Conda Integrations

This is the easiest way to deploy and test your projects on-prem or in the cloud. You can easily sync your Travis CI projects and you'll be able to test your code in just minutes. Check out our features - you can now sign up for Travis CI with your Bitbucket or GitLab account. This will allow you to connect to your repositories. It's always free to test your open-source projects! Log in to your cloud repository and tell Travis CI that you want to test a project. Then push. It couldn't be simpler. Many services and databases are already pre-installed and can easily be enabled in your build configuration. Before merging Pull Requests to your project, make sure they are tested. It's easy to update production or staging as soon as your tests pass. Travis CI builds are set up mainly through the configuration file.travis.yml found in your repository. This allows you to make your configuration version-controlled and flexible.

Package manager and build system in Fortran. Many packages are already available for fpm to provide a rich and accessible ecosystem of general-purpose and high performance code. Fortran Package Manager (fpm), is a package manager for Fortran. Its main goal is to improve the user experience for Fortran programmers. It makes it easier to create your Fortran program, library, test, and example programs, and to distribute it as a dependency to other Fortran project. Fpm's user interface was inspired by Rust's Cargo. Its long-term goal is to grow and nurture the Fortran ecosystem of modern libraries and applications. The plugin system allows the Fortran package manager to easily expand its functionality. The plugin fpm-search allows you to query the package registry. It is easy to install on our system because it is built using fpm.

Coiled makes enterprise-grade Dask easy. Coiled manages Dask clusters within your AWS or GCP account. This makes it the easiest and most secure method to run Dask in production. Coiled manages your cloud infrastructure and can deploy to your AWS account or Google Cloud account in a matter of minutes. Coiled provides a solid deployment solution that requires little effort. You can customize the cluster node types to meet your analysis needs. Run Dask in Jupyter Notebooks to get real-time dashboards, cluster insights, and other useful information. You can easily create software environments with custom dependencies for your Dask analysis. Enjoy enterprise-grade security. SLAs, user level management, and auto-termination clusters reduce costs. Coiled makes it easy for you to deploy your cluster on AWS and GCP. It takes only minutes and requires no credit card. You can launch code from anywhere you like, including cloud services like AWS SageMaker and open source solutions like JupyterHub.

Garak checks to see if we can make an LLM fail in a manner that we don't like. Garak checks for hallucinations, data leakage and prompt injection, misinformation generation, toxicity, jailbreaks and other weaknesses. We love developing garak and are always looking to add new features. Garak is a command line tool. It's developed for Linux and OSX. You can download it from PyPI. The standard pip versions of garak are updated periodically. Garak has its dependencies. You can install garak within its own Conda environment. Garak needs to know which model to scan. By default, it will use all the probes that it knows to scan the model using the vulnerability detectors suggested by each probe. Garak will print progress bars for each probe as it generates. Once the generation has been completed, a row will be displayed evaluating each probe's results for each detector.

With a single keystroke, switch between editor and command modes. Use the arrow keys to navigate between cells. All the Jupyter shortcuts are available. Fully interactive outputs are available right under the cell. Editing code cells is easy with smart code completion, quick error checking and quick fixes, and easy navigation. You can connect to remote JupyterHub or JupyterLab servers from the IDE. Interactively run Python scripts and arbitrary expressions in a Python Console. You can see the outputs and the state variables in real time. Split Python scripts into code cells using the #%% separator, and run them individually in a Jupyter notebook. Interactive controls allow you to browse DataFrames or visualizations in real time. All popular Python scientific libraries, including Plotly and Altair, ipywidgets and others, are supported.

Manage binaries and create artifacts throughout your software supply chain. All components, binaries and artifacts are available from one source. Distribute parts and containers efficiently to developers. More than 100,000 organizations worldwide have used this product. Distribute Maven/Java components, npm and NuGet, Helm and Docker, OBR, APT and GO, R components, and many more. From dev to delivery, manage components: binaries and containers, assemblies, and finished products. Advanced support for Java Virtual Machine (JVM), including Gradle, Ant and Maven, as well as Ivy. Compatible with Eclipse, IntelliJ and Hudson, Jenkins, Puppets, Puppets, Chef, Docker and many other popular tools. High availability and innovation available 24x7x365. One source of truth for all components throughout your software development lifecycle, including QA, staging, operations. Integrate with existing user access provisioning systems such as LDAP, Atlassian Crowd and more.

Industry's first IAST solution that combines active verification and sensitive data tracking for web-based applications. Automatically retests vulnerabilities and validates that they can be exploited. This is more accurate than traditional dynamic testing. It provides a real-time overview of the top security holes. Sensitive data tracking allows you to see where your most important information is stored without adequate encryption. This helps ensure compliance with industry standards and regulations such as PCI DSS or GDPR. Seeker is easy-to-implement and scale in your CI/CD workflows. Native integrations, web APIs and plugins allow seamless integration with your tools for container-based, cloud-based and microservices-based development. Without any configuration, tuning, or custom services, you'll get precise results right out of the box.

Amazon SageMaker Studio Lab provides a free environment for machine learning (ML), which includes storage up to 15GB and security. Anyone can use it to learn and experiment with ML. You only need a valid email address to get started. You don't have to set up infrastructure, manage access or even sign-up for an AWS account. SageMaker Studio Lab enables model building via GitHub integration. It comes preconfigured and includes the most popular ML tools and frameworks to get you started right away. SageMaker Studio Lab automatically saves all your work, so you don’t have to restart between sessions. It's as simple as closing your computer and returning later. Machine learning development environment free of charge that offers computing, storage, security, and the ability to learn and experiment using ML. Integration with GitHub and preconfigured to work immediately with the most popular ML frameworks, tools, and libraries.