Convert dot-separated values to Go struct using Python

import pandas as pd def convert_to_dict(data): result = {} for row in data: current_dict = result for item in row[:-1]: if item is not none: if item not in current_dict: current_dict[item] = {} current_dict = current_dict[item] return result def extract_json_key(yaml_key): if isinstance(yaml_key, str) and '.' in yaml_key: return yaml_key.split('.')[-1] else: return yaml_key def add_fields_to_struct(struct_string,go_var,go_type,json_key,toml_key): struct_string += str(go_var) + " " + str(go_type) + ' `json:"' + str(json_key) + ',omitempty" toml:"' +str(toml_key) + '"` ' + "\n" return struct_string def generate_go_struct(struct_name, struct_data): struct_name="configurations" if struct_name == "" else struct_name struct_string = "type " + struct_name + " struct {\n" yaml_key=df['yaml_key'].str.split('.').str[-1] # base case: generate fields for the current struct level for key, value in struct_data.items(): selected_rows = df[yaml_key == key] if len(selected_rows) > 1: go_var = selected_rows['go_var'].values[1] toml_key = selected_rows['toml_key'].values[1] go_type=selected_rows['go_type'].values[1] json_key=selected_rows['json_key'].values[1] else: go_var = selected_rows['go_var'].values[0] toml_key = selected_rows['toml_key'].values[0] go_type=selected_rows['go_type'].values[0] json_key=selected_rows['json_key'].values[0] # add fields to the body of the struct struct_string=add_fields_to_struct(struct_string,go_var,go_type,json_key,toml_key) struct_string += "}\n\n" # recursive case: generate struct definitions for nested structs for key, value in struct_data.items(): selected_rows = df[yaml_key == key] if len(selected_rows) > 1: go_var = selected_rows['go_var'].values[1] else: go_var = selected_rows['go_var'].values[0] if isinstance(value, dict) and any(isinstance(v, dict) for v in value.values()): nested_struct_name = go_var nested_struct_data = value struct_string += generate_go_struct(nested_struct_name, nested_struct_data) return struct_string # read excel csv_file = "~/downloads/my_configs.csv" df = pd.read_csv(csv_file) # remove rows where all columns are nan df = df.dropna(how='all') # create the 'json_key' column using the custom function df['json_key'] = df['yaml_key'].apply(extract_json_key) data=df['yaml_key'].values.tolist() # read the 'yaml_key' column data = pd.dataframe({'column':data}) # convert to dataframe data=data['column'].str.split('.', expand=true) # split by '.' nested_list = data.values.tolist() # convert to nested list data=nested_list result_json = convert_to_dict(data) # convert to dict (json) # the generated co code go_struct = generate_go_struct("", result_json) # write to file file_path = "output.go" with open(file_path, "w") as file: file.write(go_struct)

authentication.authenticator.basic authentication.authenticator.basic.parameters authentication.authenticator.basic.parameters.showAuthFailureReason authentication.authenticator.basic.parameters.showAuthFailureReasonOnLoginPage authentication.authenticator.totp authentication.authenticator.totp.parameters authentication.authenticator.totp.parameters.showAuthFailureReason authentication.authenticator.totp.parameters.showAuthFailureReasonOnLoginPage authentication.authenticator.totp.parameters.encodingMethod authentication.authenticator.totp.parameters.timeStepSize

import pandas as pd from collections import deque structs=[] class TreeNode: def __init__(self, name): self.name = name self.children = [] self.path="" def add_child(self, child): self.children.append(child) def create_tree(data): root = TreeNode('') for item in data: node = root for name in item.split('.'): existing_child = next((child for child in node.children if child.name == name), None) if existing_child: node = existing_child else: new_child = TreeNode(name) node.add_child(new_child) node = new_child return root def generate_go_struct(struct_data): struct_name = struct_data['struct_name'] fields = struct_data['fields'] go_struct = f"type {struct_name} struct {{\n" for field in fields: field_name = field['name'] field_type = field['type'] field_default_val = str(field['default_val']) json_key=field['json_key'] toml_key=field['toml_key'] tail_part=f"\t{field_name} {field_type} `json:\"{json_key},omitempty\" toml:\"{toml_key}\"`\n\n" if pd.isna(field['default_val']): go_struct += tail_part else: field_default_val = "\t// +kubebuilder:default:=" + field_default_val go_struct += field_default_val + "\n" + tail_part go_struct += "}\n\n" return go_struct def write_go_file(go_structs, file_path): with open(file_path, 'w') as file: for go_struct in go_structs: file.write(go_struct) def create_new_struct(struct_name): struct_name = "Configurations" if struct_name == "" else struct_name struct_dict = { "struct_name": struct_name, "fields": [] } return struct_dict def add_field(struct_dict, field_name, field_type,default_val,json_key, toml_key): field_dict = { "name": field_name, "type": field_type, "default_val": default_val, "json_key":json_key, "toml_key":toml_key } struct_dict["fields"].append(field_dict) return struct_dict def traverse_tree(root): queue = deque([root]) while queue: node = queue.popleft() filtered_df = df[df['yaml_key'] == node.path] go_var = filtered_df['go_var'].values[0] if not filtered_df.empty else None go_type = filtered_df['go_type'].values[0] if not filtered_df.empty else None if node.path=="": go_type="Configurations" # The structs themselves current_struct = create_new_struct(go_type) for child in node.children: if (node.name!=""): child.path=node.path+"."+child.name else: child.path=child.name filtered_df = df[df['yaml_key'] == child.path] go_var = filtered_df['go_var'].values[0] if not filtered_df.empty else None go_type = filtered_df['go_type'].values[0] if not filtered_df.empty else None default_val = filtered_df['default_val'].values[0] if not filtered_df.empty else None # Struct fields json_key = filtered_df['yaml_key'].values[0].split('.')[-1] if not filtered_df.empty else None toml_key = filtered_df['toml_key'].values[0].split('.')[-1] if not filtered_df.empty else None current_struct = add_field(current_struct, go_var, go_type,default_val,json_key, toml_key) if (child.children): # Add each child to the queue for processing queue.append(child) go_struct = generate_go_struct(current_struct) # print(go_struct,"\n") structs.append(go_struct) write_go_file(structs, "output.go") csv_file = "~/Downloads/my_configs.csv" df = pd.read_csv(csv_file) sample_data=df['yaml_key'].values.tolist() # Create the tree tree = create_tree(sample_data) # Traverse the tree traverse_tree(tree)