diff --git a/README.md b/README.md
index 27c53cf..925eaa6 100644
--- a/README.md
+++ b/README.md
@@ -46,6 +46,7 @@ spark.readStream.format("fake").load().writeStream.format("console").start()
 | [KaggleDataSource](pyspark_datasources/kaggle.py)                      | `kaggle`       | Read datasets from Kaggle                    | `kagglehub`, `pandas` |
 | [SimpleJsonDataSource](pyspark_datasources/simplejson.py)              | `simplejson`   | Write JSON data to Databricks DBFS                 | `databricks-sdk`      |
 | [OpenSkyDataSource](pyspark_datasources/opensky.py)                 | `opensky`      | Read from OpenSky Network.                   | None                  |
+| [SalesforceDataSource](pyspark_datasources/salesforce.py)              | `salesforce`   | Streaming sink for writing data to Salesforce | `simple-salesforce`   |
 
 See more here: https://allisonwang-db.github.io/pyspark-data-sources/.
 
diff --git a/docs/datasources/salesforce.md b/docs/datasources/salesforce.md
new file mode 100644
index 0000000..688b61c
--- /dev/null
+++ b/docs/datasources/salesforce.md
@@ -0,0 +1,6 @@
+# SalesforceDataSource
+
+> Requires the [`simple-salesforce`](https://github.com/simple-salesforce/simple-salesforce) library. You can install it manually: `pip install simple-salesforce`
+> or use `pip install pyspark-data-sources[salesforce]`.
+
+::: pyspark_datasources.salesforce.SalesforceDataSource
\ No newline at end of file
diff --git a/docs/index.md b/docs/index.md
index d470b0f..1470257 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -38,5 +38,6 @@ spark.readStream.format("fake").load().writeStream.format("console").start()
 | [HuggingFaceDatasets](./datasources/huggingface.md)     | `huggingface`  | Read datasets from the HuggingFace Hub        | `datasets`            |
 | [StockDataSource](./datasources/stock.md)               | `stock`        | Read stock data from Alpha Vantage            | None                  |
 | [SimpleJsonDataSource](./datasources/simplejson.md)     | `simplejson`   | Write JSON data to Databricks DBFS            | `databricks-sdk`      |
+| [SalesforceDataSource](./datasources/salesforce.md)     | `salesforce`   | Write streaming data to Salesforce objects    |`simple-salesforce`    |
 | [GoogleSheetsDataSource](./datasources/googlesheets.md) | `googlesheets` | Read table from public Google Sheets document | None                  |
 | [KaggleDataSource](./datasources/kaggle.md)             | `kaggle`       | Read datasets from Kaggle                     | `kagglehub`, `pandas` |
diff --git a/examples/salesforce_sink_example.py b/examples/salesforce_sink_example.py
new file mode 100644
index 0000000..09a549f
--- /dev/null
+++ b/examples/salesforce_sink_example.py
@@ -0,0 +1,455 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Salesforce Sink Example
+
+This example demonstrates how to use the SalesforceDataSource as a streaming sink
+to write data from various sources to Salesforce objects.
+
+Requirements:
+- PySpark 4.0+
+- simple-salesforce library
+- Valid Salesforce credentials
+
+Setup:
+    pip install pyspark simple-salesforce
+
+Environment Variables:
+    export SALESFORCE_USERNAME="your-username@company.com"
+    export SALESFORCE_PASSWORD="your-password"
+    export SALESFORCE_SECURITY_TOKEN="your-security-token"
+"""
+
+import os
+import sys
+import tempfile
+import csv
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import col, lit, current_timestamp
+from pyspark.sql.types import StructType, StructField, StringType, DoubleType, IntegerType
+
+def check_credentials():
+    """Check if Salesforce credentials are available"""
+    username = os.getenv('SALESFORCE_USERNAME')
+    password = os.getenv('SALESFORCE_PASSWORD')
+    security_token = os.getenv('SALESFORCE_SECURITY_TOKEN')
+    
+    if not all([username, password, security_token]):
+        print("❌ Missing Salesforce credentials!")
+        print("Please set the following environment variables:")
+        print("  export SALESFORCE_USERNAME='your-username@company.com'")
+        print("  export SALESFORCE_PASSWORD='your-password'")
+        print("  export SALESFORCE_SECURITY_TOKEN='your-security-token'")
+        return False, None, None, None
+    
+    print(f"✅ Using Salesforce credentials for: {username}")
+    return True, username, password, security_token
+
+def example_1_rate_source_to_accounts():
+    """Example 1: Stream from rate source to Salesforce Accounts"""
+    print("\n" + "="*60)
+    print("EXAMPLE 1: Rate Source → Salesforce Accounts")
+    print("="*60)
+    
+    has_creds, username, password, security_token = check_credentials()
+    if not has_creds:
+        return
+    
+    spark = SparkSession.builder \
+        .appName("SalesforceExample1") \
+        .config("spark.sql.shuffle.partitions", "2") \
+        .getOrCreate()
+    
+    try:
+        # Register Salesforce sink
+        from pyspark_datasources.salesforce import SalesforceDataSource
+        spark.dataSource.register(SalesforceDataSource)
+        print("✅ Salesforce sink registered")
+        
+        # Create streaming data from rate source
+        streaming_df = spark.readStream \
+            .format("rate") \
+            .option("rowsPerSecond", 2) \
+            .load()
+        
+        # Transform to Account format
+        account_data = streaming_df.select(
+            col("timestamp").cast("string").alias("Name"),
+            lit("Technology").alias("Industry"),
+            (col("value") * 10000).cast("double").alias("AnnualRevenue")
+        )
+        
+        print("📊 Starting streaming write to Salesforce Accounts...")
+        
+        # Write to Salesforce
+        query = account_data.writeStream \
+            .format("salesforce") \
+            .option("username", username) \
+            .option("password", password) \
+            .option("security_token", security_token) \
+            .option("salesforce_object", "Account") \
+            .option("batch_size", "10") \
+            .option("checkpointLocation", "/tmp/salesforce_example1_checkpoint") \
+            .trigger(once=True) \
+            .start()
+        
+        # Wait for completion
+        query.awaitTermination(timeout=60)
+        
+        # Show results
+        progress = query.lastProgress
+        if progress:
+            sources = progress.get('sources', [])
+            if sources:
+                records = sources[0].get('numInputRows', 0)
+                print(f"✅ Successfully wrote {records} Account records to Salesforce")
+            else:
+                print("✅ Streaming completed successfully")
+        
+    except Exception as e:
+        print(f"❌ Error: {e}")
+    finally:
+        spark.stop()
+
+def example_2_csv_to_contacts():
+    """Example 2: Stream from CSV files to Salesforce Contacts"""
+    print("\n" + "="*60)
+    print("EXAMPLE 2: CSV Files → Salesforce Contacts")
+    print("="*60)
+    
+    has_creds, username, password, security_token = check_credentials()
+    if not has_creds:
+        return
+    
+    # Create temporary CSV directory
+    csv_dir = tempfile.mkdtemp(prefix="salesforce_contacts_")
+    print(f"📁 CSV directory: {csv_dir}")
+    
+    spark = SparkSession.builder \
+        .appName("SalesforceExample2") \
+        .config("spark.sql.shuffle.partitions", "2") \
+        .getOrCreate()
+    
+    try:
+        # Register Salesforce sink
+        from pyspark_datasources.salesforce import SalesforceDataSource
+        spark.dataSource.register(SalesforceDataSource)
+        
+        # Create sample CSV data
+        contact_data = [
+            ["John", "Doe", "john.doe@example.com", "555-1234"],
+            ["Jane", "Smith", "jane.smith@example.com", "555-5678"],
+            ["Bob", "Johnson", "bob.johnson@example.com", "555-9012"]
+        ]
+        
+        headers = ["FirstName", "LastName", "Email", "Phone"]
+        csv_file = os.path.join(csv_dir, "contacts.csv")
+        
+        # Write CSV file
+        with open(csv_file, 'w', newline='') as f:
+            writer = csv.writer(f)
+            writer.writerow(headers)
+            writer.writerows(contact_data)
+        
+        print(f"📝 Created CSV file with {len(contact_data)} contacts")
+        
+        # Define schema for CSV
+        schema = StructType([
+            StructField("FirstName", StringType(), True),
+            StructField("LastName", StringType(), True),
+            StructField("Email", StringType(), True),
+            StructField("Phone", StringType(), True)
+        ])
+        
+        # Stream from CSV
+        streaming_df = spark.readStream \
+            .format("csv") \
+            .option("header", "true") \
+            .schema(schema) \
+            .load(csv_dir)
+        
+        print("📊 Starting streaming write to Salesforce Contacts...")
+        
+        # Write to Salesforce with custom schema
+        query = streaming_df.writeStream \
+            .format("salesforce") \
+            .option("username", username) \
+            .option("password", password) \
+            .option("security_token", security_token) \
+            .option("salesforce_object", "Contact") \
+            .option("schema", "FirstName STRING, LastName STRING NOT NULL, Email STRING, Phone STRING") \
+            .option("batch_size", "5") \
+            .option("checkpointLocation", "/tmp/salesforce_example2_checkpoint") \
+            .trigger(once=True) \
+            .start()
+        
+        # Wait for completion
+        query.awaitTermination(timeout=60)
+        
+        # Show results
+        progress = query.lastProgress
+        if progress:
+            sources = progress.get('sources', [])
+            if sources:
+                records = sources[0].get('numInputRows', 0)
+                print(f"✅ Successfully wrote {records} Contact records to Salesforce")
+            else:
+                print("✅ Streaming completed successfully")
+        
+    except Exception as e:
+        print(f"❌ Error: {e}")
+    finally:
+        spark.stop()
+        # Cleanup
+        import shutil
+        if os.path.exists(csv_dir):
+            shutil.rmtree(csv_dir)
+
+def example_3_checkpoint_demonstration():
+    """Example 3: Demonstrate checkpoint functionality with incremental data"""
+    print("\n" + "="*60)
+    print("EXAMPLE 3: Checkpoint Functionality Demonstration")
+    print("="*60)
+    
+    has_creds, username, password, security_token = check_credentials()
+    if not has_creds:
+        return
+    
+    # Create temporary directories
+    csv_dir = tempfile.mkdtemp(prefix="salesforce_checkpoint_")
+    checkpoint_dir = tempfile.mkdtemp(prefix="checkpoint_")
+    
+    print(f"📁 CSV directory: {csv_dir}")
+    print(f"📁 Checkpoint directory: {checkpoint_dir}")
+    
+    try:
+        # Phase 1: Create initial data and first stream
+        print("\n📊 Phase 1: Creating initial batch and first stream...")
+        
+        initial_data = [
+            [1, "InitialCorp_A", "Tech", 100000.0],
+            [2, "InitialCorp_B", "Finance", 200000.0],
+            [3, "InitialCorp_C", "Healthcare", 300000.0]
+        ]
+        
+        headers = ["id", "name", "industry", "revenue"]
+        csv_file1 = os.path.join(csv_dir, "batch_001.csv")
+        
+        with open(csv_file1, 'w', newline='') as f:
+            writer = csv.writer(f)
+            writer.writerow(headers)
+            writer.writerows(initial_data)
+        
+        # First stream
+        spark = SparkSession.builder \
+            .appName("SalesforceCheckpointDemo") \
+            .config("spark.sql.shuffle.partitions", "2") \
+            .getOrCreate()
+        
+        from pyspark_datasources.salesforce import SalesforceDataSource
+        spark.dataSource.register(SalesforceDataSource)
+        
+        schema = StructType([
+            StructField("id", IntegerType(), True),
+            StructField("name", StringType(), True),
+            StructField("industry", StringType(), True),
+            StructField("revenue", DoubleType(), True)
+        ])
+        
+        streaming_df1 = spark.readStream \
+            .format("csv") \
+            .option("header", "true") \
+            .schema(schema) \
+            .load(csv_dir)
+        
+        account_df1 = streaming_df1.select(
+            col("name").alias("Name"),
+            col("industry").alias("Industry"),
+            col("revenue").alias("AnnualRevenue")
+        )
+        
+        query1 = account_df1.writeStream \
+            .format("salesforce") \
+            .option("username", username) \
+            .option("password", password) \
+            .option("security_token", security_token) \
+            .option("salesforce_object", "Account") \
+            .option("batch_size", "10") \
+            .option("checkpointLocation", checkpoint_dir) \
+            .trigger(once=True) \
+            .start()
+        
+        query1.awaitTermination(timeout=60)
+        
+        progress1 = query1.lastProgress
+        records1 = 0
+        if progress1 and progress1.get('sources'):
+            records1 = progress1['sources'][0].get('numInputRows', 0)
+        
+        print(f"   ✅ First stream processed {records1} records")
+        
+        # Phase 2: Add new data and second stream
+        print("\n📊 Phase 2: Adding new batch and second stream...")
+        
+        import time
+        time.sleep(2)  # Brief pause
+        
+        new_data = [
+            [4, "NewCorp_D", "Energy", 400000.0],
+            [5, "NewCorp_E", "Retail", 500000.0]
+        ]
+        
+        csv_file2 = os.path.join(csv_dir, "batch_002.csv")
+        with open(csv_file2, 'w', newline='') as f:
+            writer = csv.writer(f)
+            writer.writerow(headers)
+            writer.writerows(new_data)
+        
+        # Second stream with same checkpoint
+        streaming_df2 = spark.readStream \
+            .format("csv") \
+            .option("header", "true") \
+            .schema(schema) \
+            .load(csv_dir)
+        
+        account_df2 = streaming_df2.select(
+            col("name").alias("Name"),
+            col("industry").alias("Industry"),
+            col("revenue").alias("AnnualRevenue")
+        )
+        
+        query2 = account_df2.writeStream \
+            .format("salesforce") \
+            .option("username", username) \
+            .option("password", password) \
+            .option("security_token", security_token) \
+            .option("salesforce_object", "Account") \
+            .option("batch_size", "10") \
+            .option("checkpointLocation", checkpoint_dir) \
+            .trigger(once=True) \
+            .start()
+        
+        query2.awaitTermination(timeout=60)
+        
+        progress2 = query2.lastProgress
+        records2 = 0
+        if progress2 and progress2.get('sources'):
+            records2 = progress2['sources'][0].get('numInputRows', 0)
+        
+        print(f"   ✅ Second stream processed {records2} records")
+        
+        # Analyze checkpoint functionality
+        print(f"\n📈 Checkpoint Analysis:")
+        print(f"   - First stream:  {records1} records (initial batch)")
+        print(f"   - Second stream: {records2} records (new batch)")
+        print(f"   - Total:         {records1 + records2} records")
+        
+        if records1 == 3 and records2 == 2:
+            print("   ✅ PERFECT: Exactly-once processing achieved!")
+            print("   ✅ Checkpoint functionality working correctly")
+        else:
+            print("   ⚠️  Results may vary due to timing or file detection")
+        
+    except Exception as e:
+        print(f"❌ Error: {e}")
+    finally:
+        spark.stop()
+        # Cleanup
+        import shutil
+        if os.path.exists(csv_dir):
+            shutil.rmtree(csv_dir)
+        if os.path.exists(checkpoint_dir):
+            shutil.rmtree(checkpoint_dir)
+
+def example_4_custom_object():
+    """Example 4: Write to custom Salesforce object"""
+    print("\n" + "="*60)
+    print("EXAMPLE 4: Custom Salesforce Object")
+    print("="*60)
+    
+    has_creds, username, password, security_token = check_credentials()
+    if not has_creds:
+        return
+    
+    print("📝 This example shows how to write to custom Salesforce objects")
+    print("   Note: Make sure your custom object exists in Salesforce")
+    
+    spark = SparkSession.builder \
+        .appName("SalesforceCustomObjectExample") \
+        .config("spark.sql.shuffle.partitions", "2") \
+        .getOrCreate()
+    
+    try:
+        from pyspark_datasources.salesforce import SalesforceDataSource
+        spark.dataSource.register(SalesforceDataSource)
+        
+        # Create sample data for custom object
+        streaming_df = spark.readStream \
+            .format("rate") \
+            .option("rowsPerSecond", 1) \
+            .load()
+        
+        # Transform for custom object (example: Product__c)
+        custom_data = streaming_df.select(
+            col("value").cast("string").alias("Product_Code__c"),
+            lit("Sample Product").alias("Name"),
+            (col("value") * 29.99).cast("double").alias("Price__c"),
+            current_timestamp().alias("Created_Date__c")
+        )
+        
+        print("📊 Example configuration for custom object...")
+        print("   Custom Object: Product__c")
+        print("   Fields: Product_Code__c, Name, Price__c, Created_Date__c")
+        print("\n   Note: Uncomment and modify the following code for your custom object:")
+        
+        # Example code (commented out since custom object may not exist)
+        print("""
+        query = custom_data.writeStream \\
+            .format("salesforce") \\
+            .option("username", username) \\
+            .option("password", password) \\
+            .option("security_token", security_token) \\
+            .option("salesforce_object", "Product__c") \\
+            .option("schema", "Product_Code__c STRING, Name STRING, Price__c DOUBLE, Created_Date__c TIMESTAMP") \\
+            .option("batch_size", "20") \\
+            .option("checkpointLocation", "/tmp/custom_object_checkpoint") \\
+            .trigger(processingTime="10 seconds") \\
+            .start()
+        """)
+        
+        print("✅ Custom object example configuration shown")
+        
+    except Exception as e:
+        print(f"❌ Error: {e}")
+    finally:
+        spark.stop()
+
+def main():
+    """Run all examples"""
+    print("🚀 Salesforce Sink Examples")
+    print("This demonstrates various ways to use the Salesforce streaming sink")
+    
+    try:
+        # Run examples
+        example_1_rate_source_to_accounts()
+        example_2_csv_to_contacts()
+        example_3_checkpoint_demonstration()
+        example_4_custom_object()
+        
+        print("\n" + "="*60)
+        print("✅ All examples completed!")
+        print("="*60)
+        print("\n💡 Key takeaways:")
+        print("   - Salesforce sink supports various input sources (rate, CSV, etc.)")
+        print("   - Checkpoint functionality enables exactly-once processing")
+        print("   - Custom schemas allow flexibility for different Salesforce objects")
+        print("   - Batch processing optimizes Salesforce API usage")
+        print("   - Error handling provides fallback to individual record creation")
+        
+    except KeyboardInterrupt:
+        print("\n⏹️  Examples interrupted by user")
+    except Exception as e:
+        print(f"\n❌ Unexpected error: {e}")
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index e66b9d4..8fde0b5 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -23,6 +23,7 @@ nav:
     - datasources/huggingface.md
     - datasources/stock.md
     - datasources/simplejson.md
+    - datasources/salesforce.md
     - datasources/googlesheets.md
     - datasources/kaggle.md
 
diff --git a/poetry.lock b/poetry.lock
index 65dd70a..529ae8b 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -154,7 +154,7 @@ description = "Classes Without Boilerplate"
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"datasets\" or extra == \"all\""
+markers = "extra == \"datasets\" or extra == \"all\" or extra == \"salesforce\""
 files = [
     {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"},
     {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"},
@@ -227,6 +227,87 @@ files = [
     {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = true
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "(extra == \"salesforce\" or extra == \"all\") and platform_python_implementation != \"PyPy\""
+files = [
+    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5da5719280082ac6bd9aa7becb3938dc9f9cbd57fac7d2871717b1feb0902ab6"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2bb1a08b8008b281856e5971307cc386a8e9c5b625ac297e853d36da6efe9c17"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:045d61c734659cc045141be4bae381a41d89b741f795af1dd018bfb532fd0df8"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:6883e737d7d9e4899a8a695e00ec36bd4e5e4f18fabe0aca0efe0a4b44cdb13e"},
+    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6b8b4a92e1c65048ff98cfe1f735ef8f1ceb72e3d5f0c25fdb12087a23da22be"},
+    {file = "cffi-1.17.1-cp310-cp310-win32.whl", hash = "sha256:c9c3d058ebabb74db66e431095118094d06abf53284d9c81f27300d0e0d8bc7c"},
+    {file = "cffi-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:0f048dcf80db46f0098ccac01132761580d28e28bc0f78ae0d58048063317e15"},
+    {file = "cffi-1.17.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:a45e3c6913c5b87b3ff120dcdc03f6131fa0065027d0ed7ee6190736a74cd401"},
+    {file = "cffi-1.17.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:30c5e0cb5ae493c04c8b42916e52ca38079f1b235c2f8ae5f4527b963c401caf"},
+    {file = "cffi-1.17.1-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f75c7ab1f9e4aca5414ed4d8e5c0e303a34f4421f8a0d47a4d019ceff0ab6af4"},
+    {file = "cffi-1.17.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a1ed2dd2972641495a3ec98445e09766f077aee98a1c896dcb4ad0d303628e41"},
+    {file = "cffi-1.17.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:46bf43160c1a35f7ec506d254e5c890f3c03648a4dbac12d624e4490a7046cd1"},
+    {file = "cffi-1.17.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a24ed04c8ffd54b0729c07cee15a81d964e6fee0e3d4d342a27b020d22959dc6"},
+    {file = "cffi-1.17.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:610faea79c43e44c71e1ec53a554553fa22321b65fae24889706c0a84d4ad86d"},
+    {file = "cffi-1.17.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:a9b15d491f3ad5d692e11f6b71f7857e7835eb677955c00cc0aefcd0669adaf6"},
+    {file = "cffi-1.17.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:de2ea4b5833625383e464549fec1bc395c1bdeeb5f25c4a3a82b5a8c756ec22f"},
+    {file = "cffi-1.17.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:fc48c783f9c87e60831201f2cce7f3b2e4846bf4d8728eabe54d60700b318a0b"},
+    {file = "cffi-1.17.1-cp311-cp311-win32.whl", hash = "sha256:85a950a4ac9c359340d5963966e3e0a94a676bd6245a4b55bc43949eee26a655"},
+    {file = "cffi-1.17.1-cp311-cp311-win_amd64.whl", hash = "sha256:caaf0640ef5f5517f49bc275eca1406b0ffa6aa184892812030f04c2abf589a0"},
+    {file = "cffi-1.17.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:805b4371bf7197c329fcb3ead37e710d1bca9da5d583f5073b799d5c5bd1eee4"},
+    {file = "cffi-1.17.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:733e99bc2df47476e3848417c5a4540522f234dfd4ef3ab7fafdf555b082ec0c"},
+    {file = "cffi-1.17.1-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1257bdabf294dceb59f5e70c64a3e2f462c30c7ad68092d01bbbfb1c16b1ba36"},
+    {file = "cffi-1.17.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da95af8214998d77a98cc14e3a3bd00aa191526343078b530ceb0bd710fb48a5"},
+    {file = "cffi-1.17.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d63afe322132c194cf832bfec0dc69a99fb9bb6bbd550f161a49e9e855cc78ff"},
+    {file = "cffi-1.17.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f79fc4fc25f1c8698ff97788206bb3c2598949bfe0fef03d299eb1b5356ada99"},
+    {file = "cffi-1.17.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b62ce867176a75d03a665bad002af8e6d54644fad99a3c70905c543130e39d93"},
+    {file = "cffi-1.17.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:386c8bf53c502fff58903061338ce4f4950cbdcb23e2902d86c0f722b786bbe3"},
+    {file = "cffi-1.17.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:4ceb10419a9adf4460ea14cfd6bc43d08701f0835e979bf821052f1805850fe8"},
+    {file = "cffi-1.17.1-cp312-cp312-win32.whl", hash = "sha256:a08d7e755f8ed21095a310a693525137cfe756ce62d066e53f502a83dc550f65"},
+    {file = "cffi-1.17.1-cp312-cp312-win_amd64.whl", hash = "sha256:51392eae71afec0d0c8fb1a53b204dbb3bcabcb3c9b807eedf3e1e6ccf2de903"},
+    {file = "cffi-1.17.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f3a2b4222ce6b60e2e8b337bb9596923045681d71e5a082783484d845390938e"},
+    {file = "cffi-1.17.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0984a4925a435b1da406122d4d7968dd861c1385afe3b45ba82b750f229811e2"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d01b12eeeb4427d3110de311e1774046ad344f5b1a7403101878976ecd7a10f3"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:706510fe141c86a69c8ddc029c7910003a17353970cff3b904ff0686a5927683"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:de55b766c7aa2e2a3092c51e0483d700341182f08e67c63630d5b6f200bb28e5"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c59d6e989d07460165cc5ad3c61f9fd8f1b4796eacbd81cee78957842b834af4"},
+    {file = "cffi-1.17.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd398dbc6773384a17fe0d3e7eeb8d1a21c2200473ee6806bb5e6a8e62bb73dd"},
+    {file = "cffi-1.17.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:3edc8d958eb099c634dace3c7e16560ae474aa3803a5df240542b305d14e14ed"},
+    {file = "cffi-1.17.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:72e72408cad3d5419375fc87d289076ee319835bdfa2caad331e377589aebba9"},
+    {file = "cffi-1.17.1-cp313-cp313-win32.whl", hash = "sha256:e03eab0a8677fa80d646b5ddece1cbeaf556c313dcfac435ba11f107ba117b5d"},
+    {file = "cffi-1.17.1-cp313-cp313-win_amd64.whl", hash = "sha256:f6a16c31041f09ead72d69f583767292f750d24913dadacf5756b966aacb3f1a"},
+    {file = "cffi-1.17.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:636062ea65bd0195bc012fea9321aca499c0504409f413dc88af450b57ffd03b"},
+    {file = "cffi-1.17.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c7eac2ef9b63c79431bc4b25f1cd649d7f061a28808cbc6c47b534bd789ef964"},
+    {file = "cffi-1.17.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e221cf152cff04059d011ee126477f0d9588303eb57e88923578ace7baad17f9"},
+    {file = "cffi-1.17.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:31000ec67d4221a71bd3f67df918b1f88f676f1c3b535a7eb473255fdc0b83fc"},
+    {file = "cffi-1.17.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6f17be4345073b0a7b8ea599688f692ac3ef23ce28e5df79c04de519dbc4912c"},
+    {file = "cffi-1.17.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e2b1fac190ae3ebfe37b979cc1ce69c81f4e4fe5746bb401dca63a9062cdaf1"},
+    {file = "cffi-1.17.1-cp38-cp38-win32.whl", hash = "sha256:7596d6620d3fa590f677e9ee430df2958d2d6d6de2feeae5b20e82c00b76fbf8"},
+    {file = "cffi-1.17.1-cp38-cp38-win_amd64.whl", hash = "sha256:78122be759c3f8a014ce010908ae03364d00a1f81ab5c7f4a7a5120607ea56e1"},
+    {file = "cffi-1.17.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b2ab587605f4ba0bf81dc0cb08a41bd1c0a5906bd59243d56bad7668a6fc6c16"},
+    {file = "cffi-1.17.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:28b16024becceed8c6dfbc75629e27788d8a3f9030691a1dbf9821a128b22c36"},
+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1d599671f396c4723d016dbddb72fe8e0397082b0a77a4fab8028923bec050e8"},
+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ca74b8dbe6e8e8263c0ffd60277de77dcee6c837a3d0881d8c1ead7268c9e576"},
+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7f5baafcc48261359e14bcd6d9bff6d4b28d9103847c9e136694cb0501aef87"},
+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98e3969bcff97cae1b2def8ba499ea3d6f31ddfdb7635374834cf89a1a08ecf0"},
+    {file = "cffi-1.17.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cdf5ce3acdfd1661132f2a9c19cac174758dc2352bfe37d98aa7512c6b7178b3"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9755e4345d1ec879e3849e62222a18c7174d65a6a92d5b346b1863912168b595"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:f1e22e8c4419538cb197e4dd60acc919d7696e5ef98ee4da4e01d3f8cfa4cc5a"},
+    {file = "cffi-1.17.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:c03e868a0b3bc35839ba98e74211ed2b05d2119be4e8a0f224fba9384f1fe02e"},
+    {file = "cffi-1.17.1-cp39-cp39-win32.whl", hash = "sha256:e31ae45bc2e29f6b2abd0de1cc3b9d5205aa847cafaecb8af1476a609a2f6eb7"},
+    {file = "cffi-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:d016c76bdd850f3c626af19b0542c9677ba156e4ee4fccfdd7848803533ef662"},
+    {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"},
+]
+
+[package.dependencies]
+pycparser = "*"
+
 [[package]]
 name = "charset-normalizer"
 version = "3.4.1"
@@ -439,6 +520,118 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 [package.extras]
 toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
+[[package]]
+name = "cryptography"
+version = "43.0.3"
+description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
+optional = true
+python-versions = ">=3.7"
+groups = ["main"]
+markers = "python_version < \"3.11\" and (extra == \"salesforce\" or extra == \"all\")"
+files = [
+    {file = "cryptography-43.0.3-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:bf7a1932ac4176486eab36a19ed4c0492da5d97123f1406cf15e41b05e787d2e"},
+    {file = "cryptography-43.0.3-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63efa177ff54aec6e1c0aefaa1a241232dcd37413835a9b674b6e3f0ae2bfd3e"},
+    {file = "cryptography-43.0.3-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e1ce50266f4f70bf41a2c6dc4358afadae90e2a1e5342d3c08883df1675374f"},
+    {file = "cryptography-43.0.3-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:443c4a81bb10daed9a8f334365fe52542771f25aedaf889fd323a853ce7377d6"},
+    {file = "cryptography-43.0.3-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:74f57f24754fe349223792466a709f8e0c093205ff0dca557af51072ff47ab18"},
+    {file = "cryptography-43.0.3-cp37-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9762ea51a8fc2a88b70cf2995e5675b38d93bf36bd67d91721c309df184f49bd"},
+    {file = "cryptography-43.0.3-cp37-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:81ef806b1fef6b06dcebad789f988d3b37ccaee225695cf3e07648eee0fc6b73"},
+    {file = "cryptography-43.0.3-cp37-abi3-win32.whl", hash = "sha256:cbeb489927bd7af4aa98d4b261af9a5bc025bd87f0e3547e11584be9e9427be2"},
+    {file = "cryptography-43.0.3-cp37-abi3-win_amd64.whl", hash = "sha256:f46304d6f0c6ab8e52770addfa2fc41e6629495548862279641972b6215451cd"},
+    {file = "cryptography-43.0.3-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:8ac43ae87929a5982f5948ceda07001ee5e83227fd69cf55b109144938d96984"},
+    {file = "cryptography-43.0.3-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:846da004a5804145a5f441b8530b4bf35afbf7da70f82409f151695b127213d5"},
+    {file = "cryptography-43.0.3-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0f996e7268af62598f2fc1204afa98a3b5712313a55c4c9d434aef49cadc91d4"},
+    {file = "cryptography-43.0.3-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:f7b178f11ed3664fd0e995a47ed2b5ff0a12d893e41dd0494f406d1cf555cab7"},
+    {file = "cryptography-43.0.3-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:c2e6fc39c4ab499049df3bdf567f768a723a5e8464816e8f009f121a5a9f4405"},
+    {file = "cryptography-43.0.3-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:e1be4655c7ef6e1bbe6b5d0403526601323420bcf414598955968c9ef3eb7d16"},
+    {file = "cryptography-43.0.3-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:df6b6c6d742395dd77a23ea3728ab62f98379eff8fb61be2744d4679ab678f73"},
+    {file = "cryptography-43.0.3-cp39-abi3-win32.whl", hash = "sha256:d56e96520b1020449bbace2b78b603442e7e378a9b3bd68de65c782db1507995"},
+    {file = "cryptography-43.0.3-cp39-abi3-win_amd64.whl", hash = "sha256:0c580952eef9bf68c4747774cde7ec1d85a6e61de97281f2dba83c7d2c806362"},
+    {file = "cryptography-43.0.3-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:d03b5621a135bffecad2c73e9f4deb1a0f977b9a8ffe6f8e002bf6c9d07b918c"},
+    {file = "cryptography-43.0.3-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:a2a431ee15799d6db9fe80c82b055bae5a752bef645bba795e8e52687c69efe3"},
+    {file = "cryptography-43.0.3-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:281c945d0e28c92ca5e5930664c1cefd85efe80e5c0d2bc58dd63383fda29f83"},
+    {file = "cryptography-43.0.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:f18c716be16bc1fea8e95def49edf46b82fccaa88587a45f8dc0ff6ab5d8e0a7"},
+    {file = "cryptography-43.0.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:4a02ded6cd4f0a5562a8887df8b3bd14e822a90f97ac5e544c162899bc467664"},
+    {file = "cryptography-43.0.3-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:53a583b6637ab4c4e3591a15bc9db855b8d9dee9a669b550f311480acab6eb08"},
+    {file = "cryptography-43.0.3-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:1ec0bcf7e17c0c5669d881b1cd38c4972fade441b27bda1051665faaa89bdcaa"},
+    {file = "cryptography-43.0.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:2ce6fae5bdad59577b44e4dfed356944fbf1d925269114c28be377692643b4ff"},
+    {file = "cryptography-43.0.3.tar.gz", hash = "sha256:315b9001266a492a6ff443b61238f956b214dbec9910a081ba5b6646a055a805"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
+docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
+nox = ["nox"]
+pep8test = ["check-sdist", "click", "mypy", "ruff"]
+sdist = ["build"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi", "cryptography-vectors (==43.0.3)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test-randomorder = ["pytest-randomly"]
+
+[[package]]
+name = "cryptography"
+version = "45.0.5"
+description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
+optional = true
+python-versions = "!=3.9.0,!=3.9.1,>=3.7"
+groups = ["main"]
+markers = "python_version >= \"3.11\" and (extra == \"salesforce\" or extra == \"all\")"
+files = [
+    {file = "cryptography-45.0.5-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:101ee65078f6dd3e5a028d4f19c07ffa4dd22cce6a20eaa160f8b5219911e7d8"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3a264aae5f7fbb089dbc01e0242d3b67dffe3e6292e1f5182122bdf58e65215d"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e74d30ec9c7cb2f404af331d5b4099a9b322a8a6b25c4632755c8757345baac5"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:3af26738f2db354aafe492fb3869e955b12b2ef2e16908c8b9cb928128d42c57"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:e6c00130ed423201c5bc5544c23359141660b07999ad82e34e7bb8f882bb78e0"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:dd420e577921c8c2d31289536c386aaa30140b473835e97f83bc71ea9d2baf2d"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:d05a38884db2ba215218745f0781775806bde4f32e07b135348355fe8e4991d9"},
+    {file = "cryptography-45.0.5-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:ad0caded895a00261a5b4aa9af828baede54638754b51955a0ac75576b831b27"},
+    {file = "cryptography-45.0.5-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9024beb59aca9d31d36fcdc1604dd9bbeed0a55bface9f1908df19178e2f116e"},
+    {file = "cryptography-45.0.5-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:91098f02ca81579c85f66df8a588c78f331ca19089763d733e34ad359f474174"},
+    {file = "cryptography-45.0.5-cp311-abi3-win32.whl", hash = "sha256:926c3ea71a6043921050eaa639137e13dbe7b4ab25800932a8498364fc1abec9"},
+    {file = "cryptography-45.0.5-cp311-abi3-win_amd64.whl", hash = "sha256:b85980d1e345fe769cfc57c57db2b59cff5464ee0c045d52c0df087e926fbe63"},
+    {file = "cryptography-45.0.5-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:f3562c2f23c612f2e4a6964a61d942f891d29ee320edb62ff48ffb99f3de9ae8"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3fcfbefc4a7f332dece7272a88e410f611e79458fab97b5efe14e54fe476f4fd"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:460f8c39ba66af7db0545a8c6f2eabcbc5a5528fc1cf6c3fa9a1e44cec33385e"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:9b4cf6318915dccfe218e69bbec417fdd7c7185aa7aab139a2c0beb7468c89f0"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:2089cc8f70a6e454601525e5bf2779e665d7865af002a5dec8d14e561002e135"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:0027d566d65a38497bc37e0dd7c2f8ceda73597d2ac9ba93810204f56f52ebc7"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:be97d3a19c16a9be00edf79dca949c8fa7eff621763666a145f9f9535a5d7f42"},
+    {file = "cryptography-45.0.5-cp37-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:7760c1c2e1a7084153a0f68fab76e754083b126a47d0117c9ed15e69e2103492"},
+    {file = "cryptography-45.0.5-cp37-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:6ff8728d8d890b3dda5765276d1bc6fb099252915a2cd3aff960c4c195745dd0"},
+    {file = "cryptography-45.0.5-cp37-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:7259038202a47fdecee7e62e0fd0b0738b6daa335354396c6ddebdbe1206af2a"},
+    {file = "cryptography-45.0.5-cp37-abi3-win32.whl", hash = "sha256:1e1da5accc0c750056c556a93c3e9cb828970206c68867712ca5805e46dc806f"},
+    {file = "cryptography-45.0.5-cp37-abi3-win_amd64.whl", hash = "sha256:90cb0a7bb35959f37e23303b7eed0a32280510030daba3f7fdfbb65defde6a97"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:206210d03c1193f4e1ff681d22885181d47efa1ab3018766a7b32a7b3d6e6afd"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:c648025b6840fe62e57107e0a25f604db740e728bd67da4f6f060f03017d5097"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b8fa8b0a35a9982a3c60ec79905ba5bb090fc0b9addcfd3dc2dd04267e45f25e"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:14d96584701a887763384f3c47f0ca7c1cce322aa1c31172680eb596b890ec30"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:57c816dfbd1659a367831baca4b775b2a5b43c003daf52e9d57e1d30bc2e1b0e"},
+    {file = "cryptography-45.0.5-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:b9e38e0a83cd51e07f5a48ff9691cae95a79bea28fe4ded168a8e5c6c77e819d"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-macosx_10_9_x86_64.whl", hash = "sha256:8c4a6ff8a30e9e3d38ac0539e9a9e02540ab3f827a3394f8852432f6b0ea152e"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:bd4c45986472694e5121084c6ebbd112aa919a25e783b87eb95953c9573906d6"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:982518cd64c54fcada9d7e5cf28eabd3ee76bd03ab18e08a48cad7e8b6f31b18"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:12e55281d993a793b0e883066f590c1ae1e802e3acb67f8b442e721e475e6463"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:5aa1e32983d4443e310f726ee4b071ab7569f58eedfdd65e9675484a4eb67bd1"},
+    {file = "cryptography-45.0.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:e357286c1b76403dd384d938f93c46b2b058ed4dfcdce64a770f0537ed3feb6f"},
+    {file = "cryptography-45.0.5.tar.gz", hash = "sha256:72e76caa004ab63accdf26023fccd1d087f6d90ec6048ff33ad0445abf7f605a"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs ; python_full_version >= \"3.8.0\"", "sphinx-rtd-theme (>=3.0.0) ; python_full_version >= \"3.8.0\""]
+docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
+nox = ["nox (>=2024.4.15)", "nox[uv] (>=2024.3.2) ; python_full_version >= \"3.8.0\""]
+pep8test = ["check-sdist ; python_full_version >= \"3.8.0\"", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
+sdist = ["build (>=1.0.0)"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi (>=2024)", "cryptography-vectors (==45.0.5)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
+test-randomorder = ["pytest-randomly"]
+
 [[package]]
 name = "databricks-sdk"
 version = "0.28.0"
@@ -966,6 +1159,19 @@ files = [
     {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"},
 ]
 
+[[package]]
+name = "isodate"
+version = "0.7.2"
+description = "An ISO 8601 date/time/duration parser and formatter"
+optional = true
+python-versions = ">=3.7"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "isodate-0.7.2-py3-none-any.whl", hash = "sha256:28009937d8031054830160fce6d409ed342816b543597cece116d966c6d99e15"},
+    {file = "isodate-0.7.2.tar.gz", hash = "sha256:4cd1aa0f43ca76f4a6c6c0292a85f40b35ec2e43e315b59f06e6d32171a953e6"},
+]
+
 [[package]]
 name = "jinja2"
 version = "3.1.6"
@@ -1009,6 +1215,117 @@ hf-datasets = ["datasets", "pandas"]
 pandas-datasets = ["pandas"]
 signing = ["betterproto (>=2.0.0b6)", "model-signing", "sigstore (>=3.6.1)"]
 
+[[package]]
+name = "lxml"
+version = "6.0.0"
+description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
+optional = true
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "lxml-6.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:35bc626eec405f745199200ccb5c6b36f202675d204aa29bb52e27ba2b71dea8"},
+    {file = "lxml-6.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:246b40f8a4aec341cbbf52617cad8ab7c888d944bfe12a6abd2b1f6cfb6f6082"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:2793a627e95d119e9f1e19720730472f5543a6d84c50ea33313ce328d870f2dd"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:46b9ed911f36bfeb6338e0b482e7fe7c27d362c52fde29f221fddbc9ee2227e7"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:2b4790b558bee331a933e08883c423f65bbcd07e278f91b2272489e31ab1e2b4"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e2030956cf4886b10be9a0285c6802e078ec2391e1dd7ff3eb509c2c95a69b76"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4d23854ecf381ab1facc8f353dcd9adeddef3652268ee75297c1164c987c11dc"},
+    {file = "lxml-6.0.0-cp310-cp310-manylinux_2_31_armv7l.whl", hash = "sha256:43fe5af2d590bf4691531b1d9a2495d7aab2090547eaacd224a3afec95706d76"},
+    {file = "lxml-6.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:74e748012f8c19b47f7d6321ac929a9a94ee92ef12bc4298c47e8b7219b26541"},
+    {file = "lxml-6.0.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:43cfbb7db02b30ad3926e8fceaef260ba2fb7df787e38fa2df890c1ca7966c3b"},
+    {file = "lxml-6.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:34190a1ec4f1e84af256495436b2d196529c3f2094f0af80202947567fdbf2e7"},
+    {file = "lxml-6.0.0-cp310-cp310-win32.whl", hash = "sha256:5967fe415b1920a3877a4195e9a2b779249630ee49ece22021c690320ff07452"},
+    {file = "lxml-6.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:f3389924581d9a770c6caa4df4e74b606180869043b9073e2cec324bad6e306e"},
+    {file = "lxml-6.0.0-cp310-cp310-win_arm64.whl", hash = "sha256:522fe7abb41309e9543b0d9b8b434f2b630c5fdaf6482bee642b34c8c70079c8"},
+    {file = "lxml-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:4ee56288d0df919e4aac43b539dd0e34bb55d6a12a6562038e8d6f3ed07f9e36"},
+    {file = "lxml-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b8dd6dd0e9c1992613ccda2bcb74fc9d49159dbe0f0ca4753f37527749885c25"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:d7ae472f74afcc47320238b5dbfd363aba111a525943c8a34a1b657c6be934c3"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5592401cdf3dc682194727c1ddaa8aa0f3ddc57ca64fd03226a430b955eab6f6"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:58ffd35bd5425c3c3b9692d078bf7ab851441434531a7e517c4984d5634cd65b"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f720a14aa102a38907c6d5030e3d66b3b680c3e6f6bc95473931ea3c00c59967"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c2a5e8d207311a0170aca0eb6b160af91adc29ec121832e4ac151a57743a1e1e"},
+    {file = "lxml-6.0.0-cp311-cp311-manylinux_2_31_armv7l.whl", hash = "sha256:2dd1cc3ea7e60bfb31ff32cafe07e24839df573a5e7c2d33304082a5019bcd58"},
+    {file = "lxml-6.0.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2cfcf84f1defed7e5798ef4f88aa25fcc52d279be731ce904789aa7ccfb7e8d2"},
+    {file = "lxml-6.0.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:a52a4704811e2623b0324a18d41ad4b9fabf43ce5ff99b14e40a520e2190c851"},
+    {file = "lxml-6.0.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c16304bba98f48a28ae10e32a8e75c349dd742c45156f297e16eeb1ba9287a1f"},
+    {file = "lxml-6.0.0-cp311-cp311-win32.whl", hash = "sha256:f8d19565ae3eb956d84da3ef367aa7def14a2735d05bd275cd54c0301f0d0d6c"},
+    {file = "lxml-6.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:b2d71cdefda9424adff9a3607ba5bbfc60ee972d73c21c7e3c19e71037574816"},
+    {file = "lxml-6.0.0-cp311-cp311-win_arm64.whl", hash = "sha256:8a2e76efbf8772add72d002d67a4c3d0958638696f541734304c7f28217a9cab"},
+    {file = "lxml-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:78718d8454a6e928470d511bf8ac93f469283a45c354995f7d19e77292f26108"},
+    {file = "lxml-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:84ef591495ffd3f9dcabffd6391db7bb70d7230b5c35ef5148354a134f56f2be"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:2930aa001a3776c3e2601cb8e0a15d21b8270528d89cc308be4843ade546b9ab"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:219e0431ea8006e15005767f0351e3f7f9143e793e58519dc97fe9e07fae5563"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bd5913b4972681ffc9718bc2d4c53cde39ef81415e1671ff93e9aa30b46595e7"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:390240baeb9f415a82eefc2e13285016f9c8b5ad71ec80574ae8fa9605093cd7"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux_2_27_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:d6e200909a119626744dd81bae409fc44134389e03fbf1d68ed2a55a2fb10991"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ca50bd612438258a91b5b3788c6621c1f05c8c478e7951899f492be42defc0da"},
+    {file = "lxml-6.0.0-cp312-cp312-manylinux_2_31_armv7l.whl", hash = "sha256:c24b8efd9c0f62bad0439283c2c795ef916c5a6b75f03c17799775c7ae3c0c9e"},
+    {file = "lxml-6.0.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:afd27d8629ae94c5d863e32ab0e1d5590371d296b87dae0a751fb22bf3685741"},
+    {file = "lxml-6.0.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:54c4855eabd9fc29707d30141be99e5cd1102e7d2258d2892314cf4c110726c3"},
+    {file = "lxml-6.0.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c907516d49f77f6cd8ead1322198bdfd902003c3c330c77a1c5f3cc32a0e4d16"},
+    {file = "lxml-6.0.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:36531f81c8214e293097cd2b7873f178997dae33d3667caaae8bdfb9666b76c0"},
+    {file = "lxml-6.0.0-cp312-cp312-win32.whl", hash = "sha256:690b20e3388a7ec98e899fd54c924e50ba6693874aa65ef9cb53de7f7de9d64a"},
+    {file = "lxml-6.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:310b719b695b3dd442cdfbbe64936b2f2e231bb91d998e99e6f0daf991a3eba3"},
+    {file = "lxml-6.0.0-cp312-cp312-win_arm64.whl", hash = "sha256:8cb26f51c82d77483cdcd2b4a53cda55bbee29b3c2f3ddeb47182a2a9064e4eb"},
+    {file = "lxml-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:6da7cd4f405fd7db56e51e96bff0865b9853ae70df0e6720624049da76bde2da"},
+    {file = "lxml-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:b34339898bb556a2351a1830f88f751679f343eabf9cf05841c95b165152c9e7"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:51a5e4c61a4541bd1cd3ba74766d0c9b6c12d6a1a4964ef60026832aac8e79b3"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d18a25b19ca7307045581b18b3ec9ead2b1db5ccd8719c291f0cd0a5cec6cb81"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d4f0c66df4386b75d2ab1e20a489f30dc7fd9a06a896d64980541506086be1f1"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9f4b481b6cc3a897adb4279216695150bbe7a44c03daba3c894f49d2037e0a24"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux_2_27_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8a78d6c9168f5bcb20971bf3329c2b83078611fbe1f807baadc64afc70523b3a"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2ae06fbab4f1bb7db4f7c8ca9897dc8db4447d1a2b9bee78474ad403437bcc29"},
+    {file = "lxml-6.0.0-cp313-cp313-manylinux_2_31_armv7l.whl", hash = "sha256:1fa377b827ca2023244a06554c6e7dc6828a10aaf74ca41965c5d8a4925aebb4"},
+    {file = "lxml-6.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:1676b56d48048a62ef77a250428d1f31f610763636e0784ba67a9740823988ca"},
+    {file = "lxml-6.0.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:0e32698462aacc5c1cf6bdfebc9c781821b7e74c79f13e5ffc8bfe27c42b1abf"},
+    {file = "lxml-6.0.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:4d6036c3a296707357efb375cfc24bb64cd955b9ec731abf11ebb1e40063949f"},
+    {file = "lxml-6.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7488a43033c958637b1a08cddc9188eb06d3ad36582cebc7d4815980b47e27ef"},
+    {file = "lxml-6.0.0-cp313-cp313-win32.whl", hash = "sha256:5fcd7d3b1d8ecb91445bd71b9c88bdbeae528fefee4f379895becfc72298d181"},
+    {file = "lxml-6.0.0-cp313-cp313-win_amd64.whl", hash = "sha256:2f34687222b78fff795feeb799a7d44eca2477c3d9d3a46ce17d51a4f383e32e"},
+    {file = "lxml-6.0.0-cp313-cp313-win_arm64.whl", hash = "sha256:21db1ec5525780fd07251636eb5f7acb84003e9382c72c18c542a87c416ade03"},
+    {file = "lxml-6.0.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:4eb114a0754fd00075c12648d991ec7a4357f9cb873042cc9a77bf3a7e30c9db"},
+    {file = "lxml-6.0.0-cp38-cp38-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:7da298e1659e45d151b4028ad5c7974917e108afb48731f4ed785d02b6818994"},
+    {file = "lxml-6.0.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:7bf61bc4345c1895221357af8f3e89f8c103d93156ef326532d35c707e2fb19d"},
+    {file = "lxml-6.0.0-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:63b634facdfbad421d4b61c90735688465d4ab3a8853ac22c76ccac2baf98d97"},
+    {file = "lxml-6.0.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:e380e85b93f148ad28ac15f8117e2fd8e5437aa7732d65e260134f83ce67911b"},
+    {file = "lxml-6.0.0-cp38-cp38-win32.whl", hash = "sha256:185efc2fed89cdd97552585c624d3c908f0464090f4b91f7d92f8ed2f3b18f54"},
+    {file = "lxml-6.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:f97487996a39cb18278ca33f7be98198f278d0bc3c5d0fd4d7b3d63646ca3c8a"},
+    {file = "lxml-6.0.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:85b14a4689d5cff426c12eefe750738648706ea2753b20c2f973b2a000d3d261"},
+    {file = "lxml-6.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f64ccf593916e93b8d36ed55401bb7fe9c7d5de3180ce2e10b08f82a8f397316"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:b372d10d17a701b0945f67be58fae4664fd056b85e0ff0fbc1e6c951cdbc0512"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:a674c0948789e9136d69065cc28009c1b1874c6ea340253db58be7622ce6398f"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:edf6e4c8fe14dfe316939711e3ece3f9a20760aabf686051b537a7562f4da91a"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:048a930eb4572829604982e39a0c7289ab5dc8abc7fc9f5aabd6fbc08c154e93"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c0b5fa5eda84057a4f1bbb4bb77a8c28ff20ae7ce211588d698ae453e13c6281"},
+    {file = "lxml-6.0.0-cp39-cp39-manylinux_2_31_armv7l.whl", hash = "sha256:c352fc8f36f7e9727db17adbf93f82499457b3d7e5511368569b4c5bd155a922"},
+    {file = "lxml-6.0.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8db5dc617cb937ae17ff3403c3a70a7de9df4852a046f93e71edaec678f721d0"},
+    {file = "lxml-6.0.0-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:2181e4b1d07dde53986023482673c0f1fba5178ef800f9ab95ad791e8bdded6a"},
+    {file = "lxml-6.0.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:b3c98d5b24c6095e89e03d65d5c574705be3d49c0d8ca10c17a8a4b5201b72f5"},
+    {file = "lxml-6.0.0-cp39-cp39-win32.whl", hash = "sha256:04d67ceee6db4bcb92987ccb16e53bef6b42ced872509f333c04fb58a3315256"},
+    {file = "lxml-6.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:e0b1520ef900e9ef62e392dd3d7ae4f5fa224d1dd62897a792cf353eb20b6cae"},
+    {file = "lxml-6.0.0-cp39-cp39-win_arm64.whl", hash = "sha256:e35e8aaaf3981489f42884b59726693de32dabfc438ac10ef4eb3409961fd402"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:dbdd7679a6f4f08152818043dbb39491d1af3332128b3752c3ec5cebc0011a72"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:40442e2a4456e9910875ac12951476d36c0870dcb38a68719f8c4686609897c4"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:db0efd6bae1c4730b9c863fc4f5f3c0fa3e8f05cae2c44ae141cb9dfc7d091dc"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9ab542c91f5a47aaa58abdd8ea84b498e8e49fe4b883d67800017757a3eb78e8"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:013090383863b72c62a702d07678b658fa2567aa58d373d963cca245b017e065"},
+    {file = "lxml-6.0.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:c86df1c9af35d903d2b52d22ea3e66db8058d21dc0f59842ca5deb0595921141"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:4337e4aec93b7c011f7ee2e357b0d30562edd1955620fdd4aeab6aacd90d43c5"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:ae74f7c762270196d2dda56f8dd7309411f08a4084ff2dfcc0b095a218df2e06"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:059c4cbf3973a621b62ea3132934ae737da2c132a788e6cfb9b08d63a0ef73f9"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:17f090a9bc0ce8da51a5632092f98a7e7f84bca26f33d161a98b57f7fb0004ca"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9da022c14baeec36edfcc8daf0e281e2f55b950249a455776f0d1adeeada4734"},
+    {file = "lxml-6.0.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:a55da151d0b0c6ab176b4e761670ac0e2667817a1e0dadd04a01d0561a219349"},
+    {file = "lxml-6.0.0.tar.gz", hash = "sha256:032e65120339d44cdc3efc326c9f660f5f7205f3a535c1fdbf898b29ea01fb72"},
+]
+
+[package.extras]
+cssselect = ["cssselect (>=0.7)"]
+html-clean = ["lxml_html_clean"]
+html5 = ["html5lib"]
+htmlsoup = ["BeautifulSoup4"]
+
 [[package]]
 name = "markdown"
 version = "3.7"
@@ -1267,6 +1584,19 @@ mkdocs-autorefs = ">=1.4"
 mkdocstrings = ">=0.28.3"
 typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 
+[[package]]
+name = "more-itertools"
+version = "10.7.0"
+description = "More routines for operating on iterables, beyond itertools"
+optional = true
+python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "more_itertools-10.7.0-py3-none-any.whl", hash = "sha256:d43980384673cb07d2f7d2d918c616b30c659c089ee23953f601d6609c67510e"},
+    {file = "more_itertools-10.7.0.tar.gz", hash = "sha256:9fddd5403be01a94b204faadcff459ec3568cf110265d3c54323e1e866ad29d3"},
+]
+
 [[package]]
 name = "multidict"
 version = "6.2.0"
@@ -1825,6 +2155,19 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.4.6,<0.7.0"
 
+[[package]]
+name = "pycparser"
+version = "2.22"
+description = "C parser in Python"
+optional = true
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "(extra == \"salesforce\" or extra == \"all\") and platform_python_implementation != \"PyPy\""
+files = [
+    {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"},
+    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
+]
+
 [[package]]
 name = "pygments"
 version = "2.19.1"
@@ -1840,6 +2183,28 @@ files = [
 [package.extras]
 windows-terminal = ["colorama (>=0.4.6)"]
 
+[[package]]
+name = "pyjwt"
+version = "2.10.1"
+description = "JSON Web Token implementation in Python"
+optional = true
+python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "PyJWT-2.10.1-py3-none-any.whl", hash = "sha256:dcdd193e30abefd5debf142f9adfcdd2b58004e644f25406ffaebd50bd98dacb"},
+    {file = "pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953"},
+]
+
+[package.dependencies]
+cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
+
+[package.extras]
+crypto = ["cryptography (>=3.4.0)"]
+dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
+docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
+tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
+
 [[package]]
 name = "pymdown-extensions"
 version = "10.14.3"
@@ -2049,6 +2414,38 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "requests-file"
+version = "2.1.0"
+description = "File transport adapter for Requests"
+optional = true
+python-versions = "*"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "requests_file-2.1.0-py2.py3-none-any.whl", hash = "sha256:cf270de5a4c5874e84599fc5778303d496c10ae5e870bfa378818f35d21bda5c"},
+    {file = "requests_file-2.1.0.tar.gz", hash = "sha256:0f549a3f3b0699415ac04d167e9cb39bccfb730cb832b4d20be3d9867356e658"},
+]
+
+[package.dependencies]
+requests = ">=1.0.0"
+
+[[package]]
+name = "requests-toolbelt"
+version = "1.0.0"
+description = "A utility belt for advanced users of python-requests"
+optional = true
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"},
+    {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"},
+]
+
+[package.dependencies]
+requests = ">=2.0.1,<3.0.0"
+
 [[package]]
 name = "rsa"
 version = "4.9"
@@ -2065,6 +2462,26 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.1.3"
 
+[[package]]
+name = "simple-salesforce"
+version = "1.12.6"
+description = "A basic Salesforce.com REST API client."
+optional = true
+python-versions = "*"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "simple-salesforce-1.12.6.tar.gz", hash = "sha256:77590606c781905f6b75430562951dd2b062438da7f55fca2b61e4cde31df15b"},
+    {file = "simple_salesforce-1.12.6-py2.py3-none-any.whl", hash = "sha256:66c74bee88d09ace46e4fc9c2f6b47c0d012817a764f70a5455d6dc2c7ed635c"},
+]
+
+[package.dependencies]
+more-itertools = "*"
+pyjwt = {version = "*", extras = ["crypto"]}
+requests = ">=2.22.0"
+typing-extensions = "*"
+zeep = "*"
+
 [[package]]
 name = "six"
 version = "1.17.0"
@@ -2150,7 +2567,7 @@ description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"datasets\" or extra == \"all\" or python_version < \"3.11\""
+markers = "extra == \"datasets\" or extra == \"all\" or extra == \"salesforce\" or python_version < \"3.11\""
 files = [
     {file = "typing_extensions-4.13.0-py3-none-any.whl", hash = "sha256:c8dd92cc0d6425a97c18fbb9d1954e5ff92c1ca881a309c45f06ebc0b79058e5"},
     {file = "typing_extensions-4.13.0.tar.gz", hash = "sha256:0a4ac55a5820789d87e297727d229866c9650f6521b64206413c4fbada24d95b"},
@@ -2461,6 +2878,35 @@ idna = ">=2.0"
 multidict = ">=4.0"
 propcache = ">=0.2.0"
 
+[[package]]
+name = "zeep"
+version = "4.3.1"
+description = "A Python SOAP client"
+optional = true
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"salesforce\" or extra == \"all\""
+files = [
+    {file = "zeep-4.3.1-py3-none-any.whl", hash = "sha256:a637aa7eedb6330bb27e8c94c5233ddf23553904323adf9398f8cf5025acb216"},
+    {file = "zeep-4.3.1.tar.gz", hash = "sha256:f45385e9e1b09d5550e0f51ab9fa7c6842713cab7194139372fd82a99c56a06e"},
+]
+
+[package.dependencies]
+attrs = ">=17.2.0"
+isodate = ">=0.5.4"
+lxml = ">=4.6.0"
+platformdirs = ">=1.4.0"
+pytz = "*"
+requests = ">=2.7.0"
+requests-file = ">=1.5.1"
+requests-toolbelt = ">=0.7.1"
+
+[package.extras]
+async = ["httpx (>=0.15.0)"]
+docs = ["sphinx (>=1.4.0)"]
+test = ["coverage[toml] (==7.6.2)", "flake8 (==7.1.1)", "flake8-blind-except (==0.2.1)", "flake8-debugger (==4.1.2)", "flake8-imports (==0.1.1)", "freezegun (==1.5.1)", "isort (==5.13.2)", "pretend (==1.0.9)", "pytest (==8.3.3)", "pytest-asyncio", "pytest-cov (==5.0.0)", "pytest-httpx", "requests-mock (==1.12.1)"]
+xmlsec = ["xmlsec (>=0.6.1)"]
+
 [[package]]
 name = "zipp"
 version = "3.21.0"
@@ -2483,14 +2929,15 @@ test = ["big-O", "importlib-resources ; python_version < \"3.9\"", "jaraco.funct
 type = ["pytest-mypy"]
 
 [extras]
-all = ["databricks-sdk", "datasets", "faker", "kagglehub"]
+all = ["databricks-sdk", "datasets", "faker", "kagglehub", "simple-salesforce"]
 databricks = ["databricks-sdk"]
 datasets = ["datasets"]
 faker = ["faker"]
 kaggle = ["kagglehub"]
 lance = []
+salesforce = ["simple-salesforce"]
 
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.9,<3.13"
-content-hash = "568b719c5b65713e7ed935ddac5d501f69f94c1f055addebfaae02e63bb17a23"
+content-hash = "3fdb397bb1f9ea104625d5eb8f379396fabf5e30fb0923cd29b5638bdc9fc11d"
diff --git a/pyproject.toml b/pyproject.toml
index c736d03..4ec0815 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,6 +18,7 @@ mkdocstrings = {extras = ["python"], version = "^0.28.0"}
 datasets = {version = "^2.17.0", optional = true}
 databricks-sdk = {version = "^0.28.0", optional = true}
 kagglehub = {extras = ["pandas-datasets"], version = "^0.3.10", optional = true}
+simple-salesforce = {version = "^1.12.0", optional = true}
 
 [tool.poetry.extras]
 faker = ["faker"]
@@ -25,7 +26,8 @@ datasets = ["datasets"]
 databricks = ["databricks-sdk"]
 kaggle = ["kagglehub"]
 lance = ["pylance"]
-all = ["faker", "datasets", "databricks-sdk", "kagglehub"]
+salesforce = ["simple-salesforce"]
+all = ["faker", "datasets", "databricks-sdk", "kagglehub", "simple-salesforce"]
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.0.0"
diff --git a/pyspark_datasources/__init__.py b/pyspark_datasources/__init__.py
index 1540dda..680dcda 100644
--- a/pyspark_datasources/__init__.py
+++ b/pyspark_datasources/__init__.py
@@ -4,5 +4,6 @@
 from .huggingface import HuggingFaceDatasets
 from .kaggle import KaggleDataSource
 from .opensky import OpenSkyDataSource
+from .salesforce import SalesforceDataSource
 from .simplejson import SimpleJsonDataSource
 from .stock import StockDataSource
diff --git a/pyspark_datasources/salesforce.py b/pyspark_datasources/salesforce.py
new file mode 100644
index 0000000..2a6a85e
--- /dev/null
+++ b/pyspark_datasources/salesforce.py
@@ -0,0 +1,399 @@
+import logging
+from dataclasses import dataclass
+from typing import Dict, List, Any
+
+from pyspark.sql.types import StructType
+from pyspark.sql.datasource import DataSource, DataSourceStreamWriter, WriterCommitMessage
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class SalesforceCommitMessage(WriterCommitMessage):
+    """Commit message for Salesforce write operations."""
+    records_written: int
+    batch_id: int
+
+
+class SalesforceDataSource(DataSource):
+    """
+    A Salesforce streaming sink for PySpark to write data to Salesforce objects.
+
+    This data sink enables writing streaming data from Spark to Salesforce using the
+    Salesforce REST API. It supports common Salesforce objects like Account, Contact,
+    Opportunity, and custom objects.
+
+    Note: This is a write-only sink, not a full bidirectional data source.
+
+    Name: `salesforce`
+
+    Notes
+    -----
+    - Requires the `simple-salesforce` library for Salesforce API integration
+    - **Write-only sink**: Only supports streaming write operations (no read operations)
+    - Uses Salesforce username/password/security token authentication
+    - Supports batch writing with Salesforce Composite Tree API for efficient processing
+    - Implements exactly-once semantics through Spark's checkpoint mechanism
+
+    Parameters
+    ----------
+    username : str
+        Salesforce username (email address)
+    password : str
+        Salesforce password
+    security_token : str
+        Salesforce security token (obtained from Salesforce setup)
+    salesforce_object : str, optional
+        Target Salesforce object name (default: "Account")
+    batch_size : str, optional
+        Number of records to process per batch (default: "200")
+    instance_url : str, optional
+        Custom Salesforce instance URL (auto-detected if not provided)
+    schema : str, optional
+        Custom schema definition for the Salesforce object. If not provided,
+        uses the default Account schema. Should be in Spark SQL DDL format.
+        Example: "Name STRING NOT NULL, Industry STRING, AnnualRevenue DOUBLE"
+
+    Examples
+    --------
+    Register the Salesforce sink:
+
+    >>> from pyspark_datasources import SalesforceDataSource
+    >>> spark.dataSource.register(SalesforceDataSource)
+
+    Write streaming data to Salesforce Accounts:
+
+    >>> from pyspark.sql import SparkSession
+    >>> from pyspark.sql.functions import col, lit
+    >>> 
+    >>> spark = SparkSession.builder.appName("SalesforceExample").getOrCreate()
+    >>> spark.dataSource.register(SalesforceDataSource)
+    >>> 
+    >>> # Create sample streaming data
+    >>> streaming_df = spark.readStream.format("rate").load()
+    >>> account_data = streaming_df.select(
+    ...     col("value").cast("string").alias("Name"),
+    ...     lit("Technology").alias("Industry"),
+    ...     (col("value") * 100000).cast("double").alias("AnnualRevenue")
+    ... )
+    >>> 
+    >>> # Write to Salesforce using the sink
+    >>> query = account_data.writeStream \\
+    ...     .format("salesforce") \\
+    ...     .option("username", "your-username@company.com") \\
+    ...     .option("password", "your-password") \\
+    ...     .option("security_token", "your-security-token") \\
+    ...     .option("salesforce_object", "Account") \\
+    ...     .option("batch_size", "100") \\
+    ...     .option("checkpointLocation", "/path/to/checkpoint") \\
+    ...     .start()
+
+    Write to Salesforce Contacts:
+
+    >>> contact_data = streaming_df.select(
+    ...     col("value").cast("string").alias("FirstName"),
+    ...     lit("Doe").alias("LastName"),
+    ...     lit("contact@example.com").alias("Email")
+    ... )
+    >>> 
+    >>> query = contact_data.writeStream \\
+    ...     .format("salesforce") \\
+    ...     .option("username", "your-username@company.com") \\
+    ...     .option("password", "your-password") \\
+    ...     .option("security_token", "your-security-token") \\
+    ...     .option("salesforce_object", "Contact") \\
+    ...     .option("checkpointLocation", "/path/to/checkpoint") \\
+    ...     .start()
+
+    Write to custom Salesforce objects:
+
+    >>> custom_data = streaming_df.select(
+    ...     col("value").cast("string").alias("Custom_Field__c"),
+    ...     lit("Custom Value").alias("Another_Field__c")
+    ... )
+    >>> 
+    >>> query = custom_data.writeStream \\
+    ...     .format("salesforce") \\
+    ...     .option("username", "your-username@company.com") \\
+    ...     .option("password", "your-password") \\
+    ...     .option("security_token", "your-security-token") \\
+    ...     .option("salesforce_object", "Custom_Object__c") \\
+    ...     .option("checkpointLocation", "/path/to/checkpoint") \\
+    ...     .start()
+
+    Using custom schema for specific Salesforce objects:
+
+    >>> # Define schema for Contact object as a DDL string
+    >>> contact_schema = "FirstName STRING NOT NULL, LastName STRING NOT NULL, Email STRING, Phone STRING"
+    >>>
+    >>> query = contact_data.writeStream \\
+    ...     .format("salesforce") \\
+    ...     .option("username", "your-username@company.com") \\
+    ...     .option("password", "your-password") \\
+    ...     .option("security_token", "your-security-token") \\
+    ...     .option("salesforce_object", "Contact") \\
+    ...     .option("schema", "FirstName STRING NOT NULL, LastName STRING NOT NULL, Email STRING, Phone STRING") \\
+    ...     .option("batch_size", "50") \\
+    ...     .option("checkpointLocation", "/path/to/checkpoint") \\
+    ...     .start()
+
+    Using schema with Opportunity object:
+
+    >>> opportunity_data = streaming_df.select(
+    ...     col("name").alias("Name"),
+    ...     col("amount").alias("Amount"),
+    ...     col("stage").alias("StageName"),
+    ...     col("close_date").alias("CloseDate")
+    ... )
+    >>> 
+    >>> query = opportunity_data.writeStream \\
+    ...     .format("salesforce") \\
+    ...     .option("username", "your-username@company.com") \\
+    ...     .option("password", "your-password") \\
+    ...     .option("security_token", "your-security-token") \\
+    ...     .option("salesforce_object", "Opportunity") \\
+    ...     .option("schema", "Name STRING NOT NULL, Amount DOUBLE, StageName STRING NOT NULL, CloseDate DATE") \\
+    ...     .option("checkpointLocation", "/path/to/checkpoint") \\
+    ...     .start()
+    
+    Key Features:
+    
+    - **Write-only sink**: Designed specifically for writing data to Salesforce
+    - **Batch processing**: Uses Salesforce Composite Tree API for efficient bulk writes
+    - **Exactly-once semantics**: Integrates with Spark's checkpoint mechanism
+    - **Error handling**: Graceful fallback to individual record creation if batch fails
+    - **Flexible schema**: Supports any Salesforce object with custom schema definition
+    """
+
+    @classmethod
+    def name(cls) -> str:
+        """Return the short name for this Salesforce sink."""
+        return "salesforce"
+
+    def schema(self) -> str:
+        """
+        Return the schema for Salesforce objects.
+
+        If the user provides a 'schema' option, use it.
+        Otherwise, return the default Account schema.
+        """
+        user_schema = self.options.get("schema")
+        if user_schema:
+            return user_schema
+        return """
+            Name STRING NOT NULL,
+            Industry STRING,
+            Phone STRING,
+            Website STRING,
+            AnnualRevenue DOUBLE,
+            NumberOfEmployees INT,
+            BillingStreet STRING,
+            BillingCity STRING,
+            BillingState STRING,
+            BillingPostalCode STRING,
+            BillingCountry STRING
+        """
+
+    def streamWriter(self, schema: StructType, overwrite: bool) -> "SalesforceStreamWriter":
+        """Create a stream writer for Salesforce sink integration."""
+        return SalesforceStreamWriter(schema, self.options)
+
+
+class SalesforceStreamWriter(DataSourceStreamWriter):
+    """Stream writer implementation for Salesforce sink integration."""
+
+    def __init__(self, schema: StructType, options: Dict[str, str]):
+        self.schema = schema
+        self.options = options
+        
+        # Extract Salesforce configuration
+        self.username = options.get("username")
+        self.password = options.get("password")
+        self.security_token = options.get("security_token")
+        self.instance_url = options.get("instance_url")
+        self.salesforce_object = options.get("salesforce_object", "Account")
+        self.batch_size = int(options.get("batch_size", "200"))
+        
+        # Validate required options
+        if not all([self.username, self.password, self.security_token]):
+            raise ValueError(
+                "Salesforce username, password, and security_token are required. "
+                "Set them using .option() method in your streaming query."
+            )
+        
+        logger.info(f"Initializing Salesforce writer for object '{self.salesforce_object}'")
+
+    def write(self, iterator) -> SalesforceCommitMessage:
+        """Write data to Salesforce."""
+        # Import here to avoid serialization issues
+        try:
+            from simple_salesforce import Salesforce
+        except ImportError:
+            raise ImportError(
+                "simple-salesforce library is required for Salesforce integration. "
+                "Install it with: pip install simple-salesforce"
+            )
+        
+        from pyspark import TaskContext
+        
+        # Get task context for batch identification
+        context = TaskContext.get()
+        batch_id = context.taskAttemptId()
+        
+        # Connect to Salesforce
+        try:
+            sf_kwargs = {
+                'username': self.username,
+                'password': self.password,
+                'security_token': self.security_token
+            }
+            if self.instance_url:
+                sf_kwargs['instance_url'] = self.instance_url
+                
+            sf = Salesforce(**sf_kwargs)
+            logger.info(f"✓ Connected to Salesforce (batch {batch_id})")
+        except Exception as e:
+            logger.error(f"Failed to connect to Salesforce: {str(e)}")
+            raise ConnectionError(f"Salesforce connection failed: {str(e)}")
+        
+        # Convert rows to Salesforce records and write in batches to avoid memory issues
+        records_buffer = []
+        total_records_written = 0
+
+        def flush_buffer():
+            nonlocal total_records_written
+            if records_buffer:
+                try:
+                    written = self._write_to_salesforce(sf, records_buffer, batch_id)
+                    logger.info(f"✅ Batch {batch_id}: Successfully wrote {written} records (buffer flush)")
+                    total_records_written += written
+                except Exception as e:
+                    logger.error(f"❌ Batch {batch_id}: Failed to write records during buffer flush: {str(e)}")
+                    raise
+                records_buffer.clear()
+
+        for row in iterator:
+            try:
+                record = self._convert_row_to_salesforce_record(row)
+                if record:  # Only add non-empty records
+                    records_buffer.append(record)
+                    if len(records_buffer) >= self.batch_size:
+                        flush_buffer()
+            except Exception as e:
+                logger.warning(f"Failed to convert row to Salesforce record: {str(e)}")
+
+        # Flush any remaining records in the buffer
+        if records_buffer:
+            flush_buffer()
+
+        if total_records_written == 0:
+            logger.info(f"No valid records to write in batch {batch_id}")
+        else:
+            logger.info(f"✅ Batch {batch_id}: Successfully wrote {total_records_written} records (total)")
+
+        return SalesforceCommitMessage(records_written=total_records_written, batch_id=batch_id)
+
+    def _convert_row_to_salesforce_record(self, row) -> Dict[str, Any]:
+        """Convert a Spark Row to a Salesforce record format."""
+        record = {}
+        
+        for field in self.schema.fields:
+            field_name = field.name
+            try:
+                # Use getattr for safe field access
+                value = getattr(row, field_name, None)
+                
+                if value is not None:
+                    # Convert value based on field type
+                    if hasattr(value, 'isoformat'):  # datetime objects
+                        record[field_name] = value.isoformat()
+                    elif isinstance(value, (int, float)):
+                        record[field_name] = value
+                    else:
+                        record[field_name] = str(value)
+                        
+            except Exception as e:
+                logger.warning(f"Failed to convert field '{field_name}': {str(e)}")
+        
+        return record
+
+    def _write_to_salesforce(self, sf, records: List[Dict[str, Any]], batch_id: int) -> int:
+        """Write records to Salesforce using REST API."""
+        success_count = 0
+        
+        # Process records in batches using sObject Collections API
+        for i in range(0, len(records), self.batch_size):
+            batch_records = records[i:i + self.batch_size]
+            
+            try:
+                # Use Composite Tree API for batch creation (up to 200 records)
+                # Prepare records for batch API
+                collection_records = []
+                for idx, record in enumerate(batch_records):
+                    # Add required attributes for Composite Tree API
+                    record_with_attributes = {
+                        "attributes": {
+                            "type": self.salesforce_object,
+                            "referenceId": f"ref{i + idx}"
+                        },
+                        **record
+                    }
+                    collection_records.append(record_with_attributes)
+                
+                # Make batch API call using Composite Tree API
+                # This API is specifically designed for batch inserts
+                payload = {
+                    "records": collection_records
+                }
+                
+                response = sf.restful(
+                    f'composite/tree/{self.salesforce_object}',
+                    method='POST',
+                    json=payload
+                )
+                
+                # Count successful records
+                # Composite Tree API returns a different response format
+                if isinstance(response, dict):
+                    # Check if the batch was successful
+                    if response.get('hasErrors', True) is False:
+                        # All records in the batch were created successfully
+                        success_count += len(batch_records)
+                    else:
+                        # Some records failed, check individual results
+                        results = response.get('results', [])
+                        for result in results:
+                            if 'id' in result:
+                                success_count += 1
+                            else:
+                                errors = result.get('errors', [])
+                                for error in errors:
+                                    logger.warning(f"Failed to create record {result.get('referenceId', 'unknown')}: {error.get('message', 'Unknown error')}")
+                else:
+                    logger.error(f"Unexpected response format: {response}")
+                    
+            except Exception as e:
+                logger.error(f"Error in batch creation for batch {i//self.batch_size + 1}: {str(e)}")
+                # Fallback to individual record creation for this batch
+                try:
+                    sf_object = getattr(sf, self.salesforce_object)
+                    for j, record in enumerate(batch_records):
+                        try:
+                            # Create the record in Salesforce
+                            result = sf_object.create(record)
+                            
+                            if result.get('success'):
+                                success_count += 1
+                            else:
+                                logger.warning(f"Failed to create record {i+j}: {result.get('errors', 'Unknown error')}")
+                                
+                        except Exception as e:
+                            logger.error(f"Error creating record {i+j}: {str(e)}")
+                except AttributeError:
+                    raise ValueError(f"Salesforce object '{self.salesforce_object}' not found")
+            
+            # Log progress for large batches
+            if len(records) > 50 and (i + self.batch_size) % 100 == 0:
+                logger.info(f"Batch {batch_id}: Processed {i + self.batch_size}/{len(records)} records")
+        
+        return success_count
diff --git a/tests/test_data_sources.py b/tests/test_data_sources.py
index ad6a2b0..54cb133 100644
--- a/tests/test_data_sources.py
+++ b/tests/test_data_sources.py
@@ -64,3 +64,30 @@ def test_opensky_datasource_stream(spark):
     result.show()
     assert len(result.columns) == 18  # Check schema has expected number of fields
     assert result.count() > 0  # Verify we got some data
+
+
+def test_salesforce_datasource_registration(spark):
+    """Test that Salesforce DataSource can be registered and validates required options."""
+    spark.dataSource.register(SalesforceDataSource)
+    
+    # Test that the datasource is registered with correct name
+    assert SalesforceDataSource.name() == "salesforce"
+    
+    # Test that the data source is streaming-only (no batch writer)
+    from pyspark.sql.functions import lit
+    
+    try:
+        # Try to use batch write - should fail since we only support streaming
+        df = spark.range(1).select(
+            lit("Test Company").alias("Name"),
+            lit("Technology").alias("Industry"),
+            lit(50000.0).alias("AnnualRevenue")
+        )
+        
+        df.write.format("salesforce").mode("append").save()
+        assert False, "Should have raised error - Salesforce DataSource only supports streaming"
+    except Exception as e:
+        # This is expected - Salesforce DataSource only supports streaming writes
+        error_msg = str(e).lower()
+        # The error can be about unsupported mode or missing writer
+        assert "unsupported" in error_msg or "writer" in error_msg or "not implemented" in error_msg