def add_data(conn, cursor, file_number, user_name):
#file_row(cursor, file_number)
table = "hormonetherapy_survival"
enter = ask.ask_y_n("Enter Hormone Therapy Details?")
if enter:
col_list = names.names_longterm(module_name="hormone")
data = hormone(file_number)
update_multiple(conn, cursor, table, col_list, file_number, data)
enter = ask.ask_y_n("Enter Recurrence and follow-up status?")
if enter:
col_list = names.names_longterm(module_name="metastasis")
data = metastasis(file_number, user_name)
update_multiple(conn, cursor, table, col_list, file_number, data)
def edit_data(conn, cursor, file_number, user_name):
table = "hormonetherapy_survival"
print("Hormone Therapy Details")
col_list = names.names_longterm(module_name="hormone")
enter = review_data(conn, cursor, table, file_number, col_list)
if enter:
data = hormone(file_number)
update_multiple(conn, cursor, table, col_list, file_number, data)
print("Recurrence and follow-up status")
col_list = names.names_longterm(module_name="metastasis")
enter = review_data(conn, cursor, table, file_number, col_list)
if enter:
data = metastasis(file_number, user_name)
update_multiple(conn, cursor, table, col_list, file_number, data)
def metastasis(file_number, user_name):
check = False
while not check:
met_has = ask.ask_y_n(
"Has the patient been examined for metastatic disease?")
if not met_has:
met_has = "Not examined for metastatic disease"
else:
met_has = "Examined for metastatic disease"
date_last = ask.check_date("Date of last follow-up: ")
recur = ask.ask_y_n("Has the patient experienced a recurrence?")
if recur:
time_recur = input("Time to disease recurrence: ")
nature_recur = ask.ask_option("Nature of recurrence",
["Distant", "Local", "Other"])
if nature_recur == "Distant":
distant_site = input("Site of distant recurrence: ")
else:
distant_site = "NA"
else:
time_recur, nature_recur, distant_site = ("NA", ) * 3
status = patient_status()
data_list = [
met_has, date_last, time_recur, nature_recur, distant_site, status,
user_name,
last_update()
]
col_list = names.names_longterm("metastasis")
check = review_input(file_number, col_list, data_list)
return data_list
def db_dict(table, module):
db_tables = {
"patient_information_history": names.names_info(module),
"radiology": names.names_radio(module),
'pet_reports': names.names_pet(module),
'biopsy_path_report_data': names.names_biopsy(module),
"neo_adjuvant_therapy": names.names_nact(module),
"surgery_report": names.names_surgery_information(module),
'surgery_path_report_data': names.names_surgery(module),
"adjuvant_chemotherapy": names.names_chemotherapy(module),
"radiotherapy": names.names_radiation(),
"hormonetherapy_survival": names.names_longterm(module),
"follow_up_data": names.name_follow_up(),
'block_list': names.block_list(module)
}
cols = db_tables.get(table)
return cols
ex_file = 'Output_radiology_12062018.xlsx'
path = os.path.join(folders, file)
ex_path = os.path.join(folders, ex_file)
conn = sqlite3.connect(path)
table = "radiotherapy"
col_list = ["File_number"] + names.names_radiation()
sql = ('SELECT ' + ", ".join(col_list[:-2]) + " FROM '" + table + "'")
df = pd.read_sql(sql, conn)
writer = pd.ExcelWriter(ex_path, engine='xlsxwriter')
df.to_excel(writer, sheet_name=table)
table = "hormonetherapy_recurrence_survival"
col_list = [
"File_number"
] + names.names_longterm("hormone") + names.names_longterm("metastasis")
sql = ('SELECT ' + ", ".join(col_list[:-2]) + " FROM '" + table + "'")
df = pd.read_sql(sql, conn)
df.to_excel(writer, sheet_name="Hormone_RecurrenceSurvival")
table = "follow_up_data"
col_list = ["File_number"] + names.name_follow_up()
sql = ('SELECT ' + ", ".join(col_list[:-2]) + " FROM '" + table + "'")
df = pd.read_sql(sql, conn)
df.to_excel(writer, sheet_name=table)
table = "patient_information_history"
col_list_bio = names.names_info("bio_info")
col_list = ["File_number"] + col_list_bio + names.names_info("phys_act") + names.names_info("habits") + \
names.names_info("nut_supplements") + names.names_info("family_details") + names.names_info("med_history") + \
nf=cols_file))
table = "follow_up_data"
if table_check(cursor_all, table) == 0:
column = ", ".join(pccm_names.name_follow_up())
cols_file = "file_number, " + column
cursor_all.execute('CREATE TABLE {tn}({nf})'.format(tn=table,
nf=cols_file))
table = "hormonetherapy_recurrence_survival"
if table_check(cursor_all, table) == 0:
column = "file_number"
cursor_all.execute('CREATE TABLE {tn}({nf})'.format(tn=table, nf=column))
module_names = ["hormone", "metastasis"]
for index in module_names:
col_name = pccm_names.names_longterm(index)
add_columns(cursor_all, table, col_name)
table = "General_Medical_History"
if table_check(cursor_all, table) == 0:
columns2 = "file_number, Condition, Diagnosis_date, Treatment"
cursor_all.execute('CREATE TABLE {tn}({nf})' \
.format(tn=table, nf=columns2))
table = "Family_Cancer_History"
if table_check(cursor_all, table) == 0:
columns3 = 'file_number, Type_Cancer, Relation_to_Patient, Type_Relation, Age_at_detection_yrs'
cursor_all.execute('CREATE TABLE {tn}({nf})' \
.format(tn=table, nf=columns3))
table = "Previous_Cancer_History"
def hormone(file_number):
check = False
while not check:
hormone = ask.ask_y_n("Hormone therapy indicated?")
if not hormone:
hormone = "Hormone therapy not indicated"
hormone_recieved, hormone_date, hormone_type, hormone_duration, hormone_disc, hormone_ovary,hormone_outcome, \
hormone_follow_up, hormone_recur = ("NA", )*9
else:
hormone = "Hormone therapy indicated"
hormone_recieved = ask.ask_y_n("Was Hormone therapy recieved?")
if hormone_recieved:
hormone_recieved = "Hormone therapy recieved"
hormone_date = ask.check_date(
"Date of starting hormone therapy: ")
hormone_type = ask.ask_option("Type of hormone therapy", [
"Tamoxifen", "Anastrazole", "Injectables", "Letrozole",
"Others"
])
if hormone_type == "Injectables":
details = input(
"Please provide details of injectables recieved: ")
hormone_type = hormone_type + ": " + details
hormone_duration = input(
"Duration of hormone therapy (years): ")
hormone_disc = ask.ask_option(
"What is the current status of hormone therapy. "
"Give specific reasons if discontinued prematurely "
"(or not taken at all)", [
'Therapy is ongoing', "Completion of planned course",
"Adverse Effects", "Stopped by patient",
"Progression of disease", "Other"
])
ovary = ask.ask_y_n_na("Has ovarian surpression been used?")
if ovary == 'Yes':
hormone_ovary = ask.ask_option(
"Type of ovarian surpression used",
["Surgery", "Drug"])
if hormone_ovary == "Drug":
details = input(
"Please provide details of drug used: ")
hormone_ovary = hormone_ovary + ": " + details
else:
hormone_ovary = ovary
hormone_outcome = input("Outcome of hormone therapy: ")
hormone_follow_up = input("Follow up after hormone therapy: ")
hormone_recur = ask.ask_y_n(
"Was there recurrence after hormone therapy?",
"Recurrence", "No recurrence")
else:
hormone_recieved = "No hormone therapy recieved"
hormone_date, hormone_type, hormone_duration, hormone_disc, hormone_ovary, hormone_outcome, \
hormone_follow_up, hormone_recur = ("NA", )*8
data_list = [
hormone, hormone_recieved, hormone_date, hormone_type,
hormone_duration, hormone_disc, hormone_ovary, hormone_outcome,
hormone_follow_up, hormone_recur
]
col_list = names.names_longterm("hormone")
check = review_input(file_number, col_list, data_list)
return data_list
def makedb(self):
db_create = CreateTable(self.cursor)
file_number = "file_number"
table = "patient_information_history"
module_list = [
"bio_info", "phys_act", "habits", "nut_supplements",
"family_details", "med_history", "cancer_history", 'family_cancer',
'det_by', "breast_symptoms", 'other_test'
]
col_names = [pccm_names.names_info(module) for module in module_list]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number=file_number,
col_names=col_list)
table = "biopsy_path_report"
module_list = [
"biopsy_report_info", "biopsy_details", 'ihc_biopsy_data',
'review_biopsy'
]
col_names = [pccm_names.names_biopsy(module) for module in module_list]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table_pk(table, col_list)
table = 'surgery_path_report_data'
module_list = [
"surgery_block_information_0", "surgery_block_information_1",
"surgery_block_information_2", "surgery_block_information_3"
]
col_names = [
pccm_names.names_surgery(module) for module in module_list
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table_pk(table, col_list, pk='fk')
table = "block_data"
col_names = pccm_names.names_surgery('block_data')[1:]
db_create.create_table_pk(table, col_names, pk='fk')
table = "mammography"
col_names = pccm_names.names_radio(table)
db_create.create_table_pk(table, col_names)
table = 'abvs'
col_names = pccm_names.names_radio(table)
db_create.create_table_pk(table, col_names)
table = 'ultrasound'
col_names = pccm_names.names_radio(table)
db_create.create_table_pk(table, col_names)
table = 'mri'
col_names = pccm_names.names_radio(table)
db_create.create_table_pk(table, col_names)
table = 'pet_reports'
module_list = [
'pet_report_identifier', 'pet_report_findings', 'pet_breast_cancer'
]
col_names = [pccm_names.names_pet(module) for module in module_list]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table_pk(table, col_list)
table = "surgery_report"
module_list = ["surgery_information", "node_excision", "post_surgery"]
col_names = [
pccm_names.names_surgery_information(module)
for module in module_list
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "general_medical_history"
col_names = ['condition', 'diagnosis_date', 'treatment']
# col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "family_cancer_history"
col_names = [
'type_cancer', 'relation_to_patient', 'type_relation',
'age_at_detection_yrs'
]
# col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "previous_cancer_history"
col_names = [
'type_cancer', 'year_diagnosis', 'surgery', 'type_surgery',
'duration_surgery', 'radiation', 'type_radiation',
'duration_radiation', 'chemotherapy', 'type_chemotherapy',
'duration_chemotherapy', 'hormone', 'type_hormone',
'duration_hormone', 'alternative', 'type_alternative',
'duration_alternative', 'homeremedy', 'type_homeremedy',
'duration_homeremedy'
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "nutritional_supplements"
col_names = [
'type_nutritional_supplements',
'quantity_nutritional_supplements_per_day',
'duration_nutritional_supplements'
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "physical_activity"
col_names = ['type_activity', 'frequency_activity']
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "breast_feeding"
col_names = [
'child_number', 'feeding_duration', 'breast_usage_feeding'
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "nact_tox_table"
col_names = pccm_names.names_nact(table)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "nact_drug_table"
col_names = pccm_names.names_nact(table)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "neo_adjuvant_therapy"
module_list = ["neo_adjuvant_therapy", "clip_information"]
col_names = [pccm_names.names_nact(module) for module in module_list]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = "adjuvant_chemotherapy"
col_names = pccm_names.names_chemotherapy(table)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "chemo_tox_table"
col_names = pccm_names.names_chemotherapy(table)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "chemo_drug_table"
col_names = pccm_names.names_chemotherapy(table)
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "radiotherapy"
col_names = pccm_names.names_radiation()
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "follow_up_data"
col_names = pccm_names.name_follow_up()
db_create.create_table(table,
file_number='file_number',
col_names=col_names)
table = "hormonetherapy_survival"
module_list = ["hormone", "metastasis"]
col_names = [
pccm_names.names_longterm(module) for module in module_list
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number='file_number',
col_names=col_list)
table = 'block_list'
col_names = pccm_names.block_list('all')
db_create.create_table_pk(table, col_names=col_names, pk='pk')
table = "clinical_exam"
module_list = ['clinical_exam_initial', 'nipple_cytology']
col_names = [
pccm_names.name_clinical(module) for module in module_list
]
col_list = ask.flatten_nested_list(col_names)
db_create.create_table(table,
file_number=file_number,
col_names=col_list)
self.conn.commit()
print(self.path + " file created")
self.conn.close()