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Automerge is a library that enables automatic merging of concurrent changes without conflicts. It’s built on the concept of Conflict-free Replicated Data Types (CRDTs), which are data structures designed to be safely replicated across multiple devices and automatically merged.
Let’s start with the most fundamental operations:
doc <- am_create()
print(doc)
#> <Automerge Document>
#> Actor: cd29ba4e192b4dd980495040de6a3300
#> Root keys: 0Note: When you’re done working with a document, you can explicitly
free its resources with am_close(doc) if you don’t want to
wait for garbage collection.
Automerge provides multiple ways to add data, from functional to R-idiomatic:
Automerge supports nested data structures (maps within maps, lists within maps, etc.).
The simplest approach is to use R’s native list structures, which are automatically converted:
# Create document with nested structure in one call
doc3 <- am_create() |>
am_put(
AM_ROOT,
"company",
list(
name = "Acme Corp",
founded = 2020L,
employees = list(
list(name = "Alice", role = "Engineer"),
list(name = "Bob", role = "Designer")
),
office = list(
address = list(
street = "123 Main St",
city = "Boston",
zip = 02101L
),
size = 5000.5
)
)
) |>
am_commit("Add company data")
# Access nested data (verbose way)
company <- doc3[["company"]]
office <- am_get(doc3, company, "office")
address <- am_get(doc3, office, "address")
am_get(doc3, address, "city")
#> [1] "Boston"For deep structures, path-based helpers make navigation much easier:
# Much simpler - use path-based access
am_get_path(doc3, c("company", "office", "address", "city"))
#> [1] "Boston"
# Create deep structure using paths
doc4 <- am_create()
am_put_path(doc4, c("config", "database", "host"), "localhost")
am_put_path(doc4, c("config", "database", "port"), 5432L)
am_put_path(doc4, c("config", "cache", "enabled"), TRUE)
am_put_path(doc4, c("config", "cache", "ttl"), 3600L)
# Retrieve values with paths
am_get_path(doc4, c("config", "database", "host"))
#> [1] "localhost"
am_close(doc3)
am_close(doc4)Use as_automerge() to convert entire R structures at
once:
# Your existing R data
config_data <- list(
app_name = "MyApp",
version = "1.0.0",
database = list(
host = "localhost",
port = 5432L,
credentials = list(
user = "admin",
password_hash = "..."
)
),
features = list("auth", "api", "websocket")
)
# Convert to Automerge document
doc5 <- as_automerge(config_data)
am_commit(doc5, "Initial configuration")
# Easy access with paths
am_get_path(doc5, c("database", "port"))
#> [1] 5432
am_close(doc5)Lists in R use 1-based indexing (standard R convention):
# Create a document with a list
doc6 <- am_create()
am_put(doc6, AM_ROOT, "items", AM_OBJ_TYPE_LIST)
items <- am_get(doc6, AM_ROOT, "items")
# Insert items
am_insert(doc6, items, 1, "first") # Insert at index 1
am_insert(doc6, items, 2, "second") # Insert at index 2
am_insert(doc6, items, 3, "third") # Insert at index 3
# Or use the "end" marker to append
am_insert(doc6, items, "end", "fourth")
am_put(doc6, items, "end", "fifth")
# Get list length
am_length(doc6, items)
#> [1] 5
# Access by index
am_get(doc6, items, 1)
#> [1] "first"
am_get(doc6, items, 2)
#> [1] "second"
am_close(doc6)Regular strings use deterministic conflict resolution (one value wins). For collaborative text editing, use text objects:
doc7 <- am_create()
# Regular string (last-write-wins)
am_put(doc7, AM_ROOT, "title", "My Document")
# Text object (CRDT - supports collaborative editing)
am_put(doc7, AM_ROOT, "content", am_text("Initial content"))
text_obj <- am_get(doc7, AM_ROOT, "content")
# Text supports character-level operations
# For the text "Hello":
# H e l l o
# 0 1 2 3 4 5 <- positions (0-based, between characters)
am_text_splice(text_obj, 8, 0, "amazing ") # Insert at position 8
am_text_content(text_obj)
#> [1] "Initial amazing content"
# For collaborative editors, use am_text_update() which computes
# and applies the minimal diff in one step:
old_text <- am_text_content(text_obj)
am_text_update(text_obj, old_text, "New content from user input")
am_text_content(text_obj)
#> [1] "New content from user input"
am_close(doc7)Counters are special values that can be incremented/decremented without conflicts:
Documents can be saved to binary format and loaded later:
# Save to binary format
bytes <- am_save(doc)
# Save to file
temp_file <- tempfile(fileext = ".automerge")
writeBin(bytes, temp_file)
# Load from binary
doc_loaded <- am_load(bytes)
# Or load from file
doc_from_file <- am_load(readBin(temp_file, "raw", 1e6))
# Verify data persisted
doc_from_file[["name"]]
#> [1] "Alice"
am_close(doc)
am_close(doc_loaded)
am_close(doc_from_file)Create independent copies:
Merge changes from one document into another:
# Create two documents
doc12 <- am_create()
doc12[["source"]] <- "doc12"
doc12[["value1"]] <- 100
doc13 <- am_create()
doc13[["source"]] <- "doc13"
doc13[["value2"]] <- 200
# Merge doc13 into doc12
am_merge(doc12, doc13)
# doc12 now has both values
doc12[["value1"]]
#> [1] 100
doc12[["value2"]]
#> [1] 200
doc12[["source"]] # One value wins deterministically for conflicting keys
#> [1] "doc13"
am_close(doc12)
am_close(doc13)Automerge’s key feature is automatic synchronization between documents:
# Create two peers
peer1 <- am_create()
peer1[["edited_by"]] <- "peer1"
peer1[["data1"]] <- 100
am_commit(peer1)
peer2 <- am_create()
peer2[["edited_by"]] <- "peer2"
peer2[["data2"]] <- 200
am_commit(peer2)
# Bidirectional sync (documents modified in place)
rounds <- am_sync(peer1, peer2)
rounds
#> [1] 4
# Both documents now have all data
peer1[["data1"]]
#> [1] 100
peer1[["data2"]]
#> [1] 200
peer2[["data1"]]
#> [1] 100
peer2[["data2"]]
#> [1] 200
am_close(peer1)
am_close(peer2)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.