{"library":"nipype","title":"Neuroimaging in Python: Pipelines and Interfaces (Nipype)","description":"Nipype is a Python project that provides a uniform interface to existing neuroimaging software packages (e.g., FSL, SPM, AFNI, ANTS, FreeSurfer). It enables users to easily create and execute robust, reproducible, and efficient pipelines for neuroimaging data analysis. The current version is 1.11.0, and it maintains an active release cadence with regular feature and bug-fix updates.","language":"python","status":"active","last_verified":"Sat May 16","install":{"commands":["pip install nipype"],"cli":null},"imports":["from nipype.pipeline.engine import Workflow","from nipype.pipeline.engine import Node","from nipype.interfaces.utility import Function","from nipype.interfaces.utility import IdentityInterface","from nipype.interfaces import fsl"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import os\nfrom nipype.pipeline.engine import Workflow, Node\nfrom nipype.interfaces.utility import Function, IdentityInterface\n\ndef simple_multiply(a, b):\n    return a * b\n\n# Create a workflow\nwf = Workflow(name=\"simple_math_workflow\")\nwf.base_dir = os.environ.get('NIPYPE_WORKDIR', os.path.abspath('nipype_work_dir'))\n\n# Input node to define initial data\ninputnode = Node(IdentityInterface(fields=['val1', 'val2']), name='inputnode')\ninputnode.inputs.val1 = 10\ninputnode.inputs.val2 = 5\n\n# Function node to perform multiplication\nmultiply_node = Node(Function(input_names=['a', 'b'],\n                              output_names=['result'],\n                              function=simple_multiply),\n                     name='multiply_node')\n\n# Connect the nodes\nwf.connect(inputnode, 'val1', multiply_node, 'a')\nwf.connect(inputnode, 'val2', multiply_node, 'b')\n\n# Run the workflow\ntry:\n    print(f\"Running workflow, output will be in {wf.base_dir}\")\n    # Use 'MultiProc' plugin for local parallel execution\n    wf.run(plugin='MultiProc')\n    print(\"Workflow completed successfully. Check the base_dir for results.\")\nexcept Exception as e:\n    print(f\"Workflow failed: {e}\")","lang":"python","description":"This quickstart demonstrates a basic Nipype workflow that takes two inputs, performs a simple multiplication using a custom Python function wrapped in a `Function` node, and executes the pipeline. Nipype workflows typically generate a working directory (`base_dir`) where intermediate and final results are stored. For complex workflows, consider `DataSink` or inspecting the cache for outputs.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-16","installed_version":"1.10.0","pypi_latest":"1.11.0","is_stale":true,"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":13.1,"avg_import_s":2.9,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":2.76,"mem_mb":36.3,"disk_size":"319.2M"},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":13.1,"import_time_s":2.64,"mem_mb":36.3,"disk_size":"310M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":3.05,"mem_mb":38.4,"disk_size":"345.9M"},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":12.8,"import_time_s":2.86,"mem_mb":38.4,"disk_size":"335M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":3.38,"mem_mb":37.6,"disk_size":"329.0M"},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":12.6,"import_time_s":3.34,"mem_mb":37.6,"disk_size":"318M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":3.18,"mem_mb":38.7,"disk_size":"327.2M"},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":12.7,"import_time_s":3.23,"mem_mb":38.7,"disk_size":"316M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":2.29,"mem_mb":31.5,"disk_size":"308.4M"},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"nipype","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":14.4,"import_time_s":2.25,"mem_mb":31.5,"disk_size":"305M"}]}}