> For the complete documentation index, see [llms.txt](https://docs.rhinofcp.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rhinofcp.com/creating-and-running-code-objects/creating-and-running-a-python-code-object/using-a-python-code-snippet-or-standalone-file.md). # Using a Python Code Snippet or Standalone File * **Code Snippet** - Ideal for relatively straightforward scripts that primarily utilize basic Python packages, along with Pandas and Numpy. FCP automatically provides access to your cohort data as a Pandas Dataframe named **df.** Additionally, it generates the output cohort of your model from this same Dataframe. This setup facilitates elementary Pandas-based operations on your raw input data, such as feature extraction and value normalization. As an example, consider this Python code snippet: ```python normalized_df = (df-df.mean())/df.std() df = normalized_df ``` Executing this code snippet yields an output cohort with z-normalized numerical features, all without requiring any additional code. * **Standalone File** - This option grants you the freedom to execute varied Python code with custom dependencies, extending beyond Pandas and Numpy. The Standalone File option lets you specify your code's prerequisites, which will be automatically installed within the image generated by FCP. If your code necessitates a specific environment – for instance, to support GPU operations - you can define the Container Base Image that supports it. Use this option for more complex code, which can still be run as a single file. Unlike the ***Code Snippet***, no additional "hidden" functionality is included here. * **Upload File(s)** - This option is similar to "Standalone File", but allows you to provide your code in more than one file, e.g., multiple Python files and/or shell scripts. Files can include non-Python files of any format, such as configuration files, model parameter files, and so forth. You just have to upload the files you need, or a folder(s), and select the entry point in the text box that appears when this option is selected. The entry point is the file that you'd like your container to run. Be sure to specify code requirements and the container environment as needed. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.rhinofcp.com/creating-and-running-code-objects/creating-and-running-a-python-code-object/using-a-python-code-snippet-or-standalone-file.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.