To connect Python to Oracle Database using an Oracle Wallet, you can use the cx_Oracle or oracledb library with Oracle Client libraries (like Oracle Instant Client). Oracle Wallet simplifies secure connections by storing credentials and SSL certificates. ✅ Steps to Connect Python to Oracle using Oracle Wallet Step 1: Install Required Python Package Step 2:…
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Directory Structure: root-folder/ config-folder/ json-file.config class-folder/ classfile.py tests/ pytest-file1.py json-file.config: { “setting1”: “value1”, “setting2”: “value2” } Now, Here I need to access json-file.config in my class file. I do not want to use dbutil, how can i access it and read it from json-file.config in my class file?? classfile.py import os import json class myclass:…
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I have following directory structure. root-folder – config-folder json-file.config – class-folder classfile.py – tests pytest-file1.py Now, I need to use a class named myclass from classfile.py in my test/pytestfile1.py. How can I import that class in my pytest file?? To import the myclass from classfile.py into your pytest-file1.py, you can use a relative import assuming…
from pyspark.sql.functions import col, lit# File location and typefile_location = “/FileStore/tables/sales_data_part1.csv”file_type = “csv”# CSV optionsinfer_schema = “false”first_row_is_header = “true”delimiter = “,”# The applied options are for CSV files. For other file types, these will # be ignored.df = spark.read.format(file_type) .option(“inferSchema”, infer_schema) .option(“header”, first_row_is_header) .option(“sep”, delimiter) .load(file_location)display(df)# Adding new column with and with default values. #…
# Databricks notebook source %sqlcreate database if not exists abcdb %sqluse abcdb %sqlcreate table student (id int , name string) %sqlinsert into studentselect 1 as id, ‘user1’ as name %sqlselect * from student spark.sql(“create database if not exists xyzdb”)spark.sql(“use xyzdb”) # Use three double quotes (“””) if SQL…
from pyspark.sql.functions import col # File location and type file_location = “/FileStore/tables/sales_data_part1.csv” file_type = “csv” # CSV options infer_schema = “false” first_row_is_header = “true” delimiter = “,” # The applied options are for CSV files. For other file types, these will be ignored. df = spark.read.format(file_type) .option(“inferSchema”, infer_schema) .option(“header”, first_row_is_header) .option(“sep”,…
# Databricks notebook source import pandas as pd # preapre dataframe df_h=pd.read_csv(“https://people.sc.fsu.edu/~jburkardt/data/csv/zillow.csv”) #Print dataframe df_h #define custom columns columns = [“Srno”, “SQFT”, “BR”, “Baths”, “Zipcode”, “YearBuilt”, “ListPrice”] df_h=pd.read_csv(“https://people.sc.fsu.edu/~jburkardt/data/csv/zillow.csv”, header=None, names=columns) #Print dataframe df_h # show top 10 rows df_h.head(10) # show last 10 rows df_h.tail(10) #Print dataframe df_h #Drop non-needed columns, column names are case…
