Skip to main content

logo_website
Whitehole is a zarr-format-based-tool that allows individuals or small teams interested in processing financial information to make investment decisions.

What do I need to know to start?


Whitehole was thought to fill the gap between the techniques used by the industry and some retail quantitative investors. Thus, the first step to think about is that there is a huge amount of data that is necessary to process for different purposes, specially for ticks market data instead of candlebars. That's why we need a format to store all the data in less storage space. In that sense, Quantmoon Technologies provides tick data using Zarr format. Zarr allows to chunk this tick data and store it in binary structure with metadata as labels.

Whithole use this light data files to upload and read it in Python environments, such as Jupyter, Spyder, PyCharm and more. The idea behind this is to get useful data arrays to work efficiently through any required process. So, xarray is the main library useful for hold the data and work with it.

As an additional features, Whitehole allows to use numpy and pandas to work with the data for different purposes, specially when the processing has to be done just once in the workflow.

Whitehole is fully developed in Windows.

Features:


  • Decryptor: because of zarr store data in binary, with this class is possible to transform it in a more human-comprenhensive way.
  • Whitehole is thought to have different features, the processing of the information will be realized in future versions.

How do I get it?


Whitehole can be installed from PyPI using pip:

pip install whitehole

Quick Start


To have a better understanding of the features, please check the notebooks on the notebook folder

Metadata

Release files for whitehole 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for whitehole 0.0.3
File Size Uploaded
whitehole-0.0.3.tar.gz 5.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for whitehole 0.0.3
File Interpreter ABI Platform
whitehole-0.0.3-py3-none-any.whl Python 3 none any Details

Total release size: 12.6 kB

Release files / whitehole-0.0.3.tar.gz

Download URL whitehole-0.0.3.tar.gz
Size 5.5 kB
Tags Source
SHA-256 checksum
How to use checksums
dc276e862ca64cf6d35fe7280df77a9778f985e42360c70493b81824a29839b4
BLAKE2b-256 checksum
How to use checksums
19ad18fbefc99c1a97d41fc1ffa88c9cc997ee1959e77828a5970a27557fc138
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.5.6

Release files / whitehole-0.0.3-py3-none-any.whl

Download URL whitehole-0.0.3-py3-none-any.whl
Size 7.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
647957ce6ffaeec2e7a96fb426539dee123f41b5888629ab9071949c76826f4b
BLAKE2b-256 checksum
How to use checksums
8af5546e4f4014cbee468e723d959d72ed3adbf092ed93a3534689f89fe93bd8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.5.6

Release history Release notifications | RSS feed

This release

0.0.3 This release

2 release files

0.0.2

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page