vignettes/LufthansaR.md
In peter0083/LufthansaR: Lufthansa API Wrapper
title: "LufthansaR"
date: "r Sys.Date()"
Introduction to LufthansaR
LufthansaR is an API wrapper package for R. It enables programmers to access to Lufthansa Open API from R environment.
This document introduces you to LufthansaR's basic set of tools, and show how to use them. Once you have installed the package, read vignette("LufthansaR") to learn more.
Lufthansa Open API
To have access to Lufthansa Open API, one has to sign in to Mashery, Lufthansa's developer platform, and apply for a key. Please visit here.
Once you are registered, you will be given:
- a key and
- a secret
These two values can be exchanged for a short-lived access token. A valid access token must be sent with every API request while accessing any Lufthansa's API. In other words, every Lufthansa API requires you to pass Oauth token when getting the data from it.
How to install LufthansaR
You can install LufthansaR development version from GitHub
```{r, eval=FALSE}
devtools::install_github("peter0083/LufthansaR")
CRAN version of the package will be scheduled to be added in the next version.
## Usage
You can load `LufthansaR` as follows.
```{r, eval=FALSE}
library(LufthansaR)
This will load the core lufthansaR functions.
How to deal with Lufthansa Open API credentials
You can store your client ID and secret in a ~/.Renviron file. R loads this file as
a system variable in each new session. The package uses these variables to request
new keys if needed. The .Renviron file should contain the lines
LUFTHANSA_API_CLIENT_ID = 'xxxxxxxxxxxxxxxxxxxxxxxx'
LUFTHANSA_API_CLIENT_SECRET = 'xxxxxxxxxx'
which specify the key and secret pair. This package does not remember the id or the
secret.
NOTE: The name of the variables should be EXACTLY:
LUFTHANSA_API_CLIENT_IDLUFTHANSA_API_CLIENT_SECRET
Because tokens last for 1.5 days and to prevent the abuse of continuously requesting
new tokens, the package by default stores the token and its expiry in a file in the
working directory called .lufthansa-token. Caching the token provides a way of
using it across R sessions until it expires. Functions in the package use the get_token()
command to access the API. For more information about the function, see help(get_token).
Caching the token can be turned off by setting the following R option through
options(lufthansar_token_cache = FALSE)
Alternately, one can choose where to cache the token by using a filename instead
options(lufthansar_token_cache = 'path/to/.token-cache')
Users can see the token being used and its expiry by calling
LufthansaR::get_creds_from_env()
How to see the active token used
Get the current token being used by the package.
```{r, eval=FALSE}
LufthansaR::get_token()
Each token is valid for a specified period of time. When the token is valid, `LufthansaR` uses the `Client ID` and `Client Secret` in your `.Renviron`.
## How to get flight status
This `get_flight_status()` function will print out the flight information
```{r, eval=FALSE}
f_status <- LufthansaR::get_flight_status(flight_num ="LH493", verbose = TRUE)
The default is the flight status for today. However, you can call 5 days into the future by passing dep_date="2018-04-15" argument. The departure date (YYYY-MM-DD) in the local time of the departure airport. To supress the update message that is printed, pass the argument verbose = FALSE.
LufthansaR package utilizes httr to parse JSON content. You can access to different attributes of the already-parsed content:
```{r, eval=FALSE}
Departure Airport abbreviation
f_status$Departure$AirportCode
Scheduled Departure Time (departure local time)
f_status$Departure$ScheduledTimeLocal$DateTime
Departure Terminal
f_status$Departure$Terminal$Name
Departure Status
f_status$Departure$TimeStatus$Definition
Arrival Airport abbreviation
f_status$Arrival$AirportCode
Scheduled Arrival Time (arrival local time)
f_status$Arrival$ScheduledTimeLocal$DateTime
Arrival Terminal
f_status$Arrival$Terminal$Name
Arrival Status
f_status$Arrival$TimeStatus$Definition
## Getting status of flights arriving at a particular airport
Let's load some packages that we will use below.
```{r, eval=FALSE}
library(tidyverse)
library(lubridate)
To obtain the information about flights at the arrival airport,
```{r, eval=FALSE}
get_flight_status_arrival(airport = "YVR", fromDateTime = "2018-04-13T00:00")
The output is the `httr` parsed content. The format of `fromDateTime` is `YYYY-MM-DDTHH:MM`. This is ISO-8601 date format.
Let's assume that we are interested in flights arriving at `FRA` around this time. And let's assume we are interested in showing some departure delays of those flights in a visualization.
```{r, eval=FALSE}
# This to get the current local time at FRA and convert it to the ISO-8601 format.
tm <- as.POSIXlt(Sys.time(), tz="Europe/Berlin", "%Y-%m-%dT%H:%M")
tm_FRA <- strftime(tm, "%Y-%m-%dT%H:%M")
# to parse the content
parsed_content <- LufthansaR::get_flight_status_arrival(airport = "FRA", fromDateTime = tm_FRA)
You can see the content return by typing parsed_content. It is possible that there might not be any flight arriving at the time specified. Let's first see how many flights the API returns.
```{r, eval=FALSE}
if (parsed_content$FlightStatusResource$Meta$TotalCount == 1){
(no_flight_returned <-parsed_content$FlightStatusResource$Meta$TotalCount)
} else{
(no_flight_returned <- summary(parsed_content$FlightStatusResource$Flights)[1])
}
In the following, a visualization is created by using the return content for departure delay for those flight arriving at FRA.
```{r, fig.width=7.5, fig.height=5, fig.align="center", eval=FALSE}
# The following is performed if the API returns some flight information
if(!(is.nan(no_flight_returned) | no_flight_returned <= 1)){
flight_departure_data <- data.frame(dept_airport = rep(NA, no_flight_returned),
scheduled_dept =rep(NA, no_flight_returned), actual_dept =rep(NA, no_flight_returned))
# wrangle the data
for (i in 1:no_flight_returned){
flight_departure_data$dept_airport[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$AirportCode
flight_departure_data$scheduled_dept[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ScheduledTimeLocal$DateTime
flight_departure_data$actual_dept[i] <-
ifelse (is.null(parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ActualTimeLocal$DateTime), NA, parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ActualTimeLocal$DateTime)
}
# clean the json data
flight_departure_data$delay <-
-as.numeric(as.duration(interval(ymd_hm(flight_departure_data$actual_dept), ymd_hm(flight_departure_data$scheduled_dept))), "minutes")
flight_departure_data<- flight_departure_data %>%
mutate(status = ifelse(is.na(delay), "not departed",
ifelse(delay>0, "delayed departure", "early/on-time"))) %>%
mutate(delay = ifelse(is.na(delay), 1, delay))
# visualize the result
ggplot(data=flight_departure_data, aes(x=as.factor(dept_airport), y=delay)) +
geom_bar(stat="identity", aes(fill=status)) +
coord_flip() +
ggtitle(paste0("Delay Status at the Departure Airports for the Flights arriving at ", "FRA")) +
theme(legend.position = "bottom") +
xlab("Airport") +
ylab("Delay (minutes)")
} else {
print("No more than one flight information available at this time!")
}
Getting status of flights departing from a particular airport
To obtain the information about flights at the departure airport,
```{r, eval=FALSE}
get_flight_status_departure(airport = "YVR", fromDateTime = "2018-04-13T00:00")
The output is the `httr` parsed content. The format of `fromDateTime` is `YYYY-MM-DDTHH:MM`. This is ISO-8601 date format.
Let's assume that we are interested in flights departing from `FRA` around this time.
```{r, eval=FALSE}
# This to get the current local time at FRA and convert it to the ISO-8601 format.
tm <- as.POSIXlt(Sys.time(), tz="Europe/Berlin", "%Y-%m-%dT%H:%M")
tm_FRA <- strftime(tm, "%Y-%m-%dT%H:%M")
# to parse the content
parsed_content <- LufthansaR::get_flight_status_departure(airport = "FRA", fromDateTime = tm_FRA)
You can see the content return by typing parsed_content. It is possible that there might not be any flight arriving at the time specified. It is possible that there might not be any flight arriving at the time specified. Let's first see how many flights the API returns.
```{r, eval=FALSE}
to count the number of flights returned
if (parsed_content$FlightStatusResource$Meta$TotalCount == 1){
(no_flight_returned <-parsed_content$FlightStatusResource$Meta$TotalCount)
} else {
(no_flight_returned <- summary(parsed_content$FlightStatusResource$Flights)[1])
}
```{r, eval=FALSE}
# The following is performed if the API returns more than one flight
if(!(is.nan(no_flight_returned) | no_flight_returned <= 1)){
flight_departure_data <- data.frame(flight_code = rep(NA, no_flight_returned),
scheduled_dept =rep(NA, no_flight_returned), destination_airport =rep(NA, no_flight_returned), arrival_time =rep(NA, no_flight_returned))
# data wrangling
for (i in 1:no_flight_returned){
flight_departure_data$flight_code[i] <-
paste0( parsed_content$FlightStatusResource$Flights[[1]][[i]]$MarketingCarrier$AirlineID,parsed_content$FlightStatusResource$Flights[[1]][[i]]$MarketingCarrier$FlightNumber)
flight_departure_data$scheduled_dept[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ScheduledTimeLocal$DateTime
flight_departure_data$destination_airport[i] <- parsed_content$FlightStatusResource$Flights[[1]][[i]]$Arrival$AirportCode
flight_departure_data$arrival_time[i] <- parsed_content$FlightStatusResource$Flights[[1]][[i]]$Arrival$ScheduledTimeLocal
}
flight_departure_data
} else {
print("No flight information available at this time!")
}
The following is a data frame of the departure data returned by Lufthansa API.
| | flight_code | scheduled_dept | destination_airport | arrival_time |
|----|-------------|------------------|---------------------|------------------|
| 1 | LH1392 | 2018-04-15T09:00 | PRG | 2018-04-15T10:00 |
| 2 | LH1388 | 2018-04-15T09:00 | POZ | 2018-04-15T10:15 |
| 3 | OS262 | 2018-04-15T09:00 | SZG | 2018-04-15T09:55 |
| 4 | LH048 | 2018-04-15T09:00 | HAJ | 2018-04-15T09:50 |
| 5 | LH902 | 2018-04-15T09:00 | LHR | 2018-04-15T09:40 |
| 6 | LH1250 | 2018-04-15T09:00 | LNZ | 2018-04-15T10:00 |
| 7 | LH1214 | 2018-04-15T09:00 | GVA | 2018-04-15T10:05 |
| 8 | LH1336 | 2018-04-15T09:00 | BUD | 2018-04-15T10:30 |
| 9 | LH1298 | 2018-04-15T09:05 | IST | 2018-04-15T13:00 |
| 10 | LH260 | 2018-04-15T09:05 | GOA | 2018-04-15T10:30 |
| 11 | LH988 | 2018-04-15T09:05 | AMS | 2018-04-15T10:20 |
| 12 | LH248 | 2018-04-15T09:10 | MXP | 2018-04-15T10:20 |
| 13 | LH1358 | 2018-04-15T09:10 | WRO | 2018-04-15T10:25 |
| 14 | LH1158 | 2018-04-15T09:10 | PMI | 2018-04-15T11:15 |
| 15 | LH352 | 2018-04-15T09:10 | BRE | 2018-04-15T10:05 |
| 16 | LH1470 | 2018-04-15T09:10 | TSR | 2018-04-15T12:00 |
| 17 | LH836 | 2018-04-15T09:10 | BLL | 2018-04-15T10:25 |
| 18 | LH1148 | 2018-04-15T09:10 | AGP | 2018-04-15T12:05 |
| 19 | LH810 | 2018-04-15T09:10 | GOT | 2018-04-15T10:45 |
| 20 | LH074 | 2018-04-15T09:10 | DUS | 2018-04-15T10:00 |
peter0083/LufthansaR documentation built on May 21, 2019, 12:05 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
title: "LufthansaR"
date: "r Sys.Date()"
Introduction to LufthansaR
LufthansaR is an API wrapper package for R. It enables programmers to access to Lufthansa Open API from R environment.
This document introduces you to LufthansaR's basic set of tools, and show how to use them. Once you have installed the package, read vignette("LufthansaR") to learn more.
Lufthansa Open API
To have access to Lufthansa Open API, one has to sign in to Mashery, Lufthansa's developer platform, and apply for a key. Please visit here.
Once you are registered, you will be given:
- a key and
- a secret
These two values can be exchanged for a short-lived access token. A valid access token must be sent with every API request while accessing any Lufthansa's API. In other words, every Lufthansa API requires you to pass Oauth token when getting the data from it.
How to install LufthansaR
You can install LufthansaR development version from GitHub
```{r, eval=FALSE} devtools::install_github("peter0083/LufthansaR")
CRAN version of the package will be scheduled to be added in the next version.
## Usage
You can load `LufthansaR` as follows.
```{r, eval=FALSE}
library(LufthansaR)
This will load the core lufthansaR functions.
How to deal with Lufthansa Open API credentials
You can store your client ID and secret in a ~/.Renviron file. R loads this file as
a system variable in each new session. The package uses these variables to request
new keys if needed. The .Renviron file should contain the lines
LUFTHANSA_API_CLIENT_ID = 'xxxxxxxxxxxxxxxxxxxxxxxx'
LUFTHANSA_API_CLIENT_SECRET = 'xxxxxxxxxx'
which specify the key and secret pair. This package does not remember the id or the secret.
NOTE: The name of the variables should be EXACTLY:
LUFTHANSA_API_CLIENT_IDLUFTHANSA_API_CLIENT_SECRET
Because tokens last for 1.5 days and to prevent the abuse of continuously requesting
new tokens, the package by default stores the token and its expiry in a file in the
working directory called .lufthansa-token. Caching the token provides a way of
using it across R sessions until it expires. Functions in the package use the get_token()
command to access the API. For more information about the function, see help(get_token).
Caching the token can be turned off by setting the following R option through
options(lufthansar_token_cache = FALSE)
Alternately, one can choose where to cache the token by using a filename instead
options(lufthansar_token_cache = 'path/to/.token-cache')
Users can see the token being used and its expiry by calling
LufthansaR::get_creds_from_env()
How to see the active token used
Get the current token being used by the package.
```{r, eval=FALSE} LufthansaR::get_token()
Each token is valid for a specified period of time. When the token is valid, `LufthansaR` uses the `Client ID` and `Client Secret` in your `.Renviron`.
## How to get flight status
This `get_flight_status()` function will print out the flight information
```{r, eval=FALSE}
f_status <- LufthansaR::get_flight_status(flight_num ="LH493", verbose = TRUE)
The default is the flight status for today. However, you can call 5 days into the future by passing dep_date="2018-04-15" argument. The departure date (YYYY-MM-DD) in the local time of the departure airport. To supress the update message that is printed, pass the argument verbose = FALSE.
LufthansaR package utilizes httr to parse JSON content. You can access to different attributes of the already-parsed content:
```{r, eval=FALSE}
Departure Airport abbreviation
f_status$Departure$AirportCode
Scheduled Departure Time (departure local time)
f_status$Departure$ScheduledTimeLocal$DateTime
Departure Terminal
f_status$Departure$Terminal$Name
Departure Status
f_status$Departure$TimeStatus$Definition
Arrival Airport abbreviation
f_status$Arrival$AirportCode
Scheduled Arrival Time (arrival local time)
f_status$Arrival$ScheduledTimeLocal$DateTime
Arrival Terminal
f_status$Arrival$Terminal$Name
Arrival Status
f_status$Arrival$TimeStatus$Definition
## Getting status of flights arriving at a particular airport
Let's load some packages that we will use below.
```{r, eval=FALSE}
library(tidyverse)
library(lubridate)
To obtain the information about flights at the arrival airport,
```{r, eval=FALSE} get_flight_status_arrival(airport = "YVR", fromDateTime = "2018-04-13T00:00")
The output is the `httr` parsed content. The format of `fromDateTime` is `YYYY-MM-DDTHH:MM`. This is ISO-8601 date format.
Let's assume that we are interested in flights arriving at `FRA` around this time. And let's assume we are interested in showing some departure delays of those flights in a visualization.
```{r, eval=FALSE}
# This to get the current local time at FRA and convert it to the ISO-8601 format.
tm <- as.POSIXlt(Sys.time(), tz="Europe/Berlin", "%Y-%m-%dT%H:%M")
tm_FRA <- strftime(tm, "%Y-%m-%dT%H:%M")
# to parse the content
parsed_content <- LufthansaR::get_flight_status_arrival(airport = "FRA", fromDateTime = tm_FRA)
You can see the content return by typing parsed_content. It is possible that there might not be any flight arriving at the time specified. Let's first see how many flights the API returns.
```{r, eval=FALSE}
if (parsed_content$FlightStatusResource$Meta$TotalCount == 1){
(no_flight_returned <-parsed_content$FlightStatusResource$Meta$TotalCount)
} else{
(no_flight_returned <- summary(parsed_content$FlightStatusResource$Flights)[1])
}
In the following, a visualization is created by using the return content for departure delay for those flight arriving at FRA.
```{r, fig.width=7.5, fig.height=5, fig.align="center", eval=FALSE}
# The following is performed if the API returns some flight information
if(!(is.nan(no_flight_returned) | no_flight_returned <= 1)){
flight_departure_data <- data.frame(dept_airport = rep(NA, no_flight_returned),
scheduled_dept =rep(NA, no_flight_returned), actual_dept =rep(NA, no_flight_returned))
# wrangle the data
for (i in 1:no_flight_returned){
flight_departure_data$dept_airport[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$AirportCode
flight_departure_data$scheduled_dept[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ScheduledTimeLocal$DateTime
flight_departure_data$actual_dept[i] <-
ifelse (is.null(parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ActualTimeLocal$DateTime), NA, parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ActualTimeLocal$DateTime)
}
# clean the json data
flight_departure_data$delay <-
-as.numeric(as.duration(interval(ymd_hm(flight_departure_data$actual_dept), ymd_hm(flight_departure_data$scheduled_dept))), "minutes")
flight_departure_data<- flight_departure_data %>%
mutate(status = ifelse(is.na(delay), "not departed",
ifelse(delay>0, "delayed departure", "early/on-time"))) %>%
mutate(delay = ifelse(is.na(delay), 1, delay))
# visualize the result
ggplot(data=flight_departure_data, aes(x=as.factor(dept_airport), y=delay)) +
geom_bar(stat="identity", aes(fill=status)) +
coord_flip() +
ggtitle(paste0("Delay Status at the Departure Airports for the Flights arriving at ", "FRA")) +
theme(legend.position = "bottom") +
xlab("Airport") +
ylab("Delay (minutes)")
} else {
print("No more than one flight information available at this time!")
}
Getting status of flights departing from a particular airport
To obtain the information about flights at the departure airport,
```{r, eval=FALSE} get_flight_status_departure(airport = "YVR", fromDateTime = "2018-04-13T00:00")
The output is the `httr` parsed content. The format of `fromDateTime` is `YYYY-MM-DDTHH:MM`. This is ISO-8601 date format.
Let's assume that we are interested in flights departing from `FRA` around this time.
```{r, eval=FALSE}
# This to get the current local time at FRA and convert it to the ISO-8601 format.
tm <- as.POSIXlt(Sys.time(), tz="Europe/Berlin", "%Y-%m-%dT%H:%M")
tm_FRA <- strftime(tm, "%Y-%m-%dT%H:%M")
# to parse the content
parsed_content <- LufthansaR::get_flight_status_departure(airport = "FRA", fromDateTime = tm_FRA)
You can see the content return by typing parsed_content. It is possible that there might not be any flight arriving at the time specified. It is possible that there might not be any flight arriving at the time specified. Let's first see how many flights the API returns.
```{r, eval=FALSE}
to count the number of flights returned
if (parsed_content$FlightStatusResource$Meta$TotalCount == 1){
(no_flight_returned <-parsed_content$FlightStatusResource$Meta$TotalCount)
} else {
(no_flight_returned <- summary(parsed_content$FlightStatusResource$Flights)[1])
}
```{r, eval=FALSE}
# The following is performed if the API returns more than one flight
if(!(is.nan(no_flight_returned) | no_flight_returned <= 1)){
flight_departure_data <- data.frame(flight_code = rep(NA, no_flight_returned),
scheduled_dept =rep(NA, no_flight_returned), destination_airport =rep(NA, no_flight_returned), arrival_time =rep(NA, no_flight_returned))
# data wrangling
for (i in 1:no_flight_returned){
flight_departure_data$flight_code[i] <-
paste0( parsed_content$FlightStatusResource$Flights[[1]][[i]]$MarketingCarrier$AirlineID,parsed_content$FlightStatusResource$Flights[[1]][[i]]$MarketingCarrier$FlightNumber)
flight_departure_data$scheduled_dept[i] <-
parsed_content$FlightStatusResource$Flights[[1]][[i]]$Departure$ScheduledTimeLocal$DateTime
flight_departure_data$destination_airport[i] <- parsed_content$FlightStatusResource$Flights[[1]][[i]]$Arrival$AirportCode
flight_departure_data$arrival_time[i] <- parsed_content$FlightStatusResource$Flights[[1]][[i]]$Arrival$ScheduledTimeLocal
}
flight_departure_data
} else {
print("No flight information available at this time!")
}
The following is a data frame of the departure data returned by Lufthansa API.
| | flight_code | scheduled_dept | destination_airport | arrival_time | |----|-------------|------------------|---------------------|------------------| | 1 | LH1392 | 2018-04-15T09:00 | PRG | 2018-04-15T10:00 | | 2 | LH1388 | 2018-04-15T09:00 | POZ | 2018-04-15T10:15 | | 3 | OS262 | 2018-04-15T09:00 | SZG | 2018-04-15T09:55 | | 4 | LH048 | 2018-04-15T09:00 | HAJ | 2018-04-15T09:50 | | 5 | LH902 | 2018-04-15T09:00 | LHR | 2018-04-15T09:40 | | 6 | LH1250 | 2018-04-15T09:00 | LNZ | 2018-04-15T10:00 | | 7 | LH1214 | 2018-04-15T09:00 | GVA | 2018-04-15T10:05 | | 8 | LH1336 | 2018-04-15T09:00 | BUD | 2018-04-15T10:30 | | 9 | LH1298 | 2018-04-15T09:05 | IST | 2018-04-15T13:00 | | 10 | LH260 | 2018-04-15T09:05 | GOA | 2018-04-15T10:30 | | 11 | LH988 | 2018-04-15T09:05 | AMS | 2018-04-15T10:20 | | 12 | LH248 | 2018-04-15T09:10 | MXP | 2018-04-15T10:20 | | 13 | LH1358 | 2018-04-15T09:10 | WRO | 2018-04-15T10:25 | | 14 | LH1158 | 2018-04-15T09:10 | PMI | 2018-04-15T11:15 | | 15 | LH352 | 2018-04-15T09:10 | BRE | 2018-04-15T10:05 | | 16 | LH1470 | 2018-04-15T09:10 | TSR | 2018-04-15T12:00 | | 17 | LH836 | 2018-04-15T09:10 | BLL | 2018-04-15T10:25 | | 18 | LH1148 | 2018-04-15T09:10 | AGP | 2018-04-15T12:05 | | 19 | LH810 | 2018-04-15T09:10 | GOT | 2018-04-15T10:45 | | 20 | LH074 | 2018-04-15T09:10 | DUS | 2018-04-15T10:00 |
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