Slackbot
03/05/2024, 10:08 AMScout
03/05/2024, 10:08 AMpython from dagster import asset, resource import sqlalchemy # Define a resource for SQL Server connection @resource def sql_server_resource(_): # Replace with your actual connection details connection_string = '<mssql+pyodbc://username:password@hostname/database>' engine = sqlalchemy.create_engine(connection_string) return engine # Define an asset that uses the SQL Server resource to get a file path @asset(required_resource_keys={'sql_server'}) def get_file_path(context): engine = context.resources.sql_server with engine.connect() as connection: result = connection.execute("SELECT file_path FROM your_table WHERE condition") file_path = result.scalar() # Assuming the query returns a single file path return file_path
In this example, sql_server_resource
is a resource that creates a connection to the SQL Server using SQLAlchemy. The get_file_path
asset uses this resource to execute a SQL query that retrieves a file path from the database. Please note that this is a conceptual example and you would need to adapt it to your specific use case, including the actual SQL query, the table and column names, and the connection details for your SQL Server instance. If you need to perform more complex interactions or if you have specific requirements, please provide more details so we can assist you further.Scout
03/05/2024, 10:23 AMScout
03/05/2024, 10:25 AMsql_server_resource
is a resource that creates a connection to the SQL Server. The get_file_paths_from_db
function uses this connection to execute a SQL query that retrieves file paths from the database. The generate_assets
function uses the retrieved file paths to dynamically generate the asset definitions. Please note that you need to implement the determine_table_name
function based on your logic for mapping file paths to table names. Also, ensure that the sling_sql
resource is correctly defined to handle the file and SQL Server connections. This is a conceptual example and you would need to adapt it to your specific use case, including the actual SQL query, the table and column names, and the connection details for your SQL Server instance.Scout
03/05/2024, 10:38 AM&
operator. Open a terminal and use the following commands: bash /path/to/your/first_script & # This will run the first script in the background /path/to/your/second_script & # This will run the second script in the background
Alternatively, you can use the nohup
command to run the scripts in the background and ignore the hangup signal: bash nohup /path/to/your/first_script & nohup /path/to/your/second_script &
If you want to run them in separate terminal tabs or windows, you can use the following commands: For new tabs (in systems that support it, like GNOME Terminal or iTerm2): bash gnome-terminal -- /path/to/your/first_script gnome-terminal -- /path/to/your/second_script
For new windows: bash xterm -e /path/to/your/first_script & xterm -e /path/to/your/second_script &
### Windows If the files are executable scripts (e.g., batch files, PowerShell scripts), you can run them simultaneously using the START
command in Command Prompt: cmd START /B path\to\your\first_script START /B path\to\your\second_script
In PowerShell, you can use the Start-Process
cmdlet: powershell Start-Process "path\to\your\first_script" Start-Process "path\to\your\second_script"
These commands will execute each script in a new window. ### Note - Replace /path/to/your/first_script
and /path/to/your/second_script
with the actual paths to your scripts. - Ensure that the scripts have the appropriate execute permissions on Unix-like systems. - The scripts will run independently, and their output will be displayed in the terminal or command prompt window from which they were started. Remember that running scripts simultaneously can lead to concurrency issues if they modify the same resources, so ensure that your scripts are designed to handle such situations.Scout
03/05/2024, 10:40 AM-f
or --python-file
option multiple times with the dagster dev
command. This allows you to specify multiple Python files where Dagster definitions reside as top-level symbols/variables and load each file as a code location in the current Python environment. Here's how you can do it: bash dagster dev -f file1.py -f file2.py
This command will load the definitions from both file1.py
and file2.py
and start a local development environment where you can execute the jobs or assets defined in those files. Alternatively, if the definitions are organized in modules, you can use the -m
or --module-name
option to specify the module names: bash dagster dev -m module1 -m module2
This will load the definitions from the top-level of both module1
and module2
. Remember that when you load multiple files or modules, each one will be loaded as a separate code location. This is useful when you have different projects or components that you want to run simultaneously in a local development environment. Please ensure that the files or modules do not have conflicting definitions, as this could cause unexpected behavior. If you have any specific requirements or configurations, make sure to adjust the command accordingly.Scout
03/05/2024, 10:42 AMpython
# Add this function to your resources file or a separate utility file
def get_base_file_paths(engine):
query = """
SELECT PropertyValue
FROM app.PropertyConfig
WHERE PropertynameId IN (
SELECT id
FROM app.PropertyNames
WHERE PropertyName='FilePath'
)
"""
with engine.connect() as connection:
result = connection.execute(query)
base_file_paths = [row['PropertyValue'] for row in result]
return base_file_paths
### Step 2: Combine File Paths with Filenames
Assuming you have a way to map base file paths to filenames, you can combine them:
python
# This could be part of your assets file or a separate utility file
def combine_file_paths_with_filenames(base_file_paths, filenames):
full_file_paths = [os.path.join(base_path, filename) for base_path in base_file_paths for filename in filenames]
return full_file_paths
### Step 3: Generate Sling Assets Dynamically
Modify your asset generation code to use the full file paths:
```python
# This should be in the same file where you define your assets
from dagster import asset, AssetSpec, Definitions, load_assets_from_modules
from dagster_embedded_elt.sling import SlingMode, build_sling_asset
from dagster_params.params import db_connection_params
from sqlalchemy import create_engine
# ... (other code)
# Create an engine and get the base file paths from the database
engine = create_engine(f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}")
base_file_paths = get_base_file_paths(engine)
# Define your filenames here (or retrieve them from somewhere)
filenames = ['dag.csv', 'dagster.csv']
# Combine base paths with filenames to get full file paths
full_file_paths = combine_file_paths_with_filenames(base_file_paths, filenames)
# Now generate your assets using the full file paths
asset_defs = []
for file_path, table_name in zip(full_file_paths, b_list):
asset_key = table_name.replace('.', '_').replace('-', '_')
sling_asset = build_sling_asset(
sling_resource_key="sling_sql",
asset_spec=AssetSpec(key=asset_key, group_name="EScout
03/05/2024, 10:43 AMsling_sql
resource is correctly defined to handle the file and SQL Server connections. This approach allows you to dynamically create Sling assets based on file paths stored in a SQL Server database, which can then be used within your Dagster environment.Scout
03/05/2024, 11:04 AMparams.py
File
In your params.py
file, you will need to include the SQL query that retrieves the base file paths from your SQL Server database.
python
# params.py
# Existing database connection details
db_connection_params = {
"type": "sqlserver",
"host": "172.16.3.126",
"port": 1433,
"database": "template_DC",
"user": "sqluser",
"password": "sqluser",
}
# SQL query to retrieve file paths
file_path_query = """
SELECT PropertyValue
FROM app.PropertyConfig
WHERE PropertynameId IN (
SELECT id
FROM app.PropertyNames
WHERE PropertyName='FilePath'
)
"""
### Step 2: Update the resource.py
File
In your resource.py
file, you will need to create a function that executes the SQL query and retrieves the file paths.
python
# resource.py
from dagster import get_dagster_logger, resource
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection
from sqlalchemy import create_engine
from .params import db_connection_params, file_path_query # Import the query from params.py
logger = get_dagster_logger()
# Function to retrieve file paths from the database
@resource
def file_paths_resource(context):
engine = create_engine(f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}")
with engine.connect() as conn:
result = conn.execute(file_path_query)
base_file_paths = [row['PropertyValue'] for row in result]
return base_file_paths
# Define the SlingResource for SQL Server
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)
### Step 3: Update the assets.py
File
In your assets.py
file, you will need to use the file paths retrieved from the database to dynamically generate the assets.
```python
# assets.py
from dagster import asset, AssetSpec
from dagster_embedded_elt.sling import SlingMode, build_sling_asset
from .resource import file_paths_resource # Import the resource function
# Function to generate assets
def generate_assets(file_paths, table_names):
asset_defs = []
for base_path, table_name in zip(file_paths, table_names):
# Here you would append the filename to the base_path
full_file_path = f"{base_path}/your_filename.csv" # Replace with your logicScout
03/05/2024, 11:05 AM### Step 4: Update the `init.py` File In your `init.py` file, you will need to load the assets generated from the `assets.py` file. ```python # init.py from dagster import Definitions, load_assets_from_modules from .assets import assets # Import the dynamically generated assets # Load assets from the assets module all_assets = load_assets_from_modules([assets]) # Define the Dagster definitions defs = Definitions( resources={ "sling_sql": resource.sling_sql, "file_paths": resource.file_paths_resource, # Add the file paths resource }, assets=all_assets, )
Please note that this is a conceptual example and you would need to adapt it to your specific use case, including the actual SQL query, the table and column names, and the connection details for your SQL Server instance. Additionally, ensure that the sling_sql
resource is correctly defined to handle the file and SQL Server connections. This approach allows you to dynamically createScout
03/05/2024, 11:15 AMIndentationError
you're encountering is due to inconsistent indentation in your Python code. Python is very strict about indentation, and all code within the same block must be indented the same amount. Here's the corrected version of your assets.py
file with consistent indentation: python from dagster import asset, AssetSpec from dagster_embedded_elt.sling import SlingMode, build_sling_asset from dagster_params.resource import file_paths_resource # Import the resource function # Function to generate assets def generate_assets(file_paths, table_names): asset_defs = [] for base_path, table_name in zip(file_paths, table_names): # Here you would append the filename to the base_path full_file_path = f"{base_path}/dagster.csv" asset_key = table_name.replace('.', '_').replace('-', '_') # Use table_name instead of table_names sling_asset = build_sling_asset( sling_resource_key="sling_sql", asset_spec=AssetSpec(key=asset_key, group_name="ETL"), source_stream=full_file_path, target_object=table_name, mode=SlingMode.FULL_REFRESH, ) asset_defs.append(sling_asset) return asset_defs # Use the file_paths_resource to get the file paths and generate assets file_paths = file_paths_resource() table_names = ['app.dagster'] # Replace with your table names assets = generate_assets(file_paths, table_names)
Please note the following changes: 1. The indentation for the asset_key
, sling_asset
, and asset_defs.append(sling_asset)
lines has been corrected to align with the for
loop block. 2. The variable table_names
has been changed to table_name
in the asset_key
line, as you are iterating over table_names
and table_name
represents the current item in the loop. Make sure that you use consistent indentation throughout your Python files—typically four spaces per indentation level. This should resolve the IndentationError
.Scout
03/05/2024, 11:20 AM[unixODBC][Driver Manager]Data source name not found and no default driver specified
typically means that the connection string is either incorrect or the ODBC driver is not installed on your system. Here are some steps to troubleshoot and resolve this issue: 1. Install the ODBC Driver: Make sure that the ODBC driver for SQL Server is installed on your machine. For SQL Server, this is typically the ODBC Driver 17 for SQL Server
on Unix-like systems. 2. Configure ODBC: If the driver is installed, ensure that it is properly configured in the odbcinst.ini
file. This file is usually located in /etc/
or /usr/local/etc/
. You should see an entry for the SQL Server driver that looks something like this: [ODBC Driver 17 for SQL Server] Description=Microsoft ODBC Driver 17 for SQL Server Driver=/path/to/libmsodbcsql-17.so
3. Update the Connection String: Modify your connection string to explicitly specify the driver. Here's an example of what the connection string might look like using pyodbc
and `SQLAlchemy`: python connection_string = '<mssql+pyodbc://sqluser:sqluser@172.16.3.126:1433/template_DC?driver=ODBC+Driver+17+for+SQL+Server>'
Make sure to replace sqluser:sqluser
with your actual username and password, 172.16.3.126
with your actual host, 1433
with your actual port, and template_DC
with your actual database name. 4. Test the Connection: Before integrating the connection into your Dagster code, test it independently to ensure that you can successfully connect to the SQL Server database. You can do this with a simple Python script using pyodbc
or SQLAlchemy
. 5. Check Permissions: Ensure that the user running the Dagster code has the necessary permissions to access the ODBC driver and the database. 6. Review the Documentation: Refer to the SQLAlchemy documentation for more details on constructing connection strings and configuring drivers. If you've gone through these steps and are still encountering issues, you may need to provide more information about your environment, such as the operating system, the version of the ODBC driver installed, and how you've configured it. This will help in diagnosing the problem further.Scout
03/05/2024, 11:22 AMcreate_engine
call in your file_paths_resource
function to include the driver information: python from dagster import get_dagster_logger, resource from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection from sqlalchemy import create_engine from dagster_params.params import db_connection_params, file_path_query # Import the query from params.py logger = get_dagster_logger() # Function to retrieve file paths from the database @resource def file_paths_resource(): # Include the driver name in the connection string connection_string = f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?driver=ODBC+Driver+17+for+SQL+Server" engine = create_engine(connection_string) with engine.connect() as conn: result = conn.execute(file_path_query) base_file_paths = [row['PropertyValue'] for row in result] return base_file_paths # Define the SlingResource for SQL Server sling_sql = SlingResource( source_connection=SlingSourceConnection(type="file"), target_connection=SlingTargetConnection(**db_connection_params) )
In the modified connection_string
, replace ODBC Driver 17 for SQL Server
with the actual name of the ODBC driver you have installed. If you're not sure which ODBC driver is installed, you can check the available drivers by running odbcinst -q -d
on Unix-like systems. Additionally, ensure that the ODBC driver is correctly installed and configured on your system. If you continue to face issues, you may need to consult the documentation for the ODBC driver and SQLAlchemy to ensure that all settings are correct for your environment. Remember to also handle any exceptions that may occur during the database connection and querying process to ensure that your resource function can fail gracefully if needed.Scout
03/05/2024, 11:26 AMTypeError: __init__() takes 1 positional argument but 7 were given
, suggests that there is a problem with how you're initializing an object—most likely the SlingTargetConnection
object in your resource.py
file. The error indicates that the constructor is being called with more arguments than it expects. In the provided code snippet from your resource.py
file, you are using the unpacking operator *
when creating the SlingTargetConnection
object: python target_connection=SlingTargetConnection(*db_connection_params)
This will unpack the db_connection_params
dictionary into positional arguments, which is not correct because SlingTargetConnection
likely expects keyword arguments instead. You should pass the db_connection_params
dictionary directly without unpacking it, like this: python target_connection=SlingTargetConnection(**db_connection_params)
Here's the corrected part of your resource.py
file: python # resource.py # ... (other imports) from dagster_params.params import db_connection_params # Import the connection params # ... (other code) # Define the SlingResource for SQL Server sling_sql = SlingResource( source_connection=SlingSourceConnection(type="file"), target_connection=SlingTargetConnection(**db_connection_params) # Use keyword arguments )
Make sure to update your resource.py
file with this change. This should resolve the TypeError
you're encountering when Dagster is trying to load your user code. Additionally, ensure that the SlingTargetConnection
class is designed to accept the keyword arguments provided in the db_connection_params
dictionary. If the class constructor expects different arguments, you will need to adjust the db_connection_params
dictionary to match the expected parameters.Scout
03/05/2024, 11:36 AMDagsterUserCodeLoadError
, indicates that there is an issue with loading the user code. This could be due to a variety of reasons, such as incorrect imports, syntax errors, or issues with the way resources and assets are defined or referenced. To troubleshoot this error, consider the following steps: 1. Check for Syntax Errors: Ensure that all your Python files are free of syntax errors. You can do this by running a Python linter or simply executing the files with the Python interpreter to check for syntax issues. 2. Verify Imports: Make sure that all imports in your Python files are correct and that there are no circular dependencies. Circular imports can cause issues when the modules are loaded. 3. Review Resource Definitions: Ensure that your resources are defined correctly. For example, check that the sling_sql
and file_paths_resource
resources are defined and imported correctly in your init.py
file. 4. Check Asset Definitions: Verify that the assets are defined correctly in the assets
module and that there are no issues with the asset definitions. 5. Validate Configuration: Make sure that the configuration parameters you're passing to your resources (like SlingTargetConnection
) match the expected parameters of the resource class constructors. 6. Run Isolated Tests: Try to isolate the problem by running parts of the code independently. For example, you can try to instantiate the resources in a standalone Python script to see if they are configured correctly. 7. Check for Missing Files or Directories: Ensure that all necessary files and directories are present and that the paths are correct. 8. Review the Error Traceback: The traceback provided with the error message can give you clues about where the problem might be. Look for the specific file and line number where the error occurs. 9. Consult the Documentation: Review the Dagster documentation to ensure that you're using the APIs correctly, especially when defining resources and assets. 10. Check Environment Variables: If your code relies on environment variables (e.g., for database connections), ensure that they are set correctly in your environment. If you've gone through these steps and are still encountering issues, you may need to provide more detailed information about the error message, including the full traceback, and the specific code where the error occurs. This will help in diagnosing the problem further.Scout
03/05/2024, 11:37 AMTypeError: __init__() takes 1 positional argument but 7 were given
suggests that the constructor of an object is being called with more arguments than it expects, and it's likely still related to the SlingTargetConnection
object. Based on the code snippets you've provided, it seems that you've attempted to correct the issue by changing the unpacking of db_connection_params
from positional to keyword arguments. However, the error persists, which suggests that the change may not have been applied correctly or there are other issues in the code. Here's what you need to ensure: 1. Make sure that the SlingTargetConnection
is being initialized with keyword arguments correctly. The correct way to pass the db_connection_params
dictionary as keyword arguments is using the **
operator, like this: python target_connection=SlingTargetConnection(**db_connection_params)
2. Ensure that the SlingTargetConnection
class's constructor is defined to accept the keys present in the db_connection_params
dictionary as keyword arguments. 3. Verify that the changes have been saved and that you are running the updated code. 4. If you have multiple instances of SlingTargetConnection
being initialized in your codebase, make sure that all instances are updated to use keyword arguments correctly. 5. Ensure that there are no circular imports in your code that might be causing issues with loading modules. If you've checked all the above and the error still occurs, it might be helpful to isolate the problem. Try creating a minimal example where you only initialize the SlingTargetConnection
with the db_connection_params
to see if the error occurs in isolation. This can help determine if the issue is with the SlingTargetConnection
initialization or elsewhere in your code. If the problem persists, please provide the exact definition of the SlingTargetConnection
class or consult the documentation or source code for the SlingTargetConnection
to ensure that you are using it correctly. If the class is part of a third-party library, there might be documentation or examples that show the correct usage.Scout
03/05/2024, 11:43 AMsqlalchemy.exc.ObjectNotExecutableError: Not an executable object
, indicates that the SQL query string you are trying to execute is not being recognized as a valid executable SQL statement by SQLAlchemy. This typically happens when the query is passed as a plain string without being compiled into a SQL construct that SQLAlchemy can execute. To resolve this issue, you should ensure that the query is passed to conn.execute()
in a form that SQLAlchemy can execute. If you're using raw SQL strings with SQLAlchemy, you can typically execute them directly without the need to compile them into a SQL construct. However, it seems like there might be an issue with how the query is being passed or executed. Here's how you can modify the file_paths_resource
function to ensure the query is executed correctly: python # resource.py # ... (other imports) from sqlalchemy.sql import text # Import the text function for SQL queries # ... (other code) # Function to retrieve file paths from the database def file_paths_resource(): engine = create_engine(f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}") with engine.connect() as conn: # Use the text() function to construct a SQL expression query = text(file_path_query) result = conn.execute(query) # Execute the SQL expression base_file_paths = [row['PropertyValue'] for row in result] return base_file_paths
In this modified code, the text()
function from SQLAlchemy is used to construct a SQL expression from the raw SQL string. This SQL expression is then passed to conn.execute()
, which should allow SQLAlchemy to execute the query without errors. Make sure to apply this change and test it to see if it resolves the issue. If the error persists, please review the rest of your code to ensure that there are no other issues, and consider consulting the SQLAlchemy documentation for further guidance on executing raw SQL queries.Scout
03/05/2024, 11:45 AMpyodbc.InterfaceError
is specifically mentioning that the Data Source Name (DSN) is not found and no default driver is specified. Here are the steps you should take to resolve this issue: 1. Install the ODBC Driver: Ensure that the ODBC driver for SQL Server is installed on your system. For Linux systems, this is typically the msodbcsql17
package. 2. Configure ODBC: If the driver is installed, make sure it is properly configured. You can check the available drivers by running odbcinst -q -d
on Unix-like systems. 3. Update the Connection String: Modify your connection string to explicitly specify the driver. Here's an example of what the connection string might look like using pyodbc
and `SQLAlchemy`: python connection_string = 'mssql+pyodbc://{user}:{password}@{host}:{port}/{database}?driver=ODBC+Driver+17+for+SQL+Server'
Replace {user}
, {password}
, {host}
, {port}
, and {database}
with your actual database credentials and details. 4. Test the Connection: Before integrating the connection into your Dagster code, test it independently to ensure that you can successfully connect to the SQL Server database. 5. Review the Documentation: Consult the SQLAlchemy and pyodbc documentation for more details on constructing connection strings and configuring drivers. 6. Check Permissions: Ensure that the user running the Dagster code has the necessary permissions to access the ODBC driver and the database. 7. Debugging: If the error persists, you may want to add additional logging around the database connection code to get more information about the failure. If you have followed these steps and the issue is still not resolved, you may need to provide more information about your environment, such as the operating system, the version of the ODBC driver installed, and how you've configured it. This will help in diagnosing the problem further.Scout
03/05/2024, 11:49 AMresource.py
file. The line from dagster_params.params import
seems to be incomplete and is likely causing an issue. You should complete the import statement or remove it if it's not needed. Regarding the connection details, the code you've provided already appears to be using the db_connection_params
from the params.py
file to create the SlingTargetConnection
and to establish the SQLAlchemy engine connection. This is the correct approach if you want to centralize your connection parameters and use them across different parts of your code. Here's the corrected section of your resource.py
file with the proper import statement: python # resource.py from dagster import get_dagster_logger, resource, ExperimentalWarning from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection from sqlalchemy import create_engine, text # Make sure to import 'text' from dagster_params.params import db_connection_params, file_path_query # Import the query from params.py import warnings warnings.filterwarnings("ignore", category=ExperimentalWarning) logger = get_dagster_logger() # Function to retrieve file paths from the database @resource def file_paths_resource(): # Ensure the connection string is correct and includes the driver connection_string = f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?driver=ODBC+Driver+17+for+SQL+Server" engine = create_engine(connection_string) with engine.connect() as conn: # Use the text() function to construct a SQL expression query = text(file_path_query) result = conn.execute(query) # Execute the SQL expression base_file_paths = [row['PropertyValue'] for row in result] return base_file_paths # Define the SlingResource for SQL Server using the connection details from params.py sling_sql = SlingResource( source_connection=SlingSourceConnection(type="file"), target_connection=SlingTargetConnection(**db_connection_params) )
Make sure that the ODBC Driver 17 for SQL Server
is installed and properly configured on your system, as the connection string now explicitly specifies this driver. If you are using a different version of the ODBC driver, you will need to adjust the connection string accordingly. If you continue to encounter issues, please ensure that the db_connection_params
dictionary contains the correct keys and values that match the expected parameters for SlingTargetConnection
and that the ODBC driver is correctly installed and configured on your system.Scout
03/05/2024, 11:52 AMTypeError: tuple indices must be integers or slices, not str
suggests that there is an issue with how you are accessing the results of your database query. It seems that the result
object is being treated as a tuple, where you should use integer indices to access its elements, but you are using a string index instead.
In SQLAlchemy, when you execute a raw SQL query, the result set can be accessed in different ways. If the result set is being returned as a tuple, you cannot use string-based keys to access the columns; you would need to use integer indices or convert the result set to a dictionary.
Here's how you can modify the file_paths_resource
function to ensure the query results are accessed correctly:
python
# resource.py
# ... (other imports)
from sqlalchemy import create_engine, text
from sqlalchemy.exc import SQLAlchemyError # Import SQLAlchemyError for exception handling
# ... (other code)
@resource
def file_paths_resource():
try:
engine = create_engine(f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}")
with engine.connect() as conn:
# Use the text() function to construct a SQL expression
query = text(file_path_query)
result = conn.execute(query) # Execute the SQL expression
# Convert the result to a list of dictionaries
base_file_paths = [dict(row) for row in result]
# Access the 'PropertyValue' using the key
base_file_paths = [row['PropertyValue'] for row in base_file_paths]
return base_file_paths
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
# ... (rest of your resource definitions)
In this modified code, we are converting each row of the result set to a dictionary using dict(row)
. This allows us to access the 'PropertyValue' column using a string key as you originally intended.
Additionally, I've wrapped the database access code in a try-except block to catch any SQLAlchemyError
that might occur during the query execution. This will help you to log the error and understand what went wrong.
Please apply this change and test it to see if it resolves the issue. If the error persists, please review the rest of your code to ensure that there are no other issues, and consider consulting the SQLAlchemy documentation for further guidance on executing raw SQL queries and accessing the results. Cannot import name 'PipelineDefinition' ... button ECS Deployment of a distributed system f... button Trying to replicate the "Using-notebooks... button [docs] - include instructions for gettin... button Thank you for your feedback!Scout
03/05/2024, 11:58 AMpyodbc.InterfaceError
indicating that the ODBC driver necessary to connect to the SQL Server database is not found or not configured correctly. This error is typically related to the configuration of the ODBC driver on your system and the connection string used in your code. Here are some steps you can take to troubleshoot and resolve this issue: 1. Verify ODBC Driver Installation: Ensure that the ODBC driver for SQL Server is installed on your system. For Linux systems, this is typically the msodbcsql17
package. 2. Check ODBC Configuration: If the driver is installed, make sure it is properly configured in the odbcinst.ini
file, which is usually located in /etc/
or /usr/local/etc/
. 3. Update Connection String: Modify your connection string to explicitly specify the driver. Here's an example of what the connection string might look like using pyodbc
and `SQLAlchemy`: python connection_string = 'mssql+pyodbc://{user}:{password}@{host}:{port}/{database}?driver=ODBC+Driver+17+for+SQL+Server'
Replace {user}
, {password}
, {host}
, {port}
, and {database}
with your actual database credentials and details. 4. Test the Connection: Before integrating the connection into your Dagster code, test it independently to ensure that you can successfully connect to the SQL Server database. 5. Review the Documentation: Consult the SQLAlchemy and pyodbc documentation for more details on constructing connection strings and configuring drivers. 6. Check Permissions: Ensure that the user running the Dagster code has the necessary permissions to access the ODBC driver and the database. 7. Debugging: If the error persists, you may want to add additional logging around the database connection code to get more information about the failure. If you have followed these steps and the issue is still not resolved, you may need to provide more information about your environment, such as the operating system, the version of the ODBC driver installed, and how you've configured it. This will help in diagnosing the problem further.Scout
03/05/2024, 12:10 PMKeyError: 'sqluser'
suggests that the code is trying to access a key named 'sqluser'
in the db_connection_params
dictionary, but it does not exist. This error typically occurs when you try to access a dictionary key that hasn't been defined. In the line that's causing the error, you're using db_connection_params['sqluser']
and other similar expressions within the f-string to format the connection string. However, the keys should be the actual keys of the dictionary, not the values. The keys in your db_connection_params
dictionary are 'type'
, 'host'
, 'port'
, 'database'
, 'user'
, and 'password'
. Here's how you should format the connection string using the keys from the db_connection_params
dictionary: python engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}" )
Make sure that the keys you use in the f-string match exactly the keys in the db_connection_params
dictionary. If the keys are correct and the error persists, double-check that the dictionary is defined and accessible in the scope where you're trying to use it. Additionally, ensure that the ODBC driver is installed and properly configured on your system, as the connection string now explicitly specifies this driver. If you are using a different version of the ODBC driver, you will need to adjust the connection string accordingly.Scout
03/05/2024, 12:11 PMcreate_engine
call. The db_connection_params
dictionary keys should be used directly without quotes, and the values should be accessed using the correct keys. Here's the corrected version of the create_engine
call: python engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}" )
Make sure to replace 'sqluser'
, '172.16.3.126'
, '1433'
, and 'template_DC'
with the actual keys from the db_connection_params
dictionary, which are 'user'
, 'host'
, 'port'
, and 'database'
. Additionally, if you are using an ODBC driver for SQL Server on a Unix-like system, you may need to specify the driver name in the connection string. Here's an example of how to include the driver: python engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" )
Replace ODBC Driver 17 for SQL Server
with the actual name of the ODBC driver you have installed on your system. If you're not sure which ODBC driver is installed, you can check the available drivers by running odbcinst -q -d
on Unix-like systems. After making these corrections, ensure that the db_connection_params
dictionary is correctly defined and accessible in the scope where you're trying to use it. If you continue to encounter issues, please review the rest of your code to ensure that there are no other issues, and consider consulting the SQLAlchemy and pyodbc documentation for further guidance on constructing connection strings and accessing the results.Scout
03/05/2024, 12:15 PMpython from dagster import get_dagster_logger, resource, ExperimentalWarning from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection from sqlalchemy import create_engine, text # Make sure to import 'text' from dagster_params.params import db_connection_params, file_path_query # Import the query from params.py import warnings from sqlalchemy.exc import SQLAlchemyError # Import SQLAlchemyError for exception handling warnings.filterwarnings("ignore", category=ExperimentalWarning) logger = get_dagster_logger() # Function to retrieve file paths from the database @resource def file_paths_resource(): try: # Construct the connection string for the SQL Server database engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) with engine.connect() as conn: # Use the text() function to construct a SQL expression query = text(file_path_query) result = conn.execute(query) # Execute the SQL expression # Convert the result to a list of dictionaries base_file_paths = [dict(row) for row in result] # Access the 'PropertyValue' using the key base_file_paths = [row['PropertyValue'] for row in base_file_paths] return base_file_paths except SQLAlchemyError as e: logger.error(f"An error occurred while fetching file paths: {e}") raise # Define the SlingResource for SQL Server using the connection details from params.py sling_sql = SlingResource( source_connection=SlingSourceConnection(type="file"), target_connection=SlingTargetConnection(**db_connection_params) )
Make sure that the db_connection_params
dictionary is correctly defined and accessible in the scope where you're trying to use it. Additionally, ensure that the ODBC driver is installed and properly configured on your system, as the connection string now explicitly specifies this driver. If you are using a different version of the ODBC driver, you will need to adjust the connection string accordingly.Scout
03/05/2024, 12:18 PMValueError: dictionary update sequence element #0 has length 23; 2 is required
suggests that there is an issue with the way you are trying to create a dictionary from the rows of the result set. It seems that the result
object does not contain rows that can be directly converted into dictionaries using dict(row)
.
In SQLAlchemy, the result of a query is typically a ResultProxy
, which can be iterated over to yield RowProxy
objects. These RowProxy
objects behave like both tuples and dictionaries. If you want to convert each row into a dictionary, you should ensure that the RowProxy
can be converted into a dictionary correctly.
Here's how you can modify the file_paths_resource
function to handle the query results properly:
python
from dagster import get_dagster_logger, resource, ExperimentalWarning
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection
from sqlalchemy import create_engine, text
from dagster_params.params import db_connection_params, file_path_query
import warnings
from sqlalchemy.exc import SQLAlchemyError
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text(file_path_query)
result = conn.execute(query)
# Use the keys() method to get column names and zip with row to create a dictionary
base_file_paths = [{column: value for column, value in zip(row.keys(), row)} for row in result]
# Access the 'PropertyValue' using the key
base_file_paths = [row['PropertyValue'] for row in base_file_paths]
return base_file_paths
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)
In this modified code, we use row.keys()
to get the column names and zip
them with the row to create a dictionary for each row. This should resolve the ValueError
you're encountering.
Please apply this change and test it to see if it resolves the issue. If the error persists, please review the rest of your code to ensure that there are no other issues, and consider consulting the SQLAlchemy documentation for further guidance on executing raw SQL querScout
03/05/2024, 12:19 PMScout
03/05/2024, 12:20 PMAttributeError: Could not locate column in row for column 'keys'
indicates that there's an attempt to access a column named 'keys'
in the result row, which does not exist. This error is likely due to a misunderstanding of how to use the row.keys()
method with SQLAlchemy's result rows. In SQLAlchemy, each row
in the result set is a RowProxy
object that can be treated as a dictionary. The row.keys()
method returns a list of column names for that row, which you can use to iterate over the columns. However, you should not use 'keys'
as a column name when accessing the row's data. Here's how you can modify the file_paths_resource
function to correctly convert each row into a dictionary: python from dagster import get_dagster_logger, resource, ExperimentalWarning from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection from sqlalchemy import create_engine, text from dagster_params.params import db_connection_params, file_path_query import warnings from sqlalchemy.exc import SQLAlchemyError warnings.filterwarnings("ignore", category=ExperimentalWarning) logger = get_dagster_logger() @resource def file_paths_resource(): try: engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) with engine.connect() as conn: query = text(file_path_query) result = conn.execute(query) # Correctly convert each row into a dictionary base_file_paths = [row._asdict() for row in result] # Access the 'PropertyValue' using the key base_file_paths = [row['PropertyValue'] for row in base_file_paths] return base_file_paths except SQLAlchemyError as e: logger.error(f"An error occurred while fetching file paths: {e}") raise sling_sql = SlingResource( source_connection=SlingSourceConnection(type="file"), target_connection=SlingTargetConnection(**db_connection_params) )
In this modified code, we use row._asdict()
to convert each RowProxy
object into a dictionary. This should resolve the AttributeError
you're encountering. Please apply this change and test it to see if it resolves the issue. If the error persists, please review the rest of your code to ensure that there are no other issues, and consider consulting the SQLAlchemy documentation for further guidance on executing raw SQL queries and accessing the results.Scout
03/05/2024, 12:24 PMapp_dagster
failed due to an issue with the Sling command. The specific error message lstat home/voziq/dbt_project//dagster.csv: no such file or directory
suggests that the Sling command is trying to access a file at the specified path, but it cannot find it. This could be due to a few reasons: 1. The file dagster.csv
does not exist at the specified location. 2. There is a typo or incorrect path in the configuration that specifies the file location. 3. The file system permissions do not allow reading the file. To resolve this issue, you should: - Verify that the file dagster.csv
exists at the path home/voziq/dbt_project/
. If the file does not exist, you will need to ensure that it is created or that the correct path is provided. - Check for any typos or errors in the path specified in your Dagster asset or resource configuration. Make sure the path is correct and points to the intended file. - Ensure that the file system permissions are set correctly and that the user running the Dagster process has read access to the file. Once you have checked and corrected these potential issues, try materializing the asset again. If the problem persists, you may need to investigate further into the Sling command execution and the environment in which your Dagster instance is running.Scout
03/05/2024, 1:10 PMhome/voziq/dbt_project//dagster.csv
is likely not the cause of the issue, as most operating systems will correctly interpret double slashes as a single slash in file paths. However, it's still good practice to use the correct file path syntax to avoid any potential confusion or issues. To address the error, you should: 1. Confirm the File's Existence: Ensure that the file dagster.csv
actually exists in the directory /home/voziq/dbt_project/
. Note that the path should be absolute, starting with a slash (/
), which represents the root directory in Unix-like systems. If the initial slash is missing, the path would be considered relative, which might not be what you intend. 2. Correct the File Path: If there was a typo in the file path, correct it to use the proper syntax. For example, change home/voziq/dbt_project//dagster.csv
to /home/voziq/dbt_project/dagster.csv
. 3. Check File Permissions: Make sure that the Dagster process has the necessary permissions to read the file. You can check the permissions using the ls -l /home/voziq/dbt_project/dagster.csv
command and modify them if necessary with chmod
. 4. Review Dagster Asset Configuration: Look at the configuration of your Dagster asset to ensure that the file path is specified correctly. If you're using an environment variable or some form of dynamic path construction, verify that it's being constructed as expected. After making these checks and any necessary corrections, try to materialize the asset again. If the error continues, you may want to add logging to your Dagster asset to output the exact file path it's trying to access, which can help you debug the issue further.Scout
03/05/2024, 1:16 PMop
) named app_dagster
has failed with an error code 1
. This error code typically signifies a generic failure in Unix-like systems, and it's not specific enough to diagnose the exact cause of the problem. Here are some steps you can take to troubleshoot this issue: 1. Review the Sling Command: Check the Sling command that is being executed. Ensure that the command is correct and that it works when run manually in the same environment where Dagster is running. 2. Check File Paths and Permissions: Since Sling is often used for file synchronization, ensure that all file paths involved in the command are correct and accessible. Verify that the Dagster process has the necessary permissions to read from or write to the specified locations. 3. Examine Sling Logs: Look for detailed error messages in the Sling logs or the output captured from the Sling command execution. These logs may provide more information about why the command failed. 4. Debug the Dagster Asset: Add logging statements before and after the Sling command execution in your Dagster asset to capture more context about the state of the system when the error occurs. 5. Check Resource Configurations: Ensure that all resources required by the app_dagster
operation are correctly configured and available. 6. Review External Dependencies: If the Sling command interacts with external services or systems, verify that those are operational and accessible from the Dagster environment. 7. Consult Sling Documentation: If the error persists, refer to the Sling documentation or support resources for guidance on error code 1
and troubleshooting tips specific to Sling. By following these steps, you should be able to identify and resolve the issue causing the Sling command to fail. If the problem continues after these checks, you may need to seek further assistance from someone with expertise in Sling or the specific context in which it's being used within your Dagster assets.Scout
03/05/2024, 1:17 PMfile_paths_resource
that connects to a SQL Server database using SQLAlchemy and retrieves file paths based on a provided SQL query. It also defines a SlingResource
that is configured with source and target connections for use with Sling operations. The file_paths_resource
function uses the db_connection_params
dictionary to construct the connection string for the SQL Server database and executes the file_path_query
to fetch file paths. The result set is then converted into a list of dictionaries, and the 'PropertyValue' is extracted from each dictionary to create a list of file paths. If you are encountering issues with this code, here are a few things to check: 1. Database Connection: Ensure that the db_connection_params
dictionary contains the correct credentials and connection details for your SQL Server database. 2. ODBC Driver: Verify that the ODBC Driver 17 for SQL Server is installed and properly configured on the system where the Dagster instance is running. 3. Query Execution: Confirm that the file_path_query
is valid SQL and that it returns the expected results when run directly against the database. 4. Error Handling: The try...except
block around the database query is correctly catching SQLAlchemyError
exceptions and logging the error. Make sure that the logger is configured to output to a location where you can access the logs. 5. SlingResource Configuration: The SlingResource
is configured with a source connection of type "file" and a target connection using the db_connection_params
. Ensure that these connections are correctly configured for your Sling operations. 6. Resource Usage: When using the file_paths_resource
within your Dagster assets or jobs, make sure that it is being referenced correctly as a resource. If you are still facing issues after checking these points, please provide more details about the specific error or behavior you are experiencing, and we can assist you further.Scout
03/05/2024, 1:18 PM1
. This error code generally indicates a generic failure, but without more specific information, it's challenging to diagnose the exact cause. Here are some steps you can take to troubleshoot and resolve this issue: 1. Review the Sling Command: Check the Sling command that is being executed. Ensure that the command is correct and that it works when run manually in the same environment where Dagster is running. 2. Check File Paths and Permissions: Since Sling is often used for file synchronization, ensure that all file paths involved in the command are correct and accessible. Verify that the Dagster process has the necessary permissions to read from or write to the specified locations. 3. Examine Sling Logs: Look for detailed error messages in the Sling logs or the output captured from the Sling command execution. These logs may provide more information about why the command failed. 4. Debug the Dagster Asset: Add logging statements before and after the Sling command execution in your Dagster asset to capture more context about the state of the system when the error occurs. 5. Check Resource Configurations: Ensure that all resources required by the operation are correctly configured and available. 6. Review External Dependencies: If the Sling command interacts with external services or systems, verify that those are operational and accessible from the Dagster environment. 7. Consult Sling Documentation: If the error persists, refer to the Sling documentation or support resources for guidance on error code 1
and troubleshooting tips specific to Sling. By following these steps, you should be able to identify and resolve the issue causing the Sling command to fail. If the problem continues after these checks, you may need to seek further assistance from someone with expertise in Sling or the specific context in which it's being used within your Dagster assets.meeniga
03/05/2024, 1:24 PMScout
03/05/2024, 1:24 PMScout
03/05/2024, 1:29 PMapp_dagster
. The specific failure is due to a Sling command that did not execute successfully, as indicated by the error code 1
. Additionally, there is an lstat
error that suggests the file dagster.csv
could not be found in the expected directory home/voziq/dbt_project/
. Here are the steps you should take to address this issue: 1. Verify File Path: Ensure that the file dagster.csv
exists at the path /home/voziq/dbt_project/
. The path should be absolute and start with a forward slash. If the file is not present, you will need to create it or provide the correct path. 2. Check Sling Command: Review the Sling command being executed to ensure it is correct. If possible, try running the Sling command manually in the same environment to see if it works outside of Dagster. 3. Inspect File Permissions: Make sure that the Dagster process has the necessary permissions to access the file dagster.csv
. You may need to adjust file permissions or run Dagster with a user that has the appropriate access. 4. Review Dagster Asset Configuration: Check the configuration of your Dagster asset to ensure that the file path and any other parameters are specified correctly. 5. Examine Logs: Look at the logs for any additional information that might indicate why the Sling command failed. The logs may provide more context or a more specific error message. 6. Debugging: If the issue is not immediately apparent, consider adding more detailed logging around the point of failure to capture the state of the system and any additional error messages. By following these steps, you should be able to identify the root cause of the failure and take the necessary actions to resolve it. If you continue to experience issues, please provide additional context or error messages that could help further diagnose the problem.Scout
03/05/2024, 1:35 PMException: ('Sling command failed with error code %s', 1)
indicates that the Sling command executed by the sling.sync
method within the SlingResource
has failed. The %s
in the error message is a placeholder for string formatting in Python, and it seems that the intended error code 1
is not being formatted into the string properly. The error code 1
typically indicates a general error, but it doesn't provide specific details about what went wrong.
Given that the error message includes lstat home/voziq/dbt_project/dagster.csv: no such file or directory
, it suggests that the Sling command is trying to access the dagster.csv
file but cannot find it. This could be due to several reasons, such as the file not existing at the specified path, permission issues, or an incorrect path being provided to the Sling command.
Here are some steps to troubleshoot this issue:
1. Verify File Path: Ensure that the file dagster.csv
exists at the path /home/voziq/dbt_project/
. The path should be absolute and start with a forward slash. If the file is not present, you will need to create it or provide the correct path.
2. Check File Permissions: Make sure that the Dagster process has the necessary permissions to access the file dagster.csv
. You may need to adjust file permissions or run Dagster with a user that has the appropriate access.
3. Review Sling Configuration: Check the configuration of your SlingResource
and ensure that the source_connection
and target_connection
are correctly set up. The source_stream
should point to the correct file path, and the target_object
should be the correct destination for the data.
4. Debug Sling Execution: Add logging around the Sling command execution to capture the exact command being run and any output or error messages it produces. This can help identify if there are issues with the command itself.
5. Manual Sling Command Test: Attempt to run the Sling command manually outside of Dagster with the same parameters to see if it succeeds or if it produces a more informative error message.
6. Check Sling Documentation: Consult the documentation for Sling to understand what error code 1
means in the context of the command you are trying to run and for troubleshooting tips specific to Sling.
7. Format Error Message Correctly: Update the error message to correctly format the error code into the string. Change the line that raises the exception to raise Exception(f"Sling command failed with error code {proc.returncode}")
.
By following these steps, you should be able to identify the root cause of the failure and take the necessary actions to resolve it. If you continue to experience issues, please provide additional context or error messages that could help fuScout
03/05/2024, 1:35 PMmeeniga
03/06/2024, 2:02 PMScout
03/06/2024, 2:02 PMfile_paths_resource
function and the generate_assets
function accordingly. Additionally, you will need to adjust the usage of these functions in your assets.py
and __init__.py
files.
Here's how you can modify the code:
### Step 1: Update the file_paths_resource
Function
Update the file_paths_resource
function to execute the new SQL query and return a list of tuples containing the file path, filename, and table name.
python
# resource.py
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
new_query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(new_query)
file_info_list = [(row['propertyvalue'], row['propertynameid']) for row in result]
return file_info_list
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
### Step 2: Update the generate_assets
Function
Modify the generate_assets
function to accept the new structure of file information and generate assets accordingly.
python
# assets.py
def generate_assets(file_info_list):
asset_defs = []
for file_info in file_info_list:
file_path, file_name, table_name = file_info
full_file_path = f"{file_path}/{file_name}"
asset_key = table_name.replace('.', '_').replace('-', '_')
sling_asset = build_sling_asset(
sling_resource_key="sling_sql",
asset_spec=AssetSpec(key=asset_key, group_name="ETL"),
source_stream=full_file_path,
target_object=table_name,
mode=SlingMode.FULL_REFRESH,
)
asset_defs.append(sling_asset)
return asset_defs
# Use the file_paths_resource to get the file paths and generate assets
file_info_list = file_paths_resource()
assets = generate_assets(file_info_list)
### Step 3: Update the __init__.py
File
Ensure that the __init__.py
file correctly loads the assets and resources.
```python
# init.py
from dagster import Definitions, load_assets_from_modules
from .assets import assets # Adjust the import according to your package structurScout
03/06/2024, 2:03 PM### Step 4: Update the `params.py` File If needed, update the `params.py` file to include any new parameters or changes to the database connection details. ```python # params.py # Update this file with any new parameters or changes
Please note that the code provided here is a conceptual example based on the information you've given. You will need to adapt it to fit the actual structure of your database results and the specific requirements of your application. Make sure to test the updated code thoroughly to ensure that it works as expected.meeniga
03/07/2024, 8:01 AMScout
03/07/2024, 8:01 AMTypeError: tuple indices must be integers or slices, not str
suggests that the code is attempting to access elements of a tuple using string indices, which is not allowed in Python. This is happening in the file_paths_resource
function when trying to create a list of tuples with row['propertyvalue']
and row['propertynameid']
. In SQLAlchemy, when you execute a query, the result
object contains RowProxy
objects that can be accessed like dictionaries, but if the result
is configured or being treated as a tuple, you must access the elements by integer indices. To resolve this issue, you should ensure that each row
in the result
is being treated as a RowProxy
object that supports dictionary-like access. If the rows are indeed RowProxy
objects, the code should work as expected. However, if the rows are tuples, you will need to access the elements by index. Here's how you can modify the file_paths_resource
function to handle the query results properly: python @resource def file_paths_resource(): try: engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) with engine.connect() as conn: new_query = text(""" SELECT propertyvalue, propertynameid FROM app.PropertyConfig WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1) """) result = conn.execute(new_query) # Ensure that each row is treated as a RowProxy object file_info_list = [(row['propertyvalue'], row['propertynameid']) for row in result] return file_info_list except SQLAlchemyError as e: logger.error(f"An error occurred while fetching file paths: {e}") raise
If the rows are indeed tuples, you will need to know the index of each column in the result set and access the values by these indices: python # Example assuming 'propertyvalue' is at index 0 and 'propertynameid' is at index 1 file_info_list = [(row[0], row[1]) for row in result]
Please ensure that the result
object is being treated correctly according to the data it contains, and adjust the code accordingly. If you continue to encounter issues, you may need to add additional logging to inspect the structure of the result
and row
objects to determine the correct way to access the data.meeniga
03/07/2024, 8:07 AMScout
03/07/2024, 8:07 AMTypeError: tuple indices must be integers or slices, not str
indicates that the code is attempting to access elements of a tuple using string indices. This error is occurring when trying to create a list of tuples with row['propertyvalue']
and row['propertynameid']
from the result of the SQL query execution. The issue likely arises because the result
object returned by SQLAlchemy's execute
method is not being interpreted as a collection of dictionaries (or RowProxy
objects), which would allow for string-indexed access. Instead, it seems to be treated as a tuple, which requires integer-based indexing. To resolve this issue, you should ensure that each row
in the result
is being treated as a RowProxy
object that supports dictionary-like access. If the rows are indeed RowProxy
objects, the code should work as expected. However, if the rows are tuples, you will need to access the elements by index. Here's how you can modify the file_paths_resource
function to handle the query results properly: python @resource def file_paths_resource(): try: engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) with engine.connect() as conn: new_query = text(""" SELECT propertyvalue, propertynameid FROM app.PropertyConfig WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1) """) result = conn.execute(new_query) # Ensure that each row is treated as a RowProxy object file_info_list = [(row['propertyvalue'], row['propertynameid']) for row in result] return file_info_list except SQLAlchemyError as e: logger.error(f"An error occurred while fetching file paths: {e}") raise
If the rows are indeed tuples, you will need to know the index of each column in the result set and access the values by these indices: python # Example assuming 'propertyvalue' is at index 0 and 'propertynameid' is at index 1 file_info_list = [(row[0], row[1]) for row in result]
Please ensure that the result
object is being treated correctly according to the data it contains, and adjust the code accordingly. If you continue to encounter issues, you may need to add additional logging to inspect the structure of the result
and row
objects to determine the correct way to access the data.meeniga
03/07/2024, 8:13 AMScout
03/07/2024, 8:13 AMpropertyvalue
and propertynameid
are the column names in the SQL query result and you are receiving a TypeError: tuple indices must be integers or slices, not str
, it suggests that the result set is being treated as a tuple rather than a RowProxy
which allows for dictionary-like access. To resolve this, you should ensure that you are accessing the SQL result rows as dictionaries. Here's the corrected file_paths_resource
function: python @resource def file_paths_resource(): try: # Create a database engine engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) # Connect to the database and execute the query with engine.connect() as conn: new_query = text(""" SELECT propertyvalue, propertynameid FROM app.PropertyConfig WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1) """) result = conn.execute(new_query) # Extract the 'propertyvalue' and 'propertynameid' from each row file_info_list = [(row['propertyvalue'], row['propertynameid']) for row in result] return file_info_list except SQLAlchemyError as e: # Log any errors that occur logger.error(f"An error occurred while fetching file paths: {e}") raise
Make sure that the text
function from SQLAlchemy is imported correctly to handle the raw SQL query: python from sqlalchemy import text
This function should now correctly interpret each row as a RowProxy
object, allowing you to access the columns by name. If you still encounter the same error, it's possible that the result
object is not returning RowProxy
objects as expected. In that case, you may need to debug further by inspecting the result
object and its contents to understand its structure and how to access the data correctly.meeniga
03/07/2024, 8:17 AMScout
03/07/2024, 8:17 AMTypeError
that occurs when trying to access elements of a row from an SQL query result using string keys, which suggests that the result set is being treated as a tuple rather than a RowProxy
object that supports dictionary-like access. To resolve this issue, you need to ensure that the rows returned by the SQL query are being accessed correctly. In SQLAlchemy, the rows returned by conn.execute(query)
are typically RowProxy
objects that can be accessed like dictionaries, allowing you to use column names as keys. Here's how you can modify the file_paths_resource
function to handle the query results properly: python @resource def file_paths_resource(): try: engine = create_engine( f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@" f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?" f"driver=ODBC+Driver+17+for+SQL+Server" ) with engine.connect() as conn: new_query = text(""" SELECT propertyvalue, propertynameid FROM app.PropertyConfig WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1) """) result = conn.execute(new_query) # Ensure that each row is treated as a RowProxy object file_info_list = [(row['propertyvalue'], row['propertynameid']) for row in result] return file_info_list except SQLAlchemyError as e: logger.error(f"An error occurred while fetching file paths: {e}") raise
If you're still encountering the TypeError
, it's possible that the result set is not returning RowProxy
objects as expected. In that case, you may need to debug further by inspecting the result
object and its contents to understand its structure and how to access the data correctly. Make sure that the text
function from SQLAlchemy is imported correctly to handle the raw SQL query: python from sqlalchemy import text
Additionally, ensure that the db_connection_params
dictionary contains the correct keys and values for your database connection, and that the SQL query is valid and returns the expected results. If the issue persists after these checks, please provide additional context or error messages that could help further diagnose the problem.meeniga
03/07/2024, 8:27 AMScout
03/07/2024, 8:27 AMresource.py
file to handle the new SQL queries and retrieve the filename, tablename, and path, you can update the file_paths_resource
function to execute each query and return a list of tuples containing the path, filename, and tablename.
Here's how you can modify the file_paths_resource
function:
```python
# resource.py
from dagster import get_dagster_logger, resource
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection
from sqlalchemy import create_engine, text
from dagster_params.params import db_connection_params
import warnings
from sqlalchemy.exc import SQLAlchemyError
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
# Query to get the file path
path_query = text("""
SELECT PropertyValue
FROM app.PropertyConfig
WHERE PropertynameId IN (
SELECT id
FROM app.PropertyNames
WHERE PropertyName='FilePath'
)
""")
path_result = conn.execute(path_query)
path = path_result.scalar() # Assuming only one path is returned
# Query to get the filename
filename_query = text("""
SELECT propertyvalue as filename
FROM app.PropertyConfig
WHERE PropertyId IN (
SELECT id FROM app.Property WHERE id=1
) AND propertynameid=2
""")
filename_result = conn.execute(filename_query)
filename = filename_result.scalar() # Assuming only one filename is returned
# Query to get the tablename
tablename_query = text("""
SELECT propertyvalue as tablename
FROM app.PropertyConfig
WHERE PropertyId IN (
SELECT id FROM app.Property WHERE id=1
) AND propertynameid=3
""")
tablename_result = conn.execute(tablename_query)
tablename = tablename_result.scalar() # Assuming only one tablename is returned
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")Scout
03/07/2024, 8:29 AMscalar()
method to get the first value of the result since we're assuming that each query will return only one row with one column. Please note that this code assumes that there is only one path, one filename, and one tablename. If your queries could return multiple rows, you will need to adjust the code to handle multiple results appropriately. Make sure to test the updated code thoroughly to ensure that it works as expected. If you encounter any issues, you may need to add additional logging or error handling to diagnose the problem.meeniga
03/07/2024, 8:32 AMScout
03/07/2024, 8:32 AMdagster
has failed with an error code 1
. This error code generally indicates a generic failure, but without more specific information, it's challenging to diagnose the exact cause of the problem. Here are some steps you can take to troubleshoot this issue: 1. Review the Sling Command: Check the Sling command that is being executed. Ensure that the command is correct and that it works when run manually in the same environment where Dagster is running. 2. Check File Paths and Permissions: Since Sling is often used for file synchronization, ensure that all file paths involved in the command are correct and accessible. Verify that the Dagster process has the necessary permissions to read from or write to the specified locations. 3. Examine Sling Logs: Look for detailed error messages in the Sling logs or the output captured from the Sling command execution. These logs may provide more information about why the command failed. 4. Debug the Dagster Asset: Add logging statements before and after the Sling command execution in your Dagster asset to capture more context about the state of the system when the error occurs. 5. Check Resource Configurations: Ensure that all resources required by the operation are correctly configured and available. 6. Review External Dependencies: If the Sling command interacts with external services or systems, verify that those are operational and accessible from the Dagster environment. 7. Consult Sling Documentation: If the error persists, refer to the Sling documentation or support resources for guidance on error code 1
and troubleshooting tips specific to Sling. By following these steps, you should be able to identify and resolve the issue causing the Sling command to fail. If the problem continues after these checks, you may need to seek further assistance from someone with expertise in Sling or the specific context in which it's being used within your Dagster assets.meeniga
03/07/2024, 10:37 AMScout
03/07/2024, 10:37 AM.csv
) and the schema (app.
) into the file_paths_resource
function, you can append these defaults to the filename
and tablename
respectively. Here's how you can modify the function:
python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
# Query to get the file path
path_query = text("""
SELECT PropertyValue
FROM app.PropertyConfig
WHERE PropertynameId IN (
SELECT id
FROM app.PropertyNames
WHERE PropertyName='FilePath'
)
""")
path_result = conn.execute(path_query)
path = path_result.scalar() # Assuming only one path is returned
# Query to get the filename and append the default extension
filename_query = text("""
SELECT propertyvalue as filename
FROM app.PropertyConfig
WHERE PropertyId IN (
SELECT id FROM app.Property WHERE id=1
) AND propertynameid=2
""")
filename_result = conn.execute(filename_query)
filename = filename_result.scalar() + '.csv' # Append the default file extension
# Query to get the tablename and prepend the default schema
tablename_query = text("""
SELECT propertyvalue as tablename
FROM app.PropertyConfig
WHERE PropertyId IN (
SELECT id FROM app.Property WHERE id=1
) AND propertynameid=3
""")
tablename_result = conn.execute(tablename_query)
tablename = 'app.' + tablename_result.scalar() # Prepend the default schema
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
In this updated function, the filename
is concatenated with the string '.csv'
to ensure that the filename always has the .csv
extension. Similarly, the tablename
is concatenated with 'app.'
to ensure that the tablename always includes the schema app.
.
Please note that this approach assumes that the filename
and tablename
do not already include the .csv
extension and app.
schema, respScout
03/07/2024, 10:38 AMmeeniga
03/07/2024, 10:52 AMScout
03/07/2024, 10:52 AMfile_paths_resource
function to use a single query and extract the path, filename, and tablename based on the propertynameid
, you can adjust the SQL query to return all the necessary information in one go. Then, you can process the results in Python to organize them into the desired format.
Here's how you can modify the file_paths_resource
function:
python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
# Single query to get the path, filename, and tablename
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
# Initialize variables to store path, filename, and tablename
path, filename, tablename = None, None, None
# Iterate over the results and assign values based on propertynameid
for row in result:
if row['propertynameid'] == 1: # Assuming 1 is the ID for the path
path = row['propertyvalue']
elif row['propertynameid'] == 2: # Assuming 2 is the ID for the filename
filename = row['propertyvalue'] + '.csv' # Append the default file extension
elif row['propertynameid'] == 3: # Assuming 3 is the ID for the tablename
tablename = 'app.' + row['propertyvalue'] # Prepend the default schema
# Check if all values are present
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
# Define the SlingResource for SQL Server using the connection details from params.py
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)
In this updated function, a single SQL query is executed to fetch all the required properties. The results are then iterated over, and based on the `propertynaScout
03/07/2024, 10:54 AM.csv
extension and app.
schema are appended/prepended as needed. Please ensure that the propertynameid
values used in the if
conditions match the actual IDs used in your database for the path, filename, and tablename. Also, make sure to handle cases where the expected properties might not be present in the database results.meeniga
03/07/2024, 10:57 AMScout
03/07/2024, 10:57 AMpropertynameid
key in the result rows returned by the SQL query. The error TypeError: tuple indices must be integers or slices, not str
indicates that the rows are being treated as tuples, which require integer indices, rather than dictionaries that allow string keys.
To resolve this issue, you need to ensure that the rows returned by the SQL query are being accessed as dictionaries. In SQLAlchemy, the rows returned by conn.execute(query)
are typically RowProxy
objects that can be accessed like dictionaries, allowing you to use column names as keys.
Here's how you can modify the file_paths_resource
function to handle the query results properly:
python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
# Single query to get the path, filename, and tablename
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
# Initialize variables to store path, filename, and tablename
path, filename, tablename = None, None, None
# Iterate over the results and assign values based on propertynameid
for row in result:
if row['propertynameid'] == 1: # Assuming 1 is the ID for the path
path = row['propertyvalue']
elif row['propertynameid'] == 2: # Assuming 2 is the ID for the filename
filename = row['propertyvalue'] + '.csv' # Append the default file extension
elif row['propertynameid'] == 3: # Assuming 3 is the ID for the tablename
tablename = 'app.' + row['propertyvalue'] # Prepend the default schema
# Check if all values are present
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
If you're still encScout
03/07/2024, 10:58 AMTypeError
, it's possible that the result set is not returning RowProxy
objects as expected. In that case, you may need to debug further by inspecting the result
object and its contents to understand its structure and how to access the data correctly. Make sure that the text
function from SQLAlchemy is imported correctly to handle the raw SQL query: python from sqlalchemy import text
Additionally, ensure that the db_connection_params
dictionary contains the correct keys and values for your database connection, and that the SQL query is valid and returns the expected results. If the issue persists after these checks, please provide additional context or error messages that could help further diagnose the problem.meeniga
03/07/2024, 10:59 AMScout
03/07/2024, 10:59 AMTypeError
that occurs when trying to access elements of a row from an SQL query result using string keys, which suggests that the result set is being treated as a tuple rather than a RowProxy
object that supports dictionary-like access.
To resolve this issue, you need to ensure that the rows returned by the SQL query are being accessed as dictionaries. In SQLAlchemy, the rows returned by conn.execute(query)
are typically RowProxy
objects that can be accessed like dictionaries, allowing you to use column names as keys.
Here's how you can modify the file_paths_resource
function to handle the query results properly:
python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
# Single query to get the path, filename, and tablename
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
# Initialize variables to store path, filename, and tablename
path, filename, tablename = None, None, None
# Iterate over the results and assign values based on propertynameid
for row in result:
if row['propertynameid'] == 1: # Assuming 1 is the ID for the path
path = row['propertyvalue']
elif row['propertynameid'] == 2: # Assuming 2 is the ID for the filename
filename = row['propertyvalue'] + '.csv' # Append the default file extension
elif row['propertynameid'] == 3: # Assuming 3 is the ID for the tablename
tablename = 'app.' + row['propertyvalue'] # Prepend the default schema
# Check if all values are present
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
If you're still encountering the TypeError
, it's possible that the result set is not returningScout
03/07/2024, 11:00 AMRowProxy
objects as expected. In that case, you may need to debug further by inspecting the result
object and its contents to understand its structure and how to access the data correctly. Make sure that the text
function from SQLAlchemy is imported correctly to handle the raw SQL query: python from sqlalchemy import text
Additionally, ensure that the db_connection_params
dictionary contains the correct keys and values for your database connection, and that the SQL query is valid and returns the expected results. If the issue persists after these checks, please provide additional context or error messages that could help further diagnose the problem.meeniga
03/07/2024, 11:01 AMScout
03/07/2024, 11:02 AMTypeError: tuple indices must be integers or slices, not str
, indicates that there is an attempt to access a tuple with string indices, which is not valid in Python. This error typically occurs when you're trying to access the results of a SQL query as if they were dictionaries, but they are actually being returned as tuples.
The error is occurring in the file_paths_resource
function within the resource.py
file when you're trying to access row['propertynameid']
. This suggests that the result
object returned by the conn.execute(query)
call is not returning RowProxy
objects as expected.
To address this issue, you should ensure that the rows are being treated as RowProxy
objects, which support dictionary-like access to columns. Here's how you can modify the file_paths_resource
function to handle the query results properly:
```python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
# Initialize variables to store path, filename, and tablename
path, filename, tablename = None, None, None
# Iterate over the results and assign values based on propertynameid
for row in result:
# Ensure that each row is treated as a RowProxy object
row_as_dict = dict(row)
if row_as_dict['propertynameid'] == 1: # Assuming 1 is the ID for the path
path = row_as_dict['propertyvalue']
elif row_as_dict['propertynameid'] == 2: # Assuming 2 is the ID for the filename
filename = row_as_dict['propertyvalue'] + '.csv' # Append the default file extension
elif row_as_dict['propertynameid'] == 3: # Assuming 3 is the ID for the tablename
tablename = 'app.' + row_as_dict['propertyvalue'] # Prepend the default schema
# Check if all values are present
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
lScout
03/07/2024, 11:02 AMIn this modified code, we convert each `row` to a dictionary using `dict(row)` before attempting to access its elements by string keys. This should resolve the `TypeError` you're encountering. Please ensure that the `text` function from SQLAlchemy is imported correctly to handle the raw SQL query: ```python from sqlalchemy import text
Additionally, ensure that the db_connection_params
dictionary contains the correct keys and values for your database connection, and that the SQL query is valid and returns the expected results. If the issue persists after these checks, please provide additional context or error messages that could help further diagnose the problem.meeniga
03/07/2024, 11:06 AMScout
03/07/2024, 11:06 AMpropertynameid
. To handle this result correctly in your file_paths_resource
function, you need to iterate over the result set and assign the propertyvalue
to the correct variable based on the propertynameid
.
Here's how you can modify the file_paths_resource
function to handle the query results properly:
python
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
# Initialize variables to store path, filename, and tablename
path, filename, tablename = None, None, None
# Iterate over the results and assign values based on propertynameid
for row in result:
if row['propertynameid'] == 1: # Assuming 1 is the ID for the path
path = row['propertyvalue']
elif row['propertynameid'] == 2: # Assuming 2 is the ID for the filename
filename = row['propertyvalue'] + '.csv' # Append '.csv' to the filename
elif row['propertynameid'] == 3: # Assuming 3 is the ID for the tablename
tablename = 'app.' + row['propertyvalue'] # Prepend 'app.' to the tablename
# Check if all values are present
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
# Return a list of tuples containing the path, filename, and tablename
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
In this updated function, we execute the provided SQL query to fetch the properties. We then iterate over the results and, based on the propertynameid
, we assign the propertyvalue
to the appropriate variable (path
, filename
, or tablename
). We also append .csv
to the filename and prepend app.
to the tablename as required.
Please ensure that the propertynameid
values usScout
03/07/2024, 11:07 AMif
conditions match the actual IDs used in your database for the path, filename, and tablename. Also, make sure to handle cases where the expected properties might not be present in the database results. After updating the function, make sure to test it thoroughly to ensure that it behaves as expected. If you encounter any issues, you may need to add additional logging or error handling to diagnose the problem.meeniga
03/07/2024, 12:01 PMScout
03/07/2024, 12:01 PMfile_paths_resource
function is defined before you try to use it in assets.py
. Additionally, you should ensure that the sling_sql
resource is defined before it's referenced in the Definitions
.
Here's the corrected form of the code with the necessary adjustments:
### resource.py
python
# This file should contain the definition of the file_paths_resource.
from dagster import get_dagster_logger, resource
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection
from sqlalchemy import create_engine, text
import warnings
from sqlalchemy.exc import SQLAlchemyError
from dagster_params.params import db_connection_params # Ensure this import is correct
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
@resource
def file_paths_resource():
# ... (The rest of your file_paths_resource function as you've defined it)
# Make sure to return the correct data structure expected by the rest of your code.
# Define the SlingResource for SQL Server using the connection details from params.py
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)
### assets.py
python
# This file should contain the definition of your assets.
from dagster import asset, AssetSpec
from dagster_embedded_elt.sling import SlingMode, build_sling_asset
from .resource import file_paths_resource # Adjust the import path as necessary
def generate_assets(file_info_list):
# ... (The rest of your generate_assets function as you've defined it)
# Use the file_paths_resource to get the file paths and generate assets
file_info_list = file_paths_resource()
assets = generate_assets(file_info_list)
### __init__.py
python
# This file should contain the Dagster Definitions.
from dagster import Definitions, load_assets_from_modules
from .assets import assets # Adjust the import path as necessary
from .resource import sling_sql, file_paths_resource # Adjust the import path as necessary
# Load assets from the assets module
all_assets = load_assets_from_modules([assets])
# Define the Dagster definitions
defs = Definitions(
resources={
"sling_sql": sling_sql,
"file_paths": file_paths_resource,
},
assets=all_assets,
)
### params.py
python
# This file should contain the database connection details and the SQL query.
db_connection_params = {
# ... (Your database connection details)
}
file_path_query = """
# ... (Your SQL query)
"""
Make sure that the file_paths_resource
function is correctlScout
03/07/2024, 12:02 PMgenerate_assets
function should then take this list and generate the assets accordingly. Please adjust the import paths based on your project's structure. The from .resource import ...
and from .assets import ...
imports assume that resource.py
and assets.py
are in the same package as __init__.py
. If they are not, you'll need to adjust the import statements to reflect the correct relative or absolute import paths. After making these changes, test your code to ensure that it works as expected. If you encounter any issues, add logging where necessary to help diagnose any problems.meeniga
03/07/2024, 12:04 PMScout
03/07/2024, 12:04 PM__init__.py
, assets.py
, and resource.py
into one Python script. Here's how you can do it:
```python
# Combined file (e.g., dagster_definitions.py)
from dagster import Definitions, load_assets_from_modules, asset, AssetSpec, get_dagster_logger, resource, ExperimentalWarning
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection, SlingMode, build_sling_asset
from sqlalchemy import create_engine, text
from sqlalchemy.exc import SQLAlchemyError
import warnings
# Suppress experimental warnings
warnings.filterwarnings("ignore", category=ExperimentalWarning)
# Logger for error messages
logger = get_dagster_logger()
# Database connection parameters
db_connection_params = {
"type": "sqlserver",
"host": "172.16.3.126",
"port": 1433,
"database": "template_DC",
"user": "sqluser",
"password": "sqluser",
}
# Resource to fetch file paths, filenames, and tablenames from the database
@resource
def file_paths_resource():
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text("""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id=1)
""")
result = conn.execute(query)
path, filename, tablename = None, None, None
for row in result:
if row['propertynameid'] == 1:
path = row['propertyvalue']
elif row['propertynameid'] == 2:
filename = row['propertyvalue'] + '.csv'
elif row['propertynameid'] == 3:
tablename = 'app.' + row['propertyvalue']
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
# Define the SlingResource for SQL Server using the connection details
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)
# Function to generate assets baScout
03/07/2024, 12:05 PMmeeniga
03/07/2024, 12:16 PMScout
03/07/2024, 12:16 PMload_assets_from_modules
function should be correctly identifying and loading the assets defined in the assets
module. 2. Dagster Instance Configuration: Verify that the Dagster instance is correctly configured to discover the assets. This includes checking that the workspace.yaml file (or equivalent configuration) is set up to point to the correct Python modules or files where the assets are defined. 3. Asset Discovery: Make sure that the assets are being defined using the @asset
decorator or the build_sling_asset
function and that they are accessible from the module you are loading with load_assets_from_modules
. 4. Dagster Daemon: Check that the Dagster daemon is running. The daemon is responsible for running scheduled jobs and updating the asset catalog. If it's not running, assets may not appear as expected. 5. Server Reload: If you've made changes to the asset definitions, you may need to reload the Dagster server to pick up those changes. 6. Error Handling: Add error handling around the asset generation and registration code to catch any issues that may be occurring silently. 7. Logging: Increase the logging level to capture more detailed information about the asset loading process. This can help identify where the process might be failing. 8. Dagster Version: Ensure that you are using a version of Dagster that supports the features you are using. If you are following examples from the documentation, make sure that your installed version of Dagster matches the version of the documentation. 9. Asset Materialization: Verify that the assets are being materialized correctly. If there is an issue with the materialization process, the assets may not appear on the server. 10. Dagster UI: Check the Dagster UI to see if there are any error messages or warnings that could provide clues about why the assets are not appearing. If you've checked all of these and still can't see the assets, you may want to reach out to the Dagster community or support channels with specific details about your setup, including the version of Dagster you're using, your workspace configuration, and any relevant logs or error messages.meeniga
03/07/2024, 12:46 PMScout
03/07/2024, 12:46 PMid
dynamically from the terminal, you can modify your file_paths_resource
function to accept an argument for the id
. You can then use an environment variable or command-line argument to pass the id
when you run your Dagster pipeline. Here's how you can modify the file_paths_resource
function to accept an id
argument: python # resource.py @resource(config_schema={"property_id": str}) def file_paths_resource(context): property_id = context.resource_config["property_id"] # ... rest of the function using property_id
In your Dagster repository definition, you would then pass the property_id
configuration when you define the file_paths
resource. When running your pipeline, you can pass the property_id
via the command line using the -c
flag to specify a run config YAML file or JSON file that includes the property_id
under the resources
section. Here's an example of how you might specify this in a YAML configuration file (run_config.yaml
): yaml resources: file_paths: config: property_id: "1"
And then you would run your pipeline with: bash dagster pipeline execute -f module_with_pipeline.py -c run_config.yaml
Make sure to replace module_with_pipeline.py
with the actual Python file where your Dagster pipeline is defined. Regarding loading all four files, if you have separated your code into different modules (files), you need to ensure that they are imported correctly within your Dagster repository definition. Typically, you would have a repository definition file that looks something like this: python # repository.py from dagster import repository from .assets import assets from .resource import file_paths_resource, sling_sql @repository def my_repository(): return [assets, file_paths_resource, sling_sql]
Make sure that the assets
, file_paths_resource
, and sling_sql
are defined and imported correctly from their respective modules. To run your Dagster pipeline, you would typically use the Dagster CLI and point to the repository definition. If you're using the dagster
CLI, you would run: bash dagster pipeline execute -f repository.py -c run_config.yaml
Again, replace repository.py
with the actual Python file where your Dagster repository is defined, and ensure that run_config.yaml
contains the necessary configuration for your resources and assets.meeniga
03/07/2024, 12:53 PMScout
03/07/2024, 12:53 PMfile_paths_resource
function to accept an id
argument from the configuration, you can use the context.resource_config
to access the property_id
. Here's the updated file_paths_resource
function:
python
# resource.py
from dagster import resource, Field, String
from sqlalchemy import create_engine, text
from sqlalchemy.exc import SQLAlchemyError
import warnings
from dagster_params.params import db_connection_params # Ensure this import is correct
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
@resource(config_schema={"property_id": Field(String)})
def file_paths_resource(context):
property_id = context.resource_config["property_id"]
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text(f"""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id={property_id})
""")
result = conn.execute(query)
path, filename, tablename = None, None, None
for row in result:
if row['propertynameid'] == 1:
path = row['propertyvalue']
elif row['propertynameid'] == 2:
filename = row['propertyvalue'] + '.csv'
elif row['propertynameid'] == 3:
tablename = 'app.' + row['propertyvalue']
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
In this code, the file_paths_resource
function now expects a configuration schema that includes a property_id
. When you define the resource in your Dagster repository, you will provide the property_id
value in the configuration.
Here's an example of how you might define the resource in your repository with the configuration:
python
# repository.py
from dagster import repository
from .assets import assets
from .resource import file_paths_resource, sling_sql
@repository
def my_repository():
return [assets, file_paths_resource.configured({"property_id": "1"}), sling_sql]
In this exScout
03/07/2024, 12:54 PMfile_paths_resource.configured({"property_id": "1"})
is used to provide the property_id
directly in the code. If you want to provide it dynamically, you would use a configuration file when you run your pipeline, as described in the previous message. Remember to replace "1"
with the actual id
you want to use, and adjust the import paths based on your project's structure.meeniga
03/07/2024, 1:03 PMScout
03/07/2024, 1:03 PMdagster
CLI does not recognize the command pipeline
. This is likely because the command has been updated in more recent versions of Dagster. The correct command to execute a pipeline or job is now dagster job execute
. Here's how you can run your job with the updated command: bash dagster job execute -f repository.py -c run_config.yaml
Make sure that your repository.py
file correctly defines and returns your job, and that your run_config.yaml
file contains the necessary configuration for your job and resources. If you're using an older version of Dagster where the pipeline
command was still valid, you might need to update to the latest version of Dagster, or use the command that is appropriate for your version. You can check the version of Dagster you're using with: bash dagster --version
And you can update Dagster to the latest version with: bash pip install -U dagster dagit
After updating, you should be able to use the dagster job execute
command as shown above. If you have any further issues, please ensure that your Dagster environment is set up correctly and that you're following the latest documentation for the version you're using.meeniga
03/07/2024, 1:09 PMdagster
(1.6.6) expected library version (0.22.6) and dagster-embedded-elt
(0.22.2).
warnings.warn(message)
Traceback (most recent call last):
File "/home/voziq/.local/bin/dagster", line 8, in <module>
sys.exit(main())
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/__init__.py", line 48, in main
cli(auto_envvar_prefix=ENV_PREFIX) # pylint:disable=E1123
File "/usr/lib/python3/dist-packages/click/core.py", line 764, in call
return self.main(*args, **kwargs)
File "/usr/lib/python3/dist-packages/click/core.py", line 717, in main
rv = self.invoke(ctx)
File "/usr/lib/python3/dist-packages/click/core.py", line 1137, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/lib/python3/dist-packages/click/core.py", line 1137, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/lib/python3/dist-packages/click/core.py", line 956, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/lib/python3/dist-packages/click/core.py", line 555, in invoke
return callback(*args, **kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/job.py", line 329, in job_execute_command
execute_execute_command(instance, kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/telemetry.py", line 172, in wrap
result = f(*args, **kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/job.py", line 342, in execute_execute_command
job_origin = get_job_python_origin_from_kwargs(kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/workspace/cli_target.py", line 535, in get_job_python_origin_from_kwargs
repository_origin = get_repository_python_origin_from_kwargs(kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/workspace/cli_target.py", line 656, in get_repository_python_origin_from_kwargs
code_pointer_dict = _get_code_pointer_dict_from_kwargs(kwargs)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_cli/workspace/cli_target.py", line 576, in _get_code_pointer_dict_from_kwargs
for loadable_target in get_loadable_targets(
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_grpc/utils.py", line 40, in get_loadable_targets
else loadable_targets_from_python_file(python_file, working_directory)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/workspace/autodiscovery.py", line 26, in loadable_targets_from_python_file
loaded_module = load_python_file(python_file, working_directory)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/code_pointer.py", line 83, in load_python_file
return import_module_from_path(module_name, python_file)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_seven/__init__.py", line 48, in import_module_from_path
spec.loader.exec_module(module)
File "<frozen importlib._bootstrap_external>", line 848, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/home/voziq/dagster_etl/dagster_params/repository.py", line 4, in <module>
from dagster_params.assets import assets
File "/home/voziq/dagster_etl/dagster_params/__init__.py", line 3, in <module>
from dagster_params import assets # Import the dynamically generated asset
File "/home/voziq/dagster_etl/dagster_params/assets.py", line 25, in <module>
file_info_list = file_paths_resource()
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/definitions/resource_definition.py", line 291, in call
return resource_invocation_result(self, None)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/definitions/resource_invocation.py", line 28, in resource_invocation_result
_init_context = _check_invocation_requirements(resource_def, init_context)
File "/home/voziq/.local/lib/python3.8/site-packages/dagster/_core/definitions/resource_invocation.py", line 74, in _check_invocation_requirements
raise DagsterInvalidInvocationError(
dagster._core.errors.DagsterInvalidInvocationError: Resource has required config schema, but no context was provided. Use the build_init_resource_context
function to create a context with config. got this error from dagster import get_dagster_logger, resource, ExperimentalWarning
from dagster_embedded_elt.sling import SlingResource, SlingSourceConnection, SlingTargetConnection
from sqlalchemy import create_engine, text
from dagster_params.params import db_connection_params
import warnings
from sqlalchemy.exc import SQLAlchemyError
from sqlalchemy import text
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
from dagster import resource, Field, String
from sqlalchemy import create_engine, text
from sqlalchemy.exc import SQLAlchemyError
import warnings
from dagster_params.params import db_connection_params # Ensure this import is correct
warnings.filterwarnings("ignore", category=ExperimentalWarning)
logger = get_dagster_logger()
@resource(config_schema={"property_id": Field(String)})
def file_paths_resource():
property_id = context.resource_config["property_id"]
try:
engine = create_engine(
f"mssql+pyodbc://{db_connection_params['user']}:{db_connection_params['password']}@"
f"{db_connection_params['host']}:{db_connection_params['port']}/{db_connection_params['database']}?"
f"driver=ODBC+Driver+17+for+SQL+Server"
)
with engine.connect() as conn:
query = text(f"""
SELECT propertyvalue, propertynameid
FROM app.PropertyConfig
WHERE PropertyId IN (SELECT id FROM app.Property WHERE id={property_id})
""")
result = conn.execute(query)
path, filename, tablename = None, None, None
for row in result:
if row['propertynameid'] == 1:
path = row['propertyvalue']
elif row['propertynameid'] == 2:
filename = row['propertyvalue'] + '.csv'
elif row['propertynameid'] == 3:
tablename = 'app.' + row['propertyvalue']
if not all([path, filename, tablename]):
raise ValueError("Missing path, filename, or tablename from the database results.")
return [(path, filename, tablename)]
except SQLAlchemyError as e:
logger.error(f"An error occurred while fetching file paths: {e}")
raise
except ValueError as e:
logger.error(f"An error occurred while processing file paths: {e}")
raise
# Define the SlingResource for SQL Server using the connection details from params.py
sling_sql = SlingResource(
source_connection=SlingSourceConnection(type="file"),
target_connection=SlingTargetConnection(**db_connection_params)
)Scout
03/07/2024, 1:09 PMdagster._core.errors.DagsterInvalidInvocationError: Resource has required config schema, but no context was provided
, indicates that the file_paths_resource
function is being invoked without the necessary context that includes the configuration schema. In Dagster, resources that require configuration must be provided with a context that includes the configuration data when they are invoked. This is typically done within the execution of a pipeline or job, where Dagster manages the context and provides the configuration to the resource. To resolve this issue, you should ensure that the file_paths_resource
is being used within a Dagster pipeline or job context, and that the necessary configuration is being provided. Here's an example of how you might define a job that uses the `file_paths_resource`: python # jobs.py from dagster import job from dagster_params.resources import file_paths_resource, sling_sql @job(resource_defs={"file_paths": file_paths_resource, "sling_sql": sling_sql}) def my_job(): # Define your job's operations here pass
When you execute this job, you will need to provide the configuration for the file_paths
resource, which includes the property_id
. This can be done via a YAML configuration file when you run the job: yaml # run_config.yaml resources: file_paths: config: property_id: "1"
Then, you can execute the job with the following command: bash dagster job execute -f jobs.py -c run_config.yaml
Make sure to replace jobs.py
with the actual Python file where your job is defined, and ensure that run_config.yaml
contains the necessary configuration for your resources. If you want to invoke the file_paths_resource
outside of a job for testing purposes, you will need to build a resource context manually using the build_init_resource_context
function: python # test_resource.py from dagster import build_init_resource_context from dagster_params.resources import file_paths_resource if __name__ == "__main__": context = build_init_resource_context(config={"property_id": "1"}) file_info_list = file_paths_resource(context) print(file_info_list)
This script manually creates a resource context with the required configuration and then invokes the file_paths_resource
function. Please ensure that your code structure and imports are correct, and that you are using the resources within the appropriate Dagster execution context. If you continue to encounter issues, please refer to the latest Dagster documentation for guidance on defining and using resources with configuration.Scout
03/07/2024, 1:15 PMfile_paths_resource
is invoked correctly within a Dagster job, you need to define a job that uses this resource and provides the necessary configuration. Here's how you can set up your Dagster job: First, define your assets using the @asset
decorator and ensure they use the file_paths_resource
. Here's an example of how you might define an asset: python # assets.py from dagster import asset from .resources import file_paths_resource @asset(required_resource_keys={"file_paths"}) def my_asset(context): file_info_list = context.resources.file_paths() # Perform operations with file_info_list # ...
Next, define your job in a separate file (e.g., jobs.py
) and include the assets you've defined: python # jobs.py from dagster import job from .assets import my_asset from .resources import file_paths_resource, sling_sql @job(resource_defs={"file_paths": file_paths_resource, "sling_sql": sling_sql}) def my_job(): my_asset()
In your repository.py
, you'll define a repository that includes your job: python # repository.py from dagster import repository from .jobs import my_job @repository def my_repository(): return [my_job]
Finally, you need to provide the configuration for the file_paths_resource
when you execute the job. You can do this by creating a YAML configuration file (e.g., run_config.yaml
): yaml # run_config.yaml resources: file_paths: config: property_id: "1"
Now, you can execute your job with the following command, specifying the configuration file: bash dagster job execute -f repository.py -c run_config.yaml
This command tells Dagster to execute the job defined in repository.py
using the configuration provided in run_config.yaml
. Make sure that the file_paths_resource
function in your resources.py
file is correctly configured to accept the property_id
from the resource context: python # resources.py @resource(config_schema={"property_id": Field(String)}) def file_paths_resource(context): property_id = context.resource_config["property_id"] # ... rest of the function
By following these steps, you should be able to run your Dagster job with the file_paths_resource
correctly receiving the property_id
from the configuration file. If you encounter any issues, please refer to the latest Dagster documentation for more detailed guidance on defining and using resources within jobs.