fix: hotfix to context manager

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "api-to-dataframe"
-version = "1.5.1"
+version = "1.5.2"
 description = "A package to convert API responses to pandas dataframe"
 authors = ["IvanildoBarauna <[email protected]>"]
 readme = "README.md"

src/api_to_dataframe/controller/client_builder.py

@@ -38,35 +38,35 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
             error_msg = "endpoint cannot be an empty string"
             logger.error(error_msg)
             telemetry.logs().new_log(
-                msg=error_msg, 
-                tags={"component": "ClientBuilder", "method": "__init__"}, 
+                msg=error_msg,
+                tags={"component": "ClientBuilder", "method": "__init__"},
                 level=40  # ERROR level
             )
             raise ValueError
         if not isinstance(retries, int) or retries < 0:
             error_msg = "retries must be a non-negative integer"
             logger.error(error_msg)
             telemetry.logs().new_log(
-                msg=error_msg, 
-                tags={"component": "ClientBuilder", "method": "__init__"}, 
+                msg=error_msg,
+                tags={"component": "ClientBuilder", "method": "__init__"},
                 level=40  # ERROR level
             )
             raise ValueError
         if not isinstance(initial_delay, int) or initial_delay < 0:
             error_msg = "initial_delay must be a non-negative integer"
             logger.error(error_msg)
             telemetry.logs().new_log(
-                msg=error_msg, 
-                tags={"component": "ClientBuilder", "method": "__init__"}, 
+                msg=error_msg,
+                tags={"component": "ClientBuilder", "method": "__init__"},
                 level=40  # ERROR level
             )
             raise ValueError
         if not isinstance(connection_timeout, int) or connection_timeout < 0:
             error_msg = "connection_timeout must be a non-negative integer"
             logger.error(error_msg)
             telemetry.logs().new_log(
-                msg=error_msg, 
-                tags={"component": "ClientBuilder", "method": "__init__"}, 
+                msg=error_msg,
+                tags={"component": "ClientBuilder", "method": "__init__"},
                 level=40  # ERROR level
             )
             raise ValueError
@@ -77,17 +77,17 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
         self.headers = headers
         self.retries = retries
         self.delay = initial_delay
-        
+
         # Record client initialization metric
         telemetry.metrics().metric_increment(
             name="client.initialization",
             tags={
-                "endpoint": endpoint, 
+                "endpoint": endpoint,
                 "retry_strategy": retry_strategy.name,
                 "connection_timeout": str(connection_timeout)
             }
         )
-        
+
         # Log initialization
         telemetry.logs().new_log(
             msg=f"ClientBuilder initialized with endpoint {endpoint}",
@@ -112,13 +112,14 @@ def get_api_data(self):
         Returns:
             dict: The JSON response from the API as a dictionary.
         """
-        # Use the telemetry spans with context manager
-        with telemetry.traces().span_in_context("get_api_data") as (span, _):
+        # Use the telemetry spans with new API
+        span = telemetry.traces().new_span("get_api_data")
+        try:
             # Add span attributes
             span.set_attribute("endpoint", self.endpoint)
             span.set_attribute("retry_strategy", self.retry_strategy.name)
             span.set_attribute("connection_timeout", self.connection_timeout)
-            
+
             # Log the API request
             telemetry.logs().new_log(
                 msg=f"Making API request to {self.endpoint}",
@@ -129,33 +130,33 @@ def get_api_data(self):
                 },
                 level=20  # INFO level
             )
-            
+
             # Record the start time for response time measurement
             start_time = time.time()
-            
+
             # Make the API request
             response = GetData.get_response(
                 endpoint=self.endpoint,
                 headers=self.headers,
                 connection_timeout=self.connection_timeout,
             )
-            
+
             # Calculate response time
             response_time = time.time() - start_time
-            
+
             # Record response time as histogram
             telemetry.metrics().record_histogram(
                 name="api.response_time",
                 tags={"endpoint": self.endpoint},
                 value=response_time
             )
-            
+
             # Record successful request metric
             telemetry.metrics().metric_increment(
                 name="api.request.success",
                 tags={"endpoint": self.endpoint}
             )
-            
+
             # Log success
             telemetry.logs().new_log(
                 msg=f"API request to {self.endpoint} successful",
@@ -169,7 +170,9 @@ def get_api_data(self):
                 level=20  # INFO level
             )
 
-        return response.json()
+            return response.json()
+        finally:
+            span.end()
 
     @staticmethod
     def api_to_dataframe(response: dict):
@@ -186,11 +189,12 @@ def api_to_dataframe(response: dict):
         Returns:
             DataFrame: A pandas DataFrame containing the data from the API response.
         """
-        # Use telemetry for this operation
-        with telemetry.traces().span_in_context("api_to_dataframe") as (span, _):
+        # Use telemetry with new API
+        span = telemetry.traces().new_span("api_to_dataframe")
+        try:
             response_size = len(response) if isinstance(response, list) else 1
             span.set_attribute("response_size", response_size)
-            
+
             # Log conversion start
             telemetry.logs().new_log(
                 msg="Converting API response to DataFrame",
@@ -202,17 +206,17 @@ def api_to_dataframe(response: dict):
                 },
                 level=20  # INFO level
             )
-            
+
             try:
                 # Convert to dataframe
                 df = GetData.to_dataframe(response)
-                
+
                 # Record metrics
                 telemetry.metrics().metric_increment(
                     name="dataframe.conversion.success",
                     tags={"size": len(df)}
                 )
-                
+
                 # Log success
                 telemetry.logs().new_log(
                     msg="Successfully converted API response to DataFrame",
@@ -224,16 +228,16 @@ def api_to_dataframe(response: dict):
                     },
                     level=20  # INFO level
                 )
-                
+
                 return df
-                
+
             except Exception as e:
                 # Record failure metric
                 telemetry.metrics().metric_increment(
                     name="dataframe.conversion.failure",
                     tags={"error_type": type(e).__name__}
                 )
-                
+
                 # Log error
                 error_msg = f"Failed to convert API response to DataFrame: {str(e)}"
                 telemetry.logs().new_log(
@@ -246,6 +250,8 @@ def api_to_dataframe(response: dict):
                     },
                     level=40  # ERROR level
                 )
-                
+
                 # Re-raise the exception
                 raise
+        finally:
+            span.end()