Overview
onetick.py is a versatile and efficient Python library designed for handling tick data with ease.
It harnesses the power of OneTick, the industry-leading tick analytics technology, to process tick
data at unparalleled speeds. This library is tailored both for existing OneTick users,
as a Python interface into OneTick, and for new users who seek an intuitive tool for tick data analysis
that comes with tick data from 200+ exchanges.
The primary strength of onetick.py lies in its similarity to the popular Python library, Pandas.
Users familiar with Pandas find onetick.py easy to learn. In particular, onetick.py users
can think in terms of Python expressions, built-ins, and native math operations on tick fields.
onetick.py goes far beyond the functionality that exists in Pandas exposing all of the power of OneTick
(decades of development for the capital markets use cases) in a Pandas-like style. Crucially, the
Pandas-like syntax is translated into the OneTick query language, executing on the high-performance
OneTick tick server engine. In a nutshell, onetick.py combines the ease of use of Python
with the performance of OneTick.
Installation
The latest version of onetick-py is available on PyPI: https://pypi.org/project/onetick-py/.
pip install onetick-py[webapi]
Use webapi extra to easily use it with remote OneTick REST Servers, such as OneTick Cloud.
See Getting Started
section in the documentation to see how quickly set up onetick-py configuration
and authentication and start running queries.
For other installation options, including using onetick-py with locally installed OneTick server,
see Installation
section in the documentation.
Key Features
- Pandas-like API: Familiar syntax and functions for those accustomed to Pandas.
- High-Performance: Executes complex queries rapidly using the underlying OneTick C++ engine.
- Real-time processing / CEP: Same intuitive syntax for real-time and historical analytics.
- Convenient Data Inspection and Testing: Integrated tools for debugging, data inspection, and testing with pytest.
- Enterprise-Grade Features: Includes support for authentication, access control, encryption, and entitlements.
- Comprehensive Documentation: Public multiversion documentation with examples, guides, and use cases.
Applications
- TCA / BestEx: Quickly implement your own TCA / BestEx analytics.
- Quant research: Ideal for complex, high-performance tick data analysis.
- Algorithmic Trading: Efficient for developing and testing trading algorithms.
- Data Visualization: Compatible with OneTick's visualization tool, OneTick Dashboard.
- Machine Learning: Integrates with the OneTick ML library onetick-ml.
- Industry Applications: Industry leading OneTick's Trade Surveillance and BestEx/TCA solutions are written in
onetick.py. - Back Testing: Retrieve historic market data and metrics.
- Market Microstructure: Consolidated Book Depth analysis.
Advantages Over Competitors
- Ease of Use: The only language that provides the performance of a DSL without having to learn a new syntax.
- Performance: Demonstrates superior performance and memory efficiency compared to similar tools.
- Parallel Processing: Natively parallelizable by security and by day.
- Production-Ready: Ideal for debugging, testing, and CI/CD.
Ways to use onetick.py
onetick.py can be used to analyze data managed and hosted by OneTick or managed and
hosted by the customer in a local OneTick installation.
Hosted OneTick
- Hosted OneTick comes with high quality tick data, daily data, and reference data for 200+ global markets.
- OneTick offers T+1 and real-time tick data that is normalized and quality checked.
- OneTick supports a variety of symbologies and handles corporate action adjustments.
- The installation is a simple
pip install(details here).
Local OneTick
- Manage all of your market data and order flow in the industry-leading tick management platform OneTick.
- Have your users access and analyze the data via a simple and intuitive
onetick.pyAPI. - Managed services options are available.
- Installation details are here.
OneTick
onetick-py is part of a bigger tick management OneTick ecosystem. You may want to turn to OneTick for
- Visual query designer.
- Collecting, loading, and storing tick data.
- Other APIs including C++, C#, Java, R, Matlab.
- Learn more at onetick.com/onetick-tick-analytics-platform.
1 maintainer
Metadata
1 maintainer
Release files for onetick-py 1.210.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| onetick_py-1.210.0.tar.gz | 511.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| onetick_py-1.210.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / onetick_py-1.210.0.tar.gz
| Download URL | onetick_py-1.210.0.tar.gz |
|---|---|
| Size | 511.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ce50621d8ae33c76729a42ee22bfaa80464f21879b4c0a864ef21c391de7bcbd
|
|
BLAKE2b-256 checksum How to use checksums |
5b0ff2db1240a0eeb7bc6b72e709f3c579bbae8bcb407acff0373208b7898753
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.9 {"installer":{"name":"uv","version":"0.12.9","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"12","id":"bookworm","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / onetick_py-1.210.0-py3-none-any.whl
| Download URL | onetick_py-1.210.0-py3-none-any.whl |
|---|---|
| Size | 578.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
60167b15a61120f4db2b11da1322e01c8da8a3c8f638835e40a8ece1e102d58f
|
|
BLAKE2b-256 checksum How to use checksums |
f7888f81138a36a7f1e9edf778bd8fb8c1576d9c2b1bc287f265fade9925ee72
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.9 {"installer":{"name":"uv","version":"0.12.9","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"12","id":"bookworm","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
