swateek

CSV to ICS Converter

This script converts a CSV file containing event details into an ICS file that can be imported into Google Calendar (and other calendar applications).

Usage

1. Prepare your CSV file: The CSV file should have the following columns (case-insensitive):
   • start date (Format: YYYY-MM-DD HH:MM or YYYY-MM-DD for all-day)

• end date (Format: YYYY-MM-DD HH:MM or YYYY-MM-DD)

swateek

import json

# Path to your HAR file
har_file = "example.har"

# Load HAR file
with open(har_file, "r", encoding="utf-8") as f:
    har_data = json.load(f)

# HAR files store entries under log.entries

swateek

#!/usr/bin/env bash
set -euo pipefail

AWS_PROFILE="devops"

function hosted_zone_exists() {
    local domain=$1
    aws route53 list-hosted-zones-by-name \
        --dns-name "$domain" \
        --query "HostedZones[?Name=='${domain}.'] | length(@)" \

swateek

import { DBSQLClient } from "@databricks/sql";
import IDBSQLSession from "@databricks/sql/dist/contracts/IDBSQLSession";

interface DataBricksWareHouseConnect {
    token: string;
    host: string;
    path: string;
}

class DataBricksManager {

swateek

from databricks import sql

DATABRICKS_USE2_PAT = ""

use2_workspace = sql.connect(
    server_hostname="<YOUR-SERVER-HOSTNAME>",
    http_path="<YOUR-HTTP-PATH>",
    access_token=DATABRICKS_USE2_PAT,
    catalog="<YOUR-CATALOG-NAME>",
    schema="<YOUR-SCHEMA-NAME>"

swateek

USE information_schema;

DESC MV_DATA_DISK_USAGE;

SELECT * FROM MV_DATA_DISK_USAGE;

SELECT DATABASE_NAME, FORMAT(SUM(`BLOBS_B`) / 1024/1024, 0) MB
FROM MV_DATA_DISK_USAGE
GROUP BY DATABASE_NAME

swateek

bedrock_agent:
  role: >
    Bedrock AI Assistant
  goal: >
    Help users generate responses using AWS Bedrock's LLM.
  backstory: >
    You are an advanced AI assistant powered by AWS Bedrock. You excel at processing
    and generating meaningful insights from textual data.
  tools:
    - bedrock_tool

swateek

jq

• Print all of the JSON content in a key value pair, like in an environment file.

echo '{"key1":"value1", "key2": "value2", "key3": "value3"}'\
| jq -r 'to_entries|map("\(.key)=\(.value|tostring)")|.[]'

echo '{"key1":"value1", "key2": "value2", "key3": "value3"}'\
| jq -r 'to_entries[] | "\(.key)=\(.value | tostring)"'

swateek

 #!/bin/bash

current_time=$(date "+%Y_%m_%dT%H_%M_%S")
rm -rf .my_job 2> /dev/null
mkdir -p .my_job
mkdir -p .my_job/{100,101,102,103,104,105,106,107,108,109,110}
ls -d .my_job/* | xargs -I {} bash -c "cd '{}' && touch sample_$random_$current_time.txt"
curl -s -X GET https://filesamples.com/samples/document/csv/sample4.csv -o .my_job/sample_$current_time.csv
curl -s -X GET https://filesamples.com/samples/document/pdf/sample2.pdf -o .my_job/sample_$current_time.pdf
curl -s -X GET https://filesamples.com/samples/document/xls/sample3.xls -o .my_job/sample_$current_time.xls

swateek

-- Delete a key from JSON Object
-- INPUT: {"somekey":"somevalue", "meta": {"ui": false, "miscTest": {"unit": "kWh", "value": 10}}}
UPDATE myTable
SET meta=JSON_DELETE_KEY(meta, 'miscTest')
WHERE id="85c8a446-fe24-11ed-8abf-af2f19c7e27f";
-- RESULT: {"somekey":"somevalue", "meta": {"ui": false}}


-- Update a key in JSON Object
-- INPUT: {"somekey":"somevalue", "meta": {"ui": false}}