diff --git a/.Rbuildignore b/.Rbuildignore
new file mode 100644
index 0000000..aed25d6
--- /dev/null
+++ b/.Rbuildignore
@@ -0,0 +1,3 @@
+^.*\.Rproj$
+^\.Rproj\.user$
+cran-comments.md
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..c833a2c
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,5 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+inst/doc
diff --git a/DESCRIPTION b/DESCRIPTION
new file mode 100644
index 0000000..aff819c
--- /dev/null
+++ b/DESCRIPTION
@@ -0,0 +1,25 @@
+Package: condusco
+Type: Package
+Title: Query-Driven Pipeline Execution and Query Templates
+Version: 0.1.0
+Author: Roland Stevenson
+Maintainer: Roland Stevenson <roland@rmg-services.com>
+Description: Runs a function iteratively over each row of either a dataframe 
+    or the results of a query.  Use the 'BigQuery' and 'DBI' wrappers to 
+    iteratively pass each row of query results to a function.  If a field 
+    contains a 'JSON' string, it will be converted to an object.  This is 
+    helpful for queries that return 'JSON' strings that represent objects.  
+    These fields can then be treated as objects by the pipeline.
+License: GPL-3
+URL: https://github.com/ras44/condusco
+BugReports: https://github.com/ras44/condusco/issues
+Encoding: UTF-8
+LazyData: true
+Suggests: knitr, rmarkdown, whisker, testthat, RSQLite
+VignetteBuilder: knitr
+Depends: R (>= 3.3.2),
+  jsonlite,
+  assertthat,
+  bigrquery,
+  DBI
+RoxygenNote: 6.0.1.9000
diff --git a/NAMESPACE b/NAMESPACE
new file mode 100644
index 0000000..e6354fd
--- /dev/null
+++ b/NAMESPACE
@@ -0,0 +1,9 @@
+# Generated by roxygen2: do not edit by hand
+
+export(run_pipeline)
+export(run_pipeline_dbi)
+export(run_pipeline_gbq)
+import(DBI)
+import(assertthat)
+import(bigrquery)
+import(jsonlite)
diff --git a/NEWS.md b/NEWS.md
new file mode 100644
index 0000000..6cd81c7
--- /dev/null
+++ b/NEWS.md
@@ -0,0 +1,7 @@
+# News
+
+## 0.1.0
+condusco now contains the following functions
+run_pipeline
+run_pipeline_dbi
+run_pipeline_gbq
diff --git a/R/run_pipeline.R b/R/run_pipeline.R
new file mode 100644
index 0000000..1c6408e
--- /dev/null
+++ b/R/run_pipeline.R
@@ -0,0 +1,192 @@
+#' Runs user-provided pipeline for each row of arguments in parameters, converting any JSON
+#' strings to objects
+#'
+#' @param pipeline User-provided function with one argument, a dataframe
+#' @param parameters An dataframe of fields to convert to json
+#'
+#' @import assertthat jsonlite
+#'
+#' @examples
+#'
+#' library(whisker)
+#'
+#' run_pipeline(
+#'   function(params){
+#'    query <- "SELECT result FROM {{table_prefix}}_results;"
+#'    whisker.render(query,params)
+#'  },
+#'  data.frame(
+#'    table_prefix = c('batman', 'robin')
+#'  )
+#')
+#'
+#' @export
+run_pipeline <- function(pipeline, parameters){
+
+  assert_that(length(parameters)>0)
+
+  #For each row in parameters, convert each column to json object if it contains json
+  apply(parameters, 1, function(row){
+    lr <- as.list(row)
+    for(n in names(lr)){
+      tryCatch({
+        lr[[n]] <- fromJSON(get(n,lr), simplifyVector=FALSE)
+      },error=function(e){
+        lr[[n]] <- toString(get(n,lr))
+      }
+      )
+    }
+
+    pipeline(lr)
+  })
+
+}
+
+
+#' A wrapper for running pipelines with a BigQuery invocation query
+#'
+#' @param pipeline User-provided function with one argument, one row of query results
+#' @param query A query to execute in Google BigQuery
+#' @param project The Google BigQuery project to bill
+#' @param ... Additional arguments passed to query_exec()
+#'
+#' @import bigrquery
+#'
+#' @examples
+#'
+#'\dontrun{
+#' library(whisker)
+#'
+#' #Set GBQ project
+#' project <- ''
+#'
+#' #Set the following options for GBQ authentication on a cloud instance
+#' options("httr_oauth_cache" = "~/.httr-oauth")
+#' options(httr_oob_default=TRUE)
+#'
+#' #Run the below query to authenticate and write credentials to .httr-oauth file
+#' query_exec("SELECT 'foo' as bar",project=project);
+#'
+#' pipeline <- function(params){
+#'
+#'   query <- "
+#'     SELECT
+#'       {{#list}}
+#'         SUM(CASE WHEN author.name ='{{name}}' THEN 1 ELSE 0 END) as n_{{name_clean}},
+#'       {{/list}}
+#'       repo_name
+#'     FROM `bigquery-public-data.github_repos.sample_commits`
+#'     GROUP BY repo_name
+#'   ;"
+#'
+#'   res <- query_exec(
+#'     whisker.render(query,params),
+#'     project=project,
+#'     use_legacy_sql = FALSE
+#'   );
+#'
+#'   print(res)
+#' }
+#'
+#' run_pipeline_gbq(pipeline, "
+#'   SELECT CONCAT('[',
+#'   STRING_AGG(
+#'     CONCAT('{\"name\":\"',name,'\",'
+#'       ,'\"name_clean\":\"', REGEXP_REPLACE(name, r'[^[:alpha:]]', ''),'\"}'
+#'     )
+#'   ),
+#'   ']') as list
+#'   FROM (
+#'     SELECT author.name,
+#'       COUNT(commit) n_commits
+#'     FROM `bigquery-public-data.github_repos.sample_commits`
+#'     GROUP BY 1
+#'     ORDER BY 2 DESC
+#'     LIMIT 10
+#'   )
+#' ",
+#' project,
+#' use_legacy_sql = FALSE
+#' )
+#'}
+#' @export
+run_pipeline_gbq <- function(pipeline, query, project, ... ){
+
+  #run the query to generate the intitialization table
+  parameters <- query_exec(query, project=project, ...)
+
+  run_pipeline(pipeline, parameters)
+
+}
+
+#' A wrapper for running pipelines with a DBI connection invocation query
+#'
+#' @param pipeline User-provided function with one argument, one row of query results
+#' @param query A query to execute via the DBI connection
+#' @param con The DBI connection
+#' @param ... Additional arguments passed to dbSendQuery() and dbFetch()
+#'
+#' @import DBI
+#'
+#' @examples
+#'
+#'\dontrun{
+#' library(whisker)
+#' library(RSQLite)
+#'
+#' con <- dbConnect(RSQLite::SQLite(), ":memory:")
+#'
+#' dbWriteTable(con, "mtcars", mtcars)
+#'
+#' #for each cylinder count, count the number of top 5 hps it has
+#' pipeline <- function(params){
+#'
+#'   query <- "SELECT
+#'     {{#list}}
+#'     SUM(CASE WHEN hp='{{val}}' THEN 1 ELSE 0 END )as n_hp_{{val}},
+#'   {{/list}}
+#'     cyl
+#'     FROM mtcars
+#'     GROUP BY cyl
+#'   ;"
+#'
+#'
+#'   dbGetQuery(
+#'     con,
+#'     whisker.render(query,params)
+#'   )
+#' }
+#'
+#'
+#' #pass the top 5 most common hps as val params
+#' run_pipeline_dbi(
+#'   pipeline,
+#'   '
+#'   SELECT "[" || GROUP_CONCAT("{ ""val"": """ || hp ||  """ }") || "]" AS list
+#'   FROM (
+#'     SELECT
+#'       CAST(hp as INTEGER) as HP,
+#'       count(hp) as cnt
+#'     FROM mtcars
+#'     GROUP BY hp
+#'     ORDER BY cnt DESC
+#'     LIMIT 5
+#'   )
+#'   ',
+#'   con
+#' )
+#'
+#'
+#' dbDisconnect(con)
+#'}
+#' @export
+run_pipeline_dbi <- function(pipeline, query, con, ...){
+
+  rs <- dbSendQuery(con, query, ...)
+  parameters <- dbFetch(rs, ...)
+
+  dbClearResult(rs, ...)
+
+  run_pipeline(pipeline, parameters)
+
+}
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..61f9328
--- /dev/null
+++ b/README.md
@@ -0,0 +1,255 @@
+# condusco
+
+## Overview
+
+condusco lets you run a function iteratively, passing it the rows of a dataframe or the results of a query.
+
+We call the functions condusco runs pipelines, and define a pipeline as a function that accepts a list of parameters and run a series of customized commands based on the values of the parameters.
+
+The most common use case for condusco are data pipelines.  For data pipelines that primarily run SQL queries, we can template queries with a library (ie. [whisker](https://github.com/edwindj/whisker)), so that parametrized values are separated from the query logic.  We can then render the query with the appropriate values:
+
+```
+parameters <- source("params.R")
+
+#define a pipeline
+pipeline <- function(parameters){
+ query <- "SELECT * FROM {{dataset}}.{{table_prefix}}_results LIMIT {{limit_size}}"
+ query_with_params <- whisker.render(query, parameters)
+ run_query(query_with_params)
+}
+
+# run the pipeline with the parameters in 'params.R'
+pipeline(parameters)
+```
+
+
+condusco provides the following extensions in functionality to the above design pattern:
+ - the user can provide a data-frame that contains multiple rows of parameters to be iteratively passed to the pipeline
+ - the user can provide a query and each row of results is iteratively passed to the pipeline
+ - any JSON-string parameter will be converted to an object before being passed to the pipeline
+ 
+
+## Functions
+
+|function|description|
+|:--------------|:--------------|
+|run_pipeline(pipeline, parameters)| iteratively pass each row of parameters to a pipeline, converting any JSON parameters to objects|
+|run_pipeline_gbq(pipeline, query, project)|calls run_pipeline with the results of query executed via bigrquery|
+|run_pipeline_dbi(pipline, query, con)|calls run_pipeline with the results of query executed via DBI|
+
+
+## Installation
+
+```{r, eval = FALSE}
+install.packages("condusco")
+```
+
+## Features
+
+*   Name-based substitution of local parameters into pipelines, iterating through rows of parameters:
+    
+    ```{r}
+    run_pipeline(
+      #the pipeline
+      function(parameters){
+        query <- "SELECT * FROM {{table_prefix}}_results;"
+        print(whisker.render(query,parameters))
+      },
+      #the parameters
+      data.frame(
+        table_prefix = c('batman', 'robin')
+      )
+    )
+    ```
+
+
+
+*   Name-based substitution of query-results into pipelines, iterating through rows of parameters dataframe:
+    
+    ```{r}
+    con <- dbConnect(RSQLite::SQLite(), ":memory:")
+
+    pipeline <- function(parameters){
+
+      query <-"
+        SELECT count(*) as n_hits 
+        FROM user_hits 
+        WHERE date(date_time) BETWEEN date('{{{date_low}}}') AND date('{{{date_high}}}')
+      ;"
+
+      whisker.render(query,parameters)
+
+    }
+
+    run_pipeline_dbi(pipeline,
+      "SELECT date('now', '-5 days') as date_low, date('now') as date_high",
+      con
+    )
+
+    dbDisconnect(con)
+    ```
+
+
+*   Dynamic query generation based on JSON strings:
+    
+    ```{r}
+    con <- dbConnect(RSQLite::SQLite(), ":memory:")
+    mtcars
+    dbWriteTable(con, "mtcars", mtcars)
+
+    #for each cylinder count, count the number of top 5 hps it has
+    pipeline <- function(swap){
+
+      query <- "SELECT
+        {{#list}}
+          SUM(CASE WHEN hp='{{val}}' THEN 1 ELSE 0 END )as n_hp_{{val}},
+        {{/list}}
+        cyl
+        FROM mtcars
+        GROUP BY cyl
+      ;"
+
+      print(whisker.render(query,swap))
+
+      print(
+        dbGetQuery(
+          con,
+          whisker.render(query,swap)
+        )
+      )
+    }
+
+
+    #pass the top 5 most common hps as val parameters
+    run_pipeline_dbi(
+      pipeline,
+      '
+      SELECT "[" || GROUP_CONCAT("{ ""val"": """ || hp ||  """ }") || "]" AS list
+      FROM (
+        SELECT 
+          CAST(hp as INTEGER) as HP,
+          count(hp) as cnt
+        FROM mtcars 
+        GROUP BY hp
+        ORDER BY cnt DESC
+        LIMIT 5
+      )
+      ',
+      con
+    )
+
+
+    dbDisconnect(con)
+    ```
+
+
+
+# Google BigQuery Examples
+
+This is not available as a vignette because it requires user authentication
+
+```{r }
+library(whisker)
+library(bigrquery)
+library(condusco)
+
+#Set GBQ project
+project <- ''
+
+#Set the following options for GBQ authentication on a cloud instance
+options("httr_oauth_cache" = "~/.httr-oauth")
+options(httr_oob_default=TRUE)
+
+#Run the below query to authenticate and write credentials to .httr-oauth file
+query_exec("SELECT 'foo' as bar",project=project);
+
+```
+
+
+
+## Dynamically generated queries via JSON
+If list is defined, convert the JSON string to an object and iterate through name1,name2 pairs. 
+This illustrates how to dynamically generate a query based on the JSON constructed by another query.
+In this example, we create a trivial JSON object manually.  We'll use a dynamically generated JSON object in the next example.
+```{r}
+pipeline <- function(params){
+
+  query <- "SELECT {{{value}}} as dollars_won,
+    {{#list}}
+    '{{name1}}' as {{name2}},
+    {{/list}}
+    {{{field}}} as field
+  FROM {{table_name}}
+  LIMIT {{limit_size}}
+  ;"
+
+  res <- query_exec(whisker.render(query,params),
+                    project=project,
+                    use_legacy_sql = FALSE
+  );
+  
+  print(res)
+}
+
+project
+
+run_pipeline_gbq(pipeline, "
+    SELECT 1000 as value,
+    'word' as field,
+    '[{\"name1\":\"foo\", \"name2\":\"bar\"},{\"name1\":\"foo2\", \"name2\":\"bar2\"}]' as list,
+    'publicdata:samples.shakespeare' AS table_name,
+    5 AS limit_size
+", project)
+
+```
+
+
+
+## Feature Generation Query
+Create features for each of the repos describing how many commits the top 10 commiters made to that repo.
+```{r}
+pipeline <- function(params){
+
+  query <- "
+    SELECT
+      {{#list}}
+        SUM(CASE WHEN author.name ='{{name}}' THEN 1 ELSE 0 END) as n_{{name_clean}},
+      {{/list}}
+      repo_name
+    FROM `bigquery-public-data.github_repos.sample_commits`
+    GROUP BY repo_name
+  ;"
+
+  res <- query_exec(
+    whisker.render(query,params),
+    project=project,
+    use_legacy_sql = FALSE
+  );
+  
+  print(res)
+}
+
+run_pipeline_gbq(pipeline, "
+  SELECT CONCAT('[',
+  STRING_AGG(
+    CONCAT('{\"name\":\"',name,'\",'
+      ,'\"name_clean\":\"', REGEXP_REPLACE(name, r'[^[:alpha:]]', ''),'\"}'
+    )
+  ),
+  ']') as list
+  FROM (
+    SELECT author.name,
+      COUNT(commit) n_commits
+    FROM `bigquery-public-data.github_repos.sample_commits`
+    GROUP BY 1
+    ORDER BY 2 DESC
+    LIMIT 10
+  )
+",
+project,
+use_legacy_sql = FALSE
+)
+
+```
+
+
diff --git a/condusco.Rproj b/condusco.Rproj
new file mode 100644
index 0000000..270314b
--- /dev/null
+++ b/condusco.Rproj
@@ -0,0 +1,21 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace
diff --git a/cran-comments.md b/cran-comments.md
new file mode 100644
index 0000000..eb23901
--- /dev/null
+++ b/cran-comments.md
@@ -0,0 +1,53 @@
+# Resubmission
+This is a resubmission. In this version I have:
+
+* removed package name redundancy in description
+
+## Test environments
+* Debian GNU/Linux 8.6 (jessie), R 3.3.2
+* win-builder (devel)
+
+## R CMD check results
+There were no ERRORs or WARNINGs.
+
+## Downstream dependencies
+None
+
+
+
+
+# Resubmission
+This is a resubmission. In this version I have:
+
+* writen package names and software names in single quotes (e.g. 'JSON')
+
+* elaborated the description and updated title
+
+* added a small executable example in the Rd-files for run_pipeline
+
+* added examples for run_pipeline_dbi and run_pipeline_gbq
+  - run_pipeline_gbq example requires user authentication to 'BigQuery'
+
+## Test environments
+* Debian GNU/Linux 8.6 (jessie), R 3.3.2
+* win-builder (devel)
+
+## R CMD check results
+There were no ERRORs or WARNINGs.
+
+## Downstream dependencies
+None
+
+
+
+# First submission
+
+## Test environments
+* Debian GNU/Linux 8.6 (jessie), R 3.3.2
+* win-builder (devel)
+
+## R CMD check results
+There were no ERRORs or WARNINGs.
+
+## Downstream dependencies
+None
diff --git a/man/run_pipeline.Rd b/man/run_pipeline.Rd
new file mode 100644
index 0000000..5fe6732
--- /dev/null
+++ b/man/run_pipeline.Rd
@@ -0,0 +1,33 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/run_pipeline.R
+\name{run_pipeline}
+\alias{run_pipeline}
+\title{Runs user-provided pipeline for each row of arguments in parameters, converting any JSON
+strings to objects}
+\usage{
+run_pipeline(pipeline, parameters)
+}
+\arguments{
+\item{pipeline}{User-provided function with one argument, a dataframe}
+
+\item{parameters}{An dataframe of fields to convert to json}
+}
+\description{
+Runs user-provided pipeline for each row of arguments in parameters, converting any JSON
+strings to objects
+}
+\examples{
+
+library(whisker)
+
+run_pipeline(
+  function(params){
+   query <- "SELECT result FROM {{table_prefix}}_results;"
+   whisker.render(query,params)
+ },
+ data.frame(
+   table_prefix = c('batman', 'robin')
+ )
+)
+
+}
diff --git a/man/run_pipeline_dbi.Rd b/man/run_pipeline_dbi.Rd
new file mode 100644
index 0000000..9538430
--- /dev/null
+++ b/man/run_pipeline_dbi.Rd
@@ -0,0 +1,72 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/run_pipeline.R
+\name{run_pipeline_dbi}
+\alias{run_pipeline_dbi}
+\title{A wrapper for running pipelines with a DBI connection invocation query}
+\usage{
+run_pipeline_dbi(pipeline, query, con, ...)
+}
+\arguments{
+\item{pipeline}{User-provided function with one argument, one row of query results}
+
+\item{query}{A query to execute via the DBI connection}
+
+\item{con}{The DBI connection}
+
+\item{...}{Additional arguments passed to dbSendQuery() and dbFetch()}
+}
+\description{
+A wrapper for running pipelines with a DBI connection invocation query
+}
+\examples{
+
+\dontrun{
+library(whisker)
+library(RSQLite)
+
+con <- dbConnect(RSQLite::SQLite(), ":memory:")
+
+dbWriteTable(con, "mtcars", mtcars)
+
+#for each cylinder count, count the number of top 5 hps it has
+pipeline <- function(params){
+
+  query <- "SELECT
+    {{#list}}
+    SUM(CASE WHEN hp='{{val}}' THEN 1 ELSE 0 END )as n_hp_{{val}},
+  {{/list}}
+    cyl
+    FROM mtcars
+    GROUP BY cyl
+  ;"
+
+
+  dbGetQuery(
+    con,
+    whisker.render(query,params)
+  )
+}
+
+
+#pass the top 5 most common hps as val params
+run_pipeline_dbi(
+  pipeline,
+  '
+  SELECT "[" || GROUP_CONCAT("{ ""val"": """ || hp ||  """ }") || "]" AS list
+  FROM (
+    SELECT
+      CAST(hp as INTEGER) as HP,
+      count(hp) as cnt
+    FROM mtcars
+    GROUP BY hp
+    ORDER BY cnt DESC
+    LIMIT 5
+  )
+  ',
+  con
+)
+
+
+dbDisconnect(con)
+}
+}
diff --git a/man/run_pipeline_gbq.Rd b/man/run_pipeline_gbq.Rd
new file mode 100644
index 0000000..f3c20dc
--- /dev/null
+++ b/man/run_pipeline_gbq.Rd
@@ -0,0 +1,78 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/run_pipeline.R
+\name{run_pipeline_gbq}
+\alias{run_pipeline_gbq}
+\title{A wrapper for running pipelines with a BigQuery invocation query}
+\usage{
+run_pipeline_gbq(pipeline, query, project, ...)
+}
+\arguments{
+\item{pipeline}{User-provided function with one argument, one row of query results}
+
+\item{query}{A query to execute in Google BigQuery}
+
+\item{project}{The Google BigQuery project to bill}
+
+\item{...}{Additional arguments passed to query_exec()}
+}
+\description{
+A wrapper for running pipelines with a BigQuery invocation query
+}
+\examples{
+
+\dontrun{
+library(whisker)
+
+#Set GBQ project
+project <- ''
+
+#Set the following options for GBQ authentication on a cloud instance
+options("httr_oauth_cache" = "~/.httr-oauth")
+options(httr_oob_default=TRUE)
+
+#Run the below query to authenticate and write credentials to .httr-oauth file
+query_exec("SELECT 'foo' as bar",project=project);
+
+pipeline <- function(params){
+
+  query <- "
+    SELECT
+      {{#list}}
+        SUM(CASE WHEN author.name ='{{name}}' THEN 1 ELSE 0 END) as n_{{name_clean}},
+      {{/list}}
+      repo_name
+    FROM `bigquery-public-data.github_repos.sample_commits`
+    GROUP BY repo_name
+  ;"
+
+  res <- query_exec(
+    whisker.render(query,params),
+    project=project,
+    use_legacy_sql = FALSE
+  );
+
+  print(res)
+}
+
+run_pipeline_gbq(pipeline, "
+  SELECT CONCAT('[',
+  STRING_AGG(
+    CONCAT('{\\"name\\":\\"',name,'\\",'
+      ,'\\"name_clean\\":\\"', REGEXP_REPLACE(name, r'[^[:alpha:]]', ''),'\\"}'
+    )
+  ),
+  ']') as list
+  FROM (
+    SELECT author.name,
+      COUNT(commit) n_commits
+    FROM `bigquery-public-data.github_repos.sample_commits`
+    GROUP BY 1
+    ORDER BY 2 DESC
+    LIMIT 10
+  )
+",
+project,
+use_legacy_sql = FALSE
+)
+}
+}
diff --git a/tests/testthat.R b/tests/testthat.R
new file mode 100644
index 0000000..fcad17f
--- /dev/null
+++ b/tests/testthat.R
@@ -0,0 +1,3 @@
+library(testthat)
+
+test_check("condusco")
diff --git a/tests/testthat/test-data-frame-swaps.R b/tests/testthat/test-data-frame-swaps.R
new file mode 100644
index 0000000..afeaf25
--- /dev/null
+++ b/tests/testthat/test-data-frame-swaps.R
@@ -0,0 +1,75 @@
+context("data frame swaps")
+library(whisker)
+
+test_that(" data.frame '<' swaped into {{{three_escapes}}} via whisker == '<' ", {
+
+  if (!isNamespaceLoaded("whisker")) {
+    stop("Package whisker needed for this function to work. Please install it.")
+  }
+
+  expect_true(
+    run_pipeline(
+      #the pipeline
+      function(swap){
+        query <- "{{{three_escapes}}}"
+        whisker.render(query,swap)
+      },
+      #the swap
+      data.frame(
+        three_escapes = '<'
+      )
+    )
+    #should equal '<'
+    =="<"
+  )
+
+})
+
+test_that(" data.frame '<' swaped into {{two_escapes}} via whisker == '&lt;", {
+
+  if (!isNamespaceLoaded("whisker")) {
+    stop("Package whisker needed for this function to work. Please install it.")
+  }
+
+  expect_true(
+    run_pipeline(
+      #the pipeline
+      function(swap){
+        query <- "{{two_escapes}}"
+        whisker.render(query,swap)
+      },
+      #the swap
+      data.frame(
+        two_escapes = '<'
+      )
+    )
+    #should equal '<'
+    =="&lt;"
+  )
+
+})
+
+
+test_that("single element dataframe is converted to a named list", {
+
+  if (!isNamespaceLoaded("whisker")) {
+    stop("Package whisker needed for this function to work. Please install it.")
+  }
+
+  expect_true(
+    run_pipeline(
+      #the pipeline
+      function(swap){
+        query <- "{{two_escapes}}"
+        whisker.render(query,swap)
+      },
+      #the swap
+      data.frame(
+        two_escapes = 1
+      )
+    )
+    #should equal 1
+    =="1"
+  )
+
+})
diff --git a/vignettes/dbi.Rmd b/vignettes/dbi.Rmd
new file mode 100644
index 0000000..2c58e75
--- /dev/null
+++ b/vignettes/dbi.Rmd
@@ -0,0 +1,141 @@
+---
+title: "Examples with DBI and SQLite"
+author: "Roland Stevenson"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{DBI and SQLite}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r }
+library(whisker)
+library(DBI)
+library(condusco)
+```
+
+## Simple Example
+
+Create pipelines that run dynamic queries based on results of a query.  A common use case is to dynamically query a range of dates, without hard-coding the any variables.
+```{r}
+con <- dbConnect(RSQLite::SQLite(), ":memory:")
+
+pipeline <- function(params){
+
+  query <-"
+    SELECT count(*) as n_hits 
+    FROM user_hits 
+    WHERE date(date_time) BETWEEN date('{{{date_low}}}') AND date('{{{date_high}}}')
+  ;"
+
+  whisker.render(query,params)
+
+}
+
+run_pipeline_dbi(pipeline,
+  "SELECT date('now', '-5 days') as date_low, date('now') as date_high",
+  con
+)
+
+dbDisconnect(con)
+
+```
+
+
+## Dynamically generated queries via JSON
+If list is defined, convert the JSON string to an object and iterate through name1,name2 pairs.
+This dynamically generates a query of variable length, based on the JSON object.
+In this example, we create a trivial JSON object manually.  We'll use a dynamically generated JSON object in the next example.
+```{r}
+con <- dbConnect(RSQLite::SQLite(), ":memory:")
+
+pipeline <- function(params){
+
+  query <- "SELECT {{{value}}} as dollars_won,
+    {{#list}}
+    '{{name1}}' as {{name2}},
+    {{/list}}
+    '{{{field}}}' as field
+  ;"
+
+  whisker.render(query,params)
+
+}
+
+
+run_pipeline_dbi(
+  pipeline,
+  "SELECT value,
+    field,
+    list
+  FROM (
+    SELECT 1000 as value,
+      'word' as field,
+      '[{\"name1\":\"foo1\", \"name2\":\"bar1\"},{\"name1\":\"foo2\", \"name2\":\"bar2\"}]' as list
+  )
+  UNION ALL
+  SELECT 2000 as value,
+    'word' as field,
+    '[{\"name1\":\"foo1\", \"name2\":\"bar1\"},{\"name1\":\"foo2\", \"name2\":\"bar2\"}]' as list
+  ",
+  con
+)
+
+
+dbDisconnect(con)
+
+```
+
+
+## Feature Generation Query
+For the top 5 represented horsepowers in the mtcars dataset, create features for each of those horsepowers for each of the types of cylinders.  For example, we dynamically create features like n_hp_110=4, for cyl=6.
+```{r}
+con <- dbConnect(RSQLite::SQLite(), ":memory:")
+
+dbWriteTable(con, "mtcars", mtcars)
+
+#for each cylinder count, count the number of top 5 hps it has
+pipeline <- function(params){
+  
+  query <- "SELECT
+    {{#list}}
+    SUM(CASE WHEN hp='{{val}}' THEN 1 ELSE 0 END )as n_hp_{{val}},
+  {{/list}}
+    cyl
+    FROM mtcars
+    GROUP BY cyl
+  ;"
+
+
+  dbGetQuery(
+    con,
+    whisker.render(query,params)
+  )
+}
+
+
+#pass the top 5 most common hps as val params
+run_pipeline_dbi(
+  pipeline,
+  '
+  SELECT "[" || GROUP_CONCAT("{ ""val"": """ || hp ||  """ }") || "]" AS list
+  FROM (
+    SELECT 
+      CAST(hp as INTEGER) as HP,
+      count(hp) as cnt
+    FROM mtcars 
+    GROUP BY hp
+    ORDER BY cnt DESC
+    LIMIT 5
+  )
+  ',
+  con
+)
+
+
+dbDisconnect(con)
+
+```
+
+
diff --git a/vignettes/no-db.Rmd b/vignettes/no-db.Rmd
new file mode 100644
index 0000000..148e413
--- /dev/null
+++ b/vignettes/no-db.Rmd
@@ -0,0 +1,37 @@
+---
+title: "Examples with no database access"
+author: "Roland Stevenson"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{No Database}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r }
+library(whisker)
+library(condusco)
+```
+
+
+## Simple Example
+
+This example shows how to simply swap out a value using the whisker library. A common use case is two users working on a the same logic, but wanting to keep their datasets separate.  A namespace can be provided for each user with {{table_prefix}}, and the swap can be set in a user-specific configuration file, thereby allowing users to separate the logic of the pipelines from the user-specific configuration variables.  They can commit changes to the logic in which the commits are free of their specific variables.
+```{r}
+
+run_pipeline(
+  #the pipeline
+  function(params){
+    query <- "SELECT result FROM {{table_prefix}}_results;"
+    whisker.render(query,params)
+  },
+  #the swap
+  data.frame(
+    table_prefix = c('batman', 'robin')
+  )
+)
+
+
+```
+