> For the complete documentation index, see [llms.txt](https://docs.zerve.ai/guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zerve.ai/guide/canvas-view.md).

# Canvas View

- [Navigating Your Canvas](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas.md): This section is for exploring different functionalities of canvas
- [Creating a Canvas](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/creating-a-canvas.md)
- [My Canvases](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/my-canvases.md): The canvas view in the my canvases section can be adjusted according to the user's preference. The different views are show below:
- [Edit and Sort](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/edit-and-sort.md)
- [Shared with me](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/shared-with-me.md)
- [Starred](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/starred.md)
- [Layers Overview](https://docs.zerve.ai/guide/canvas-view/layers-overview.md): Layers are used for arranging blocks as individual workflows. Each canvas can be set up to contain multiple workflows of same/different types for different parts of a data science problem.
- [Development](https://docs.zerve.ai/guide/canvas-view/layers-overview/development.md): The IDE Layer. Development layer is similar to any scripting environment - Jupyter or datascience Coding IDE - but better.
- [Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment.md): API builder allows developers to define endpoints, map data structures, set up authentication and authorization mechanisms, and generate documentation for their APIs.
- [Create Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/create-deployment.md): There are 3 components to setup a deployment in Zerve - API Controller, API Route and the code blocks to execute as part of the deployment.
- [Download Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/download-deployment.md)
- [API Methods](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/api-methods.md)
- [Scheduled Jobs](https://docs.zerve.ai/guide/canvas-view/layers-overview/scheduled-jobs.md): Each canvas in Zerve has an inbuilt scheduler as part of it. This can be used to run analytics workflows that need to be run at scheduled intervals - hourly/daily/weekly/custom (cron string)
- [Files](https://docs.zerve.ai/guide/canvas-view/files.md): File system is the storage space for all the files required to create, run and execute the canvas.
- [Storing Files](https://docs.zerve.ai/guide/canvas-view/files/storing-files.md): Canvas file system is a dynamic environment to store files of any type with a specified size limit.
- [Import Files](https://docs.zerve.ai/guide/canvas-view/files/import-files.md): Once the file is uploaded, it can be accessed in the Python or R blocks, and the files can be of any type.
- [Download Files](https://docs.zerve.ai/guide/canvas-view/files/download-files.md): The files can also be seamlessly downloaded into file system from Python or R blocks.
- [Deleting Files](https://docs.zerve.ai/guide/canvas-view/files/deleting-files.md): The zerve's canvas offers different ways to delete a file from file system
- [Files in Folder](https://docs.zerve.ai/guide/canvas-view/files/files-in-folder.md)
- [Installing Packages](https://docs.zerve.ai/guide/canvas-view/installing-packages.md): User can install Python, Linux and R packages by using the Environment feature.
- [Requirements](https://docs.zerve.ai/guide/canvas-view/installing-packages/requirements.md): By default, zerve canvas run in containers with Python 3.11.1, and a number of pre-installed packages. The user has the option to add new packages, new python versions, etc. from the requirements tab.
- [Global Imports](https://docs.zerve.ai/guide/canvas-view/global-imports.md): Imports done under each code block will work only inside it. Users can add a package or function to Global Imports section to make it available across all the blocks in the canvas.
- [Blocks and Connections](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections.md)
- [Block types](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types.md)
- [Python](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/python.md)
- [Query](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/query.md)
- [R](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/r.md)
- [Markdown](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/markdown.md)
- [Gen AI](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/gen-ai.md): GenAI blocks can be used to connect to LLMs on Bedrock/OpenAI making it suitable for various applications, including text generation, summarization, translation, text to image, and more.
- [R Markdown](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/r-markdown.md): Zerve’s R Markdown block enables users to integrate and execute R code within their analytics environment, facilitating the creation and publication of dynamic, interactive reports.
- [UI Blocks (Input and Output)](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/ui-blocks-input-and-output.md): These blocks help the user to create an application in the canvas
- [Aggregator](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/aggregator.md)
- [Logic Gate](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/logic-gate.md)
- [Code and Variable Mode](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/code-and-variable-mode.md)
- [Block level Security](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-level-security.md)
- [Language Interoperability](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/language-interoperability.md): This functionality of Zerve allows users to share the data between two programming languages
- [Compute Settings](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/compute-settings.md)
- [Lambda vs Fargate vs GPU](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/compute-settings/lambda-vs-fargate-vs-gpu.md)
- [How Zerve Works](https://docs.zerve.ai/guide/canvas-view/how-zerve-works.md)
- [Assets](https://docs.zerve.ai/guide/canvas-view/assets.md): Assets are used for storing functions, queries, constants, secrets, and connections for seamless development.
- [Functions & Classes](https://docs.zerve.ai/guide/canvas-view/assets/functions-and-classes.md): "Functions & Classes" are reusable code snippets that encapsulate specific logic or operations or classes.  This provides code modularity, readability, and reduces duplication.
- [Constants & Secrets](https://docs.zerve.ai/guide/canvas-view/assets/constants-and-secrets.md): "Constants" are used for unchanging data in code to enhance readability and maintainability, "Secrets" refer to sensitive information that should be protected and not exposed in your code.
- [Connections](https://docs.zerve.ai/guide/canvas-view/assets/connections.md): Zerve offers support to integrate with popular database solutions which can be queried directly from canvas and can be used across different blocks/languages.
- [AI Agent](https://docs.zerve.ai/guide/canvas-view/ai-agent.md)
- [Chat](https://docs.zerve.ai/guide/canvas-view/ai-agent/chat.md)
- [Search](https://docs.zerve.ai/guide/canvas-view/ai-agent/search.md): Agent can search the internet for you based on your input
- [Code](https://docs.zerve.ai/guide/canvas-view/ai-agent/code.md)
- [Best Practices](https://docs.zerve.ai/guide/canvas-view/ai-agent/best-practices.md)
- [Fleets](https://docs.zerve.ai/guide/canvas-view/fleets.md): Fleets is Zerve's built-in feature for parallel processing. With a single line of code, users can parallelize code to run across multiple blocks.