... yes, this is reinventing the wheel again and again, but ...
So I decided to write my own xlsx export for two reasons:
First and foremost, the two existing engines I use (openpyxl, xlsxwriter) available in pandas do not store large files efficiently. The problem is when I must load large number of records, up to Excel limit (2^20 = 1048576) and then send it over email (this is quite often the easies way to share data...). The files get way big.
Secondly, I just want to understand xlsx internals and use the simples possible code to handle files. As a side effect, it is simpler and faster than using some other libraries.
As a simple benchmark consider a sample file of 700+k records and 18 columns. Standard pandas creates files of about 40MB. The simple_xls_writer's file is as small as 8MB which makes it more email friendly.
(Of course when saving modified file it gets much bigger but this not the point).
The project consists of submodules:
- writer
- oracle_handler.
This generic module exposes function(s) to write raw data (array of arrays) into Excel file.
This should be clear when reading the helper function:
def write_dummy(base_path: str, target_name: str) -> None:
data = [["A", "B", "C"], ["TEST", 1.23, "2024-10-01 12:34:56"], ["TEST", 200, "2024-10-01 12:34:56"]]
write_raw_data(base_path, target_name, data)
Note that the only supported data types are: str, int and float, which relates to the way data is saved in xlsx file.
So you may have to prepare the input array yourself or use other submodules (see below).
There's a helper function write_dummy that saves predefined tiny file under given name.
If you use Oracle database you can use helper method that reads query result into required structure.
First of all you may wish to verify connection. I prefer to do it this way:
print("db time: "+oracle_handler.get_sysdate(username,password,dh_url).strftime("%Y-%m-%d %H:%M:%S"))
To save query results simply run:
oracle_handler.write_oracle_query(query,base_path, "all_tables",username,password,dh_url)
See: main.py
...
username = input("username: ")
password = getpass.getpass()
dh_url = input("DSN: ")
# verify connection
print("db time: "+oracle_handler.get_sysdate(username,password,dh_url).strftime("%Y-%m-%d %H:%M:%S"))
# fetch all tables' metadata
query = "select * from all_tables"
base_path = os.path.dirname(__file__)
oracle_handler.write_oracle_query(query,base_path, "all_tables",username,password,dh_url)
...
Install package using pip:
pip install simple-xlsx-writer
If you wish to use Oracle connectivity, add option:
pip install simple-xlsx-writer[oracle]
To verify installation run:
import os
from simple_xlsx_writer import writer
base_path = os.path.dirname(__file__) # or provide explicit path in interactive mode
writer.write_dummy(base_path, "dummy01")
You should find dummy01.xlsx file in a given containig:
A | B | C |
---|---|---|
TEST | 1,23 | 2024-10-01 12:34:56 |
TEST | 200 | 2024-10-01 12:34:56 |