Optimizing Database Population with Django - django

Question

I have a 10GB csv file (34 million rows) with data(without column description/header) that needs to be populated in a Postgres database.
The row data has columns that need to go in different Models.
I have the following DB schema:
Currently what I do is:
Loop through rows:
Create instance B with specific columns from row and append to an array_b
Create instance C with specific columns from row and append to an array_c
Create instance A with specific columns from row and relation to B and C, and
append to an array_a
Bulk create in order: B, C and A
This works perfectly fine, however, it takes 4 hours to populate the DB.
I wanted to optimize the population and came across the psql COPY FROM command.
So I thought I would be able to do something like:
Create instance A with specific columns from the file
for foreign key to C
create instance C with specific columns from the row
for foreign key to B
create instance B with specific columns from the row
Go to 1.
After a short research on how to do that, I found out that it does not allow table manipulations while copying data (such as looking up to another table for fetching proper foreign keys to insert)
Anyone can guide me in what to look for, any other method or 'hack' on how to optimize the data population?
Thanks in advance.
Management command:
with open(settings.DATA_PATH, 'r') as file:
csvreader = csv.reader(file)
next(csvreader)
b_array = []
c_array = []
a_array = []
for row in csvreader:
some_data = row[0]
some_data = row[1]
....
b = B(
some_data=some_data
)
b_array.append(b)
c = C(
some_data=some_data
)
c_array.append(c)
a = A(
some_data=_some_data,
b=b,
c=c
)
a_array.append(property)
B.objects.bulk_create(b_array)
C.objects.bulk_create(c_array)
A.objects.bulk_create(a_array)
References:
Use COPY FROM command in PostgreSQL to insert in multiple tables
Postgres: \copy syntax
Create multiple tables using single .sql script file
https://www.sqlshack.com/different-approaches-to-sql-join-multiple-tables/