I’ve got a lot of ground to cover, picking up where I left off several months ago. In earlier posts I presented the concept for creating reports from sqlite databases using Python, Jinja, and LaTeX, and looked at different methods for passing data from the database to the template. I’m using the NYC Geodatabase as our test case. In this entry I’ll cover how I implemented my preferred approach – creating Python dictionaries to pass to the Jinja template.

One of the primary decisions I had to make was how to loop through the database. Since the reports we’re making are profiles (lots of different data for one geographic area), we’re going to want to loop through the database by geography. So, for each geography select all the data from a specific table, pass the data out to the template where the pertinent variables are pulled, build the report and move on to the next geography. In contrast, if we were building comparison tables (one specific variable for many geographic areas) we would want to loop through the data by variable.

In the beginning of the script we import the necessary modules, set up the Jinja environment, and specify our template (not going to repeat that code here – see the previous post). Then we have our function that creates a dictionary for a specific data table for a specific geography:

def pulltab(tabname,idcol,geog):
    query='SELECT * FROM %s WHERE %s = %s' %(tabname,idcol,geog)
    curs.execute(query)
    col_names = [cn[0] for cn in curs.description]
    rows = curs.fetchall()
    for row in rows:
        thedict=dict(zip(col_names,row))
    return thedict

We connect to the database and create a dictionary of all the geographies (limited to 3 PUMAs since this is just a test):

#Connect to database and create dictionary of all geographies

conn = sqlite3.connect('nyc_gdb_jan2015a/nyc_gdb_jan2015.sqlite')
curs = conn.cursor()
curs.execute('SELECT geoid10, namelsad10 FROM a_pumas2010 ORDER BY geoid10 LIMIT 3')
rows = curs.fetchall()
geodict=dict(rows)

And then we generate reports by looping through all the geographies in that dictionary, and we pass in the ID of each geography to pull all data from a data table for that geography out of the table and into a dictionary.

#Generate reports by looping through geographies and passing out
#dictionaries of values

for geog in geodict.keys():
    acs1dict=pulltab('b_pumas_2013acs1','GEOID2',geog)
    acs2dict=pulltab('b_pumas_2013acs2','GEOID2',geog)
    name=geodict.get(geog)
    filename='zzpuma_' + geog + '.tex'
    folder='test5'
    outpath=os.path.join(folder,filename)

Lastly, we pass the dictionaries out to the template, and run LaTeX to generate the report from the template:

  outfile=open(outpath,'w')
    outfile.write(template.render(geoid=geog, geoname=name, acs1=acs1dict, acs2=acs2dict))
    outfile.close()

    os.system("pdflatex -output-directory=" + folder + " " + outpath)

conn.close()

The Jinja template (as a LaTeX file) is below – the example here is similar to what I covered in my previous post. We passed two dictionaries into the template, one for each data table. The key is the name of the variable (the column name in the table) and the value is the American Community Survey estimate and the margin of error. We pass in the key and get the value in return. The PDF output follows.

documentclass{article}
usepackage[margin=0.5in]{geometry}
usepackage{graphicx}
usepackage[labelformat=empty]{caption}
usepackage[group-separator={,}]{siunitx}

title{VAR{acs1.get('GEOLABEL') | replace("&","&")} VAR{acs1.get('GEOID2')}}
date{}

begin{document}

maketitle
pagestyle{empty}
thispagestyle{empty}  

begin{table}[h]
centering
caption{Commuting to Work - Workers 16 years and over}
begin{tabular}{|c|c|c|c|c|}

hline
& Estimate & Margin of Error & Percent Total & Margin of Error\
hline

Car, truck, or van alone & num{VAR{acs1.get('COM02_E')}} & +/- num{VAR{acs1.get('COM02_M')}}
& num{VAR{acs1.get('COM02_PC')}} & +/- num{VAR{acs1.get('COM02_PM')}}\

Car, truck, or van carpooled & num{VAR{acs1.get('COM03_E')}} & +/- num{VAR{acs1.get('COM03_M')}}
& num{VAR{acs1.get('COM03_PC')}} & +/- num{VAR{acs1.get('COM03_PM')}}\

Public transit & num{VAR{acs1.get('COM04_E')}} & +/- num{VAR{acs1.get('COM04_M')}}
& num{VAR{acs1.get('COM04_PC')}} & +/- num{VAR{acs1.get('COM04_PM')}}\

Walked & num{VAR{acs1.get('COM05_E')}} & +/- num{VAR{acs1.get('COM05_M')}}
& num{VAR{acs1.get('COM05_PC')}} & +/- num{VAR{acs1.get('COM05_PM')}}\

Other means & num{VAR{acs1.get('COM06_E')}} & +/- num{VAR{acs1.get('COM06_M')}}
& num{VAR{acs1.get('COM06_PC')}} & +/- num{VAR{acs1.get('COM06_PM')}}\

Worked at home & num{VAR{acs1.get('COM07_E')}} & +/- num{VAR{acs1.get('COM07_M')}}
& num{VAR{acs1.get('COM07_PC')}} & +/- num{VAR{acs1.get('COM07_PM')}}\
hline

end{tabular}
end{table}

begin{table}[h]
centering
caption{Housing Tenure}
begin{tabular}{|c|c|c|c|c|}

hline
& Estimate & Margin of Error & Percent Total & Margin of Error\
hline

Occupied housing units & num{VAR{acs2.get('HTEN01_E')}} & +/- num{VAR{acs2.get('HTEN01_M')}} &  &\

Owner-occupied & num{VAR{acs2.get('HTEN02_E')}} & +/- num{VAR{acs2.get('HTEN02_M')}}
& num{VAR{acs2.get('HTEN02_PC')}} & +/- num{VAR{acs2.get('HTEN02_PM')}}\

Renter-occupied & num{VAR{acs2.get('HTEN03_E')}} & +/- num{VAR{acs2.get('HTEN03_M')}}
& num{VAR{acs2.get('HTEN03_PC')}} & +/- num{VAR{acs2.get('HTEN03_PM')}}\
hline

end{tabular}
end{table}
end{document}

In this example we took the simple approach of grabbing all the variables that were in a particular table, and then we just selected what we wanted within the template. This is fine since we’re only dealing with 55 PUMAs and a table that has 200 columns or so. If we were dealing with gigantic tables or tons of geographies, we could modify the Python script to pull just the variables we wanted to speed up the process; my inclination would be to create a list of variables in a text file, read that list into the script and modify the SQL function to just select those variables.

What if we want to modify some of the variables before we pass them into the template? I’ll cover that in the next post.

In this post, I’m picking up where I left off and will cover the different methods I experimented with to get data out of a SQLite database and into a Jinja LaTeX template using Python. I’m using the NYC Geodatabase as my test case.

Standard Elements – Used Each Time

First – the Python script. For each iteration, the top half of the script remains the same. I import the necessary modules, and I set up my Jinja2 environment. This tells Jinja how to handle LaTeX syntax. I borrowed this code directly from the invaluable slides posted here. The only part that gets modified each time is the .get_template() bit, which is the actual LaTeX template with Jinja mark-up that is used for creating the reports.

import sqlite3

import jinja2
import os
from jinja2 import Template

latex_jinja_env = jinja2.Environment(
    block_start_string = 'BLOCK{',
    block_end_string = '}',
    variable_start_string = 'VAR{',
    variable_end_string = '}',
    comment_start_string = '#{',
    comment_end_string = '}',
    line_statement_prefix = '%-',
    line_comment_prefix = '%#',
    trim_blocks = True,
    autoescape = False,
    loader = jinja2.FileSystemLoader(os.path.abspath('.'))
)
# Modify to specify the template
template = latex_jinja_env.get_template('test1.tex')

The method for connecting to a SQLite database is also the same each time. There are a zillion tutorials and posts for working with Python and SQLite so I won’t belabor that here. Take a look at this excellent one or this awesome one.

conn = sqlite3.connect('nyc_gdb_jan2015a/nyc_gdb_jan2015.sqlite')
curs = conn.cursor()
curs.execute('SELECT * FROM b_pumas_2013acs1 ORDER BY GEOID2 LIMIT 3')

col_names = [cn[0] for cn in curs.description]
rows = curs.fetchall()
conn.close()

First Iteration – Pass Individual Variables to the Template

Here’s the bit that I modify each time. Using the example from the tutorial slides, I loop through the rows returned from my database, and I specify individual variables each time by slicing the elements in the row and assigning them a name which is passed out to the template with template.render(). Then I make a call to LaTeX to generate the PDF file (straightforward since I’m using Linux), one for each row (which represent geographic areas). Each file is named using the unique ID number of the geography, which we grabbed from our row list.

for row in rows:
    filename='zpuma_' + row[0] + '.tex'
    folder='test1'
    outpath=os.path.join(folder,filename)
    outfile=open(outpath,'w')
    outfile.write(template.render(geoid=row[0], geolabel=row[1], hshld=row[2], hshldmoe=row[3]))
    outfile.close()
    os.system("pdflatex -output-directory=" + folder + " " + outpath)

That’s the Python piece. The LaTeX template with the Jinja mark-up looks like this:

documentclass{article}
usepackage[margin=0.5in]{geometry}
usepackage[group-separator={,}]{siunitx}

title{VAR{geolabel | replace("&","&")} VAR{geoid}}
date{}

begin{document}

maketitle
pagestyle{empty}
thispagestyle{empty}  

begin{tabular}{|c|c|c|}
hline
& Estimate & Margin of Error\
Households: & num{VAR{hshld}} & +/- num{VAR{hshldmoe}}\
hline
end{tabular}

end{document}

You can see here where I’m passing in the variables with VAR – I’m using the same variable names that I created in the script to hold the row elements. I have to do a little bit of formatting to get this to work. First, one of my variables is text description that consistently contains an ampersand, so I have to use replace (a construct from Jinja) to replace & with & so LaTeX can properly escape it. Second, I want to format my numeric variables with a thousands separator. Here I use a LaTeX construct with the siunitx package, and every place a number appears I mark it with num. For this to work I always need to know that this variable will be a number; if it’s text or null LaTeX will throw an error and the doc won’t compile (an alternative to using this LaTeX solution would be to use Python’s formatting constructs). My simple output is below.

Second Iteration – Pass Variables to Template in a List

Since I’m going to be passing lots of variables out to my template, it would be tedious if I had to declare them all individually, one by one. It would be better if I could pass out an entire list, and then do the slicing to get what I want in the template. Here’s the Python for doing that:

for row in rows:
    filename='zzpuma_' + row[0] + '.tex'
    folder='test2'
    outpath=os.path.join(folder,filename)
    outfile=open(outpath,'w')
    outfile.write(template.render(thelist=row))
    outfile.close()
    os.system("pdflatex -output-directory=" + folder + " " + outpath)

And here’s the LaTeX template – in this example I modified the variables a bit.

documentclass{article}
usepackage[margin=0.5in]{geometry}
usepackage[group-separator={,}]{siunitx}

title{VAR{thelist[2] | replace("&","&")} VAR{thelist[1]}}
date{}

begin{document}

maketitle
pagestyle{empty}
thispagestyle{empty}  

begin{tabular}{|c|c|c|c|c|}
hline
& Estimate & Margin of Error & Percent Total & Percent Margin of Error\
Car, truck, or van alone: & num{VAR{thelist[171]}} & +/- num{VAR{thelist[172]}} & num{VAR{thelist[173]}} & +/- num{VAR{thelist[174]}}\
Car, truck, or van carpooled: & num{VAR{thelist[175]}} & +/- num{VAR{thelist[176]}} & num{VAR{thelist[177]}} & +/- num{VAR{thelist[178]}}\
hline
end{tabular}

end{document}

While this is a bit better, the template is harder to read – you can’t really figure out what’s in there as you just have a bunch of list slices. You also have to keep careful track of which indices apply to what element, so you know what you’re generating. I thought I could improve this by creating nested lists where the column headings from the database get carried along, and I could reference them somehow. Then I had a better idea.

Third Iteration – Pass Variables to Template in a Dictionary

I decided to use a dictionary instead of a list. Here’s the Python – since I grabbed the columns back in the database section of my code, I can loop through the elements in each row and create a dictionary by zipping the column names and row elements together, so the column name becomes the key and the row element is my data value. Then I pass the whole dictionary out to the template.

for row in rows:
    thedict=dict(zip(col_names,row))
    filename='zzpuma_' + row[0] + '.tex'
    folder='test3'
    outpath=os.path.join(folder,filename)
    outfile=open(outpath,'w')
    outfile.write(template.render(d=thedict))
    outfile.close()
    os.system("pdflatex -output-directory=" + folder + " " + outpath)

Now in the template, using Jinja I embed dict.get() for each variable and specify the key (column name) and the output will be the value. This is now highly readable, as I can see the names of the columns for the variables and there’s less potential for a mix-up.

documentclass{article}
usepackage[margin=0.5in]{geometry}
usepackage[group-separator={,}]{siunitx}

title{VAR{d.get('GEOLABEL') | replace("&","&")} VAR{d.get('GEOID2')}}
date{}

begin{document}

maketitle
pagestyle{empty}
thispagestyle{empty}  

begin{tabular}{|c|c|c|c|c|}
hline
& Estimate & Margin of Error & Percent Total & Margin of Error\

Car, truck, or van alone: & num{VAR{d.get('COM02_E')}} & +/- num{VAR{d.get('COM02_M')}} & num{VAR{d.get('COM02_PC')}} & +/- num{VAR{d.get('COM02_PM')}}\

Car, truck, or van carpooled: & num{VAR{d.get('COM03_E')}} & +/- num{VAR{d.get('COM03_M')}} & num{VAR{d.get('COM03_PC')}} & +/- num{VAR{d.get('COM03_PM')}}\
hline
end{tabular}

end{document}

In this case, the output looks the same as it did in our last iteration. Those are some basic methods for getting data into a template, and in my case I think the dictionary is the ideal data structure for this. In going further, my goal is to keep all the formatting and presentation issues in LaTeX, and all the data processing and selection pieces in Python.