<jupyter_start><jupyter_text>Install Kubeflow Pipelines SDK<jupyter_code>!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.3/kfp.tar.gz --upgrade<jupyter_output><empty_output><jupyter_text>Import required library<jupyter_code>import kfp
from kfp import compiler
from kubernetes import client as k8s_client<jupyter_output><empty_output><jupyter_text>Import pipeline definition<jupyter_code>from cs_pipeline import github_code_index_update<jupyter_output><empty_output><jupyter_text>Create an experiment first<jupyter_code>client = kfp.Client()
exp = client.create_experiment(name='code-search-25')
# Compile it into a tar package.
compiler.Compiler().compile(github_code_index_update, 'github_code_index_update.tar.gz')

# Submit a run.
# inputs - experiment id, run name, tarball file
run = client.run_pipeline(exp.id, 'code-search-index-update', 'github_code_index_update.tar.gz')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1064516129032258, 'fraction_numerical': 0.007526881720430108, 'mean_word_length': 8.904255319148936, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '651760', 'license': 'Apache-2.0', 'n_tokens_mistral': 326, 'n_tokens_neox': 321, 'n_words': 53, 'path': 'code_search/pipeline/CodeSearchPipelineNotebook.ipynb', 'repo_name': 'larrydisdog/examples', 'size': '930'}