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examples/SimpleSamples/AskBidACCInfo.py

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+from tradelocker import TLAPI
+import pandas as pd
+from datetime import datetime
+
+# Initialize the TradeLocker API client with your credentials
+tl_api = TLAPI(
+    environment="https://demo.tradelocker.com",
+    username="[email protected]",
+    password="yourpassword",
+    server="yourBrokerPropFirm"
+)
+
+pair = input('Pair: ').strip().upper()
+
+# Get the instrument ID
+pair_id = tl_api.get_instrument_id_from_symbol_name(pair)
+
+# Get price information
+price = tl_api.get_latest_asking_price(pair_id)
+acc_info = tl_api.get_account_state()
+balance = acc_info['balance']
+actual_balance = acc_info['availableFunds']
+ask = tl_api.get_latest_asking_price(pair_id)
+bid = tl_api.get_latest_bid_price(pair_id)
+
+
+def acc_info():
+    print('Pair Price: ', str(price), '\nBalance: ', str(balance), '\nActual Balance: ', actual_balance, '\nAsk: ', str(ask), 'Bid: ', str(bid))
+
+
+def main():
+    acc_info()
+
+if __name__ == "__main__":
+    main()

examples/SimpleSamples/lastCandleInfo.py

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+from tradelocker import TLAPI
+import pandas as pd
+from datetime import datetime
+
+def get_last_candle_details():
+    # Initialize the API client with your credentials
+    tl = TLAPI(environment="https://demo.tradelocker.com",
+               username="[email protected]",
+               password="somepassword",
+               server="yourBrokerProfirm")
+
+    # Specify the instrument you're interested in
+    instrument_name = "BTCUSD"  # Change this to your desired instrument
+
+    # Get the instrument ID
+    instrument_id = tl.get_instrument_id_from_symbol_name(instrument_name)
+
+    # Fetch the price history for the instrument
+    price_history = tl.get_price_history(instrument_id, resolution="1D", start_timestamp=0, end_timestamp=0, lookback_period="5D")
+
+    # Convert the price history to a DataFrame for easier manipulation
+    df = pd.DataFrame(price_history)
+
+    # Rename the first column to 'unix_timestamp_millis' for clarity
+    df.rename(columns={df.columns[0]: 'unix_timestamp_millis'}, inplace=True)
+
+    # Convert the millisecond timestamps to datetime objects
+    df['datetime'] = pd.to_datetime(df['unix_timestamp_millis'], unit='ms')
+
+    # Sort the DataFrame by the new 'datetime' column in descending order
+    df_sorted = df.sort_values(by='datetime', ascending=False)
+
+    # Access the first row of the sorted DataFrame, which should now be the last candle
+    last_candle_row = df_sorted.iloc[0]
+
+    # Extracting the candle details
+    timestamp = last_candle_row['datetime']
+    date_time = timestamp.strftime('%Y-%m-%d %H:%M:%S')  # Format the datetime object as a string
+    open_price = last_candle_row['o']
+    close_price = last_candle_row['c']
+    low_price = last_candle_row['l']
+    high_price = last_candle_row['h']
+
+    return {
+        "Date": date_time,
+        "Time": date_time.split(' ')[1],  # Extract just the time part
+        "Open": open_price,
+        "Close": close_price,
+        "Low": low_price,
+        "High": high_price
+    }
+
+# Print the last candle details
+result = get_last_candle_details()
+if result:
+    print(result)
+else:
+    print("Failed to retrieve the last candle details.")