diff --git a/examples/rest/bulk_aggs_downloader.py b/examples/rest/bulk_aggs_downloader.py
new file mode 100644
index 00000000..c5c6099e
--- /dev/null
+++ b/examples/rest/bulk_aggs_downloader.py
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+import datetime
+import concurrent.futures
+import logging
+from polygon import RESTClient
+import signal
+import sys
+import pickle
+import lz4.frame  # type: ignore
+
+"""
+This script performs the following tasks:
+
+1. Downloads aggregated market data (referred to as 'aggs') for specific stock symbols using the Polygon API.
+2. Handles data for multiple dates and performs these operations in parallel to improve efficiency.
+3. Saves the downloaded data in a compressed format (LZ4) using Python's pickle serialization.
+4. Utilizes logging to track its progress and any potential errors.
+5. Designed to be interruptible: listens for a Ctrl+C keyboard interrupt and exits gracefully when detected.
+
+Usage:
+1. pip install lz4
+2. Set your Polygon API key in the environment variable 'POLYGON_API_KEY'.
+3. Specify the date range and stock symbols you are interested in within the script.
+4. Run the script.
+
+The script will create compressed '.pickle.lz4' files containing the aggs for each specified stock symbol and date.
+
+Note: This script is designed to be compatible with a data reader script, such as 'bulk_aggs_reader.py'.
+"""
+
+# Set up logging
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(message)s")
+
+
+def signal_handler(sig, frame):
+    print("You pressed Ctrl+C!")
+    sys.exit(0)
+
+
+signal.signal(signal.SIGINT, signal_handler)
+
+
+def get_aggs_for_symbol_and_date(symbol_date_pair):
+    """Retrieve aggs for a given symbol and date"""
+    symbol, date = symbol_date_pair
+    aggs = []
+    client = RESTClient(trace=True)  # Uses POLYGON_API_KEY environment variable
+
+    for a in client.list_aggs(
+        symbol,
+        1,
+        "minute",
+        date,
+        date,
+        limit=50000,
+    ):
+        aggs.append(a)
+
+    print(len(aggs))
+
+    filename = f"{symbol}-aggs-{date}.pickle.lz4"
+    with open(filename, "wb") as file:
+        try:
+            compressed_data = lz4.frame.compress(pickle.dumps(aggs))
+            file.write(compressed_data)
+        except TypeError as e:
+            print(f"Serialization Error: {e}")
+
+    logging.info(f"Downloaded aggs for {date} and saved to {filename}")
+
+
+def weekdays_between(start_date, end_date):
+    """Generate all weekdays between start_date and end_date"""
+    day = start_date
+    while day <= end_date:
+        if day.weekday() < 5:  # 0-4 denotes Monday to Friday
+            yield day
+        day += datetime.timedelta(days=1)
+
+
+def main():
+    start_date = datetime.date(2023, 8, 1)
+    end_date = datetime.date(2023, 8, 31)
+
+    symbols = ["TSLA", "AAPL", "HCP", "GOOG"]  # The array of symbols you want
+
+    dates = list(weekdays_between(start_date, end_date))
+
+    # Generate a list of (symbol, date) pairs
+    symbol_date_pairs = [(symbol, date) for symbol in symbols for date in dates]
+
+    # Use ThreadPoolExecutor to download data in parallel
+    with concurrent.futures.ThreadPoolExecutor(max_workers=50) as executor:
+        executor.map(get_aggs_for_symbol_and_date, symbol_date_pairs)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/rest/bulk_aggs_reader.py b/examples/rest/bulk_aggs_reader.py
new file mode 100644
index 00000000..fcc91915
--- /dev/null
+++ b/examples/rest/bulk_aggs_reader.py
@@ -0,0 +1,57 @@
+import lz4.frame  # type: ignore
+import pickle
+import datetime
+
+"""
+This script performs the following tasks:
+
+1. Reads aggregated market data ('aggs') for a specific stock symbol for multiple dates.
+2. Data is read from compressed (LZ4) and pickled files, which should have been generated by a separate data downloading script.
+3. Displays the read data to the console.
+4. Handles exceptions gracefully: informs the user if a file for a specific date was not found or if any other error occurred.
+
+Usage:
+1. pip install lz4
+2. Ensure that the compressed '.pickle.lz4' files for the specified stock symbol and date range exist in the same directory as this script.
+3. Modify the date range and stock symbol in the script as per your requirements.
+4. Run the script.
+
+The script will read and display the market data for each specified date and stock symbol.
+
+Note: This script is designed to be compatible with files generated by a data downloading script, such as 'bulk_aggs_downloader.py'.
+"""
+
+
+def read_trades_for_date(symbol, date):
+    """Reads trades for a given symbol and date, then prints them."""
+
+    # Construct the filename, similar to your writer script
+    filename = f"{symbol}-aggs-{date}.pickle.lz4"
+
+    try:
+        with open(filename, "rb") as file:
+            compressed_data = file.read()
+            trades = pickle.loads(lz4.frame.decompress(compressed_data))
+            print(trades)
+            return trades
+    except FileNotFoundError:
+        print(f"No file found for {date}")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+
+def main():
+    start_date = datetime.date(2023, 8, 1)
+    end_date = datetime.date(2023, 8, 31)
+    symbol = "HCP"
+
+    # Loop through each weekday between the start and end dates and read the trades
+    day = start_date
+    while day <= end_date:
+        if day.weekday() < 5:  # 0-4 denotes Monday to Friday
+            read_trades_for_date(symbol, day)
+        day += datetime.timedelta(days=1)
+
+
+if __name__ == "__main__":
+    main()