<jupyter_start><jupyter_text>Graph<jupyter_code>edges = pd.read_csv('edge_list.csv')
straight_dist = pd.read_csv('straight_line.csv',header=None,index_col=0,squeeze=True).to_dict()
start_node, end_node = 'A','R'
result = (a_search(edges, straight_dist, start_node, end_node),
          hill_climbing(edges, straight_dist, start_node, end_node),
          greedy_best_first_search(edges, straight_dist, start_node, end_node))
  
print_result(result, start_node, end_node, edges, straight_dist)
start_node, end_node = 'P','R'
result = (a_search(edges, straight_dist, start_node, end_node),
          hill_climbing(edges, straight_dist, start_node, end_node),
          greedy_best_first_search(edges, straight_dist, start_node, end_node))
print_result(result, start_node, end_node, edges, straight_dist)<jupyter_output>################# A* Search #################
==== Traversed Path ====
  node estimated_cost
0    P             65
========== Total Cost (Shortest Path)=============
Path -> Start-Goal: [('P', 'R')]
Cost: 65
{'fraction_non_alphanumeric': 0.1748046875, 'fraction_numerical': 0.005859375, 'mean_word_length': 6.1678321678321675, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 5, 'https://': 0, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '305046', 'license': 'MIT', 'n_tokens_mistral': 360, 'n_tokens_neox': 351, 'n_words': 65, 'path': '15XW87 - Soft Computing Lab/Assignments/2/2.ipynb', 'repo_name': 'aakashhemadri/courses', 'size': '1024'}