Skip to main content

Query through Python, returning Pandas DataFrames

Project description

Access .. from Python.

This is a package consisting of a single, simple function for submitting ``SQL`` queries to .. from ``python``. While you could simply copy-and-paste the function from script-to-script, this makes it quicker and easier to get up and running!

It also has some helpers to make a Twitter bot from the data.

Install with pip.::

pip install treasuryio


Basic query
Send an SQL query and receive a pandas data frame.::

# Operating cash balances for May 22, 2013
import treasuryio
sql = 'SELECT * FROM "t1" WHERE "date" = \'2013-05-22\';'

Twitter bot
Write a ``~/.twitter.yml`` file.::

consumer_key: oeshaoduhsaousaoeuhts
consumer_secret: b233tsao-enuhsaoehsunoesudtuhoelaouhs2uo
access_token: 2349081293-astoehusatoehusaoeustahoeuhh2AOEUTAouhc
access_token_secret: 9023uonshesuaHONETuoeuoeouo0eOHNEuhOuoeu

Define a function that produces the text of the tweet, and decorate it with the
``@treasurio.tweet`` decorator.::

import treasuryio
import humanize
import math

MIL = 1e6

# Helpers to humanize numbers / dates
def human_number(num):
return humanize.intword(int(math.ceil(num))).lower()

def human_date(date):
return humanize.naturalday(date).title()

def total_debt_tweet():
df = treasuryio.query('SELECT date, close_today FROM t3c WHERE (item LIKE \'%subject to limit%\' AND year = 2013 AND month >=1) ORDER BY date DESC')

# determine length of DataFrame
end = len(df)-1

# extract current amount and amount at the beginning of the year
current_amt = df['close_today'][0]*MIL
previous_amt = df['close_today'][end]*MIL

# calculate change
delta = abs(current_amt - previous_amt)

# generate word to represnet the direction of change
if current_amt > previous_amt:
change = "increased"
elif current_amt < previous_amt:
change = "decreased"

# humanize values
# Notice the included ``human_date`` and ``human_number`` functions which simplify these values for you
current_date = human_date(df['date'][0])
amt = human_number(current_amt)
delta = human_number(delta)
previous_date = human_date(df['date'][end])

# generate tweet
vals = (current_date, amt, change, previous_date, '')
return "As of %s, the US Gov is $%s in debt. This amount has %s since %s - %s" % vals

Then just run it.::


You can get fancy by switching the functions that you use.::

import treasuryio
import random

def tweet_a():
# ...

def tweet_b():
# ...

def tweet_c():
# ...

random.choice([tweet_a, tweet_b, tweet_c])()

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for treasuryio, version 0.0.4
Filename, size File type Python version Upload date Hashes
Filename, size treasuryio-0.0.4-py2-none-any.whl (7.0 kB) File type Wheel Python version py2 Upload date Hashes View
Filename, size treasuryio-0.0.4.tar.gz (4.4 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page