] = df2.iloc[:, (df2.columns.get_level_values(1)=='sum') & (df2.columns.get_level_values(0)=='Cost')].applymap('${:,.2f}'.format)
return df2
# def split_row_item(item:str) -> float:
# return item.split(" ")[-1]
def make_report_html(df:DataFrame, start_date:date, end_date:date) -> str:
@@ -63,23 +56,20 @@ def make_report_html(df:DataFrame, start_date:date, end_date:date) -> str:
output = []
logger.debug(f"Report DataFrame: {df}")
for ii, row in enumerate(df.iterrows()):
# row = [item for item in row]
logger.debug(f"Row {ii}: {row}")
lab = row[0][0]
logger.debug(type(row))
logger.debug(f"Old lab: {old_lab}, Current lab: {lab}")
logger.debug(f"Name: {row[0][1]}")
data = [item for item in row[1]]
# logger.debug(data)
# logger.debug(f"Cost: {split_row_item(data[1])}")
# logger.debug(f"Kit count: {split_row_item(data[0])}")
# logger.debug(f"Sample Count: {split_row_item(data[2])}")
kit = dict(name=row[0][1], cost=data[1], plate_count=int(data[0]), sample_count=int(data[2]))
# if this is the same lab as before add together
if lab == old_lab:
output[-1]['kits'].append(kit)
output[-1]['total_cost'] += kit['cost']
output[-1]['total_samples'] += kit['sample_count']
output[-1]['total_plates'] += kit['plate_count']
# if not the same lab, make a new one
else:
adder = dict(lab=lab, kits=[kit], total_cost=kit['cost'], total_samples=kit['sample_count'], total_plates=kit['plate_count'])
output.append(adder)
@@ -91,83 +81,6 @@ def make_report_html(df:DataFrame, start_date:date, end_date:date) -> str:
return html
# def split_controls_dictionary(ctx:dict, input_dict) -> list[dict]:
# # this will be the date in string form
# dict_name = list(input_dict.keys())[0]
# # the data associated with the date key
# sub_dict = input_dict[dict_name]
# # How many "count", "Percent", etc are in the dictionary
# data_size = get_dict_size(sub_dict)
# output = []
# for ii in range(data_size):
# new_dict = {}
# for genus in sub_dict:
# logger.debug(genus)
# sub_name = list(sub_dict[genus].keys())[ii]
# new_dict[genus] = sub_dict[genus][sub_name]
# output.append({"date":dict_name, "name": sub_name, "data": new_dict})
# return output
# def get_dict_size(input:dict):
# return max(len(input[item]) for item in input)
# def convert_all_controls(ctx:dict, data:list) -> dict:
# dfs = {}
# dict_list = [split_controls_dictionary(ctx, datum) for datum in data]
# dict_list = [item for sublist in dict_list for item in sublist]
# names = list(set([datum['name'] for datum in dict_list]))
# for name in names:
# # df = DataFrame()
# # entries = [{item['date']:item['data']} for item in dict_list if item['name']==name]
# # series_list = []
# # df = pd.json_normalize(entries)
# # for entry in entries:
# # col_name = list(entry.keys())[0]
# # col_dict = entry[col_name]
# # series = pd.Series(data=col_dict.values(), index=col_dict.keys(), name=col_name)
# # # df[col_name] = series.values
# # # logger.debug(df.index)
# # series_list.append(series)
# # df = DataFrame(series_list).T.fillna(0)
# # logger.debug(df)
# dfs['name'] = df
# return dfs
# def convert_control_by_mode(ctx:dict, control:models.Control, mode:str) -> list[dict]:
# """
# split control object into analysis types... can I move this into the class itself?
# turns out I can
# Args:
# ctx (dict): settings passed from gui
# control (models.Control): control to be parsed into list
# mode (str): analysis type
# Returns:
# list[dict]: list of records
# """
# output = []
# data = json.loads(getattr(control, mode))
# for genus in data:
# _dict = {}
# _dict['name'] = control.name
# _dict['submitted_date'] = control.submitted_date
# _dict['genus'] = genus
# _dict['target'] = 'Target' if genus.strip("*") in control.controltype.targets else "Off-target"
# for key in data[genus]:
# _dict[key] = data[genus][key]
# output.append(_dict)
# # logger.debug(output)
# return output
def convert_data_list_to_df(ctx:dict, input:list[dict], subtype:str|None=None) -> DataFrame:
"""
Convert list of control records to dataframe