M kovalsky/dynamicdocumentation

.github/workflows/_generate_func_examples.py

@@ -0,0 +1,97 @@
+import inspect
+import os
+import typing
+import sempy_labs
+import sempy_labs.migration
+import sempy_labs.report
+import sempy_labs.directlake
+from sempy_labs.tom import TOMWrapper
+import sempy_labs.lakehouse
+
+dirs = {
+    sempy_labs: 'labs',
+    sempy_labs.directlake: 'directlake',
+    sempy_labs.lakehouse: 'lake',
+    sempy_labs.migration: 'migration',
+    sempy_labs.report: 'rep',
+    TOMWrapper: 'tom',
+}
+
+link_prefix = "https://semantic-link-labs.readthedocs.io/en/stable/"
+tab = '    '
+skip_functions = ['connect_semantic_model', '__init__', 'close']
+
+markdown_example = '## Function Examples\n'
+# Function Examples
+for d, d_alias in dirs.items():
+    d_name = d.__name__   
+    for attr_name in dir(d):
+        attr = getattr(d, attr_name)
+        if inspect.isfunction(attr):
+            if attr_name not in skip_functions:
+                link = f"{link_prefix}{d_name}.html#{d_name}.{attr_name}"
+                if d_alias == 'tom':
+                    link = f"{link_prefix}sempy_labs.{d_alias}.html#sempy_labs.{d_alias}.{d_name}.{attr_name}"
+                sig = inspect.signature(attr)
+                markdown_example += f"\n### [{attr_name}]({link})\n```python"
+                markdown_example += "\nimport sempy_labs as labs"
+                if d_alias == 'tom':
+                    markdown_example += "\nfrom sempy_labs.tom import connect_semantic_model"
+                    tf = 'True'
+                    markdown_example += f"\nwith connect_semantic_model(dataset='', workspace='', readonly={tf}) as tom:"
+                elif d_alias != 'labs':
+                    markdown_example += f"\nimport {d_name} as {d_alias}"
+                func_print = f"{d_alias}.{attr_name}("
+                if d_alias == 'tom':
+                    markdown_example += f"\n{tab}{func_print}"
+                else:
+                    markdown_example += f"\n{func_print}"
+                params = [param for param_name, param in sig.parameters.items() if param_name not in ['kwargs', 'self']]
+                param_count = len(params)
+                for param_name, param in sig.parameters.items():
+                    is_optional = False
+                    if param_name not in ['kwargs', 'self']:
+                        param_value = ''
+                        if param.default != inspect.Parameter.empty:
+                            param_value = param.default
+                            is_optional = True
+                        elif param_name == 'dataset':
+                            param_value = "AdvWorks"
+                        elif param_name in ['email_address', 'user_name']:
+                            param_value = '[email protected]'
+                        elif param_name == 'languages':
+                            param_value = ['it-IT', 'zh-CN']
+                        elif param_name == 'dax_query':
+                            param_value = 'EVALUATE SUMMARIZECOLUMNS("MyMeasure", 1)'
+                        elif param_name == 'column':
+                            param_value = 'tom.model.Tables["Geography"].Columns["GeographyKey"]'
+                        elif param_name in ['object']:
+                            if attr_name in ['row_count', 'total_size', 'used_in_relationships', 'used_in_rls', 'set_translation']:
+                                param_value = 'tom.model.Tables["Sales"]'
+                            elif attr_name in ['records_per_segment']:
+                                param_value = 'tom.model.Tables["Sales"].Partitions["Sales"]'
+                            elif attr_name in ['used_size']:
+                                param_value = 'tom.model.Tables["Geography"].Hierarchies["Geo Hierarchy"]'
+                            elif attr_name in ['fully_qualified_measures']:
+                                param_value = 'tom.model.Tables["Sales"].Measures["Sales Amount"]'
+                        elif param_name == 'dependencies':
+                            param_value = 'labs.get_model_calc_dependencies(dataset=tom._dataset, workspace=tom._workspace)'
+
+                        if param_value not in [None, True, False] and not isinstance(param_value, list) and param_name not in ['object', 'column', 'dependencies']:
+                            param_value = f"'{param_value}'"
+                        p = f"{tab}{param_name}={param_value},"
+                        if is_optional:
+                            p += " # This parameter is optional"
+                        if d_alias == 'tom':
+                            markdown_example += f"\n{tab}{p}"
+                        else:
+                            markdown_example += f"\n{p}"
+                closing = ")\n```\n"
+                if param_count == 0:
+                    markdown_example += closing
+                else:
+                    markdown_example += f"\n{closing}"
+
+output_path = os.path.join('/root/semantic-link-labs', 'function_examples.md')
+with open(output_path, 'w') as f:
+    f.write(markdown_example)