feature: remove otel-wrapper and increase unittests

Author: IvanildoBarauna

CLAUDE.md

@@ -0,0 +1,25 @@
+# API-TO-DATAFRAME DEVELOPMENT GUIDE
+
+## Build & Test Commands
+- Setup: `poetry install`
+- Run all tests: `poetry run pytest`
+- Run single test: `poetry run pytest tests/test_file.py::test_function`
+- Coverage: `poetry run coverage run -m pytest && poetry run coverage report`
+- Lint: `poetry run pylint src/`
+- Format: `poetry run black src/ tests/`
+
+## Code Style Guidelines
+- Use Python 3.9+ features
+- Import order: stdlib → third-party → local
+- Type hints required for function parameters and return values
+- Follow black formatting (max line length 88)
+- Variable naming: snake_case for variables/functions, PascalCase for classes
+- Error handling: use try/except with specific exceptions, log errors
+- Use f-strings for string formatting
+- Test coverage target: 90%+
+- Use dataclasses or typed dictionaries for structured data
+
+## Architecture
+- MVC-like pattern: controllers, models, utils
+- Core functionality in models package
+- Client interactions in controller package

poetry.lock

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "api-to-dataframe"
-version = "1.5.2"
+version = "2.0.0"
 description = "A package to convert API responses to pandas dataframe"
 authors = ["IvanildoBarauna <[email protected]>"]
 readme = "README.md"
@@ -27,7 +27,6 @@ python = "^3.9"
 pandas = "^2.2.3"
 requests = "^2.32.3"
 logging = "^0.4.9.6"
-otel-wrapper = "^0.1.1"
 
 [tool.poetry.group.dev.dependencies]
 poetry-dynamic-versioning = "^1.3.0"

pyproject.toml

@@ -1,7 +1,6 @@
 from api_to_dataframe.models.retainer import retry_strategies, Strategies
 from api_to_dataframe.models.get_data import GetData
-from api_to_dataframe.utils.logger import logger, telemetry
-import time
+from api_to_dataframe.utils.logger import logger
 
 
 class ClientBuilder:
@@ -37,38 +36,18 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
         if endpoint == "":
             error_msg = "endpoint cannot be an empty string"
             logger.error(error_msg)
-            telemetry.logs().new_log(
-                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__"},
-                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__"},
-                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__"},
-                level=40  # ERROR level
-            )
             raise ValueError
 
         self.endpoint = endpoint
@@ -78,28 +57,6 @@ def __init__(  # pylint: disable=too-many-positional-arguments,too-many-argument
         self.retries = retries
         self.delay = initial_delay
 
-        # Record client initialization metric
-        telemetry.metrics().metric_increment(
-            name="client.initialization",
-            tags={
-                "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}",
-            tags={
-                "endpoint": endpoint,
-                "retry_strategy": retry_strategy.name,
-                "connection_timeout": str(connection_timeout),
-                "component": "ClientBuilder"
-            },
-            level=20  # INFO level
-        )
-
     @retry_strategies
     def get_api_data(self):
         """
@@ -112,67 +69,13 @@ def get_api_data(self):
         Returns:
             dict: The JSON response from the API as a dictionary.
         """
-        # 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}",
-                tags={
-                    "endpoint": self.endpoint,
-                    "component": "ClientBuilder",
-                    "method": "get_api_data"
-                },
-                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",
-                tags={
-                    "endpoint": self.endpoint,
-                    "response_status": response.status_code,
-                    "response_time": response_time,
-                    "component": "ClientBuilder",
-                    "method": "get_api_data"
-                },
-                level=20  # INFO level
-            )
+        response = GetData.get_response(
+            endpoint=self.endpoint,
+            headers=self.headers,
+            connection_timeout=self.connection_timeout,
+        )
 
-            return response.json()
-        finally:
-            span.end()
+        return response.json()
 
     @staticmethod
     def api_to_dataframe(response: dict):
@@ -189,69 +92,4 @@ def api_to_dataframe(response: dict):
         Returns:
             DataFrame: A pandas DataFrame containing the data from the API response.
         """
-        # 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",
-                tags={
-                    "response_size": response_size,
-                    "response_type": type(response).__name__,
-                    "component": "ClientBuilder",
-                    "method": "api_to_dataframe"
-                },
-                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",
-                    tags={
-                        "dataframe_rows": len(df),
-                        "dataframe_columns": len(df.columns),
-                        "component": "ClientBuilder",
-                        "method": "api_to_dataframe"
-                    },
-                    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(
-                    msg=error_msg,
-                    tags={
-                        "error": str(e),
-                        "error_type": type(e).__name__,
-                        "component": "ClientBuilder",
-                        "method": "api_to_dataframe"
-                    },
-                    level=40  # ERROR level
-                )
-
-                # Re-raise the exception
-                raise
-        finally:
-            span.end()
+        return GetData.to_dataframe(response)