feat(Docs): prepare for sphinx-pages (#205)

* feat(Docs): prepare for sphinx-pages

* feat(CI): added sphinx workflow

* feat(Docs): added content

* fix(CI): use the patched GH action

* fix(CI): set source dir

* chore(Docs): reorder project structure

* chore(Docs): moved index.rst one level up?

* fix(Config): restore the config file, etc.

* fix(Docs): adjusted config
This commit is contained in:
Mark Aron Szulyovszky
2022-02-02 17:56:25 +01:00
committed by GitHub
parent 1f813f89e3
commit 62686393f5
15 changed files with 299 additions and 1 deletions
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on: [push]
jobs:
build:
name: Sphinx Pages
runs-on: ubuntu-latest
steps:
- uses: toniher/sphinx-pages@patch-1
id: sphinx-pages
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
create_readme: true
source_dir: docs
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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
SOURCEDIR = content
BUILDDIR = _build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
import os
import sys
sys.path.insert(0, os.path.abspath('.'))
# -- Project information -----------------------------------------------------
project = 'Drift'
copyright = '2022, Daniel Szemerey and Mark Szulyovszky'
author = 'Daniel Szemerey, Mark Szulyovszky'
# The full version, including alpha/beta/rc tags
release = '1.0'
# -- General configuration ---------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['sphinx.ext.autodoc',
'sphinx.ext.autosectionlabel'
]
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This pattern also affects html_static_path and html_extra_path.
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', 'sphinx-env']
# -- Options for HTML output -------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = 'furo'
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
# html_static_path = ['_static']
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.. drift documentation master file, created by
Daniel Szemerey and Mark Szulyovszky on Wed Feb 02 14:02:22 2022.
Welcome to drift's documentation!
==================================
TLDR: *Drift helps you train and make predictions on time-series data.*
.. figure:: images/pipeline.png
:alt: Figure of Data transformation pipeline
Pipeline of the entire process.
Drift is an **end-to-end***, **composable*** **modelling pipeline for financial time-series prediction**. It was designed for quantitative financial predictions.
Drift was specifically engineered not to fool the user: it uses walk-forward method for analysis and makes sure no future information is introduced.
Drift makes it easy to use state-of-the-art methods financial ML techniques, like the triple-barrier labeling method, ensembling models and adding bet-sizing into the mix (with meta-labeling).
Drift has two level of usage: You can simply use existing models and transformations and just provide the data and the target asset, or you can customize your own pipeline.
Technical Explanation
==================================
Why Drift
--------------------------------
Machine learning on financial time series requires a fundamentally different approach compared to standard ML domains.
The (small amount of) data is non-stationary, extremely noisy, where the patterns frequently change, and it's extremely important to not to leak out-of-sample data into the test set.
How Drift is different
--------------------------------
There are very few open-source end-to-end machine learning pipelines that can be effectively used to train and evaluate ML models on financial time series. Among them are: [qlib](https://github.com/microsoft/qlib), [AlphaPy](https://github.com/ScottfreeLLC/AlphaPy).
Drift is different to them in a couple of angles:
- All pre-processing steps are *online (up until a certain point),* ****so they never inject lookahead bias into the mix. (this is a major issue with finML papers)
- Feature extraction and selection are an important, pre-built step in the pipeline. Garbage in, garbage out!
- Evaluation is done in a [walk-forward manner](https://en.wikipedia.org/wiki/Walk_forward_optimization). We argue that that a train/validation/test split is not adequate to evaluate an ML model's performance in a non-stationary, regime changing environment. The walk-forward methodology enables us to evaluate the model's performance on almost the whole time series.
- Training can be done in any way possible, including Combinatorial purged k-fold cross-validation. You can shuffle the past in any way you prefer, but you can never use data from the future to train the model.
- Instead of training one model, you train tons of models **over time**, that are making predictions until they become obsolete. The walk-forward training/evaluation methodology enables "online" (ever-changing) models, that adapt to the market environment. You can specify how frequently would you like to re-train the models.
- Ensemble-by-default: train multiple models, and average their predictions. Improves performance and adds a lot of robustness in a low signal-to-noise environment, like financial time series.
- Bet sizing and Meta-labeling (training a model to evaluate a lower level model's prediction for each timestamp) is a built-in feature.
This project is inspired partially by [Marcos Lopez de Prado's Advances in Financial Machine Learning](https://www.wiley.com/en-us/Advances+in+Financial+Machine+Learning-p-9781119482086) and [The Alpha Scientist's blogposts](https://alphascientist.com/).
External Links
--------------------------------
For more information refer
`here<www.python.org>`
.. py:function:: square(x)
return the square of a function
Contents
==================================
.. toctree::
:maxdepth: 2
setup/index
basic-usage/index
advanced-usage/index
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@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd
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Sphinx
sphinx_rtd_theme
sphinx_rtd_theme_ext_color_contrast
myst_nb
sphinx-lesson
furo
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Advanced Usage
==========
.. toctree::
:maxdepth: 2
installguide
@@ -0,0 +1,16 @@
Setup and Installation
======================
Install using pip
-----------------
This is a sub heading to install using pip
.. code-block:: python
pip install library
.. note::
This is a note. Add your note here
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Basic Usage
==========
.. toctree::
:maxdepth: 2
installguide
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Setup and Installation
======================
Install using pip
-----------------
This is a sub heading to install using pip
.. code-block:: python
pip install library
.. note::
This is a note. Add your note here
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Start Here
==========
.. toctree::
:maxdepth: 2
installguide
quick_start
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Setup and Installation
======================
Install using pip
-----------------
This is a sub heading to install using pip
.. code-block:: python
pip install library
.. note::
This is a note. Add your note here
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Quick Start
======================
Install using pip
-----------------
This is a sub heading to install using pip
.. code-block:: python
pip install library
.. note::
This is a note. Add your note here
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@@ -10,4 +10,4 @@ dependencies:
- pip:
- black
- libcst
prefix: /usr/local/anaconda3/envs/strip
prefix: /usr/local/anaconda3/envs/strip