| #!/usr/bin/env python3 | |
| """ Binary search tree with method to invert in-place. """ | |
| class Node(object): | |
| def __init__(self, x): | |
| self.value = x | |
| self.left = None | |
| self.right = None |
| #include "btree.h" | |
| template <typename T> | |
| void Btree<T>::insert(const T &x) { | |
| if (root == nullptr) { | |
| node_ptr node = std::make_unique<Node>(x); | |
| root = std::move(node); | |
| return; | |
| } |
| def chunk(xs, n): | |
| """ Split an iterable into chunks. | |
| Parameters | |
| ---------- | |
| xs : iterable | |
| Iterable to be split. | |
| n : int | |
| Chunk size. |
| from collections import OrderedDict | |
| class LRUCache(object): | |
| def __init__(self, max_size=4): | |
| if max_size <= 0: | |
| raise ValueError | |
| self.max_size = max_size | |
| self._items = OrderedDict() |
| from scipy.stats import norm | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| plt.style.use("ggplot") | |
| def save_and_close(fig, filename): |
| from scipy.stats import norm | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| plt.style.use("ggplot") | |
| # Simulate from a Univariate Gaussian Mixture Model. |
| # open terminal | |
| cmd - return : osascript -e 'tell application "iTerm" to create window with default profile' | |
| # enter fullscreen mode for the focused container | |
| # cmd + f clobbers text search in firefox. | |
| shift + cmd - f : yabai -m window --toggle zoom-fullscreen | |
| # kill focused window | |
| shift + cmd - q : yabai -m window --close |
| """Parse data element numbers as trees.""" | |
| # XXX: Second spectral digit is broken - both values are 0! | |
| from dataclasses import dataclass | |
| from lxml import html | |
| from typing import Any, Dict, List | |
| DELIMITER = "\x97" # — | |
| MIN_COLSPAN = 1 |
| import boto3 | |
| s3_client = boto3.client("s3") | |
| # List available operations. | |
| s3_client._service_model.operation_names | |
| operation_name = "ListObjectsV2" | |
| params = { |
Add packages to the Spark session from within python. They'll be automatically downloaded if they're not already available.
# Using `JsonSerDe` as an example.
os.environ["PYSPARK_SUBMIT_ARGS"] = (
'--packages "org.apache.hive.hcatalog.data.JsonSerDe" pyspark-shell'
)
spark = SparkSession.builder.config().getOrCreate()