| EXCEL_TIME = 42607.5234143519 | |
| # way 1 | |
| import datetime | |
| def xldate_as_datetime(xldate, datemode): | |
| # datemode: 0 for 1900-based, 1 for 1904-based | |
| return ( | |
| datetime.datetime(1899, 12, 30) | |
| + datetime.timedelta(days=xldate + 1462 * datemode) | |
| ) |
| # RAW CX_ORACLE | |
| import cx_Oracle | |
| import os | |
| DB_USERNAME = '...' | |
| DB_PASSWORD = '...' | |
| DB_SID = '...' # basicaly a schema | |
| DB_IP = '...' | |
| DB_PORT = int |
First of all, it just seems like doing anything with Oracle is obnoxiously painful for no good reason. It's the nature of the beast I suppose. cx_oracle is a python module that allows you to connect to an Oracle Database and issue queries, inserts, updates..usual jazz.
Step 1:
sudo apt-get install build-essential unzip python-dev libaio-devStep 2. Click here to download the appropriate zip files required for this. You'll need:
| # coding=utf-8 | |
| # github.com/sancau | |
| from collections import Counter | |
| from collections import namedtuple | |
| from random import randint | |
| import matplotlib.pyplot as plt | |
| import mpl_toolkits.mplot3d.axes3d as p3 |
| # coding=utf-8 | |
| """ | |
| Minimalistic util for building async pipelines of functions in Python | |
| (c) github.com/sancau | |
| """ | |
| from multiprocessing.dummy import Pool as ThreadPool | |
| from multiprocessing import Pool as ProcessPool |
| !# /bin/sh | |
| sudo mkdir /shared | |
| sudo chmod a+rwxs /shared | |
| sudo setfacl -d -m o:rwx /shared |
| pipenv shell | |
| pipenv install ipykernel | |
| python -m ipykernel install --user --name=VENV_NAME | |
| jupyter lab |
| data = [ | |
| ['User', 'Content Type', 'File', 'Mb'], | |
| ['User 1', 'Text', 'F1', 0.1], | |
| ['User 1', 'Text', 'F2', 0.5], | |
| ['User 1', 'Video', 'V1', 100], | |
| ['User 2', 'Text', 'F1', 2], | |
| ['User 2', 'Video', 'V1', 75], | |
| ['User 3', 'Video', 'V2', 60], | |
| ] |