add some cool badges to README

Author: cezary.maszczyk

.gitignore

@@ -292,4 +292,7 @@ doc/build/html/.buildinfo
 RELEASE_INSTRUCTION.md
 
 notebooks/
-classification_tabular_datasets/
+classification_tabular_datasets/
+.coverage
+junit.xml
+reports/

README.md

@@ -1,5 +1,12 @@
+[![Coverage Status](./badges/coverage-badge.svg?dummy=8484744)](./reports/coverage/index.html)
+[![Tests Status](./badges/test-badge.svg?dummy=8484744)](./reports/junit/report.html)
+[![Flake8 Status](./badges/flake8-badge.svg?dummy=8484744)](./reports/flake8/index.html)
+![PyPI](https://img.shields.io/pypi/v/rulekit?label=pypi%20package)
+![PyPI - Downloads](https://img.shields.io/pypi/dm/rulekit)
+
 # Rulekit
- 
+
+
 This package is python wrapper for [RuleKit](https://github.com/adaa-polsl/RuleKit) library - a versatile tool for rule learning. 
 
 Based on a sequential covering induction algorithm, it is suitable for classification, regression, and survival problems.

badges/coverage-badge.svg

@@ -46,3 +46,31 @@ make.bat`
     >
     </li>
 ```
+
+### 3. Update badges
+
+In repo root directory:
+
+1. Update coverage badge
+```bash
+python -m coverage run -m unittest discover ./tests 
+python -m coverage xml -o ./reports/coverage/coverage.xml  
+python -m coverage html -d ./reports/coverage/
+genbadge coverage -i ./reports/coverage/coverage.xml  -o ./badges/coverage-badge.svg
+```
+
+2. Update test badge
+
+```bash
+mkdir ./reports/junit
+python -m junitxml.main --o ./reports/junit/junit.xml
+
+genbadge tests -o ./badges/test-badge.svg
+```
+
+3. Update flake8 badge
+
+```bash
+flake8 ./rulekit --exit-zero --format=html --htmldir ./reports/flake8 --statistics --tee --output-file ./reports/flake8/flake8stats.txt
+genbadge flake -o ./badges/flake8-badge.svg
+```

badges/flake8-badge.svg

@@ -1,2 +1,5 @@
 pre-commit
-autopep8
+autopep8
+genbadge[all]
+coverage
+junitxml

badges/test-badge.svg

@@ -1,2 +1,4 @@
 # pylint: disable=missing-module-docstring
-from .main import RuleKit
+from .main import RuleKit  # pylint: disable=unused-import
+
+RuleKit

doc/HOW_TO_DEPLOY.md

@@ -1,5 +1,5 @@
-"""Module containing class for running experiments using legacy Java RuleKit CLI. For more
-details see  `documentation \
+"""Module containing class for running experiments using legacy
+Java RuleKit CLI. For more details see  `documentation \
 <https://github.com/adaa-polsl/RuleKit/wiki/7-Library-API#71-running-an-experiment
 """
 from jpype import JClass

requirements-dev.txt

@@ -1,12 +1,17 @@
 """Contains helper functions and classes
 """
 import io
-from typing import Any, Union
+from typing import Any
+from typing import Union
 
 import numpy as np
 import pandas as pd
-from jpype import JArray, JClass, JObject, java
-from jpype.pickle import JPickler, JUnpickler
+from jpype import JArray
+from jpype import java
+from jpype import JClass
+from jpype import JObject
+from jpype.pickle import JPickler
+from jpype.pickle import JUnpickler
 
 from .main import RuleKit
 from .params import Measures
@@ -17,7 +22,8 @@ def get_rule_generator(expert: bool = False) -> Any:
     """Factory for Java RuleGenerator class object
 
     Args:
-        expert (bool, optional): Whether expert induction is enables. Defaults to False.
+        expert (bool, optional): Whether expert induction is enables.
+         Defaults to False.
 
     Returns:
         Any: RuleGenerator instance
@@ -124,8 +130,8 @@ def make(
         Args:
             X (Union[pd.DataFrame, np.ndarray]): Data
             y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.
-            survival_time_attribute (str, optional): Name of survival time attribute. 
-            Defaults to None.
+            survival_time_attribute (str, optional): Name of survival time attribute.
+             Defaults to None.
             contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.
 
         Returns:
@@ -327,7 +333,7 @@ def map_to_numerical(predicted_example_set: JObject, remap: bool = True) -> np.n
             for i in range(predicted_example_set.size())
         ])
 
-    @ staticmethod
+    @staticmethod
     def map_survival(predicted_example_set) -> np.ndarray:
         """Maps survival models predictions to numpy array. Used as alternative to `map` method
         used in survival analysis
@@ -359,7 +365,7 @@ def map_survival(predicted_example_set) -> np.ndarray:
             estimators.append(estimator)
         return np.array(estimators)
 
-    @ staticmethod
+    @staticmethod
     def _get_column_by_role(predicted_example_set: JObject, role: str) -> JObject:
         return predicted_example_set.getAttributes().getColumnByRole(role)
 
@@ -368,7 +374,7 @@ class ModelSerializer:
     """Class for serializing models
     """
 
-    @ staticmethod
+    @staticmethod
     def serialize(real_model: object) -> bytes:
         """Serialize Java ruleset object.
 
@@ -381,7 +387,7 @@ def serialize(real_model: object) -> bytes:
         in_memory_file.close()
         return serialized_bytes
 
-    @ staticmethod
+    @staticmethod
     def deserialize(serialized_bytes: bytes) -> object:
         """Deserialize Java ruleset object from bytes.
 

rulekit/__init__.py

@@ -2,18 +2,24 @@
 """
 from __future__ import annotations
 
-from typing import Any, Optional, Union
+from typing import Any
+from typing import Optional
+from typing import Union
 
 import numpy as np
 import pandas as pd
 from pydantic import BaseModel
 
-from ._helpers import (ExampleSetFactory, ModelSerializer,
-                       PredictionResultMapper, RuleGeneratorConfigurator,
-                       get_rule_generator)
-from .events import RuleInductionProgressListener, command_listener_factory
+from ._helpers import ExampleSetFactory
+from ._helpers import get_rule_generator
+from ._helpers import ModelSerializer
+from ._helpers import PredictionResultMapper
+from ._helpers import RuleGeneratorConfigurator
+from .events import command_listener_factory
+from .events import RuleInductionProgressListener
 from .main import RuleKit
-from .rules import Rule, RuleSet
+from .rules import Rule
+from .rules import RuleSet
 
 Data = Union[np.ndarray, pd.DataFrame, list]
 
@@ -136,8 +142,8 @@ def get_coverage_matrix(self, values: Data) -> np.ndarray:
         -------
         coverage_matrix : np.ndarray
             Each row of the matrix represent single example from dataset and every column represent
-            on rule from rule set. Value 1 in the matrix cell means that rule covered certain 
-            example, value 0 means that it doesn't.
+            on rule from rule set. Value 1 in the matrix cell means that rule covered certain
+             example, value 0 means that it doesn't.
         """
         if self.model is None:
             raise ValueError(
@@ -156,8 +162,8 @@ def get_coverage_matrix(self, values: Data) -> np.ndarray:
         return np.array(result)
 
     def add_event_listener(self, listener: RuleInductionProgressListener):
-        """Add event listener object to the operator which allows to monitor 
-        rule induction progress.
+        """Add event listener object to the operator which allows to monitor
+         rule induction progress.
 
         Example:
             >>> from rulekit.events import RuleInductionProgressListener