Logging VS Puts Debuggerer

You can choose from a number of third-party logging libraries, including Logging — based on Java's log4j library — and Lograge. Lograge is a feature-rich logging library meant to simplify the often messy and verbose Rails logs characteristic of the default application logger.

For Ruby I use (Logging)[https://github.com/TwP/logging] and while I'm not happy with its Rails gem it can be used without it.

git reset -- lichess-bot git add . git commit -m "hosting" git remote add origin https://github.com/username/repository.git - CHANGE THIS git push --set-upstream origin master

git clone https://github.com/tungbq/repos.git cd repos ./generate_content.sh repository_list.txt

GitHub, as one of the leading web-based Git repository hosting service, provides a powerful suite of CI/CD tools in the form of GitHub Actions. These are directly integrated into the platform which empowers developers to increase the speed, efficiency and reliability of delivering products. In this brief article, we will take a look at what CI/CD is, why we should use it, as well as some of its applications in my projects.

Head over to the GitHub website by clicking here, and register for an account.

githubConfigUrl: "https://github.com/" githubConfigSecret: "pre-defined-secret" maxRunners: 100 runnerScaleSetName: "arc-runner-set-arm" template: metadata: annotations: karpenter.sh/do-not-disrupt: "true" spec: nodeSelector: kubernetes.io/arch: "arm64" serviceAccountName: arc-runner-base-role tolerations: - key: github/arm value: "true" effect: NoSchedule initContainers: - name: init-dind-externals image: ghcr.io/actions/actions-runner:latest command: ["cp", "-r", "-v", "/home/runner/externals/.", "/home/runner/tmpDir/"] volumeMounts: - name: dind-externals mountPath: /home/runner/tmpDir containers: - name: runner image: ghcr.io/actions/actions-runner:latest command: ["/home/runner/run.sh"] env: - name: DOCKER_HOST value: unix:///run/docker/docker.sock resources: requests: cpu: 1 volumeMounts: - name: work mountPath: /home/runner/_work - name: dind-sock mountPath: /run/docker readOnly: true - name: dind image: public.ecr.aws/docker/library/docker:dind args: - dockerd - --host=unix:///run/docker/docker.sock - --group=$(DOCKER_GROUP_GID) env: - name: DOCKER_GROUP_GID value: "123" securityContext: privileged: true volumeMounts: - name: work mountPath: /home/runner/_work - name: dind-sock mountPath: /run/docker - name: dind-externals mountPath: /home/runner/externals volumes: - name: work emptyDir: {} - name: dind-sock emptyDir: {} - name: dind-externals emptyDir: {} controllerServiceAccount: name: arc-gha-rs-controller namespace: arc-systems

The first step is to create a GitHub account. You can do it here.

Collaboration and version control are crucial in AI/ML development projects due to the iterative nature of model development and the need for reproducibility. GitHub is the leading platform for source code management, allowing teams to collaborate on code, track issues, and manage project milestones. DVC (Data Version Control) complements Git by handling large data files, data sets, and machine learning models that Git can't manage effectively, enabling version control for the data and model files used in AI projects.

Scenario('Github login', ({ I }) => { I.amOnPage('https://github.com') I.click('Sign in'); I.fillField('Username', 'davert'); I.fillField('Password', '123345'); I.click('Login'); I.see('Incorrect username or password'); });