Skip to main content

Basic algo engine

Project description

PyAlgoEngine: Python Algo-Trading Engine

This module is a high-performance market data buffer implementation written in Python, Cython and C, designed for HFT (High Frequency Trading) system.

📦 Features

  • C-level data structures for fast market data access
  • Efficient shared memory support for interprocess communication
  • Compile-time configurable parameters for memory and layout tuning

⚙️ Compile-Time Configuration

This module allows overriding several constants at compile time via environment variables.

Available Parameters

Variable Default Description
TICKER_SIZE 32 Max length of a ticker symbol
BOOK_SIZE 10 Max depth of the order book
ID_SIZE 16 Max length of ID field
MAX_WORKERS 128 Max number of concurrent workers

These values are defined in c_market_data_config.h, but can be overridden at build time.


🚀 Building with Custom Parameters

To override default values, set environment variables before building:

Using pip install

TICKER_SIZE=64 BOOK_SIZE=20 pip install .

Using setup.py directly

TICKER_SIZE=64 BOOK_SIZE=20 python setup.py build_ext --inplace

These environment variables are passed to the C compiler as -D flags and will override the fallback values in c_market_data_config.h.


🧪 Verify Compilation

You can verify the values were compiled correctly by running:

from algo_engine.base import C_CONFIG

print(C_CONFIG)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyalgoengine-0.11.1.post2-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

pyalgoengine-0.11.1.post2-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (11.6 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

pyalgoengine-0.11.1.post2-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (11.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

pyalgoengine-0.11.1.post2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file pyalgoengine-0.11.1.post2-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyalgoengine-0.11.1.post2-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 bb0901447f437259d8f48de36ea08d6e7dec2d45b0b5f7b2d79f3c35b0088de6
MD5 2bb63ee4d953a2990876cd60d2c3be6f
BLAKE2b-256 b38156d498f876985956443f69975737e68c82473e897b61cdc810787a5e600d

See more details on using hashes here.

File details

Details for the file pyalgoengine-0.11.1.post2-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyalgoengine-0.11.1.post2-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 0513ef65fc05af1d5122641b9f4e2fa2b516b9c6de23eb4698b10c65ca74573b
MD5 f10610b0c03009a8aafbbbb825d15725
BLAKE2b-256 d54d01bccbcc70ab8ff5bc9f2fef3efff80032a308de4124c7670e5953c44fc6

See more details on using hashes here.

File details

Details for the file pyalgoengine-0.11.1.post2-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyalgoengine-0.11.1.post2-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 58b9570c1c933979ebe2673fa534ff69953148346c4c6456039dec6e4894d6be
MD5 3500e6615441a39baeb226c3d6a72c86
BLAKE2b-256 925a9c035df795c9fbfb84f957976e55d36ea6c6b820aaf80ed9a3010d33a259

See more details on using hashes here.

File details

Details for the file pyalgoengine-0.11.1.post2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyalgoengine-0.11.1.post2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f7d4094a2bbc35dfb710a26d73c99c7f25f672c4de36b4060f7c1b5c7a296056
MD5 3e73cbb6cf0303a9624d161ece6fdf34
BLAKE2b-256 96d397e3af89a2634dd172c6edade8ea4a54d1838f3f1bb33024d4586935329c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page