semvec/pypi-packages huggingface dataset:
ukb-api 0.409
UKB API
Requires Python: >=3.6

# UKB_API

This library has been designed to provide convenient access to UKB dataset to users of PSC and Openmind7 clusters by leveraging Datalad package. Datalad allows its users to store large datasets in a distributed manner and faciliate easier collaboration. Currently the repo has modules dedicated to three types of data stored within the UKB dataset namely Scalar, Genetic and Bulk data types. The library also serves as a directory for all the unique categories and field ids which are part of UKB dataset. 

Datalad is designed as a tool to version control large datasets in a manner quite similar to Git but limited to either a single network, HPC cluster. This library has been designed to help the end user make use the principles of datalad to access data stored on a different cluster and even with limited knowledge of how datalad works.

Additionally this repository also houses the notebook files related to this project showcasing exploratory data analysis done on multiple categories.The modules are currently designed to give access to the necessary data through the use of maximum of three-four lines of code.
## Documentation
```
[Documentation for this repo can be found here]
```

![Documentation](docs/build/html/index.html)



## Installation
```
pip install ukb-api==0.370

```

1. Import relevant modules and initilize objects
```
from UKBRepo.UKBRepo import module_scalar_data_handler as scalar_module

scalar_handler_object=scalar_module.scalar_data_handler()
```
2. Pick the main category to which your datatype belongs (T1_Images/Freesurfer/Diet/Smoking)
```
scalar_handler_object.display_all_ukb_categories()
```
3. Fetch relevant field for that Category
```
bulk_handler_object.get_field_ids_for_category(Category_Name)
```
4. Retrive the list of subjects who have those particular field ids
```
bulk_handler_object.get_subject_list_field_ids(Field_Id_List)
```
5. Retrive relevant data for the subjects
```
bulk_handler_object.get_data_bulk(Field_Id,subject_id)
```

After executing the funtion of data retrival,the output user receives depends upon the type of data bieng requested. In case of scalar data the user will recive the actual data in the output whereas in case of bulk data it will be the path where the fetched bulk data files have been stored. 

# Requirements

1. Datalad
2. Git-annex
3. Pandas
4. Numpy

# Refrences

http://handbook.datalad.org/en/latest/
pontis 0.6.3
Core package for Pontis oracle on Starknet
Requires Python: ==3.7.*

# Pontis Oracle

## About

For more information, see the project's repository [here](https://github.com/42labs/Pontis).

## Usage

### Publishing a Price Feed

First, please register with the Pontis team. Currently being a data publisher is permissioned, while we build out the safeguards that will allow us to enable anyone to be a data publisher in the future. Reach out to @JonasNelle on Telegram to inquire about becoming a data publisher.

Once you have chosen your publisher_id and have a public/private key pair that is registered, you can start publishing prices!

Simply install this package and run:

```
from pontis.core.entry import construct_entry
from pontis.publisher.client import PontisPublisherClient

client = PontisPublisherClient(private_key, publisher_address)
entry = construct_entry(key, value, timestamp, publisher)
client.publish(entry)
```