Run list of dates

db_analytics_tools/__init__.py

@@ -7,4 +7,4 @@
 
 from .utils import Client
 
-__version__ = "0.1.4.11"
+__version__ = "0.1.4.12"

db_analytics_tools/integration.py

@@ -32,19 +32,46 @@ def __init__(self, client):
         self.client = client
 
     @staticmethod
-    def generate_date_range(start_date, stop_date=None, freq='d', reverse=False):
+    def generate_date_range(start_date, stop_date=None, freq=None, dates=None, reverse=False, streamlit=False):
         """
         Generate a range of dates.
 
         :param start_date: The start date for the range.
         :param stop_date: The stop date for the range.
         :param freq: The frequency of the dates ('d' for daily, 'm' for monthly).
+        :param dates: A list of dates
         :param reverse: If True, the date range is generated in reverse order (from stop_date to start_date).
+        :param streamlit: If True, use Streamlit for progress updates.01
         :return: A list of formatted date strings.
         """
-        if stop_date is None:
+        a = start_date and (start_date or stop_date) and freq and dates is None # Date Range
+        b = start_date is None and stop_date is None and freq is None and dates # Specific list of dates
+        assert (a and not b) or (not a and b)
+
+        if dates:
+            dates_ranges = dates
+            # Reverse
+            if reverse:  # Recent to Old
+                dates_ranges.sort(reverse=True)
+
+            print(f'Date Range  : From {dates_ranges[0]} to {dates_ranges[-1]}')
+            print(f'Iterations  : {len(dates_ranges)}')
+
+            if streamlit:
+                import streamlit as st
+                st.markdown(f"<p>Date Range  : From {dates_ranges[0]} to {dates_ranges[-1]}</p>", unsafe_allow_html=True)
+                st.markdown(f"<p>Iterations  : {len(dates_ranges)}</p>", unsafe_allow_html=True)
+
+            return dates_ranges
+
+        if start_date and stop_date is None:
             print(f'Date        : {start_date}')
-            print(f'Iterations  : 1')
+            print('Iterations  : 1')
+
+            if streamlit:
+                import streamlit as st
+                st.markdown(f"<p>Date        : {start_date}</p>", unsafe_allow_html=True)
+                st.markdown(f"<p>Iterations  : 1</p>", unsafe_allow_html=True)
 
             return [start_date]
 
@@ -68,23 +95,30 @@ def generate_date_range(start_date, stop_date=None, freq='d', reverse=False):
         print(f'Date Range  : From {dates_ranges[0]} to {dates_ranges[-1]}')
         print(f'Iterations  : {len(dates_ranges)}')
 
+        if streamlit:
+            import streamlit as st
+            st.markdown(f"<p>Date Range  : From {dates_ranges[0]} to {dates_ranges[-1]}</p>", unsafe_allow_html=True)
+            st.markdown(f"<p>Iterations  : {len(dates_ranges)}</p>", unsafe_allow_html=True)
+
         return dates_ranges
 
-    def run(self, function, start_date, stop_date=None, dates=[], freq='d', reverse=False, streamlit=False):
+    def run(self, function, start_date=None, stop_date=None, freq=None, dates=None, reverse=False, streamlit=False):
         """
         Run a specified SQL function for a range of dates.
 
         :param function: The SQL function to run for each date.
         :param start_date: The start date for the range.
         :param stop_date: The stop date for the range.
+        :param dates: A list of dates
         :param freq: The frequency of the dates ('d' for daily, 'm' for monthly).
+        :param dates: A list of dates
         :param reverse: If True, the date range is generated in reverse order (from stop_date to start_date).
         :param streamlit: If True, use Streamlit for progress updates.
         """
-        print(f'Function    : {function}')
-
         # Generate Dates Range
-        dates_ranges = self.generate_date_range(start_date, stop_date, freq, reverse)
+        dates_ranges = self.generate_date_range(start_date, stop_date, freq, dates, reverse, streamlit)
+
+        print(f'Function    : {function}')
 
         # Send query to the server
         for date in dates_ranges:
@@ -110,77 +144,28 @@ def run(self, function, start_date, stop_date=None, dates=[], freq='d', reverse=
                 st.markdown(f"<span style='font-weight: bold;'>Execution time: {duration}</span>",
                             unsafe_allow_html=True)
 
-    def run_dates(self, functions, dates, reverse=False, streamlit=False):
-        """
-        Run multiple specified SQL functions for a range of dates.
-
-        :param functions: A list of SQL functions to run for each date.
-        :param dates: A list of dates
-        :param reverse: If True, the date range is generated in reverse order (from stop_date to start_date).
-        :param streamlit: If True, use Streamlit for progress updates.
-        """
-        print(f'Functions   : {functions}')
-
-        # Compute MAX Length of functions (Adjust display)
-        max_fun = max(len(function) for function in functions)
-
-        # Generate Dates Range
-        dates_ranges = dates
-        if reverse:
-            dates_ranges = list(reversed(dates_ranges))
-
-        ##
-        print(f'Iterations  : {len(dates_ranges)}')
-
-        # Send query to the server
-        for date in dates_ranges:
-            # Show date separator line
-            print("*" * (NBCHAR + max_fun))
-            for function in functions:
-                print(f"[Running Date: {date}] [Function: {function.ljust(max_fun, '.')}] ", end="", flush=True)
-                if streamlit:
-                    import streamlit as st
-                    st.markdown(
-                        f"<span style='font-weight: bold;'>[Running Date: {date}] [Function: {function}] </span>",
-                        unsafe_allow_html=True)
-
-                query = f"select {function}('{date}'::date);"
-                duration = datetime.datetime.now()
-
-                try:
-                    self.client.execute(query)
-                except Exception as e:
-                    raise Exception("Something went wrong!")
-                # finally:
-                #     self.client.close()
-
-                duration = datetime.datetime.now() - duration
-                print(f"Execution time: {duration}")
-                if streamlit:
-                    st.markdown(f"<span style='font-weight: bold;'>Execution time: {duration}</span>",
-                                unsafe_allow_html=True)
-
-        # Show final date separator line
-        print("*" * (NBCHAR + max_fun))
-
-    def run_multiple(self, functions, start_date, stop_date=None, dates=[], freq='d', reverse=False, streamlit=False):
+    def run_multiple(self, functions, start_date=None, stop_date=None, freq=None, dates=None, reverse=False, streamlit=False):
         """
         Run multiple specified SQL functions for a range of dates.
 
         :param functions: A list of SQL functions to run for each date.
         :param start_date: The start date for the range.
         :param stop_date: The stop date for the range.
         :param freq: The frequency of the dates ('d' for daily, 'm' for monthly).
+        :param dates: A list of dates
         :param reverse: If True, the date range is generated in reverse order (from stop_date to start_date).
         :param streamlit: If True, use Streamlit for progress updates.
         """
+        # Generate Dates Range
+        dates_ranges = self.generate_date_range(start_date, stop_date, freq, dates, reverse, streamlit)
+
         print(f'Functions   : {functions}')
 
         # Compute MAX Length of functions (Adjust display)
         max_fun = max(len(function) for function in functions)
 
         # Generate Dates Range
-        dates_ranges = self.generate_date_range(start_date, stop_date, freq, reverse)
+        dates_ranges = self.generate_date_range(start_date, stop_date, freq, dates, reverse)
 
         # Send query to the server
         for date in dates_ranges:
@@ -214,7 +199,7 @@ def run_multiple(self, functions, start_date, stop_date=None, dates=[], freq='d'
         print("*" * (NBCHAR + max_fun))
 
 
-def create_etl(host, port, database, username, password, engine):
+def create_etl(host, port, database, username, password, engine, keep_connection):
     """
     Create an ETL (Extract, Transform, Load) instance with the specified database connection parameters.
 
@@ -224,13 +209,16 @@ def create_etl(host, port, database, username, password, engine):
     :param username: The username for authenticating the database connection.
     :param password: The password for authenticating the database connection.
     :param engine: The database engine to use, currently supports 'postgres' and 'sqlserver'.
+    :param keep_connection: If True, the connection will be maintained until explicitly closed. If False, the connection
+                           will be opened and closed for each database operation (default is False).
     :return: An ETL instance for performing data extraction, transformation, and loading.
     """
     client = Client(host=host,
                     port=port,
                     database=database,
                     username=username,
                     password=password,
-                    engine=engine)
+                    engine=engine,
+                    keep_connection=keep_connection)
     etl = ETL(client)
     return etl

requirements.txt

@@ -1,6 +1,6 @@
-psycopg2-binary==2.9.7
-pyodbc==4.0.39
-pandas==2.0.3
-SQLAlchemy==2.0.20
-streamlit==1.26.0
-matplotlib
+psycopg2-binary>=2.9.9
+pyodbc>=5.1.0
+pandas>=2.2.1
+SQLAlchemy>=2.0.29
+streamlit>=1.32.2
+matplotlib>=3.8.3

setup.py

@@ -7,7 +7,7 @@
 
 setup(
     name="db_analytics_tools",
-    version="0.1.4.11",
+    version="0.1.4.12",
     url="https://josephkonka.com/#projects",
     download_url="https://github.com/joekakone/db-analytics-tools",
     project_urls={
@@ -23,13 +23,13 @@
     long_description=long_description,
     long_description_content_type="text/markdown",
     install_requires=[
-        "psycopg2-binary",
-        "pyodbc",
-        "pandas",
-        "SQLAlchemy",
-        "streamlit",
-        "matplotlib"
+        "psycopg2-binary>=2.9.9",
+        "pyodbc>=5.1.0",
+        "pandas>=2.2.1",
+        "SQLAlchemy>=2.0.29",
+        "streamlit>=1.32.2",
+        "matplotlibmatplotlib>=3.8.3"
     ],
     python_requires=">=3.6",
     packages=find_packages()
-)
+)