This code (in both Python and R) will read from a SQLite database of Hillary Clinton's emails and display basic information about the database.

read_db.py

import pandas as pd
import sqlite3

#Set up connection to the SQLite database
connection = sqlite3.connect('clinton.sqlite')

#Print all tables
print("Tables")
all_tables = pd.read_sql("SELECT name FROM sqlite_master WHERE type = 'table'", connection)
print(all_tables)

#Print information about 'docs' table
docs = pd.read_sql("SELECT * FROM %s" % ("docs"), connection)
print("Column Names")
print(list(docs.columns.values))
print("Number of Rows: %d" % len(docs))

#Clean up connection to the database
connection.close()

read_db.R

library(dplyr)
library(RSQLite)

#Set up connection to the SQLite database
connection <- dbConnect(RSQLite::SQLite(), dbname = "clinton.sqlite")

#Print all tables
print("Tables")
all_tables <-  dbListTables(connection)
print(all_tables)

#Print information about 'docs' table
docs <- dbGetQuery(connection, sprintf("SELECT * FROM %s", "docs"))
print("Column Name")
print(colnames(docs))
print(sprintf("Number of Rows: %d", nrow(docs)))

#Clean up connection to the database
dbDisconnect(connection)

sample_python_output.txt

Tables
                 name
0     classreason_doc
1        classreasons
2                docs
3    recipient_doc_cc
4  recipient_doc_from
5    recipient_doc_to
6          recipients
Column Names
['date', 'posted_date', 'pdf_link', 'doc_class', 'message_num', 'case_num', 'declass_date', 'classification', 'reason', 'author', 'id', 'subject', 'body', 'full_path', 'is_document', 'doc_date', 'pdf_url']
Number of Rows: 40737

sample_R_output.txt

[1] "Tables"
[1] "classreason_doc"    "classreasons"       "docs"               "recipient_doc_cc"  
[5] "recipient_doc_from" "recipient_doc_to"   "recipients"        
[1] "Column Name"
 [1] "date"           "posted_date"    "pdf_link"       "doc_class"      "message_num"   
 [6] "case_num"       "declass_date"   "classification" "reason"         "author"        
[11] "id"             "subject"        "body"           "full_path"      "is_document"   
[16] "doc_date"       "pdf_url"       
[1] "Number of Rows: 40737"