Type: Package
Title: Access 'Piwik Pro' Website Statistics
Date: 2022-08-29
Version: 0.4.0
Author: Martin Stingl <martin.stingl@dfv.de>
Maintainer: Martin Stingl <martin.stingl@dfv.de>
Description: Run Queries against the API of 'Piwik Pro' https://developers.piwik.pro/en/latest/custom_reports/http_api/http_api.html. The result is a tibble.
URL: https://piwikpror.rstats-tips.net
BugReports: https://github.com/dfv-ms/piwikproR/issues
License: GPL (≥ 3)
Encoding: UTF-8
Imports: httr, rjson, tibble, purrr, lubridate, magrittr, dplyr, rlang, stringr, readr (≥ 2.1.0), digest, fs, tidyr, glue
RoxygenNote: 7.2.1
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-08-31 18:47:13 UTC; stingl
Repository: CRAN
Date/Publication: 2022-09-01 09:10:38 UTC

Maximum number of lines requested in Analytics-API

Description

Maximum number of lines requested in Analytics-API

Usage

MAX_LINES_PER_REQUEST_ANALYTICS_API()

Value

int

Maximum number of lines requested in Users-API

Description

Maximum number of lines requested in Users-API

Usage

MAX_LINES_PER_REQUEST_USERS_API()

Value

int

Convert column-type according to column_name

Description

Convert column-type according to column_name

Usage

apply_types(data, timestamp_to_date = TRUE)

Arguments

data

tibble

timestamp_to_date

boolean convert timestamp to date

Value

tibble

Build filter from tribble

Description

Build filter from tribble

Usage

build_filter(filters, global_operator = "and")

Arguments

filters

tribble with columns

  • column

  • operator

  • value

Possible values for operator:

  • (not_)contains

  • (not_)icontains

  • start_with

  • ends_with

  • (not_)matches

  • eq

  • neq

  • (not_)empty

global_operator

"and" or "or"

Value

filter json encoded to feed to build_query

Examples

filters <- tibble::tribble(
 ~column, ~operator, ~value,
 "event_url", "matches", "Zamperoni",
 "event_url", "matches", "-1[34]"
)
# With optional transformation
filters <- tibble::tribble(
 ~column, ~operator, ~value, ~transformation,
 "event_url", "starts_with", "/medien", "to_path",
 "event_url", "matches", "-1[34]", NULL
)
 filters <- build_filter(filters, "and")

# If values of two or more different types are used use lists

filters <- tibble::tribble(
  ~column, ~operator, ~value,
  "device_type", "eq", list(0),
  "location_country_name", "eq", list("DE")
)

# This also works for transformation

Build the query

Description

Build the query

Usage

build_query(
  date_from,
  date_to,
  website_id,
  columns,
  filters = NULL,
  metric_filters = NULL,
  offset = 0,
  max_lines = 0
)

Arguments

date_from

Start date of query

date_to

End date of query

website_id

website_id from piwik

columns

tibble containing columns and transformations (metrics and dimensions)

filters

list containing filter, best built by build_filter

metric_filters

list containing filter, best built by build_filter

offset

offset

max_lines

limit

Value

query as list

Examples

columns <- tibble::tribble(
  ~column, ~transformation,
  "event_url", "to_path",
  "event_url", "to_domain",
  "website_name", "",
  "timestamp", "",
  "timestamp", "to_hour_of_day",
  "page_views", ""
  )
  build_query(lubridate::ymd("2021-01-01"), lubridate::ymd("2021-01-19"),
              "xxx", columns)

get_app_detail fetching details about an app

Description

get_app_detail fetching details about an app

Usage

get_app_detail(token, app)

Arguments

token

login token generated by get_login_token

app

app id, see get_apps_list

Value

data.frame with details about the app

get_apps_list fetch all apps

Description

get_apps_list fetch all apps

Usage

get_apps_list(token)

Arguments

token

login token generated by get_login_token

Value

data.frame

Convert column-type according to column_name

Description

Convert column-type according to column_name

Usage

get_column_type(column_name, timestamp_to_date = TRUE)

Arguments

column_name

string

timestamp_to_date

boolean convert timestamp to date

Value

string suggested type of column

get_generic_list fetches all rows of a given api

Description

get_generic_list fetches all rows of a given api

Usage

get_generic_list(token, offset, api_endpoint, columns, datetime_columns)

Arguments

token

login token generated by get_login_token

offset

defailt 0, integer, where to start fetching usergroups

api_endpoint

string with api endpoint

columns

vector of strings containing columnnames

datetime_columns

vector of strings containing columnnames which are converted to datetime

Value

data.frame

Fetch login token

Description

Fetch login token

Usage

get_login_token(credentials)

Arguments

credentials

List with fields client_id, client_secret and url

Value

List with login_token

get_metasites_list

Description

get_metasites_list

Usage

get_metasites_list(token)

Arguments

token

login token generated by get_login_token

Value

data.frame

get_permissions_for_app

Description

get_permissions_for_app

Usage

get_permissions_for_app(token, app)

Arguments

token

login token generated by get_login_token

app

app id, see get_apps_list

Value

data.frame

get_permissions_for_metasite

Description

get_permissions_for_metasite

Usage

get_permissions_for_metasite(token, metasite)

Arguments

token

login token generated by get_login_token

metasite

app id, see get_metasites_list

Value

data.frame

get_test_credentials getting credentials for testing

Description

Fills credentials out of ENV into a list

Usage

get_test_credentials()

Value

list

get_usergroup_members

Description

get_usergroup_members

Usage

get_usergroup_members(token, usergroup_id)

Arguments

token

login token generated by get_login_token

usergroup_id

usergroup (see get_usergroups_list)

Value

data.frame

get_usergroups_list fetch all usergroups

Description

get_usergroups_list fetch all usergroups

Usage

get_usergroups_list(token)

Arguments

token

login token generated by get_login_token

Value

data.frame

get_users_list fetch all users

Description

get_users_list fetch all users

Usage

get_users_list(token)

Arguments

token

login token generated by get_login_token

Value

data.frame

is_column_a_metric Checks if column_name indicates numeric values Uses https://developers.piwik.pro/en/latest/custom_reports/columns.html

Description

is_column_a_metric Checks if column_name indicates numeric values Uses https://developers.piwik.pro/en/latest/custom_reports/columns.html

Usage

is_column_a_metric(column_name)

Arguments

column_name

string

Value

boolean

Ask package specific question during release-process

Description

Ask package specific question during release-process

Usage

release_questions()

Value

vector of strings

Send the query and receive the result

Description

Send the query and receive the result

Usage

send_query(
  query,
  token,
  use_csv = TRUE,
  fetch_by_day = FALSE,
  api = "query",
  caching = FALSE,
  caching_dir = "cache",
  convert_types = TRUE
)

Arguments

query

list generated by build_query

token

login token generated by get_login_token

use_csv

logical to choose whether to fetch data via extra csv-request

fetch_by_day

logical fetch data day by day

api

API endpoint ("query", "sessions", "events")

caching

logical Set TRUE to enable caching

caching_dir

character Set directory for saving caching data, default cache

convert_types

logical guess type of columns and set them

Value

result as tibble

Send the query and receive the result

Description

Send the query and receive the result

Usage

send_query_single(query, token, use_csv, api, caching, caching_dir)

Arguments

query

list generated by build_query()

token

login token

use_csv

logical to choose whether to fetch data via extra csv-request

api

API endpoint (query, sessions, events)

caching

logical Set TRUE to enable caching

caching_dir

character Set directory for saving caching data

Value

result as list with values data and meta