Cheatsheet

Learning skills from daily projects

Unscheduled update

Greek Alphabet

Capital Letters	Lowercase Letters	Description	Symbol / Character
Α	α	alpha	Α
Β	β	beta	Β
Γ	γ	gamma	Γ
Δ	δ	delta	Δ
Ε	ε	epsilon	Ε
Ζ	ζ	zeta	Ζ
Η	η	eta	Η
Θ	θ	theta	Θ
Ι	ι	iota	Ι
Κ	κ	kappa	Κ
Λ	λ	lambda	Λ
Μ	μ	mu	Μ
Ν	ν	nu	Ν
Ξ	ξ	xi	Ξ
Ο	ο	omicron	Ο
Π	π	pi	Π
Ρ	ρ	rho	Ρ
Σ	σ	sigma	Σ
Τ	τ	tau	Τ
Υ	υ	upsilon	Υ
Φ	φ	phi	Φ
Χ	χ	chi	Χ
Ψ	ψ	psi	Ψ
Ω	ω	omega	Ω

markers:

interrogation mark: ?
colon: :
sharp: #
dash: -
(forward)slash: /, back slash: \
Parentheses or round brackets: ( )
Curly or brace brackets: { }
Square or box brackets: [ ]
Angle brackets: < >
Single or double quotation: "" ''
Tilde: ~
Indentation: \t

VS Code shortcut

ctrl+shift+space show function help
ctrl+enter insert a new line below
ctrl+shift+enter insert a new line above

Ubuntu version cheatsheet

Ubuntu Terminal Bash

Shortcuts

Ctrl+L: clear up to the beginning
Ctrl+W: delete just a word
Ctrl+C: cancel
Ctrl+A: Go to beginning of the line
Ctrl+E: Go to end of the line
Ctrl+D：Stop current work(loop)
Ctrl+Q: clear current cli input

Definition

PATH: system package search path.
PYTHONPATH: python package search path.

ls

ls -a

list all files (inclduing hidden ones)

Unzip

unzip -n src_path -d dest_path

-n: extract not existing.

When unzip a very large file(like 30+GB), use this to continue extracting in case of "not enough memory"

-d: dest path

zipinfo file_path

show details of the zipfile and total number of zip sub files

find

find . -type f | wc -l

show total number of sub files

Copy

cp /path/to/source /path/to/dest/directory/

copy file

Wget

wget -O dataset/fma_metadata.zip -nc https://os.unil.cloud.switch.ch/fma/fma_metadata.zip

-O: directed dest, including file name -nc: not covering existing files

Du

du -h --max-depth=1 ~/download

show the size of first level foulders

A good way to show google drive folder size in google colab

https://askubuntu.com/questions/1224/how-do-i-determine-the-total-size-of-a-directory-folder-from-the-command-line

du -sh
df -h --total

show free space / total space

nohup

nohup <process> &
nohup <process> & > logger.log # logging

run command in the background

ps -ef | grep py_downloader.py
kill <PID>

stop that command

tmux

tmux new-session -s my_project
tmux -a
tmux kill-session -t mysession

new session, attach and kill session

ctrl+b D

Detach current session, very useful for remote server.

ctrl+b [

Enter copy mode. But it still kind of tricky to use.

diff

diff [options] File1 File2

-c: context -u: unified, same as -c except redundant lines -y: Short for "side-by-side"

rename

mv oldname newname
mv olddir newdir

Create file/folder

cat > filename1.txt
touch filename2.txt
mkdir folder
mkdir -p folder0/folder1/folder2

Delete file/folder

rm filename
rm -r foldername

Search history commands

control + R

Shutdown

sudo shutdown now

Processes

ps aux

touch

touch file1 file2    # create a file if not existing (-c to avoid creating), or change the timestamp to the current time if already existing
touch file_{1...10}  # create files in batch
touch -t <timestamp> <filename>  # set timestamp[[CC]YY]MMDDhhmm[.ss] or string(tomorrow | 19 August 2020 | Sunday)

Systemctl

sudo systemctl start/status/restart service

chmod

chmod +x filename.sh    # make a file executable

which

which python    # return python interpretor path

realpath

realpath relative/path    # return the absolute path

Dual Ubuntu Installation

Download Ubuntu 22.04, because Ubuntu 20.04 has lots of questions from my experiences
Use Rufus to create a USB medium installer, with GTP partition and NTFS format
Go to UEFI/BIOS and start from USB
install Ubuntu with three partitions
- EFI 500MB Primary Partition
- Swap 2*Memory Size but 32GB usually enough Logical Partition
- / just root directory rest of space Ext4 Logical Partition
Install Applications
- sudo apt update
- sudo apt install build-essential vim
Grub configuration
- vim /etc/default/grub
- set GRUB_DEFAULT=saved and GRUB_SAVEDEFAULT=true
- sudo update-grub
Fix time difference between Win and Linux in link

git

Thanks to the cheat sheet from hbons

Thanks to the workflow from jdsalaro

git init
vim .gitignore    # create a file to avoid adding certain files into repo
git add -A        # or git add .
git commit -m "comment"
git remote add origin <url>
git push -u origin master     # or origin main, -u means tracking and creating remote branch if non-existing

convert a existing folder to a local repository

git remote add origin <git_url>
git branch -M main
git push -u origin main

Useful cheatsheet in Chinese

git clone -b <url>   # direct clone the specific branch
git push origin local_branch:remote_branch

switch to a remote branch

use git in a docker and get errors git vscode container error "Error: Cannot find module '/tmp/vscode-remote-containers-*'"

git submodule

vim

dd     # delete whole line
u :u   # undo

System Version

cat /etc/issue                  # Ubuntu 20.04.6 LTS \n \l
cat /etc/os-release             # NAME="Ubuntu" VERSION="20.04.6 LTS (Focal Fossa)" ...
hostnamectl                     # Static Machine ID Operating System Kernel Architecture
uname -a                        # Linux xxx 5.15.0-88-generic
cat /etc/debian_version         # bullseye/sid
lsb_release -a                  # No LSB modules are available. Distributor ID:	Ubuntu Description:	Ubuntu 22.04.4 LTS Release:	22.04 Codename:	jammy

Goole Colab

link to google drive

from google.colab import drive
import os
root_path = "/content/drive/MyDrive/dest_path"
drive.mount('/content/drive')
os.chdir(root_path)

the bash commands below are now all under root_path

!ls
!pwd
!git clone

Pip

pip show numpy
# or
pip list | grep numpy

show package numpy version

pip config list

show pip source

pip install -r requirements.txt

Change Source

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

# Pip source
# mk ''
# [global]
# index-url = https://mirrors.aliyun.com/pypi/simple/
# 
# [install]
# trusted-host=mirrors.aliyun.com

Python Tricks

list(set(A)-set(B))

unduplicate list A - unduplicate list B

from multiprocessing import Pool
from itertools import repeat
p = Pool(8)
p.starmap(func, zip(arg_list, repeat(single_arg)))

multithread pool executes multi-arguments function

isinstance(s, str)

check if s is a string or int etc.

from typing import List, Tuple, Dict

indicate data type

def function(param_a: str, param_b: np.array) -> dict

list

a = list()
a.append(element)          # add single element to the end
a.extend(iterable)         # add iterable(multi elements) to the end
a.insert(index, element)   # add single element to the specified position

dict

value = my_dict.setdefault('c', 3)

if my_dict['c'] exists, get its value. If not, set it as 3.

tuple

(1,2,3) + (3,4,5) = (1,2,3,3,4,5)

tuples can add but their elements are unchangable.

*args and **kargs

input *args, and arg will be a tuple
input **kargs, which should be （karg_1=1, karg_2=2...), and karg will be a dictionary {karg_1: 1, karg_2: 2...}

print

>>> print('I want to learn %s. How about you?' %'Python')
I want to learn Python. How about you?
>>> print('10 - 23 is %d, not %u' %(-13, 13) )
10 - 23 is -13, not 13
print("{} {}".format("hello", "world")) # No position assignment, deault
'hello world'
txt = "I have {an:.2f} Rupees!"
print(txt.format(an = 4))
print("{1} {0} {1}".format("hello", "world") ) # assigned position
'world hello world'
print(f"mean_reward: {mean_reward:.2f} +/- {std_reward:.2f}")
print("\033[91mHello World!\033[0m")  # prints "Hello World!" in red color

Relatively import

from . import module_name                 # same director
from .package_name import module_name     # same director
from .. import module name                # upper director
from ..package_name import module_name    # upper director

Add PYTHONPATH for import

export PYTHONPATH=/path/to/directory:$PYTHONPATH

Super()

class A (B):
  def __init___ ():
    super().__init()__
    super().func_of_parent()

tqdm()

from tqdm import tqdm
for iter in tqdm(iterative)

as wrapper

# Template
with tqdm(total=args.max_train_steps, desc='PPO Trainning', leave=True, ncols=80, unit='steps', unit_scale=True, colour="red") as pbar:
  Iteration
  pbar.update(n)

Where, desc('str'): prefix description of the bar, mininterval/maxinterval(float): min/max updating time, miniters(int/float): min mode, ascii(bool/str): True(ASCII) False(unicode), ncols(int): bar width, nrows(int): , dynamic_ncols(bool): auto mode, smoothing(float): smooth bar updation, bar_format(str): to customize, position(int): bar position, colour(str): bar color

tqdm.write()

display string above the bar.

assert

assert a == 9 , 'a must be 9'

if a != 9 then assert exception of 'a must be 9'

os

# os.system()
import os
command = "ls"
a = os.system(command)
# a = 0 if it runs well

# save IP address
# os.popen()  execute the cmd and get the output
import os
cmd = 'hostname -I'
result = os.popen(cmd)
ip_addr = result.readlines()[0].replace(' ','').replace('\n','')
print(ip_addr)

files = os.listdir(directory_path)    # equal to bash ls

sys

import sys
sys.executable

get the current python interpretor path

sys.path.append(parent_dir)

add a path for python module search, equal to export PYTHONPATH=$PYTHONPATH:/path/to/dir

re

regular expression

dir

The dir() function returns all properties and methods of the specified object, without the values.

but firstly returns the __dir__ if the target has

numpy

a = np.array([[1,2,3],[4,5,6],[7,8,9]])
# a[0] return np.ndarray [1,2,3], shape=(3,)
# a[0:1] return np.ndarray [[1,2,3]], shape=(1,3)

Slice to array or vector

np.tile( A,(2,2) )
# A -> [A A]
#      [A A]

np.concatenate((A,B),axis=0)

connect Matrix A and B

import numpy as np
a = np.random.random(3)
print('before set precision: \n',a)

np.set_printoptions(precision=3, suppress=True)
print('after set precision: \n',a)

np.set_printoptions(formatter={'float': '{: 0.3f}'.format})
print('after set formatter: \n',a

# output
# before set options: 
# [ 0.05856348 0.5400039 0.70000603]
# after set precision: 
# [ 0.059 0.54 0.7]
# after set formatter: 
# [ 0.059 0.540 0.700]

print with precision and point

a = np.random.random((3,4))
b = a >= 0.5
print(a[b[:,0], : ])    # b[:,0] is a vector (3,), it works
print(a[b[:,0:1],:])    # b[:,0:1] is a matrix (3,1), it fails
# when b[:,0] is all False, result will be []

slides and index

opencv

about mat:

opencv uses numpy as data framework or discriber.

BGR vs RGB:

OpenCV imread, imwrite and imshow indeed all work with the BGR order, so there is no need to change the order when you read an image with cv2.imread and then want to show it with cv2.imshow.

While BGR is used consistently throughout OpenCV, most other image processing libraries use the RGB ordering. If you want to use matplotlib's imshow but read the image with OpenCV, you would need to convert from BGR to RGB.

cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

convert img in opencv from bgr to rgb.

tensorflow

print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))

check GPU condition

loc: location parameter, in most cases is 'Mean'

# tf.where mode1: return the indexes of non-zero elements
tf.where()

# tf.where mode2:
tf.where([True, False, False, True],          # Bool
...          [1, 2, 3, 4],                    # values replace True
...          [100, 200, 300, 400]).numpy()    # values replace False
# >>> array([  1, 200, 300,   4], dtype=int32)

tf.where

tensorflow.Sequence
np.save(... , allow_tickle=True)
np.load(... , allow_tickle=True)

to handle the error of "allow_tickle=False" or "raise pickle.UnpicklingError" in tesorflow.Sequence

tf.broadcast_to(A,B.shape)
tf.boolean_mask(Tensor, Mask)
tf.reshape(tensor, shape, name=None)

tensor tools

EinSum [https://rockt.github.io/2018/04/30/einsum]

data_batch = dataset.batch(1)    # divide the dataset into batches of size 1
data_iter = iter(data_batch)     # returns an iterator from an iterable object
data_next = next(data_iter)      # returns the next item from the iterator. Here it fetches the very first iteration
data_infer = model(data_next)    # infer with the model

_, _ = model(next(iter(dataset.batch(1))), training=False)   # used to initialized the model inference with the firt iter

tensorboard

Remote tensorboard

On the remote machine, start TensorBoard on a known port, e.g. 6006:

tensorboard --logdir /path/to/logs --port 6006 --host 0.0.0.0

On your local machine, create an SSH tunnel:

ssh -L 6006:localhost:6006 username@remote_server

Then open locally, visit:

http://localhost:6006

matplotlib

fig, ax = plt.subplots()    # fig, axs = plt.subplots(m,n) -> axs[m-1,n-1]
ax.plot(x, A @ theta, label='Estimation', color='red')
ax.scatter(x, y, label='Observation', color='blue', marker='x')
ax.legend()
plt.show()

plt.show() will display the current figure that you are working on.

plt.draw() will re-draw the figure. This allows you to work in interactive mode and, should you have changed your data or formatting, allow the graph itself to change.

Subplots and title

fig = plt.figure(figsize=(10,10))                  # figure size
ax1 = fig.add_subplot(2,2,1, projection='3d')      # subplot
# other subplot ...
ax1.axes.set_zlim3d(1,4)                           # axis limit
ax1.set_zlabel('Depth-axis')                       # axis label
# other axis ...
ax1.view_init(elev=-60, azim=-90)                  # veiw position
ax1.set_title('Front View', fontstyle='italic')    # subplot title
ax1.legend()
# other axis ...
sc1 = ax1.scatter(0, 0, 0, color='r', label='Kalman + Inlier')                                   # scatter init with color and label
sc1._offsets3d = (-scatter_mat_Kalman[:,0], scatter_mat_Kalman[:,1], scatter_mat_Kalman[:,2])    # scatter update in for loop, ._offsets3d is the inner attribute not the method

dynamic scatter

Python Virtual Env

source virtual_env_path/bin/activate
deactivate

activate & deactivate

VScode import unresolved, but can be interpreted.

https://github.com/microsoft/pylance-release/blob/main/TROUBLESHOOTING.md#unresolved-import-warnings

Poetry

poetry init
poetry install
poetry shell
poetry add <dependency>
poetry lock                # update poetry.lock

Conda

conda info
conda info -e
# sudo chmod 600 PATH
conda create -n <env name> python=x.x
conda create --prefix=/var/www/myblog/felixvenv python=3.7.1
conda remove -n <env name>
conda remove --name ENV_NAME --all
conda update --all

show env information

show all envs

create a virtual env

conda install --yes --file requirements.txt

conda install packages in requirement.txt

SSH Connection

ssh-keygen -m PEM -t rsa -b 4096

When lose connection in a public network, the reason might be the "wireless mode". Try to modify the "wireless mode" to 'IEEE 802.11 b/g'

# configuration
Host Alias/Abbreviation
  HostName <xxx.xxx.xxx.xxx>
  User <username>
  Port 22
  IdentityFile <C:\Users\username\.ssh\xxx.pem>

Files Transfer through SSH

scp ./filename username@ip-address:~/path/to/put/it/           # upload to robot
scp username@ip-address:/path/to/filename ~/path/to/put/it/    # download from robot

Upload or Download files

Google Cloud Computing

gcloud auth login
gcloud init
gcloud compute ssh --project=PROJECT_ID --zone=ZONE VM_NAME # direct ssh connect via Putty
gcloud compute config-ssh # generate ssh config in your .ssh folder

Change Source

Ubuntu

# apt source (Raspberry Debian10 Buster)
# /etc/apt/sources.list
deb http://mirrors.tuna.tsinghua.edu.cn/raspbian/raspbian/ buster main non-free contrib rpi
deb-src http://mirrors.tuna.tsinghua.edu.cn/raspbian/raspbian/ buster main non-free contrib rpi
# /etc/apt/sources.list.d/raspi.list
deb http://mirrors.tuna.tsinghua.edu.cn/raspberrypi/ buster main ui

Python in Ubuntu

# Pip source
# mk ''
# [global]
# index-url = https://mirrors.aliyun.com/pypi/simple/
# 
# [install]
# trusted-host=mirrors.aliyun.com

Conda in Win

# Tsinghua source for China Mainland
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge 
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
# show
conda config --set show_channel_urls yes
# reset
conda config --remove-key channels

ROS2 Humble

source /opt/ros/humble/setup.bash
echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc    # add source to .bashrc

ros2 pkg create --build-type ament_cmake --license Apache-2.0 <package_name>    # create a package

Ros2 run

ros2 run <package_name> <executable_name>    # ros2 run turtlesim turtlesim_node

ros2 node

ros2 node list
ros2 node info <node_name>
ros2 param list                  # show parameters in node namespaces
ros2 param get <node_name> <parameter_name>
ros2 param set <node_name> <parameter_name> <value>
ros2 param dump <node_name> > node_param.yaml      # View all of a node’s current parameter values and save to file
ros2 param load <node_name> <parameter_file>       # load param from file
ros2 run <package_name> <executable_name> --ros-args --params-file <file_name>

ros2 topic

ros2 topic echo <topic_name>      # To see the data being published on a topic
ros2 topic info <topic_name>      # Type, Publisher/Subscriber count
ros2 interface show <msg type>    # to learn Type details
ros2 topic pub <topic_name> <msg_type> '<args>'    # ros2 topic pub --once /turtle1/cmd_vel geometry_msgs/msg/Twist "{linear: {x: 2.0, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 1.8}}"

ros2 service

ros2 service list -t                # -t=--show-types, show services and their types
ros2 service type <service_name>    # To find out the type of a service, service type like "std_srvs/srv/Empty
ros2 service find <type_name>       # To see the request and response arguments of the service type
ros2 service call <service_name> <service_type> <arguments>

ros2 launch

ros2 launch turtlesim multisim.launch.py

But ROS 2 launch formats in Using Python, XML, and YAML for ROS 2 Launch Files.

# turtlesim/launch/multisim.launch.py

from launch import LaunchDescription
import launch_ros.actions

def generate_launch_description():
    return LaunchDescription([
        launch_ros.actions.Node(
            namespace= "turtlesim1", package='turtlesim', executable='turtlesim_node', output='screen'),
        launch_ros.actions.Node(
            namespace= "turtlesim2", package='turtlesim', executable='turtlesim_node', output='screen'),
    ])

ros2 bag

ros2 bag record <topic_name>
ros2 bag record -o subset /turtle1/cmd_vel /turtle1/pose  # -o indicates the save bagfile
ros2 bag info <bag_file_name>
ros2 bag play <bag_file_name>
ros2 topic hz /turtle1/pose        # topic frequency

colcon build

Different from catkin build, the ROS2 use colcon build

colcon build --symlink-install     # colcon supports the option --symlink-install. This allows the installed files to be changed by changing the files in the source space

package

CMakeLists.txt file that describes how to build the code within the package
include/<package_name> directory containing the public headers for the package
package.xml file containing meta information about the package
src directory containing the source code for the package

ROS2 XML

Substitution Attribute: ${}
Substitution Function: $()

ROS1 Noetic

Nodes: A node is an executable that uses ROS to communicate with other nodes.
Messages: ROS data type used when subscribing or publishing to a topic.
Topics: Nodes can publish messages to a topic as well as subscribe to a topic to receive messages.
Master: Name service for ROS (i.e. helps nodes find each other)
rosout: ROS equivalent of stdout/stderr
roscore: Master + rosout + parameter server (parameter server will be introduced later)
rosservice: Services are another way that nodes can communicate with each other. Services allow nodes to send a request and receive a response.
rosparam: rosparam allows you to store and manipulate data on the ROS Parameter Server.
msg: msg files are simple text files that describe the fields of a ROS message. They are used to generate source code for messages in different languages.
srv: an srv file describes a service. It is composed of two parts: a request and a response.

Ros Package

catkin_create_pkg <package_name> [depend1] [depend2] [depend3]
rospack depends1 beginner_tutorials

ROS Nodes

rosnode list
rosndoe info /rosrun

Run the node from the package

rosrun [package_name] [node_name] __name:=[customed name]

ROS Topics

rostopic bw     display bandwidth used by topic
rostopic echo   print messages to screen
rostopic hz     display publishing rate of topic    
rostopic list   print information about active topics
rostopic pub    publish data to topic
rostopic type   print topic type

rostopic list   -v, --verbose         list full details about each topic

$ rostopic type /turtle1/command_velocity
> turtlesim/Velocity
$ rosmsg show turtlesim/Velocity
float32 linear
float32 angular

rostopic pub [topic] [msg_type] [args]
$ rostopic pub -1 /turtle1/cmd_vel geometry_msgs/Twist -- '[2.0, 0.0, 0.0]' '[0.0, 0.0, 1.8]'

Plot topics

rosrun rqt_plot rqt_plot

ROS Services

rosservice list         print information about active services
rosservice call         call the service with the provided args
rosservice type         print service type
rosservice find         find services by service type
rosservice uri          print service ROSRPC uri

rosservice call [service] [args]

ROSPARAM

rosparam set            set parameter
rosparam get            get parameter
rosparam load           load parameters from file
rosparam dump           dump parameters to file
rosparam delete         delete parameter
rosparam list           list parameter names

rosparam set [param_name]    # rosparam set /turtlesim/background_r 150
rosparam get [param_name]
rosparam get /               # get all params

rosparam dump [file_name] [namespace]
rosparam load [file_name] [namespace]

ROS msg & srv

roscd rospackage
mkdir srv msg
# ceate .msg and .srv like
Header header
string child_frame_id
geometry_msgs/PoseWithCovariance pose
geometry_msgs/TwistWithCovariance twist
---
int64 sum    # response only exists in srv

# check them
rosmsg show [message type]
rossrv show <service type>

Modify package.xml and CMakelists.txt with the link [http://wiki.ros.org/ROS/Tutorials/CreatingMsgAndSrv]

ROS scripts

roscd rospackage
mkdir scripts

Add codes and modify CMakelists.txt like [http://wiki.ros.org/ROS/Tutorials/WritingPublisherSubscriber%28python%29], then test

cd ~/catkin_ws
catkin_make
rosrun beginner_tutorials talker.py
rosrun beginner_tutorials listener.py

ROS Service & Client

Follow the link[http://wiki.ros.org/ROS/Tutorials/WritingServiceClient%28python%29], then test with

rosrun beginner_tutorials add_two_ints_server.py
rosrun beginner_tutorials add_two_ints_client.py 1 3

ROSBAG

mkdir ~/bagfiles
cd ~/bagfiles
rosbag record -a  # record all topics
rosbag record [TOPIC1 TOPIC2 TOPIC3 ...]

rosbag play
rosbag info

All rosbag link[http://wiki.ros.org/rosbag/Tutorials]

# run and record
roscore
roslaunch 
rosbag record -O <output_name> /turtle1/cmd_vel /turtle1/pose --duration 1m # record selected topics for 1 minute into name.bag
roslaunch realsense2_camera rs_camera.launch align_depth:=true

run ros script and record topics

Ros_numpy

The ros_numpy in ROS-noetic is too old to match the new Python and Numpy

Q1. AttributeError: module 'numpy' has no attribute 'float'

try: 
    import ros_numpy
except AttributeError:
    import numpy as np
    np.float = np.float64  # temp fix for following import
    import ros_numpy

Q2. AttributeError: module 'collections' has no attribute 'Sequence'

go to ros_numpy and replace collections with collections.abc

C++

- vs. &

int var = 3000;
int *ptr;        // type * to define variable
int val;
ptr = &var;      // operator & to get the address 
val = *ptr;      // operator * to get the value

// Declaration
void fun1 (int& n1, int& n2)    // type & to define reference. Reference is an alias. We use this to direct modify the arguement from upper function
{
  int temp = n1;                // variable n1 is an alias
  n1 = n2; n2 = temp;
}

void fun2 (int* n1, int* n2)    // type * to define pointer
{
  int temp = *n1;               // operator * to get the value
  *n1 = *n2; *n2 = temp;
}

Name		Name	Last commit message	Last commit date
Latest commit History 149 Commits
Greek.md		Greek.md
Init_MacOS_Checklist.md		Init_MacOS_Checklist.md
README.md		README.md
Ubuntu_skills		Ubuntu_skills
VM_init.sh		VM_init.sh
gittimeworkflow.png		gittimeworkflow.png
preview.png		preview.png
test.cpp		test.cpp

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