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lieuzhenghong / auth_flow.ts
Created June 3, 2021 11:29
sample auth flow
// Login to User Pool
const userPoolToken = ... // Get JWT Token from signing in to Cognito User pool here
// Not 100% sure how to do this. AWS Amplify?
// Get Id
const getIdParams = {
AccountId: 'what is this?',
IdentityPoolId: 'identity pool',
@lieuzhenghong
lieuzhenghong / requirements.txt
Last active December 26, 2020 10:38
Files needed to reproduce the bug
# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: linux-64
_libgcc_mutex=0.1=conda_forge
_openmp_mutex=4.5=1_gnu
appdirs=1.4.4=py_0
attrs=20.3.0=pyhd3deb0d_0
black=19.10b0=py_0
boost-cpp=1.74.0=h9359b55_0
brotlipy=0.7.0=py38h27cfd23_1003
# On a new EC2 instance:
# Setup locale
sudo locale-gen en_US en_US.UTF-8
sudo update-locale LC_ALL=en_US.UTF-8 LANG=en_US.UTF-8
export LANG=en_US.UTF-8
# Setup sources
sudo apt update && sudo apt install curl gnupg2 lsb-release
curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
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@lieuzhenghong
lieuzhenghong / not_any_slower.py
Last active February 3, 2020 18:23
why is this code running slower and slower, but very similar code isn't?
def convert_point_distances_to_tract_distances(pttm, DM_PATH, SAVE_FILE_TO):
'''Returns a JSON file giving driving durations from all points in the Census Tract
to all other points in every other Census Tract.
Takes in three things:
1. A mapping from points to tracts (Dict[PointId : TractId]
2. The distance matrix file path
3. The path to save the output tract distance file to
Reads line by line
@lieuzhenghong
lieuzhenghong / SimpleApp.scala
Created September 16, 2019 14:26
Scala code for doing data analysis
object SimpleApp {
def main(args: Array[String]) {
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions.explode
val spark = SparkSession.builder.appName("TripAnalysis").getOrCreate()
import spark.implicits._
val results_path = "s3a://results/"
val paths = "s3a://trips/*"
val tripDF = spark.read.option("multiline", "true").json(paths)
// "Explode" the data array into individual rows
object SimpleApp {
def main(args: Array[String]) {
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions.explode
val spark = SparkSession.builder.appName("TripAnalysis").getOrCreate()
import spark.implicits._
val results_path = "s3a://results/"
val paths = "s3a://trips/*"
val tripDF = spark.read.option("multiline", "true").json(paths)
val linksDF = tripDF.select(explode($"data").as("data"))
@lieuzhenghong
lieuzhenghong / setup.md
Last active September 16, 2019 14:16
Setting up Apache Spark on the Raspberry Pi Cluster

Preliminaries

Have the spark folder in a directory of your choice.

For my master it was home/lieu/dev/spark and for my slaves it was /home/pirate/spark.

Do the following export on master because the slaves and the master have their spark folder in different directories (we'll make use of this later)

export $SLAVE_SPARK_HOME=/home/pirate/spark/spark-2.4.4-bin-without-hadoop

@lieuzhenghong
lieuzhenghong / bloom_filter_false_positives.ipynb
Created September 20, 2017 09:29
False positives of a Bloom filter
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