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CUDA_LAUNCH_BLOCKING=1
CUDA_VISIBLE_DEVICES=0,1,2,3

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"""Do not let the zen slip through your fingers."""
import this


zen = "".join([this.d[x] if x.isalnum() else x for x in this.s])

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import pandas as pd
import pandas.io.sql as pdsql
import psycopg2


# Database connection details
creds = {
    "dbname": "mydb",
    "user": "jsmith",
    "password": "hello1234",

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Connect and Select

connect()

The shortest connect:

from psycopg2 import connect
psql_conn = connect("dbname=XXX user=XXX password=XXX host=localhost sslmode=require")
psql_conn.close()

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word_df.to_csv("words.tsv", sep="\t", header=False, index=False, quoting=csv.QUOTE_NONE, quotechar="",  escapechar="\\")
vec_df.to_csv("vectors.tsv", sep="\t", header=False, index=False, quoting=csv.QUOTE_NONE, quotechar="",  escapechar="\\")

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saved_model_cli show --dir /path/to/saved/model/1521687978/ --all

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#!/bin/bash
#
# Adds a jupyter kernel for a virtualenv 
# This makes the virtualenv available for use in a Jupyter notebook
# Run this from the directory containing your virtualenv directory and
# pass it the directory name for your virtualenv.
#
# Usage: 
# $ ./add_jupyter_kernel.sh myvenv
#

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export PS1="\[\e[1;34m\]\W\[\e[m\] \\$ "

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# Summary statistics for numeric variables
df.describe().transpose()

# Summary statistics for categorical/string variables
df.describe(include=['O']).transpose()

# Info about column names, datatypes, and null values
df.info()

# Get a sample 

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import matplotlib.pyplot as plt

plt.rcParams["figure.figsize"] = (20,10)