alchemy | A collection of deep learning models built using Merlin | Machine Learning library

Sometimes there is a need to display points on the graph on top of the axes so that the result looks something like this:

Previously, when I used R, it took a certain amount of alchemy to get the desired result: first the size of the rendering field was set, then the position of the axis, and at the end data points were drawn on top of all this:

I have a piece of code that dumps a dataframe with 30k rows into a table on my Vertica database. But since its taking way too long to run, I'm trying to use fast_executemany parameter of sqlalchemy.

This question is essentially a follow-up to this question. I have been trying to follow Alchemy documentation to create an NFT contract but encountered the need (as described in the linked question) to import ERC721URIStorage. However, I now get a number of compilation problems that do not make clear sense to me.

In response to the first error (see below), I have tried adding in the import statement for ERC721: import "@openzeppelin/contracts/token/ERC721/ERC721.sol"; This did not change anything in the set of compilation errors.

I need to write a Python SQLAlchemy code converting this SQL query, but I cannot find a meaningful way to perform this query in SQL Alchemy.

I have the following tables, and I wanted to see if I could perform an insert, where for each inserted row, the value of the linked column gets selected by the other one using SQL alchemy and the insert function. The tables are:

While trying to set up a basic self-hosted unit testing environment (and CI) that tests this Chainlink VRF random number contract, I am experiencing slight difficulties in how to simulate any relevant blockchains/testnets locally.

For example, I found this repository that tests Chainlinks VRF. However, for default deployment it suggests/requires a free KOVAN_RPC_URL e.g. from Infura's site and even for "local deployment" it suggests/requires a free MAINNET_RPC_URL from e.g. Alchemy's site.

I adopted a unit test environment from the waffle framework which is described as:

I am using Python and SQL Alchemy to automate some categorizations of products. Essentially I am looking to take any csv with items as the rows and format it into search strings for a case statement of a SQL query.

I want to write a function in python that will measure the length of a row (or list) and insert text in between each of the words and output a string that will feed into SQL to find those words. The screenshot attached is how I've been doing it in excel. I'm sure this is fairly straightforward for someone with some concatenation skills.

Script Output Example

I have a pandas dataframe and I'm trying to use the pd.df.to_sql() function to an Oracle database. My Oracle database is 19.3c. Seems easy enough right? Why won't it work??

I saw in a few other another stackoverflow posts that I should be using sqlalchemy datatypes. Okay. Links:

• Pandas and SQL Alchemy: Specify Column Data Types
• Pandas to_sql changing datatype in database table
• https://docs.sqlalchemy.org/en/14/dialects/oracle.html#oracle-data-types

Seems there's a problem with my sql alchemy connection, don't get why? it works sometimes and then doesn't the next. Also vs code isn't auto recommending sql alchemy methods, maybe I've set it up wrong?

--database.py file