python-sdk | MercadoLibre 's Python SDK | SDK library

I uploaded a CSV file containing 9 documents to a collection in Watson Discovery. I've tried searching this collection with some queries but the confidences are really low(0.01 -> 0.02), despite returning the correct document. That led me to Relevancy training. I input around 60 questions and rate the returning results (on the Improvement tools panel). However, it seems to me that the training never starts. IBM keeps showing "IBM will begin learning soon". Here is the project status checked by python-sdk API. It has been like this for a couple of days.

My questions are:

1. What could be possibly wrong with the relevancy training that lead to the training process not running?
2. Is confidence of 0.01 -> 0.02 normal for an untrained collection (untrained strategy)?

Thank you in advance.

I want to use RCF's "test" channel, to get performance-metrics of the model.

I have previously used the record_set() method without specifying a channel and training worked fine.

However if I upload my feature matrix and label vector using record_set() and set channel='test' like this:

Kucoin Futures API documentation for placing a limit order ( https://docs.kucoin.com/futures/#place-an-order ) has a param called "size" with type Integer. The description is given as "Order size. Must be a positive number".

A limit order to buy "CELRUSDTM" with param size = 1 results in an order placed to buy 10 CELR. A limit order to buy "ETHUSDTM" with param size = 1 results in an order placed to buy .01 ETH.

What does "size" actually refer to?

For reference, I'm using a python library called kucoin-futures-python-sdk (https://github.com/Kucoin/kucoin-futures-python-sdk/blob/main/kucoin_futures/trade/trade.py) and the class method is called create_limit_order

Here's the python to call this method to place the orders:

I am building a snap to test integration of a python script and a python SDK with snapcraft and there appears to be a conflict when two python 'parts' are built in the same snap.

What is the best way to build a snap with multiple python modules?

I have a simple script which imports the SDK and then prints some information. I also have the python SDK library (https://help.iotconnect.io/documentation/sdk-reference/device-sdks-flavors/download-python-sdk/) in a different folder.

I have defined the two parts, and each one can be built stand alone (snapcraft build PARTNAME), however it seems the python internals are conflicting at the next step of 'staging' them together.

tree output of structure

I have fed some data into a TravelTime (https://github.com/traveltime-dev/traveltime-python-sdk) API which calculates the time it takes to drive between 2 locations. The result of this (called out) is a dictionary with that looks like this:

I need to import function from different python scripts, which will used inside preprocessing.py file. I was not able to find a way to pass the dependent files to SKLearnProcessor Object, due to which I am getting ModuleNotFoundError.

Code:

Creating a simple client library so that someone who uses my api will have an easy time of it. Fairly new to python (3 months) and never created my own module/library/package before. I watched a ton of very simple tutorials and thought I was doing it properly. But I'm getting a module not found error despite following the instructions to the letter. Here is the basic format (Note, I've replaced the names of most files, classes, and methods because of a workplace policy, it should have no impact on the structure however)

I am using the sample program from the Snowflake document on using Python to ingest the data to the destination table.

So basically, I have to execute put command to load data to the internal stage and then run the Python program to notify the snowpipe to ingest the data to the table.

This is how I create the internal stage and pipe:

I am using Oracle NoSQL Cloud Service on OCI and I want to write a program using the Oracle NoSQL Database Python SDK.

I did a test using the OCI SDK, I am using instance-principal IAM vs creating config files with tenancy/user ocid and API private keys on the nodes which invoke the noSQL api calls

Is it possible to do a connection using instance-principal instead of creating config files with tenancy/user ocid and API private keys with the Oracle NoSQL Database Python SDK.

I read the examples provided in the documentation https://github.com/oracle/nosql-python-sdk but I cannot find information about instance-principal support