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Diesel learning pathway

1. Diesel CLI : Familiarise with Diesel's command-line tools for managing projects and migrations.
2. Migrations: Understand managing database schema changes over time with Diesel's ]LI.
3. Schema Management: Learn how Diesel uses schema.rs and the table! macro to reflect database structures.
4. Type Safety and Conversion : Grasp how Rust types correspond to SQL types and handling custom types.
5. Query Builder: Learn to construct SQL queries using Rust, utilising methods like filter, order, and limit
6. CRUD Operations: Understand how to perform create, read, update, and delete operations using Diesel.
7. Connection Handling: Learn about managing database connections, executing queries, and handling transactions.
8. Associations and Joins: (TODO) Learn about expressing r

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Tutorial on Using the tracing::instrument Macro in Rust

Introduction

This document provides a comprehensive guide on using the tracing::instrument macro in Rust. It covers the basics of the tracing crate, the purpose and functioning of the instrument macro, and best practices for its effective use in software development.

What is the tracing::instrument Macro?

• Overview: The tracing crate is a collection of Rust libraries for application-level tracing and asynchronous diagnostics. It provides a framework for collecting structured, event-based diagnostic information. The instrument macro, specifically, is a part of this crate. It automatically attaches context-specific information to logs, such as function arguments and return values, making it easier to track the flow and performance of the code.

• Purpose: The primary purpose of the tracing::instrument macro is to aid in diagnostics and performance analysis. By annotating functions with this macro, developers can automatic

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#!/bin/bash

# Use nmap to find open ports fast and then run a detailed scans on the returned ports

if [ -z "$1" ]
  then
    echo "__nmap_fast__"
    echo "Usage: ./nmap_fast TARGET_HOSTNAME"
fi
TARGET_HOSTNAME=$1

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## Encrypt
tar cz folder | openssl aes-256-cbc -salt -pbkdf2 -e > out.tar.gz.enc
## Decrypt
openssl aes-256-cbc -d -salt -pbkdf2 -in out.tar.gz.enc | tar xz

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#!/bin/bash

set -e

sudo -u ec2-user -i <<'EOF'

conda create --prefix ~/your_project  -y -c conda-forge python=3.7 ipykernel
source activate /home/ec2-user/your_project
conda install -y your_libs
python -m ipykernel install --user

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binary_search(){
  TARGET=$1
	TO_SEARCH=(${@:2})
	LENGTH=${#TO_SEARCH[@]}

	START=0
	END=$((LENGTH - 1))
	while [[ $START -le $END ]]; do
		MIDDLE=$((START + ((END - START)/2)))
		ITEM_AT_MIDDLE=${TO_SEARCH[MIDDLE]}

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#!/bin/bash

ME=`whoami`
PROCESS=$1

echo $PROCESS
echo $ME

IPCS_S=`ipcs -s $PROCESS | egrep "0x[0-9a-f]+0-9]+" | grep $ME | cut -f2 -d" "`
IPCS_M=`ipcs -m $PROCESS | egrep "0x[0-9a-f]+[0-9]+" | grep $ME | cut -f2 -d" "`

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#expose yam facts under /var/lib/puppet/yaml/facts/ in /etc/puppet/fileserver.conf and access via http

curl -k -H "Accept: yaml" https://puppetmaster:8140/production/facts/hostname

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require 'puppet'
require 'puppet/application'
require 'facter'

typeobj = Puppet::Type.type("package")
properties = typeobj.properties.collect { |s| s.name }
format = proc {|trans|
    trans.dup.collect do |param, value|
        if value.nil? or value.to_s.empty?
            trans.delete(param)

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#!/bin/sh -x
## REST API JIRA KEY check

#List of projects that do not require strict JIRA KEY commits
#list in space and case-insensitive
NON_STRICT="sports"


# Authentication credentials
username=root