addrs provides IP address related types and data structures for the Go programming language with a clean and complete API and many nice features when compared with correspanding types in the Go net package. The basic types are opaque, immutable, comparable, space efficient, and defined as simple structs that don't require extra memory allocation.

One key difference which sets this library apart from others is that it maintains a clear distinction between IPv4 and IPv6 addresses and related types.

The types described in this section are opaque, immutable, comparable, space efficient and do not allocate memory. They can be used as map keys.

An Address does not store anything more than an IP address. Its size is 32 bits for IPv4 and 128 bits for IPv6 -- exactly the same size as when they appear network packet headers. However, they are not stored as bytes in network order and cannot be directly serialized as such. They can be converted to and from their net.IP representation.

A Mask is like an Address (same size) except that it must be in the format of a (potentially empty) string of 1 bits in the most significant positions, followed by 0 bits to fill out the remainder.

A Prefix is an Address plus a Mask. However, the mask is stored more efficiently as a length indicating the number of 1s.

Any Address can be used with a Prefix. It is not limited to 0s where the Mask has 0s. For example, 203.0.113.17/24 is valid and preserves the .17 at the end. If you need to mask off those bits, you can call .Network().

A Range represents the set of all addresses between a first and a last address (inclusive) and is store efficiently as such.

One thing to note is that there is no valid representation of an empty Range. The API will not return one in any case and the zero value of a Range has one address in it (Address{} - Address{}).

This is the immutable representation of Set_. See the full description below under the mutable type section for more detail.

This is the immutable representation of Table_. See the full description below under the mutable type section for more detail.

The two most complex types in this library have both mutable and immutable representations -- Set and Table. The mutable types are marked with a trailing underbar -- Set_ and Table_.

Unlike the simpler, immutable types mentioned above, Memory for Sets and Tables is allocated from the heap.

Set_ and Table_ behave like Go maps in a couple of ways:

1. They are reference types where each instance points to a shared data structure. Passing and returning them by value is efficient. Changes to any of the copies are reflected in all of them.

2. They must be initialized to be modifiable. An unitialized instance will behave like it is empty when you read from it but any attempt to modify it (e.g. insert entries) will result in a panic. Each provides a factory function which will return a fully-initialized instance which can then be modified.

There are a few ways in which these types do not behave like a Go map:

1. Converting between mutable and immutable instances is as efficient as copying a pointer. If you convert from mutable -> immutable -> mutable you end up with a mutable clone which is detached from the original, meaning modifications to it will not modify the original.

2. They are safe to read and write concurrently. All read operations work on a consistent representation of the underlying datastructure which is not affected by concurrent writes. However, subsequent reads on the same instance may -- depending on timing -- reflect concurrent writes from other goroutines.

3. Multiple concurrent writes will cause a panic.

A nice pattern to ensure consistency is to reserve writing to a single goroutine and then send fixed Sets or Tables through channels to other goroutines to consume it.

A Set contains any arbitrary collection of individual, distinct Address values. Address, Prefix, and Range are similar to sets but are more constrained. The API provides methods to convert freely between these types.

Sets are immutable and Set_s are mutable. A fixed Set can be efficiently obtained by calling .Set() on an Address, Prefix, Range, or Set_. A mutable Set_ can be obtained by calling .Set_() on a Set.

The memory required to store a Set is proportional to the minimum number of minimal length Prefixes required to exactly cover all of its Addresses. This proportionality is maintained as modifications occur. For example, subsequentially inserting two equally sized, and properly aligned Prefixes will result in changes to the underlying structure to represent them both with a single Prefix. It can get arbitrarily complicated and this will hold true.

The above is especially important when it comes to storing IPv6 addresses. For example, an entire /64 Prefix has a massive number of distinct Addresses but is stored in a very small space.

A Table maps Prefixes to arbitrary values. They use Go generics so that any type of value can be stored and retreived in a type-safe manner. Bits in the Address part that would be masked off by 0s in the Mask are ignored when using it as a key in a Table_.

Tables are immutable and Table_s are mutable. One can be efficiently obtained a fixed table by calling .Table() on a Table_ and vice-versa. This requires go 1.18 or newer because it uses generics to map prefixes to any type of your choosing.

At first glance, Table may seem similar but more restrictive than Go's map. Afterall, a Prefix can be used as a map key so why is it necessary?

Table is more capable than Go map in a few very important ways besides the ones mentioned above.

1. Walking a Table always orders the keys lexigraphically. Much like strings, shorter Prefixes come first followed by longer ones that it contains. Prefixes of the same length are ordered by their upper bits, up to that length.

2. It supports an efficient longest prefix match. When you search using a Prefix, it will return the entry whose key is closest to it (longest) yet still contains it.

3. It can convert itself to an aggregated form containing the minimum number of entries required such that any search using an Address as the search key will return the same value as it would on the original. (This operation requires that the values be of a comparable type, either by using a type that is inherently comparable with == and != or by implementing a custom compare function to compare elements of the type you store in the map.

4. It supports an efficient diff operation so that you can iterate the entries removed, added, changed, or (optionally) unchanged from one to the other.

   Starting with a large Table_, if you make a small number of modifications to it and then diff the before and after snapshots, the diff operation efficiency will be very good -- proportional to the changes made between the two.

   The exception to this is if you pass a handler for unchanged prefixes. In this case, every prefix is always visited. This can be always be avoided by passing nil for the unchanged handler.