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Vinoth Chellamuthu ecevinoth

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@ecevinoth
ecevinoth / git-gen-commit
Last active January 31, 2026 11:46 — forked from Tavernari/git-gen-commit
This script automates commit message generation using AI. It analyzes the current git diff, sends it to an Ollama model (tavernari/git-commit-message:reasoning), and formats the output neatly. Latest Changes (Timing & JSON Output) New Flags --timing Show detailed timing information for each Ollama call: - Time spent on file analysis - Time spent…
#!/usr/bin/env bash
set -u
set -o pipefail
# =======================================================
# Minimalist Colors
# =======================================================
BOLD=$'\033[1m'
RESET=$'\033[0m'
FG_RED=$'\033[31m'
@ecevinoth
ecevinoth / setup-textanalytics.sh
Created February 2, 2021 01:34
azure shell script to create setup-textanalytics instance through CLI
#!/usr/bin/env bash
RESOURCE_GROUP=$(az group list --query "[0].name" -o tsv)
TA_ACCT_NAME="TweetAnalytics"
TA_LOCATION=$(shuf -n1 -e $(az cognitiveservices account list-skus --query "[?tier=='Free' && kind=='TextAnalytics'].locations[]" | jq -r '.[]' | sed '/EUAP$/d'))
echo "Creating Text Analytics account..."
az cognitiveservices account create --name "$TA_ACCT_NAME" --resource-group "$RESOURCE_GROUP" --kind TextAnalytics --sku F0 --location "$TA_LOCATION" --yes
TA_KEY=$(az cognitiveservices account keys list --name $TA_ACCT_NAME --resource-group "$RESOURCE_GROUP" --query key1 -o tsv)
TA_ENDPOINT=$(az cognitiveservices account show --name $TA_ACCT_NAME --resource-group "$RESOURCE_GROUP" --query endpoint -o tsv)
echo "Done!"
echo
#!/usr/bin/env bash
RESOURCE_GROUP=$(az group list --query "[0].name" -o tsv)
SQL_LOCATION=$(az group show --name "$RESOURCE_GROUP" --query location -o tsv)
SQL_LOCATION=WESTUS
SQL_SERVERNAME="mslearn-exercise-sqlserver-$(openssl rand -hex 5)"
SQL_PWD="Ab#1$(openssl rand -hex 10)"
SQL_USERNAME=sqladmin
SQL_DBNAME=PositiveTweetDatabase
echo
echo "Creating SQL Server..."
@ecevinoth
ecevinoth / multiprocess_selenium.py
Created December 29, 2019 15:28 — forked from wooddar/multiprocess_selenium.py
Easy Python script to run selenium web workers/browsers in parallel
"""
This is an adaptable example script for using selenium across multiple webbrowsers simultaneously. This makes use of
two queues - one to store idle webworkers and another to store data to pass to any idle webworkers in a selenium function
"""
from multiprocessing import Queue, cpu_count
from threading import Thread
from selenium import webdriver
from time import sleep
from numpy.random import randint