Improving interface after experiment01 (#30)

* fix: fixes of backwords

* fixing hotel information with image placeholders

* chore: clean up product display in hotel and cleaner interfacing

* adding loader with historical data loading

* feature: cleaning up pipeline

* chore: simple surge pricer

* created new pricing pipeline

* adding a checkout page to both sites

* fix: fixing stale pacakge

* test: we wont be using elasticity anymore so its okay

* chore: cleaning elasticity references

* chore: store sting

* feature: e2e intro pipline surge pricing

* fix: CVE vulnerability patching

experiments/procesing/pricers/base.py

@@ -25,7 +25,7 @@ class PricingFunction(ABC):
     """
 
     @abstractmethod
-    def fit(self, historical_data: pd.DataFrame, **kwargs):
+    def fit(self, *kwargs):
         """
         Offline training on historical data.
 
@@ -36,7 +36,7 @@ class PricingFunction(ABC):
         pass
 
     @abstractmethod
-    def predict(self, state_space) -> np.ndarray:
+    def predict(self, *kwargs) -> np.ndarray:
         """
         Generate optimal prices given current state.