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| <html lang="en" > | |
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| <meta charset="utf-8"> | |
| <title>test</title> | |
| <link rel="apple-touch-icon" sizes="180x180" href="https://cdn.holoviz.org/panel/1.2.3/dist/images/apple-touch-icon.png"> | |
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I host a blog on github pages that is generated using jekyll. Every time I get a new Mac, I need to set up the backend for developing the blog. This setup process always takes way longer than I'd like, so it's documented here for convenience.
Jekyll is a ruby package, and thus requires us to have ruby installed on our machine. Note that Macs come with a system installation of ruby, e.g. if you run
which ruby
# /usr/bin/ruby
ruby -v
| from scipy import stats | |
| from typing import Tuple, Union | |
| import numpy as np | |
| import pandas as pd | |
| def xi_corr( | |
| x: np.ndarray, y: np.ndarray, return_p_values: bool = False | |
| ) -> Union[float, Tuple[float, float]]: | |
| """Implementation of Chatterjee's correlation, which can capture both monotonic |
| name: numerai-quant | |
| channels: | |
| - conda-forge | |
| dependencies: | |
| - python=3.8 | |
| - conda-build | |
| - pip | |
| - ipython | |
| - loguru | |
| - numpy |
| """ | |
| ## Example Airflow Workflow (DAG) | |
| Markdown docstrings are rendered in the Airflow UI!!! | |
| """ | |
| from airflow import DAG | |
| from airflow.models import BaseOperator | |
| from datetime import datetime, timedelta |