From 87a8810eb962a1770b1ef432c13ec1a964c93afe Mon Sep 17 00:00:00 2001
From: Stavros Theocharis <stavrostheocharis@yahoo.gr>
Date: Wed, 14 Feb 2024 16:11:41 +0100
Subject: [PATCH] Generalised args in functions

---
 setup.py                          |  4 ++--
 timepulse/data/data_collection.py | 13 +++++++------
 timepulse/models/lstm.py          |  1 -
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/setup.py b/setup.py
index 81a317b..e66cc3d 100644
--- a/setup.py
+++ b/setup.py
@@ -6,7 +6,7 @@
 setup(
     name="timepulse",
     version="0.2.0",
-    description="A set of tools to help with timeseries flow",
+    description="A set of algorithms to help with timeseries flow",
     long_description=long_description,
     long_description_content_type="text/markdown",
     author="SQUAREDEV BV",
@@ -39,7 +39,7 @@
         "Programming Language :: Python :: 3.11",
     ],
     python_requires=">=3.9",  # Minimum version requirement of the package
-    keywords="timeseries tools ml flow python machine learning",  # Short descriptors for your package
+    keywords="timeseries algorithms ml flow ai python machine learning",  # Short descriptors for your package
     package_data={},
     entry_points={
         "console_scripts": [
diff --git a/timepulse/data/data_collection.py b/timepulse/data/data_collection.py
index 9ffcbff..95ea537 100644
--- a/timepulse/data/data_collection.py
+++ b/timepulse/data/data_collection.py
@@ -5,15 +5,16 @@
 
 
 def fetch_stringency_index(
-    country: Literal["Italy", "Spain"], period: Literal["D", "M"] = "M"
+    country: str, period: Literal["D", "M"] = "M"
 ) -> pd.DataFrame:
     """
     Fetches and processes stringency index data for the specified country and period.
 
     Parameters:
-    - country (Literal["Italy", "Spain"]): The name of the country for which the stringency index data is fetched.
-    - period (Literal["D", "M"], optional): The time period for data resampling, either "D" for daily or "M" for monthly.
-                                             Defaults to "M".
+    - country (str): The name of the country for which the
+    stringency index data is fetched.
+    - period (Literal["D", "M"], optional): The time period for data resampling,
+    either "D" for daily or "M" for monthly. Defaults to "M".
 
     Returns:
     - pd.DataFrame: Processed DataFrame containing the stringency index data with date-wise categories.
@@ -65,14 +66,14 @@ def fetch_stringency_index(
 
 
 def fetch_holidays(
-    years: List, country_code: Literal["IT", "ES"], period: Literal["D", "M"] = "M"
+    years: List[int], country_code: str, period: Literal["D", "M"] = "M"
 ) -> pd.DataFrame:
     """
     Fetches and processes holidays data for the specified country and period.
 
     Parameters:
     - years (List): A list of years for which holidays data is fetched.
-    - country_code (Literal["IT", "ES"]): The country code for the country of interest.
+    - country_code (str): The country code for the country of interest.
     - period (Literal["D", "M"], optional): The time period for data resampling, either "D" for daily or "M" for monthly.
                                              Defaults to "M".
 
diff --git a/timepulse/models/lstm.py b/timepulse/models/lstm.py
index dab6bc6..2ff828b 100644
--- a/timepulse/models/lstm.py
+++ b/timepulse/models/lstm.py
@@ -1,7 +1,6 @@
 from timepulse.utils.models import create_early_stopping
 from timepulse.processing.min_max_scaler import MinMaxScalerWrapper
 import tensorflow as tf
-import pandas as pd
 import numpy as np
 from typing import List, Optional, Tuple, Type