54 lines
1.5 KiB
YAML
54 lines
1.5 KiB
YAML
{% set name = "ferro-ta" %}
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{% set version = "1.2.0" %}
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package:
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name: {{ name|lower }}
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version: {{ version }}
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source:
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# Build from PyPI wheel (simplest approach; no Rust toolchain required).
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# Replace with url/sha256 of the specific wheel for your platform or
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# use `pip_install: true` to let conda-build fetch it.
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pip_install: true
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packages:
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- ferro-ta=={{ version }}
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build:
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number: 0
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# Use noarch: python only if wheels are already compiled. For source builds
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# remove noarch and add the maturin build steps below.
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noarch: python
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script: |
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{{ PYTHON }} -m pip install ferro-ta=={{ version }} --no-deps --ignore-installed -vv
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requirements:
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host:
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- python
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- pip
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run:
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- python >=3.10
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- numpy >=1.20
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test:
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imports:
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- ferro_ta
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commands:
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- python -c "from ferro_ta import SMA, RSI; import numpy as np; print(SMA(np.array([1.0,2.0,3.0,4.0,5.0]), timeperiod=3))"
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about:
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home: https://github.com/pratikbhadane24/ferro-ta
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license: MIT
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license_family: MIT
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summary: Rust-powered Python technical analysis library with a TA-Lib-compatible API
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description: |
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ferro-ta is a Rust-powered Python technical analysis library with a
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TA-Lib-compatible API and pre-compiled wheels for the supported platforms.
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It provides 155+ indicators via a Rust core and PyO3 bindings, with
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optional pandas and streaming APIs.
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doc_url: https://github.com/pratikbhadane24/ferro-ta
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dev_url: https://github.com/pratikbhadane24/ferro-ta
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extra:
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recipe-maintainers:
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- pratikbhadane24
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