sudo apt update
sudo apt install python3
Verify Installation:
python3 --version
python3
sudo apt install python3-pip
pip3 --version
Interpreter -
Python3 filename.py
sudo apt update
sudo apt install python3
Verify Installation:
python3 --version
python3
sudo apt install python3-pip
pip3 --version
Interpreter -
Python3 filename.py
https://support.google.com/analytics/answer/9304153?hl=en
https://analytics.google.com/analytics/web/#/p213025502/reports/intelligenthome
https://www.youtube.com/watch?v=QmEOPuJr05w&list=PLI5YfMzCfRtZ4bHJJDl_IJejxMwZFiBwz&index=4
Setting up a Google Analytics account involves a few steps. Follow these step-by-step instructions:
Create a Google Account: If you don't have a Google Account, you'll need to create one. Visit the Google Account creation page and follow the instructions.
Sign in to Google Analytics: Once you have a Google Account, go to the https://analytics.google.com/analytics/web/#/ and sign in with your Google Account credentials.
Set Up a New Google Analytics Account:
Set Up a Property:
Configure Data Sharing Settings:
Create a Google Analytics 4 Property:
Agree to Terms and Create:
Install the Tracking Code:
Verify Tracking Installation:
Explore Google Analytics:
Remember that it may take some time for data to appear in your reports, so be patient. Regularly check your Google Analytics account to gain insights into your website's performance and user behavior.
Below is the Google tag for this account. Copy and paste it in the code of every page of your website, immediately after the <head> element. Don’t add more than one Google tag to each page.
There are several excellent free courses available for Artificial Intelligence (AI) studies. Here are some of the best free courses for AI:
1. Stanford University's CS229: Machine Learning: This course is available for free online and covers various machine learning algorithms and techniques. It is widely regarded as one of the best resources for learning machine learning.
2. Stanford University's CS231n: Convolutional Neural Networks for Visual Recognition: This course focuses on deep learning techniques applied to computer vision. It covers topics such as CNNs, image classification, object detection, and more.
3. University of Helsinki's Elements of AI: This online course provides a beginner-friendly introduction to AI. It covers various AI concepts and applications, offering a comprehensive overview of the field.
4. Google's Machine Learning Crash Course: This free online course offers an introduction to machine learning concepts. It covers topics such as linear regression, classification, neural networks, and more.
5. Microsoft's Artificial Intelligence (AI) Ethics, Law, and Policy: This course explores the ethical implications of AI. It covers topics such as fairness, transparency, privacy, and bias in AI systems.
6. deeplearning.ai's Deep Learning Specialization: This specialization on Coursera offers the first course, "Neural Networks and Deep Learning," for free. It provides a comprehensive introduction to deep learning techniques.
7. Berkeley's Artificial Intelligence: This course, available on edX, covers various AI topics such as search algorithms, logic, planning, and more. It provides a solid foundation in AI principles.
8. Fast.ai's Practical Deep Learning for Coders: This course is designed to make deep learning accessible for coders. It covers practical aspects of deep learning and provides hands-on experience with real-world applications.
9. UC San Diego's Machine Learning Fundamentals: This course offers an overview of machine learning principles, algorithms, and applications. It covers topics such as regression, clustering, and reinforcement learning.
10. IBM's Applied AI: This course on Coursera explores various AI applications in industries like healthcare, finance, and cybersecurity. It offers insights into how AI is being used in real-world scenarios.
These free courses provide a solid foundation in AI and cover a range of topics including machine learning, deep learning, ethics, and applications. They are a great way to get started and gain knowledge in the field of AI without incurring any cost.
If you face this "connection timed out error"
$ sudo apt update
Could not connect to in.archive.ubuntu.com:80 (*2403:8940:ffff::f*), connection timed out Could not connect to in.archive.ubuntu.com:80 (103.97.84.254), connection timed out
Err:8 http://in.archive.ubuntu.com/ubuntu bionic-updates InRelease
Unable to connect to in.archive.ubuntu.com:http:
Err:9 http://in.archive.ubuntu.com/ubuntu bionic-backports InRelease
Unable to connect to in.archive.ubuntu.com:http:
------------------------------------------------------------------------ 1)sudo nano /etc/apt/sources.list2)replace allhttp://**xx**.archive.ubuntu.com/ubuntu...tohttp://archive.ubuntu.com/ubuntu ...
https://askubuntu.com/questions/1198621/apt-get-cannot-connect-to-ubuntu-archives
Download the Ubuntu to your system
REFERENCES:
https://ubuntu.com/tutorials/create-a-usb-stick-on-ubuntu#3-launch-startup-disk-creator
node -e 'console.log(v8.getHeapStatistics().heap_size_limit/(1024*1024))' That said, to increase the memory, in the terminal where you run your Node.js process:
export NODE_OPTIONS="--max-old-space-size=8192" Reference https://stackoverflow.com/questions/53230823/fatal-error-ineffective-mark-compacts-near-heap-limit-allocation-failed-javas
1) Go to the website https://reqbin.com/curl
2) paste the curl and run to see validation errors
To increase the storage space of an Amazon EC2 instance, you can follow these general steps. Keep in mind that this process may vary slightly depending on the EC2 instance type and your specific requirements:
Create a Backup (Snapshot): Before making any changes, it's crucial to create a backup (snapshot) of your EC2 instance's EBS (Elastic Block Store) volume. This ensures that you have a point-in-time copy of your instance's data that you can restore if anything goes wrong during the resizing process.
To create a snapshot, go to the AWS Management Console, navigate to the "EC2" service, select "Volumes" from the left sidebar, find your instance's EBS volume, right-click it, and choose "Create Snapshot."
Stop the EC2 Instance: To make changes to the instance's storage, you will typically need to stop it first. In the AWS Management Console, right-click your instance, and choose "Instance State" > "Stop."
Resize the EBS Volume: After stopping the instance, you can resize the EBS volume attached to it. Here's how:
a. In the AWS Management Console, go to "EC2" and navigate to the "Volumes" section.
b. Find the EBS volume that is attached to your EC2 instance.
c. Right-click the volume and choose "Modify Volume."
d. In the "Modify Volume" dialog, increase the volume size to your desired capacity.
e. Confirm the changes, and AWS will perform the resize operation. This process usually completes quickly, but it might take a few minutes.
Start the EC2 Instance: Once the volume is resized, you can start your EC2 instance again. Right-click your instance in the AWS Management Console and choose "Instance State" > "Start."
Resize the File System: After resizing the EBS volume, you'll need to resize the file system on the instance to make use of the additional storage space. This step depends on the operating system you're using:
For Linux: If you're using Linux, you can use the resize2fs command to resize the file system. For example, if you're using ext4, you can run:
bashlsblk //to find out partition name xvda1df -hT //to find the type of partitionsudo growpart /dev/xvda 1 //to extend the partition (eg: sudo growpart /dev/nvme0n1 1)if the result is ext4findmnt -no FSTYPE / //check the file system
sudo resize2fs /dev/xvda1 /to resize (eg: sudo resize2fs /dev/nvme0n1p1)
Verify the Storage Increase:
df -h
Remember that these steps might vary slightly based on your specific EC2 instance type, region, and operating system. Always take precautions and create backups before making changes to your EC2 instance's storage to prevent data loss.
If server key is not available:
https://console.cloud.google.com/apis/api/googlecloudmessaging.googleapis.com
2. In the project settings, add a web app (if you don't already have one) and download the Firebase configuration JSON file. You'll need this for server authentication.
3. To get VAPID key, in the "cloud message" generate web push certificate key pair
References: https://stackoverflow.com/questions/37427709/firebase-messaging-where-to-get-server-key
REFERENCES:
https://www.freecodecamp.org/news/where-are-docker-images-stored-docker-container-paths-explained/
1) The output contains information about your storage driver and your docker root directory
$ docker info 2) A Docker container consists of network settings, volumes, and images. Ubuntu:/var/lib/docker/
3) Docker images Docker images are stored in /var/lib/docker/overlay2 4) Docker Volumes$ docker run --name nginx_container -v /var/log nginx 5)Clean up space used by Docker
$ docker system prune -a 6) To get container size and container info
$ docker ps -s
$ docker ps -a
7) pull down an image from a repository,
docker pullcreate a container from an image that does not yet exist locally, each layer is pulled down separately, and stored in Docker's local storage area, which is usually/var/lib/docker/
8) Check out the sizes of the images:
docker image ls
9) create a volume
docker volume create my-vol
10) List Volumes
docker volume ls
11) Inspect volumedocker volume inspect my-vol
12) To backup volume
docker run --volumes-from --container_name-- -v $(pwd):--path-- ubuntu tar cvf --path--/storage.tar /app/storage/app/public
13) To restore volume
docker run --rm --volumes-from --container_name-- -v $(pwd):--path-- bash -c "cd storage/app/public && tar xvf --path--/storage.tar"
14) To restore volume
docker exec -it docker-webserver-1 /bin/bash
TTo Set up ssl certificate:
docker compose run --rm certbot certonly --manual --preferred-challenges dns -d example.com -d *.example.com -v
docker ps
docker restart docker-name
docker system df
df -h
docker builder prune
docker exec -it docker-webserver-1 /bin/sh
docker logs docker-webserver-1
Dangling images are images that are not associated with any running containers and are not tagged with a specific version or name. These images are typically left behind when you build or pull new images, and older, unused versions are no longer needed. They can accumulate over time and consume disk space.
docker image prune
docker container prune
java -Dsonar.token=SONAR_TOKEN -Dlicense.file=/home/mysupply/Downloads/bitegarden-sonarcloud-report-1.3.4/LICENSE.txt -Dsonar.projectKey=examplecode1_phpbackend -Dsonar.organizationKey=examplecode1 -Dreport.type=0 -jar bitegarden-sonarcloud-report-1.3.4.jar
If you encounter the error message "Invalid domain for site key" when working with Google reCAPTCHA, it typically means that the site key you are using is not associated with the domain or website where you are trying to implement reCAPTCHA.
To resolve this issue, you need to ensure that you have registered the correct domain or website with Google reCAPTCHA and obtained the appropriate site key. Follow these steps to fix the problem:
By following these steps and using the correct site key associated with the domain or website, you should be able to resolve the "Invalid domain for site key" error.
Add the site key to
(search for recaptcha)
clients: supplier portal , admin portal , user portal (to their env.docker files)
Add secret key to
server: laravel back-end