import pypyodbc
print('\n'.join(pypyodbc.drivers()))

Microsoft Access Driver (*.mdb)
Microsoft dBase Driver (*.dbf)
Microsoft Excel Driver (*.xls)
Microsoft ODBC for Oracle
Microsoft Paradox Driver (*.db )
Microsoft Text Driver (*.txt; *.csv)
SQL Server
Oracle in OraClient10g_home1
SQL Server Native Client 11.0
ODBC Driver 17 for SQL Server
Microsoft Access Driver (*.mdb, *.accdb)
Microsoft Excel Driver (*.xls, *.xlsx, *.xlsm, *.xlsb)
Microsoft Access dBASE Driver (*.dbf, *.ndx, *.mdx)
Microsoft Access Text Driver (*.txt, *.csv)

SQL Server
PostgreSQL ANSI(x64)
PostgreSQL Unicode(x64)
PostgreSQL ANSI
PostgreSQL Unicode
SQL Server Native Client 11.0
ODBC Driver 17 for SQL Server

import pypyodbc

pypyodbc.lowercase = False
conn = pypyodbc.connect(
    r"Driver={Microsoft Access Driver (*.mdb, *.accdb)};"
    + r"Dbq=..\\access_data.accdb;"
)
cur = conn.cursor()

for row in cur.tables(tableType="TABLE"):
    print(row)

import pypyodbc
import struct
import json
from datetime import datetime, date
import decimal

print("running as {0}-bit".format(struct.calcsize("P") * 8))

def normalize(s):
    """A simple function to normalize table names"""
    return s.lower().replace(" ", "_")


conn = pypyodbc.connect(
    r"Driver={Microsoft Access Driver (*.mdb, *.accdb)};"
    + r"Dbq=..\\access_data.accdb;"
)
cur = conn.cursor()
tables = []
for row in cur.tables(tableType="TABLE"):
    # Only get the table names
    tables.append(row[2])

# data will contain the data of all tables. It will have the following structure:
# {"table_1": [{"column_1": value, "column_2": value}, ...], "table_2": ...}
data = {}
# descriptions will have  a description of all the tables. It will have the following structure:
# [
#   {
#       "table_name": "table 1",
#       "fixed_table_name": "table_1",
#       "columns": [
#           {"name": "column_1", "fixed_name": "column_1","type": "str"},
#           {"name": "column_2", "fixed_name": "column_2","type": "int"},
# ]
descriptions = []

for table_name in tables:
    fixed_table_name = normalize(table_name)
    print(f"~~~~~~~~~~~~~{table_name} {fixed_table_name}~~~~~~~~~~~~~")
    q = f'SELECT * FROM "{table_name}"'
    description = {
        "table_name": table_name,
        "fixed_table_name": fixed_table_name,
        "columns": [],
    }
    descriptions.append(description)

    cur.execute(q)
    # Here we get the description of the columns of the table from the cursor; we'll use that to fill the description.columns list
    columns = cur.description
    for c in columns:
        description["columns"].append(
            {"name": c[0], "fixed_name": normalize(c[0]), "type": c[1].__name__}
        )

    print("")

    # And here we retrieve the data of the whole table
    # Notice we use some double for loop comprehension to 
    # create a json object with a column_name: value structure
    # for each row
    data[fixed_table_name] = [
        {normalize(columns[index][0]): column for index, column in enumerate(value)}
        for value in cur.fetchall()
    ]

cur.close()
conn.close()

# This is a function to serialize datetime and decimal objects 
# to json; without it the json.dump function will fail if the 
# results contain dates or decimals
def json_serial(obj):
    """JSON serializer for objects not serializable by default json code"""

    if isinstance(obj, (datetime, date)):
        return obj.isoformat()
    elif isinstance(obj, decimal.Decimal):
        return str(obj)
    raise TypeError("Type %s not serializable" % type(obj))


with open("..\\access_description.json", "w") as outfile:
    # Notice the default=json_serial 
    json.dump(descriptions, outfile, default=json_serial)

with open("..\\access_data.json", "w") as outfile:
    json.dump(data, outfile, default=json_serial)

import json

def get_ctype(t):
    """Depending on the type of each column add a different field in the model"""
    if t == "str":
        return "TextField(blank=True, )"
    elif t == "int":
        return "IntegerField(blank=True, null=True)"
    elif t == "float":
        return "FloatField(blank=True, null=True)"
    elif t == "bool":
        return "BooleanField(blank=True, null=True)"
    elif t == "datetime":
        return "DateTimeField(blank=True, null=True)"
    elif t == "date":
        return "DateField(blank=True, null=True)"
    elif t == "Decimal":
        return "DecimalField(blank=True, null=True, max_digits=15, decimal_places=5)"
    else:
        print(t)
        raise NotImplementedError

# Load the descriptions we created in the previous step
descriptions = json.load(open("..\\access_description.json"))

# mlines will be an array of the lines of the models.py file
mlines = ["from django.db import models", "", ""]

for d in descriptions:
    # Create a model for each table
    mname = d["fixed_table_name"].capitalize()
    mlines.append(f"class {mname}(models.Model):")
    for c in d["columns"]:
        ctype = get_ctype(c["type"])
        mlines.append(f"    {c['fixed_name']} = models.{ctype}")
    mlines.append("")
    mlines.append("    class Meta:")
    mlines.append(f"        db_table = '{d['fixed_table_name']}'")
    mlines.append(f"        verbose_name = '{d['table_name']}'")

    mlines.append("")
    mlines.append("")


with open("..\\access_models.py", "w", encoding="utf-8") as outfile:
    outfile.write("\n".join(mlines))

from django.core.management.base import BaseCommand
import json
from django.db import transaction
from access_data import models

# This is a list of all the fields that are foreign keys; these need special handling
FK_FIELDS = [
    # ...
]

# You need to add the table names from the access database here. This is required
# if you have relations in order to add first the tables without dependencies and last
# the tables that belong on these 
TABLE_NAMES = [
    # ...
]

def fix_fks(k):
    """Add _id to the end of the field name if it is a foreign key to pass the pk of the
    foreign key instead of the whole object"""
    if k in FK_FIELDS:
        return k + '_id'
    return k

def get_model_by_table(table):
    """Get the model by the table name"""
    return getattr(models, table.capitalize())

class Command(BaseCommand):

    @transaction.atomic
    def handle(self, *args, **options):

        with open("..\\access_data.json") as f:
            j = json.load(f)

        # Delete the existing data before importing. This is optional but I find it useful
        # Notice that we delete the tables in reverse order to avoid foreign key errors
        for table in reversed(TABLE_NAMES):
            get_model_by_table(table).objects.all().delete()

        for table in TABLE_NAMES:
            for row in j[table]:
                # Create a dictionary with the column name: column value;
                # notice the fix_fks to add the _id to the column
                row_ok = {fix_fks(k): v for k,v in row.items()}
                print(row_ok)
                # Create the object; we could add thse to an array and do a bulk_create instead
                get_model_by_table(table).objects.create(**row_ok)