Revolutions

by Hong Ooi

I’m happy to announce that Microsoft365R 2.1.0 is now on CRAN with Outlook email support! Here’s a quick summary of the new features:

• Send, reply to and forward emails, optionally composed with blastula or emayili
• Copy and move emails between folders
• Create, delete, copy and move folders
• Add, remove and download attachments

Here’s a sample of how to write an email using blastula:

library(Microsoft365R)

# 1st one is for your personal Microsoft account
# 2nd is for your work & school account
outl <- get_personal_outlook()
outlb <- get_business_outlook()

# compose an email with blastula
library(blastula)
bl_body <- "## Hello!

This is an email message that was generated by the blastula package.

We can use **Markdown** formatting with the `md()` function.

Cheers,

The blastula team"

bl_em <- compose_email(
    body=md(bl_body),
    footer=md("sent via Microsoft365R")
)
em <- outl$create_email(bl_em, subject="Hello from R",
                        to="bob@example.com")

# add an attachment and send it
em$add_attachment("mydocument.docx")
em$send()

And on the other side, here’s a sample of how to work with the emails in your inbox:

# list the most recent emails in your inbox
emlst <- outl$list_emails()

# get the most recent email
em <- emlst[[1]]

# list and download attachments
em$list_attachments()
em$download_attachment("mydatafile.csv")

# reply to it
em$create_reply("Replying from R")$send()

# list the folders in your account
outl$list_folders()

# move the move recent email to a given folder
folder <- outl$get_folder("My project folder")
em$move(folder)

In addition, this release fixes a bug in the list_files() method for OneDrive/Sharepoint drives and drive items, and adds the ability to create nested drive folders in one call.

Please note that if you’re using one of the workarounds mentioned in the authentication vignette, they won’t work with Outlook. You’ll need to get the Microsoft365R app approved for your tenant, or alternatively, if you have admin rights you can create your own tenant with the required permissions. (This applies if you’re using Microsoft365R at work; if you’re using it at home on your personal account, you shouldn’t have any problems.)

If you have any feedback or comments, you can email me or open an issue at the repo.

by Hong Ooi

This is an announcement that a beta Outlook email client is now part of the Microsoft365R package. You can install it from the GitHub repository with:

devtools::install_github("Azure/Microsoft365R")

The client provides the following features:

• Send, reply to and forward emails, optionally composed with blastula or emayili
• Copy and move emails between folders
• Create, delete, copy and move folders
• Add, remove and download attachments

The plan is to submit this to CRAN sometime next month, after a period of public testing. Please give it a try and give me your feedback: either via email or by opening an issue at the repo.

Here’s a small sample of the client in action (taken from the README):

library(Microsoft365R)

# 1st one is for your personal Microsoft account
# 2nd is for your work & school account
outl <- get_personal_outlook()
outlb <- get_business_outlook()

# compose an email with blastula
library(blastula)
bl_body <- "## Hello!

This is an email message that was generated by the blastula package.

We can use **Markdown** formatting with the `md()` function.

Cheers,

The blastula team"

bl_em <- compose_email(
    body=md(bl_body),
    footer=md("sent via Microsoft365R")
)
em <- outl$create_email(bl_em, subject="Hello from R",
                        to="bob@example.com")

# add an attachment and send it
em$add_attachment("mydocument.docx")
em$send()

# list the most recent emails in your inbox
emlst <- outl$list_emails()

# reply to the most recent email
emlst[[1]]$
    create_reply("Replying from R")$
    send()

Please note though, that if you’re using one of the workarounds mentioned in the authentication vignette, they won’t work with Outlook. You’ll need to get the Microsoft365R app approved for your tenant, or alternatively, if you have admin rights you can create your own tenant with the required permissions. (This applies if you’re using Microsoft365R at work; if you’re using it at home on your personal account, you shouldn’t have any problems.)

by Hong Ooi

I’m happy to announce that version 2.0 of Microsoft365R, the R interface to Microsoft 365, is now on CRAN! This version adds support for Microsoft Teams, a much-requested feature.

To access a team in Microsoft Teams, use the get_team() function and provide the team name or ID. You can also list the teams you’re in with list_teams(). These return objects of R6 class ms_team, which has methods for working with channels and drives.

list_teams()
team <- get_team("My team")

# list the channels in a team (including your private channels)
team$list_channels()

# get the primary channel for a team
team$get_channel()

# get a specific channel
team$get_channel("My channel")

# drives for a team
team$list_drives()
team$get_drive()

A drive is an ms_drive object, so if you’re already using Microsoft365R to interface with OneDrive and SharePoint document libraries, you already know how to use a team’s drives. Each team will generally have at least one drive, and possibly two: the default “Shared Documents” drive, which is where uploaded files are stored, and the “Teams Wiki Data” drive, if the team has a wiki. Each team channel will usually also have an associated folder in each drive.

drv <- team$get_drive()

# one folder per channel
drv$list_files()

# upload will appear in Files tab of "My channel" in the Teams client
drv$upload_file("myfile.csv", "My channel/myfile.csv")

chan <- team$get_channel()

# retrieve most recent messages from the server
msgs <- chan$list_messages()

# get the latest message by ID
msg <- chan$get_message(msgs[[1]]$properties$id)

# body of the message
msg$properties$body

# 10 most recent replies
repl_list <- msg$list_replies(n=10)

# body of an individual reply
repl_list[[1]]$properties$body

# sending messages to a channel
chan$send_message("Hello from R")
chan$send_message(
    "<div>Hello from <em>R</em></div>", content_type="html")

# attachments and inline images
chan$send_message("Hello with attachments",
    attachments=c("intro.md", "myfile.csv"))
chan$send_message("",
    content_type="html", inline="graph.png")

# send a reply to a message
msg <- chan$send_message("Starting a new thread in R")
msg$send_reply("Reply from R")

# files for the channel
chan$list_files()

# upload a file to the channel
chan$upload_file("myfile.docx")

# open the uploaded document for editing in Word Online
chan_folder <- chan$get_folder()
item <- chan_folder$get_item("myfile.docx")
item$open()

# download it again
item$download(overwrite=TRUE)

by Hong Ooi

I’m pleased to announce that the AzureTableStor package, providing a simple yet powerful interface to the Azure table storage service, is now on CRAN. This is something that many people have requested since the initial release of the AzureR packages nearly two years ago.

Azure table storage is a service that stores structured NoSQL data in the cloud, providing a key/attribute store with a schemaless design. Because table storage is schemaless, it’s easy to adapt your data as the needs of your application evolve. Access to table storage data is fast and cost-effective for many types of applications, and is typically lower in cost than traditional SQL for similar volumes of data.

You can use table storage to store flexible datasets like user data for web applications, address books, device information, or other types of metadata your service requires. You can store any number of entities in a table, and a storage account may contain any number of tables, up to the capacity limit of the storage account.

AzureTableStor builds on the functionality provided by the AzureStor package. The table storage service is available both as part of general Azure storage and via Azure Cosmos DB; AzureTableStor is able to work with either.

library(AzureTableStor)

# storage account endpoint
endp <- table_endpoint(
    "https://mystorageacct.table.core.windows.net",
    key="mykey")
# Cosmos DB w/table API endpoint
endp <- table_endpoint(
    "https://mycosmosdb.table.cosmos.azure.com:443",
    key="mykey")

create_storage_table(endp, "mytable")
list_storage_tables(endp)
tab <- storage_table(endp, "mytable")

insert_table_entity(tab, list(
    RowKey="row1",
    PartitionKey="partition1",
    firstname="Bill",
    lastname="Gates"
))

get_table_entity(tab, "row1", "partition1")

# we can import to the same table as above:
# table storage doesn't enforce a schema
import_table_entities(tab, mtcars,
    row_key=row.names(mtcars),
    partition_key=as.character(mtcars$cyl))

list_table_entities(tab)
list_table_entities(tab, filter="firstname eq 'Satya'")
list_table_entities(tab, filter="RowKey eq 'Toyota Corolla'")

ir <- subset(iris, Species == "setosa")

# property names must be valid C# variable names
names(ir) <- sub("\\.", "_", names(ir))

# create the PartitionKey and RowKey properties
ir$PartitionKey <- ir$Species
ir$RowKey <- sprintf("%03d", seq_len(nrow(ir)))

# generate the array of insert operations: 1 per row
ops <- lapply(seq_len(nrow(ir)), function(i)
    create_table_operation(endp, "mytable", body=ir[i, ],
                           http_verb="POST")))

# create a batch transaction and send it to the endpoint
bat <- create_batch_transaction(endp, ops)
do_batch_transaction(bat)