[V2]Add Script for metrics markdown table

scripts/metrics-md.py

@@ -0,0 +1,101 @@
+import json
+import json
+
+
+def generate_markdown_table(metrics, title):
+    """
+    Generates a markdown table for the given metrics.
+
+    Args:
+        metrics (dict): The dictionary of metrics.
+        title (str): The title of the metrics group.
+
+    Returns:
+        str: The generated markdown table as a string.
+    """
+    table = f"### {title}\n\n"
+    table += "| Metric Name | Inner Parameters |\n"
+    table += "|-------------|------------------|\n"
+
+    for metric_name, inner_params in metrics.items():
+        # Extract the keys of the inner parameters, if any
+        inner_keys = ', '.join(inner_params.keys()) if inner_params else ''
+        table += f"| {metric_name} | {inner_keys} |\n"
+
+    return table
+
+def generate_spans_markdown_table(v1_spans, v2_spans):
+    """
+    Generates a markdown table specifically for spans metrics with two main columns V1 and V2.
+
+    Args:
+        v1_spans (dict): The dictionary of V1 spans metrics.
+        v2_spans (dict): The dictionary of V2 spans metrics.
+
+    Returns:
+        str: The generated markdown table as a string.
+    """
+    table = "### Equivalent Metrics\n\n"
+    table += "| V1 Metric | V1 Parameters | V2 Metric | V2 Parameters |\n"
+    table += "|-----------|---------------|-----------|---------------|\n"
+
+    # Get the maximum length of the spans to align the table rows
+    max_len = max(len(v1_spans), len(v2_spans))
+
+    # Iterate through the metrics using zip_longest to handle mismatched lengths
+    from itertools import zip_longest
+
+    for (v1_metric, v1_params), (v2_metric, v2_params) in zip_longest(v1_spans.items(), v2_spans.items(), fillvalue=('', {})):
+        v1_inner_keys = ', '.join(v1_params.keys()) if v1_params else ''
+        v2_inner_keys = ', '.join(v2_params.keys()) if v2_params else ''
+        table += f"| {v1_metric} | {v1_inner_keys} | {v2_metric} | {v2_inner_keys} |\n"
+
+    return table
+
+class Convert_Json():
+
+    def __init__(self, json_fp, h1):
+        self.fp = json_fp
+        self.h1 = h1
+        self.jdata = self.get_json()
+        self.mddata = self.format_json_to_md()
+
+    def get_json(self):
+        with open(self.fp) as f:
+            res = json.load(f)
+        return res
+
+    def format_json_to_md(self):
+        text = f'# {self.h1}\n'
+        dct = self.jdata
+        print(dct)
+        common_metrics_table = generate_markdown_table(dct["common_metrics"], "Common Metrics")
+        v1_metrics_table = generate_markdown_table(dct["v1_only_metrics"], "V1 Only Metrics")
+        v2_metrics_table = generate_markdown_table(dct["v2_only_metrics"], "V2 Only Metrics")
+
+
+        filtered_v1_metrics = {}
+        for metric, params in dct["v1_only_metrics"].items():
+           if "jaeger_collector_spans_rejected_total" in metric:
+                filtered_v1_metrics[metric] = params
+
+        filtered_v2_metrics = {}
+        for metric, params in dct["v2_only_metrics"].items():
+           if "receiver_refused_spans" in metric:
+               filtered_v2_metrics[metric] = params
+        spans_metrics_table = generate_spans_markdown_table(filtered_v1_metrics, filtered_v2_metrics)
+
+        text=common_metrics_table+v1_metrics_table+v2_metrics_table+spans_metrics_table
+        return text
+
+    def convert_dict_to_md(self, output_fn):
+        with open(output_fn, 'w') as writer:
+            writer.writelines(self.mddata)
+        print('Dict successfully converted to md')
+
+
+# Convert the JSON generated by compare_metrics.py to markdown
+fn = 'differences.json'
+title = "TITLE"
+converter = Convert_Json(fn, title)
+converter.convert_dict_to_md(output_fn='metrics.md')