You:
I want to connect to a various databases using rust, send select queries, and return polars data frames.
I need to connect to vertica, db2, ms sql server, and postgres databases. how do you recommend that I do each of those? It can be a different method for each database type if necessary.
ChatGPT:
You:
I'm building a model in power bi. I have two tables, and there is a one-to-one relationship between them based on the combination of these columns: branch_origin_key, branch_dest_key, outbound_revenue_customer_key How do I get around the limitation that relationships between tables in power bi can only be based on one column?
ChatGPT:
Thought for 13 seconds
Power BI’s model designer can only link two tables on one column, so you have to collapse your three-column key into a single surrogate key (or refactor the model). Here are the two common ways:
Under Sarbanes-Oxley (SOX) Section 404, companies must maintain effective internal control over financial reporting – which includes IT general controls like change management. Both management and auditors (guided by PCAOB/AICPA standards) evaluate whether changes to production systems (especially those impacting financial data) are properly controlled. In practice, change management is expected to be “a systematic and standardised approach to ensuring all changes to the IT environment are appropriate, authorised and preserve the integrity of… programs and data”. The widely-used COSO internal control framework reinforces that principle: it highlights control activities such as proper authorizations/approvals and segregation of duties as fundamental to mitigating risks. In short, SOX compliance demands that moving any update into a production environment be subject to
| # Ensure the ScheduledTasks module is available | |
| Import-Module ScheduledTasks | |
| # Define the search string | |
| $searchString = '\scheduled_reports\' | |
| # Retrieve all scheduled tasks that have actions defined | |
| $allTasks = Get-ScheduledTask | Where-Object { $_.Actions -ne $null } | |
| # Initialize an array to store matching tasks |
| from confluent_kafka import Consumer, TopicPartition | |
| # Consumer configuration | |
| conf = { | |
| 'bootstrap.servers': 'your_broker', | |
| 'group.id': 'your_group', | |
| 'enable.auto.commit': False, | |
| 'auto.offset.reset': 'none', | |
| } | |
| consumer = Consumer(conf) |
| import networkx as nx | |
| from ortools.sat.python import cp_model | |
| from typing import List, Optional | |
| import matplotlib.pyplot as plt | |
| def generate_random_directed_graph( | |
| num_nodes: int, | |
| edge_prob: float, | |
| seed: int | None = None |
| -- Assuming table t has one row with lower_bound and upper_bound | |
| WITH Numbers AS ( | |
| -- Anchor member: start with the lower bound | |
| SELECT lower_bound AS number | |
| FROM t | |
| UNION ALL | |
| -- Recursive member: increment the number by 1 each time | |
| SELECT number + 1 | |
| FROM Numbers | |
| WHERE number + 1 <= (SELECT upper_bound FROM t) |
| DECLARE @SchemaName NVARCHAR(128) = 'YourSchemaName'; | |
| DECLARE @SQL NVARCHAR(MAX) = ''; | |
| -- Select all columns that have a NOT NULL constraint | |
| SELECT @SQL = @SQL + 'ALTER TABLE [' + s.name + '].[' + t.name + '] ALTER COLUMN [' + c.name + '] ' | |
| + TYPE_NAME(c.system_type_id) | |
| + CASE | |
| WHEN c.max_length = -1 THEN '(MAX)' | |
| WHEN c.system_type_id IN (231, 167) THEN '(' + CAST(c.max_length AS VARCHAR(10)) + ')' | |
| WHEN c.system_type_id IN (106, 108) THEN '(' + CAST(c.precision AS VARCHAR(10)) + ',' + CAST(c.scale AS VARCHAR(10)) + ')' -- Handle DECIMAL/NUMERIC |
| def prorate_proportionally(df: pd.DataFrame, group: pd.DataFrame): | |
| # Get the total tonnage values from the first row | |
| total_tonnage_moved_contract = group.iloc[0]["tonnage_moved_contract"] | |
| total_tonnage_moved_spot = group.iloc[0]["tonnage_moved_spot"] | |
| total_tonnage_moved_unknown = group.iloc[0]["tonnage_moved_unknown"] | |
| # Calculate the total commitment | |
| total_commitment = group["tonnage_committed"].sum() | |
| # Compute proration factors for each row |