### Main script for MFA authentication examples

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect

Command-line interface to run different MFA authentication examples. Usage: python auth_by_mfa.py <example> [passcode]. Examples include push, passcode, password, callback, and cache.

```python
if __name__ == "__main__":
    import sys

    print("Snowflake MFA Authentication Examples")
    print("=" * 40)

    if len(sys.argv) < 2:
        print(
            """
Usage: python auth_by_mfa.py <example> [passcode]

Examples:
  python auth_by_mfa.py push              # MFA with push notification
  python auth_by_mfa.py passcode 123456   # MFA with TOTP passcode
  python auth_by_mfa.py password 123456   # MFA with passcode in password
  python auth_by_mfa.py callback          # MFA with callback function
  python auth_by_mfa.py cache             # MFA with token caching
"""
        )
        sys.exit(1)

    example = sys.argv[1].lower()

    if example == "push":
        connect_with_mfa_push()
    elif example == "passcode":
        if len(sys.argv) < 3:
            print("Error: Please provide a passcode")
            sys.exit(1)
        connect_with_mfa_passcode(sys.argv[2])
    elif example == "password":
        if len(sys.argv) < 3:
            print("Error: Please provide a passcode")
            sys.exit(1)
        connect_with_passcode_in_password(sys.argv[2])
    elif example == "callback":
        connect_with_mfa_callback()
    elif example == "cache":
        connect_with_mfa_token_caching()
    else:
        print(f"Unknown example: {example}")
        sys.exit(1)
```

--------------------------------

### Get login information from environment variables

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect

Example of retrieving login information such as password and warehouse from environment variables.

```python
PASSWORD = os.getenv('SNOWSQL_PWD')
WAREHOUSE = os.getenv('WAREHOUSE')
...
```

--------------------------------

### Run a query

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-asyncio

Example of executing a query and fetching results using the asyncio connector.

```python
async with conn.cursor() as cur:
    await cur.execute("SELECT col1, col2 FROM testtable")
    async for col1, col2 in cur:
        print(f"{col1}, {col2}")
```

--------------------------------

### Main example class to create and query a table

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

This is the main example program that uses the Snowflake Python Connector. It creates a table named test_table, inserts two rows, and then queries the table, printing each row. The main block instantiates the class and calls its main method.

```python
import sys

# -- (> ---------------------- SECTION=import_connector ---------------------
import snowflake.connector
# -- <) ---------------------------- END_SECTION ----------------------------


# Import the base class that contains methods used in many tests and code
# examples.
from python_veritas_base import python_veritas_base


class python_connector_example (python_veritas_base):

  """
  PURPOSE:
      This is a simple example program that shows how to use the Snowflake
      Python Connector to create and query a table.
  """

  def __init__(self):
    pass


  def do_the_real_work(self, conn):

    """
    INPUTS:
        conn is a Connection object returned from snowflake.connector.connect().
    """

    print("\nCreating table test_table...")
    # -- (> ----------------------- SECTION=create_table ---------------------
    conn.cursor().execute(
        "CREATE OR REPLACE TABLE "
        "test_table(col1 integer, col2 string)")

    conn.cursor().execute(
        "INSERT INTO test_table(col1, col2) VALUES " +
        "    (123, 'test string1'), " +
        "    (456, 'test string2')")
    # -- <) ---------------------------- END_SECTION -------------------------


    print("\nSelecting from test_table...")
    # -- (> ----------------------- SECTION=querying_data --------------------
    cur = conn.cursor()
    try:
        cur.execute("SELECT col1, col2 FROM test_table ORDER BY col1")
        for (col1, col2) in cur:
            print('{0}, {1}'.format(col1, col2))
    finally:
        cur.close()
    # -- <) ---------------------------- END_SECTION -------------------------




# ============================================================================

if __name__ == '__main__':

    test_case = python_connector_example()
    test_case.main(sys.argv)

```

--------------------------------

### Install and test Snowflake Connector for Python 5.0.0

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-upgrade

Install the connector, verify the version, and run tests with deprecation warnings treated as errors. The printed version should be 5.0.0.

```bash
pip install --upgrade snowflake-connector-python
python -c "import snowflake.connector; print(snowflake.connector.__version__)"
python -W error::DeprecationWarning -m pytest
```

--------------------------------

### Install legacy secure-local-storage and pandas extras (pre-5.0)

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-pandas

Before version 5.0, Linux token caching required the secure-local-storage extra. This command installs both that extra and pandas. See the MFA token caching documentation for details.

```bash
pip install "snowflake-connector-python[secure-local-storage,pandas]"
```

--------------------------------

### Longer Snowflake Python Connector example

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

A comprehensive example demonstrating connecting to Snowflake, creating warehouse/database/schema, creating tables, inserting data, copying from internal and external stages, querying, binding parameters, retrieving column names, catching syntax errors, retrieving query ID, and closing the connection.

```python
#!/usr/bin/env python
#
# Snowflake Connector for Python Sample Program
#

# Logging
import logging
logging.basicConfig(
    filename='/tmp/snowflake_python_connector.log',
    level=logging.INFO)

import snowflake.connector

# Connecting to Snowflake
con = snowflake.connector.connect()

# Creating a database, schema, and warehouse if none exists
con.cursor().execute("CREATE WAREHOUSE IF NOT EXISTS tiny_warehouse")
con.cursor().execute("CREATE DATABASE IF NOT EXISTS testdb")
con.cursor().execute("USE DATABASE testdb")
con.cursor().execute("CREATE SCHEMA IF NOT EXISTS testschema")

# Using the database, schema and warehouse
con.cursor().execute("USE WAREHOUSE tiny_warehouse")
con.cursor().execute("USE SCHEMA testdb.testschema")

# Creating a table and inserting data
con.cursor().execute(
    "CREATE OR REPLACE TABLE "
    "testtable(col1 integer, col2 string)")
con.cursor().execute(
    "INSERT INTO testtable(col1, col2) "
    "VALUES(123, 'test string1'),(456, 'test string2')")

# Copying data from internal stage (for testtable table)
con.cursor().execute("PUT file:///tmp/data0/file* @%testtable")
con.cursor().execute("COPY INTO testtable")

# Copying data from external stage (S3 bucket -
# replace <s3_bucket> with the name of your bucket)
con.cursor().execute("""
COPY INTO testtable FROM s3://<s3_bucket>/data/
     STORAGE_INTEGRATION = myint
     FILE_FORMAT=(field_delimiter=',')
""")

# Querying data
cur = con.cursor()
try:
    cur.execute("SELECT col1, col2 FROM testtable")
    for (col1, col2) in cur:
        print('{0}, {1}'.format(col1, col2))
finally:
    cur.close()

# Binding data
con.cursor().execute(
    "INSERT INTO testtable(col1, col2) "
    "VALUES(%(col1)s, %(col2)s)", {
        'col1': 789,
        'col2': 'test string3',
        })

# Retrieving column names
cur = con.cursor()
cur.execute("SELECT * FROM testtable")
print(','.join([col[0] for col in cur.description]))

# Catching syntax errors
cur = con.cursor()
try:
    cur.execute("SELECT * FROM testtable")
except snowflake.connector.errors.ProgrammingError as e:
    # default error message
    print(e)
    # user error message
    print('Error {0} ({1}): {2} ({3})'.format(e.errno, e.sqlstate, e.msg, e.sfqid))
finally:
    cur.close()

# Retrieving the Snowflake query ID
cur = con.cursor()
cur.execute("SELECT * FROM testtable")
print(cur.sfqid)

# Closing the connection
con.close()
```

--------------------------------

### Unsafe SQL binding with .format() (UNSAFE EXAMPLE)

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Unsafe example using Python .format() to bind data, risking SQL injection.

```python
# Binding data (UNSAFE EXAMPLE)
con.cursor().execute(
    "INSERT INTO testtable(col1, col2) "
    "VALUES({col1}, '{col2}')".format(
        col1=789,
        col2='test string3')
    )
```

--------------------------------

### Unsafe SQL binding with % formatting and positional args (UNSAFE EXAMPLE)

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Unsafe example using Python % formatting with positional arguments to bind data, risking SQL injection.

```python
# Binding data (UNSAFE EXAMPLE)
con.cursor().execute(
    "INSERT INTO testtable(col1, col2) "
    "VALUES(%d, '%s')" % (
        789,
        'test string3'
    ))
```

--------------------------------

### Unsafe SQL binding with % formatting (UNSAFE EXAMPLE)

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Unsafe example using Python % formatting to bind data, risking SQL injection.

```python
# Binding data (UNSAFE EXAMPLE)
con.cursor().execute(
    "INSERT INTO testtable(col1, col2) "
    "VALUES(%(col1)d, '%(col2)s')" % {
        'col1': 789,
        'col2': 'test string3'
    })
```

--------------------------------

### Set warehouse, database, and schema

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Use these commands to set the warehouse, database, and schema for the session. The example uses the database 'testdb_mg', schema 'testschema_mg', and warehouse 'tiny_warehouse_mg'.

```python
conn.cursor().execute("USE WAREHOUSE tiny_warehouse_mg")
conn.cursor().execute("USE DATABASE testdb_mg")
conn.cursor().execute("USE SCHEMA testdb_mg.testschema_mg")
```

--------------------------------

### connect() - account parameter usage

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-api

Examples of using the account parameter with the connect method, showing both account name and account locator formats.

```APIDOC
## connect() - account parameter usage

### Description
Examples of using the account parameter with the connect method, showing both account name and account locator formats.

### Method
connect

### Parameters
#### account (string) - Required
- Specify your account identifier. The account identifier does not include the `snowflakecomputing.com` domain name. Snowflake automatically appends this when creating the connection.

### Request Example
```python
ctx = snowflake.connector.connect(
    user='<user_name>',
    password='<password>',
    account='myorganization-myaccount',
    ... )
```

### Request Example (account locator)
```python
ctx = snowflake.connector.connect(
    user='<user_name>',
    password='<password>',
    account='xy12345',
    ... )
```
```

--------------------------------

### Install pandas extra for Snowflake Connector for Python

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-pandas

Install the pandas-compatible version of the connector. The square brackets are required and must be quoted to prevent wildcard interpretation. Token caching is included; no secure-local-storage extra is published.

```bash
pip install "snowflake-connector-python[pandas]"
```

--------------------------------

### Use DictCursor

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-asyncio

Example of using DictCursor to fetch rows as dictionaries.

```python
from snowflake.connector.aio import DictCursor

async with conn.cursor(DictCursor) as cur:
    await cur.execute("SELECT col1, col2 FROM testtable")
    print(await cur.fetchone())
```

--------------------------------

### Section marker example

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Shows the format of section markers used in the sample code to identify importable sections. These markers are not required in user code.

```python
# -- (> ---------------------- SECTION=import_connector ---------------------
...
# -- <) ---------------------------- END_SECTION ----------------------------
```

--------------------------------

### Run python_connector_example.py with command-line arguments

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Executes the sample program with required arguments for warehouse, database, schema, account, and user. Warning: this deletes the warehouse, database, and schema at the end of the program, so do not use an existing database name.

```bash
python3 python_connector_example.py --warehouse <unique_warehouse_name> --database <new_warehouse_zzz_test> --schema <new_schema_zzz_test> --account myorganization-myaccount --user MyUserName
```

--------------------------------

### Install the latest Python Connector with pip

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-install

Use this command to install the latest version of the Snowflake Python Connector. Note that pip install --upgrade snowflake-connector-python installs version 5.x, which may break Snowpark for Python, Snowflake ML, Snowflake SQLAlchemy, and Snowflake CLI. Pin a release before 5.0 if you need the previous connector, for example snowflake-connector-python>=4,<5.

```bash
pip install snowflake-connector-python
```

--------------------------------

### Set up test environment

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Sets up the environment for running a test by creating a temporary warehouse, database, and schema. This method can be overridden for specific test/demo needs.

```python
    def set_up(self, connection):

        """
        PURPOSE:
            Set up to run a test. You can override this method with one
            appropriate to your test/demo.
        """

        # Create a temporary warehouse, database, and schema.
        self.create_warehouse_database_and_schema(connection)
```

--------------------------------

### Retrieve result batches as PyArrow tables

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-distributed-fetch

Use fetch_arrow_all() to get a PyArrow table with all results, or fetch_arrow_batches() to iterate over PyArrow tables for each result batch. The example shows both methods after executing a query.

```python
with connect(...) as conn:
 with conn.cursor() as cur:
     # Execute a query.
     cur.execute('select seq4() as n from table(generator(rowcount => 100000));')

     # Return a PyArrow table containing all of the results.
     table = cur.fetch_arrow_all()

     # Iterate over a list of PyArrow tables for result batches.
     for table_for_batch in cur.fetch_arrow_batches():
       my_pyarrow_table_processing_function(table_for_batch)
```

--------------------------------

### Get AWS credentials from environment variables

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect

Example of retrieving AWS access key ID and secret access key from environment variables, needed when copying data from your own Amazon S3 bucket.

```python
import os

AWS_ACCESS_KEY_ID = os.getenv('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.getenv('AWS_SECRET_ACCESS_KEY')
```

--------------------------------

### Retrieve result batches as ResultBatch objects

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-distributed-fetch

After executing a query, call get_result_batches() on the Cursor object to get a list of ResultBatch objects. The example splits the list into two lists to distribute work between two workers.

```python
with connect(...) as conn:
 with conn.cursor() as cur:
     # Execute a query.
     cur.execute('select seq4() as n from table(generator(rowcount => 100000));')

     # Get the list of result batches
     result_batch_list = cur.get_result_batches()

     # Get the number of result batches in the list.
     num_result_batches = len(result_batch_list)

     # Split the list of result batches into two
     # to distribute the work of fetching results
     # between two workers.
     result_batch_list_1 = result_batch_list[:: 2]
     result_batch_list_2 = result_batch_list[1 :: 2]
```

--------------------------------

### Base class methods for setup and cleanup

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

These methods are part of the python_veritas_base class. The default run method executes a simple SQL command (SELECT PI()) to verify the connection. The create_warehouse_database_and_schema method creates a warehouse, database, and schema if they don't exist, and then uses them. The drop_warehouse_database_and_schema method drops the schema, database, and warehouse. The clean_up method calls the drop method.

```python
        """
        PURPOSE:
            Your sub-class should override this to include the code required for
            your documentation sample or your test case.
            This default method does a very simple self-test that shows that the
            connection was successful.
        """

        # Create a cursor for this connection.
        cursor1 = conn.cursor()
        # This is an example of an SQL statement we might want to run.
        command = "SELECT PI()"
        # Run the statement.
        cursor1.execute(command)
        # Get the results (should be only one):
        for row in cursor1:
            print(row[0])
        # Close this cursor.
        cursor1.close()


    def clean_up(self, connection):

        """
        PURPOSE:
            Clean up after a test. You can override this method with one
            appropriate to your test/demo.
        """

        # Create a temporary warehouse, database, and schema.
        self.drop_warehouse_database_and_schema(connection)


    def create_warehouse_database_and_schema(self, conn):

        """
        PURPOSE:
            Create the temporary schema, database, and warehouse that we use
            for most tests/demos.
        """

        # Create a database, schema, and warehouse if they don't already exist.
        print("\nCreating warehouse, database, schema...")
        # -- (> ------------- SECTION=create_warehouse_database_schema -------
        conn.cursor().execute("CREATE WAREHOUSE IF NOT EXISTS tiny_warehouse_mg")
        conn.cursor().execute("CREATE DATABASE IF NOT EXISTS testdb_mg")
        conn.cursor().execute("USE DATABASE testdb_mg")
        conn.cursor().execute("CREATE SCHEMA IF NOT EXISTS testschema_mg")
        # -- <) ---------------------------- END_SECTION ---------------------

        # -- (> --------------- SECTION=use_warehouse_database_schema --------
        conn.cursor().execute("USE WAREHOUSE tiny_warehouse_mg")
        conn.cursor().execute("USE DATABASE testdb_mg")
        conn.cursor().execute("USE SCHEMA testdb_mg.testschema_mg")
        # -- <) ---------------------------- END_SECTION ---------------------


    def drop_warehouse_database_and_schema(self, conn):

        """
        PURPOSE:
            Drop the temporary schema, database, and warehouse that we create
            for most tests/demos.
        """

        # -- (> ------------- SECTION=drop_warehouse_database_schema ---------
        conn.cursor().execute("DROP SCHEMA IF EXISTS testschema_mg")
        conn.cursor().execute("DROP DATABASE IF EXISTS testdb_mg")
        conn.cursor().execute("DROP WAREHOUSE IF EXISTS tiny_warehouse_mg")
        # -- <) ---------------------------- END_SECTION ---------------------


# ----------------------------------------------------------------------------

if __name__ == '__main__':
    pvb = python_veritas_base()
    pvb.main(sys.argv)

```

--------------------------------

### Sample program output

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Expected output when running the sample program, showing connection, object creation, table creation, selection results, and connection closing.

```text
Connecting...

Creating warehouse, database, schema...

Creating table test_table...

Selecting from test_table...
123, test string1
456, test string2

Closing connection...
```

--------------------------------

### Install FIPS-supporting version on Windows PowerShell

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-install

Set the SNOWFLAKE_FIPS environment variable in PowerShell, then run the same install command as on Linux/macOS. This version doesn't build on Windows on ARM. On Windows, the install places the module's shared libraries next to the connector.

```powershell
$env:SNOWFLAKE_FIPS = "1"
python -m pip install --no-binary snowflake-connector-python snowflake-connector-python
```

--------------------------------

### write_pandas example: Write pandas DataFrame to Snowflake table

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-api

Example from the write_pandas function documentation. It creates a connection, builds a DataFrame, and writes it to the 'customers' table. The connection object is created with placeholder arguments.

```python
import pandas
from snowflake.connector.pandas_tools import write_pandas

# Create the connection to the Snowflake database.
cnx = snowflake.connector.connect(...)

# Create a DataFrame containing data about customers
df = pandas.DataFrame([('Mark', 10), ('Luke', 20)], columns=['name', 'balance'])

# Write the data from the DataFrame to the table named "customers".
success, nchunks, nrows, _ = write_pandas(cnx, df, 'customers')
```

--------------------------------

### executemany with qmark binding

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-api

Example showing how to use executemany with qmark binding. Requires setting connector.paramstyle='qmark'. Demonstrates passing a list of lists and a tuple of tuples as sequences of parameters. Internally, multiple execute calls are made and the last result set remains.

```python
# This example uses qmark (question mark) binding, so
# you must configure the connector to use this binding style.
from snowflake import connector
connector.paramstyle='qmark'

stmt1 = "create table testy (V1 varchar, V2 varchar)"
cs.execute(stmt1)

# A list of lists
sequence_of_parameters1 = [ ['Smith', 'Ann'], ['Jones', 'Ed'] ]
# A tuple of tuples
sequence_of_parameters2 = ( ('Cho', 'Kim'), ('Cooper', 'Pat') )

stmt2 = "insert into testy (v1, v2) values (?, ?)"
cs.executemany(stmt2, sequence_of_parameters1)
cs.executemany(stmt2, sequence_of_parameters2)
```

--------------------------------

### Open a connection with async with

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-asyncio

Use async with snowflake.connector.aio.connect() to open a session when entering the block and close it when leaving. The connection parameters are the same as for the synchronous connector.

```python
async with snowflake.connector.aio.connect() as conn:
    ...
```

--------------------------------

### Connect using account locator

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-api

Example of connecting to Snowflake using an account locator (e.g., 'xy12345'). This example uses an account in the AWS US West (Oregon) region; other regions or cloud providers may require additional segments after the account locator.

```python
ctx = snowflake.connector.connect(
    user='<user_name>',
    password='<password>',
    account='xy12345',
    ... )
```

--------------------------------

### Create warehouse, database, and schema with Python Connector

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Creates a warehouse named tiny_warehouse_mg, a database named testdb_mg, and a schema named testschema_mg. Executes USE DATABASE before CREATE SCHEMA to ensure the schema is created in the correct database.

```python
conn.cursor().execute("CREATE WAREHOUSE IF NOT EXISTS tiny_warehouse_mg")
conn.cursor().execute("CREATE DATABASE IF NOT EXISTS testdb_mg")
conn.cursor().execute("USE DATABASE testdb_mg")
conn.cursor().execute("CREATE SCHEMA IF NOT EXISTS testschema_mg")
```

--------------------------------

### Create a Snowflake connection from environment and command-line parameters

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Creates a connection to Snowflake using account identifier and login information from environment variables and command-line parameters. Requires at least 11 command-line arguments and the SNOWSQL_PWD environment variable. Exits with error codes -1 and -2 on missing parameters or password.

```python
    def create_connection(self, argv):

        """
        PURPOSE:
            This gets account identifier and login information from the
            environment variables and command-line parameters, connects to the
            server, and returns the connection object.
        INPUTS:
            argv: This is usually sys.argv, which contains the command-line
                  parameters. It could be an equivalent substitute if you get
                  the parameter information from another source.
        RETURNS:
            A connection.
        """

        # Get account identifier and login information from environment variables and command-line parameters.
        # For information about account identifiers, see
        # https://docs.snowflake.com/en/user-guide/admin-account-identifier.html .
        # -- (> ----------------------- SECTION=set_login_info ---------------

        # Get the password from an appropriate environment variable, if
        # available.
        PASSWORD = os.getenv('SNOWSQL_PWD')

        # Get the other login info etc. from the command line.
        if len(argv) < 11:
            msg = "ERROR: Please pass the following command-line parameters:\n"
            msg += "--warehouse <warehouse> --database <db> --schema <schema> "
            msg += "--user <user> --account <account_identifier> "
            print(msg)
            sys.exit(-1)
        else:
            connection_parameters = self.args_to_properties(argv)
            USER = connection_parameters["user"]
            ACCOUNT = connection_parameters["account"]
            WAREHOUSE = connection_parameters["warehouse"]
            DATABASE = connection_parameters["database"]
            SCHEMA = connection_parameters["schema"]
            # Optional: for internal testing only.
            try:
                PORT = connection_parameters["port"]
            except:
                PORT = ""
            try:
                PROTOCOL = connection_parameters["protocol"]
            except:
                PROTOCOL = ""

        # If the password is set by both command line and env var, the
        # command-line value takes precedence over (is written over) the
        # env var value.

        # If the password wasn't set either in the environment var or on
        # the command line...
        if PASSWORD is None or PASSWORD == '':
            print("ERROR: Set password, e.g. with SNOWSQL_PWD environment variable")
            sys.exit(-2)
        # -- <) ---------------------------- END_SECTION ---------------------

        # Optional diagnostic:
        #print("USER:", USER)
        #print("ACCOUNT:", ACCOUNT)
        #print("WAREHOUSE:", WAREHOUSE)
        #print("DATABASE:", DATABASE)
        #print("SCHEMA:", SCHEMA)
        #print("PASSWORD:", PASSWORD)
        #print("PROTOCOL:" "'" + PROTOCOL + "'")
        #print("PORT:" + "'" + PORT + "'")

        print("Connecting...")
        # If the PORT is set but the protocol is not, we ignore the PORT (bug!!).
        if PROTOCOL is None or PROTOCOL == "" or PORT is None or PORT == "":
            # -- (> ------------------- SECTION=connect_to_snowflake ---------
            conn = snowflake.connector.connect(
                user=USER,
                password=PASSWORD,
                account=ACCOUNT,
                warehouse=WAREHOUSE,
                database=DATABASE,
                schema=SCHEMA
                )
            # -- <) ---------------------------- END_SECTION -----------------
        else:

            conn = snowflake.connector.connect(
                user=USER,
                password=PASSWORD,
                account=ACCOUNT,
                warehouse=WAREHOUSE,
                database=DATABASE,
                schema=SCHEMA,
                # Optional: for internal testing only.
                protocol=PROTOCOL,
                port=PORT
                )

        return conn
```

--------------------------------

### Convert ResultBatch to pandas DataFrame and PyArrow table

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-distributed-fetch

Use `to_pandas()` to get a pandas DataFrame and `to_arrow()` to get a PyArrow table from a result batch. Requires the pandas-compatible version of the Snowflake Connector for Python for `to_pandas()`. Works on all batch types, including JSON batches.

```python
with conn_cnx as con:
  with con.cursor() as cur:
    cur.execute("select col1 from table")
    batches = cur.get_result_batches()

    # Get the row from the ResultBatch as a pandas DataFrame.
    dataframe = batches[0].to_pandas()

    # Get the row from the ResultBatch as a PyArrow table.
    table = batches[0].to_arrow()
```

--------------------------------

### Run a query

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-asyncio

Demonstrates how to execute a query using the AsyncIO cursor and iterate over the results.

```APIDOC
## Run a query

### Description
Executes a query and iterates over the result set asynchronously.

### Method
N/A (SDK method)

### Endpoint
N/A (SDK method)

### Parameters
- **sql** (str) - Required - The SQL query to execute.
- **params** (tuple) - Optional - Bound values for the query parameters.

### Request Example
```python
async with conn.cursor() as cur:
    await cur.execute(
        "SELECT col1, col2 FROM testtable WHERE col1 > %s",
        (100,),
    )
    async for col1, col2 in cur:
        print(f"{col1}, {col2}")
```

### Response
#### Success Response
- **rows** (iterator) - An asynchronous iterator of result rows.

#### Response Example
```python
async for col1, col2 in cur:
    print(f"{col1}, {col2}")
```

```

--------------------------------

### Verify FIPS status of installed connector

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-install

Use this Python code to confirm whether the installed connector is FIPS-supporting. The value is True for a FIPS-supporting version and False for a standard version. A true value means this process loaded that version and its TLS provider is the FIPS module; it does not certify the connector.

```python
import snowflake.connector

status = snowflake.connector.get_fips_status()
print(status.is_fips)
```

--------------------------------

### Import snowflake.connector module

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect

Execute this command to import the snowflake.connector module.

```python
import snowflake.connector
```

--------------------------------

### Run queries concurrently

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-asyncio

Example of running multiple queries concurrently using asyncio.gather.

```python
async def fetch_rows(conn, sql):
    async with conn.cursor() as cur:
        await cur.execute(sql)
        return await cur.fetchall()

async with snowflake.connector.aio.connect() as conn:
    results = await asyncio.gather(
        fetch_rows(conn, "SELECT 1"),
        fetch_rows(conn, "SELECT 2"),
    )
```

--------------------------------

### Cursor.execute(command [, parameters][, timeout][, file_stream])

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-api

Prepares and executes a database command. Supports optional parameters for binding data, timeout, and file stream for PUT commands.

```APIDOC
## Cursor.execute(command [, parameters][, timeout][, file_stream])

### Description
Prepares and executes a database command.

### Method
execute(command [, parameters][, timeout][, file_stream])

### Parameters
- **command** (string) - Required - A string containing the SQL statement to execute.
- **parameters** (list or dict) - Optional - If you used parameters for binding data in the SQL statement, set this to the list or dictionary of variables that should be bound to those parameters.
- **timeout** (int) - Optional - Number of seconds to wait for the query to complete. If the query has not completed after this time has passed, the query should be aborted.
- **file_stream** (file-like object) - Optional - When executing a PUT command, you can use this parameter to upload an in-memory file-like object (e.g. the I/O object returned from the Python `open()` function), rather than a file on the filesystem. Set this parameter to that I/O object.

### Returns
Returns the reference of a Cursor object.

### Example
```python
cursor.execute(
    "PUT file://this_directory_path/is_ignored/myfile.csv @mystage",
    file_stream=<io_object>)
```
```

--------------------------------

### snowflake.connector.connect

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-connect

Establishes a connection to Snowflake. This example shows setting connection timeout parameters.

```APIDOC
## snowflake.connector.connect

### Description
Establishes a connection to Snowflake. This example shows setting connection timeout parameters.

### Method
connect

### Parameters
#### Connection Parameters
- `login_timeout` (int) - Optional - How long, in seconds, to keep retrying the login. Default is 120.
- `query_timeout` (int) - Optional - Wall-clock timeout, in seconds, for query execution including retries. Default is 0 (no timeout).
- `request_timeout` (int) - Optional - Wall-clock timeout, in seconds, for other operations (e.g., closing session, heartbeats) including retries. Default is 120. 0 means no timeout.
- `connect_timeout` (int) - Optional - Timeout, in seconds, for establishing a single HTTP connection. No default cap.
- `retry_timeout` (int) - Optional - Hard wall-clock cap, in seconds, on one HTTP attempt, including the response body. No default cap.

### Request Example
```python
conn = snowflake.connector.connect(
    login_timeout=60,
    query_timeout=30,
    request_timeout=30,
    retry_timeout=10,
)
```

### Notes
- `network_timeout` and `socket_timeout` are deprecated names. Passing either emits a `DeprecationWarning`.
- `network_timeout` value is copied to both `query_timeout` and `request_timeout` unless you set one of those yourself.
- `socket_timeout` value is copied to both `connect_timeout` and `retry_timeout`.

```

--------------------------------

### Using qmark binding with connection paramstyle

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Sets paramstyle to 'qmark' in connection parameters and executes an INSERT with ? placeholders. Requires the snowflake.connector.connect call and a table named testtable2.

```python
from snowflake.connector import connect

connection_parameters = {
 'account': 'xxxxx',
 'user': 'xxxx',
 'password': 'xxxxxx',
 "host": "xxxxxx",
 "port": 443,
 'protocol': 'https',
 'warehouse': 'xxx',
 'database': 'xxx',
 'schema': 'xxx',
 'paramstyle': 'qmark'  # note paramstyle setting here at connection level
}

con = connect(**connection_parameters)

con.cursor().execute(
 "INSERT INTO testtable2(col1,col2,col3) "
 "VALUES(?,?,?)", (
     987,
     'test string4',
     ("TIMESTAMP_LTZ", datetime.now())
 )
)
```

--------------------------------

### Fetch a single row with fetchone

Source: https://docs.snowflake.com/en/developer-guide/python-connector/python-connector-example

Use fetchone() to get a single row from the result set.

```python
col1, col2 = con.cursor().execute("SELECT col1, col2 FROM testtable").fetchone()
print('{0}, {1}'.format(col1, col2))
```