abelsonlive

#!/usr/bin/env python
import json
import copy
import sys
import argparse
from datetime import datetime, timedelta
from subprocess import Popen, PIPE


# dictionary of partiton names to variable generating functions

abelsonlive

aws_access_key_id: 
aws_secret_access_key: 
rs_user: 
rs_server: 
rs_db: 
rs_port: 
rs_password: 

abelsonlive

install.packages("foreign")
library("foreign")
data = read.dbf("path/to/file.dbf")
write.csv(data, "path/to/file.csv", row.names=F)

abelsonlive

profile_dir: '~/.dbt'                    # the location of dbt configurations
target: prod                             # the dbt profile to use for connection
source_schema: fivetran_app              # the tables' source schema (where fivetran imports your data to)
materialized: view                       # how to materialize these views
target_schema: app                       # the schema to materialize the base models under (where users will access the data from)
table_prefix: app                        # a prefix to prepend to each base model/view
directory: models/base/                  # the directory under which to save the base models
empty_as_null: true                      # whether or not to apply EMPTYASNULL logic to all text fields
incl_fivetran_deleted: false             # whether or not to include records marked as "deleted" by fivetran
excl_fivetran_synced: true               # whether or not to include the time fivetran synced each record

abelsonlive

# Brian Abelson @brianabelson
# Harmony Institute
# December 5, 2012

# lda is a wrapper for lda.collapsed.gibbs.sampler in the "lda" package
# it fits topic models using latent dirichlet allocation
# it provides arguments for cleaning the input text and tuning the parameters of the model
# it also returns alot of useful information about the topics/documents in a format that you can easily join back to your original data
# this allows you to easily model outcomes based on the distribution of topics within a collection of texts

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# yay!
cbind.fill<-function(...){
    nm <- list(...) 
    nm<-lapply(nm, as.matrix)
    n <- max(sapply(nm, nrow)) 
    do.call(cbind, lapply(nm, function (x) 
    rbind(x, matrix(, n-nrow(x), ncol(x))))) 
}

abelsonlive

Keybase proof

I hereby claim:

• I am abelsonlive on github.
• I am brianabelson (https://keybase.io/brianabelson) on keybase.
• I have a public key ASB8plf3RA_IBu07tMbiBLNUcqZ1lS-uzC8TtsNL49eFfwo

To claim this, I am signing this object:

abelsonlive

# best practices for web scraping in R #

# function should be used with ldply
# eg: 

ldply(urls, scrape)

# add a try to ignore broken links/ unresponsive pages
# eg: 

abelsonlive

tic tac toe

A simple two player game of Tic Tac Toe written in Python 3.6+

To play, download the file below, open a terminal, and run the following command:

$ python3 tic-tac-toe.py

abelsonlive

import sys
import json

import nltk
from nltk.tokenize import RegexpTokenizer

# For a list of all POS tags and their definitions, see:
# https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html
SUPERLATIVE_TAGS = {"JJS", "RBS"}