Typical helps you serialize data in a language-independent fashion. You define data types in a file called a schema, then Typical generates the corresponding serialization and deserialization code for various languages. The generated code can be used for marshalling messages between services, storing structured data on disk, etc. Typical uses a compact binary encoding which supports forward and backward compatibility between different versions of your schema to accommodate evolving requirements.
The main difference between Typical and related toolchains like Protocol Buffers and Apache Thrift is that Typical has a more modern type system based on algebraic data types, emphasizing a safer programming style with non-nullable types and pattern matching. You'll feel at home if you have experience with languages which embrace that style, such as Rust, Swift, Kotlin, Haskell, etc. Typical offers a new solution ("asymmetric" fields) to the classic problem of how to safely add and remove required fields in structs as well as the lesser-known dual problem of how to safely add and remove cases in sum types while supporting exhaustive pattern matching.
In short, Typical offers two important features that are conventionally thought to be at odds: (1) uncompromising type safety and (2) binary compatibility between schema versions.
Supported languages:
Suppose you want to build an API for sending emails, and you need to decide how requests and responses will be serialized for transport. You could use a self-describing format like JSON or XML, but you may want better type safety and performance. Typical has a great story to tell about those things.
You can start by creating a schema file called email_api.t with the relevant types for your email API:
```perl struct SendEmailRequest { to: String = 0 subject: String = 1 body: String = 2 }
choice SendEmailResponse { success = 0 error: String = 1 } ```
A struct, such as our SendEmailRequest type, describes messages containing a fixed set of fields (in this case, to, subject, and body). A choice, such as our SendEmailResponse type, describes messages containing exactly one field from a fixed set of possibilities (in this case, success and error). structs and choices are called algebraic data types due to their correspondence to ideas from category theory called products and sums, respectively, but you don't need to know anything about that to use Typical.
Each field in a struct or a choice has both a name (e.g., subject) and an integer index (e.g., 1). The name is just for humans, as only the index is used to identify fields in the binary encoding. You can freely rename fields without worrying about binary incompatibility.
Each field also has a type, either explicitly or implicitly. If the type is missing, as it is for the success field above, then it implicitly defaults to a built-in type called Unit.
Now that we've defined some types, we can use Typical to generate the code for serialization and deserialization. For example, you can generate Rust code with the following:
sh
typical generate email_api.t --rust-out email_api.rs
Refer to the example Rust project for how to automate this with a Cargo build script.
The client and server can then use the generated code to serialize and deserialize messages for mutual communication. If the client and server are written in different languages, you can generate code for each language.
Note that Typical only does serialization and deserialization. It has nothing to do with service meshes, encryption, authentication, or authorization, but it can be used together with those technologies.
With the code generated in the previous section, a program could construct a message and serialize it to a file (for example) as follows:
```rust let request = SendEmailRequestOut { to: "typical@example.com".toowned(), subject: "I love Typical!".toowned(), body: "It makes serialization easy and safe.".to_owned(), };
let mut file = BufWriter::new(File::create("/tmp/request")?); request.serialize(&mut file)?; ```
Another program, possibly written in a different language, could read the message from disk (for example) and deserialize it as follows:
```rust let mut file = BufReader::new(File::open("/tmp/request")?); let request = SendEmailRequestIn::deserialize(&mut file)?;
println!("to: {}", request.to); println!("subject: {}", request.subject); println!("body: {}", request.body); ```
The full code for this example can be found here.
We'll see in the next section why our SendEmailRequest type turned into SendEmailRequestOut and SendEmailRequestIn.
optional, and asymmetric fieldsFields are required by default. This is an unusual design decision, since required fields are often thought to cause trouble for backward and forward compatibility between schema versions. Let's explore this topic in detail and see how Typical deals with it.
Experience has taught us that it can be difficult to introduce a required field to a type that is already being used. For example, suppose your new email API is up and running, and you want to add a new from field to the request type:
perl
struct SendEmailRequest {
to: String = 0
from: String = 3 # A new required field
subject: String = 1
body: String = 2
}
The only safe way to roll out this change (as written) is to finish updating all clients before beginning to update any servers. Otherwise, a client still running the old code might send a request to an updated server, which promptly rejects the request because it lacks the new field.
That kind of attentive rollout may not be feasible. You may not be in control of the order in which clients and servers are updated. Or, the clients and servers might be updated together, but not atomically. The client and the server might even be part of the same replicated service, so it wouldn't be possible to update one before the other no matter how careful you are.
Removing a required field can present analogous difficulties. Suppose, despite the aforementioned challenges, you were able to successfully introduce from as a required field. Now, an unrelated issue is forcing you to roll it back. That's just as dangerous as adding it was in the first place: if a client gets updated before a server, that client may then send the server a message without the from field, which the server will reject since it still expects that field to be present.
optional fields to required and vice versaA somewhat safer way to introduce a required field is to first introduce it as optional, and later promote it to required. For example, you can safely introduce this change:
perl
struct SendEmailRequest {
to: String = 0
optional from: String = 3 # A new optional field
subject: String = 1
body: String = 2
}
You would then update clients to set the new field. Once you're confident that the new field is always being set, you can promote it to required.
The trouble is that, as long as the field is optional, you can't rely on the type system to ensure the new field is always being set. Even if you're confident you've updated the client code appropriately, a collaborator might not be aware of your efforts and might introduce a new violation of your policy before you have the chance to promote the field to required.
You can run into analogous trouble when demoting a required field to optional. Once the field has been demoted, clients might stop setting the field before the servers can handle its absence, unless you can be sure the servers are updated promptly enough.
optionalDue to the trouble associated with required fields, the conventional wisdom is simply to never use them; all fields should be declared optional. For example:
perl
struct SendEmailRequest {
optional to: String = 0
optional subject: String = 1
optional body: String = 2
}
However, this advice ignores the reality that some things really are semantically required, even if they aren't declared required in the schema. An API cannot be expected to work if it doesn't have the data it needs. Having semantically required fields declared as optional places extra burden on both writers and readers: writers cannot rely on the type system to prevent them from accidentally forgetting to set the fields, and readers must address the case of the fields being missing to satisfy the type checker even though those fields are always supposed to be set.
asymmetric fieldsTypical offers an intermediate state between optional and required: asymmetric. An asymmetric field in a struct is considered required for the writer, but optional for the reader. Unlike optional fields, an asymmetric field can be safely promoted to required and vice versa.
Let's make that more concrete with our email API example. Instead of directly introducing the from field as required, we first introduce it as asymmetric:
perl
struct SendEmailRequest {
to: String = 0
asymmetric from: String = 3 # A new asymmetric field
subject: String = 1
body: String = 2
}
Let's take a look at the generated code for this schema; we'll choose Rust for this example. The generated code has two flavors of our SendEmailRequest type, one for serialization and another for deserialization:
```rust pub struct SendEmailRequestOut { pub to: String, pub from: String, pub subject: String, pub body: String, }
pub struct SendEmailRequestIn {
pub to: String,
pub from: Option
impl Serialize for SendEmailRequestOut { // Serialization code omitted. }
impl Deserialize for SendEmailRequestIn { // Deserialization code omitted. } ```
We can see the effect of from being an asymmetric field: its type is String in SendEmailRequestOut, but its type is Option<String> in SendEmailRequestIn. That means clients (which use SendEmailRequestOut) are now required to set the new field, but servers (which use SendEmailRequestIn) aren't yet allowed to rely on it. Once this change has been rolled out (at least to clients), we can safely promote the field to required in a subsequent change.
It works in reverse too. Suppose we now want to remove a required field. It may be unsafe to delete the field directly, since then clients might stop setting it before servers can handle its absence. But we can demote it to asymmetric, which forces servers to consider it optional and handle its potential absence, even though clients are still required to set it. Once that change has been rolled out (at least to servers), we can confidently delete the field (or demote it to optional), as the servers no longer rely on it.
In some situations, a field might stay in the asymmetric state for months, say, if you're waiting for a sufficient fraction of your users to update your mobile app. Typical can help immensely in those situations by preventing new code which uses the field inappropriately from being introduced during that period.
choices?Our discussion so far has been framed around structs, since they are more familiar to most programmers. However, the same kind of consideration must be given to choices.
The code generated for choices supports case analysis, so clients can take different actions depending on which field was set. Happily, this is done in a way that ensures you've handled all the cases. This is called exhaustive pattern matching, and it's a great feature to help you write correct code. But that extra rigor can be a double-edged sword: readers will fail to deserialize a choice if they don't recognize the field that was set.
That means it's unsafe, in general, to add or remove required fields to a choice—just like with structs. If you add a required field, updated writers may start setting it before non-updated readers know how to handle it. Conversely, if you remove a required field, updated readers will no longer be able to handle it even though non-updated writers may still be setting it.
Not to worry—choices can have optional and asymmetric fields, just like structs!
An optional field of a choice must be paired with a fallback field, which is used as a backup in case the reader doesn't recognize or doesn't want to handle the original field. So readers aren't required to handle optional fields; hence, optional. Note that the fallback itself might be optional, in which case the fallback must have a fallback, etc. Eventually, the fallback chain ends with a required field. Readers will scan the fallback chain for the first field they recognize.
An asymmetric field must also be paired with a fallback, but the fallback chain is not made available to readers; they must be able to handle the asymmetric field directly. Thus, asymmetric fields in choices behave like optional fields for writers and like required fields for readers—the opposite of their behavior in structs.
As with structs, an asymmetric field in a choice can be safely promoted to required and vice versa.
Consider a more elaborate version of our API response type:
perl
choice SendEmailResponse {
success = 0
error: String = 1
optional authentication_error: String = 2 # A more specific type of error for curious clients
asymmetric please_try_again = 3 # To be promoted to required in the future
}
Let's inspect the generated code. As with structs, we end up with separate types for serialization and deserialization:
```rust
pub enum SendEmailResponseOut {
Success,
Error(String),
AuthenticationError(String, Box
pub enum SendEmailResponseIn {
Success,
Error(String),
AuthenticationError(String, Box
impl Serialize for SendEmailResponseOut { // Serialization code omitted. }
impl Deserialize for SendEmailResponseIn { // Deserialization code omitted. } ```
The required cases (Success and Error) are as you would expect in both types.
The optional case, AuthenticationError, has a String for the error message and a second payload for the fallback. A writer might set the less specific Error case as the fallback. Readers can use the fallback if they don't wish to handle the optional case, and readers which don't even know about the optional case will use the fallback automatically.
The asymmetric case, PleaseTryAgain, also requires writers to provide a fallback. However, readers don't get to use it. This is a safe intermediate state to use before changing the field to required (which will stop requiring writers to provide a fallback) or changing the field from required to optional or nonexistent (which will stop readers from having to handle it).
Typical has no notion of a "default" value for each type. This means, for example, if a reader sees the value 0 for a field, it can be confident that this value was explicitly set by a writer, and that the writer didn't just accidentally forget to set it. Zeroes, empty strings, empty arrays, and so on aren't special in any way.
Any schema can be safely migrated to any other schema through a series of backward and forward compatible changes. Here are the rules for what is allowed in a single change:
optional and asymmetric fields.asymmetric and vice versa.struct with exactly one field, which must be required, into a choice with just that field and vice versa.In mathematical terms, these rules define a homogeneous compatibility relation over schemas which is reflexive (every schema is compatible with itself) and symmetric (forward compatibility and backward compatibility imply each other), but not transitive (two individually safe schema changes are not necessarily safe as a single change).
A schema contains only two kinds of things: imports and user-defined types. The order of those things doesn't matter. Whitespace doesn't matter either.
You don't need to fit all your type definitions in one schema file. You can organize your types into separate schema files at your leisure, and then import schemas from other schemas. For example, suppose you have a schema called email_util.t with the following contents:
perl
struct Address {
local_part: String = 0
domain: String = 1
}
Then you can import it from another file, say email_api.t:
```perl import 'email_util.t'
struct SendEmailRequest { to: email_util.Address = 0 subject: String = 1 body: String = 2 } ```
The generated code for email_api.t will now include the types from both email_api.t and email_util.t, as the latter is imported by the former.
Import paths are considered relative to the directory containing the schema doing the importing. Typical has no notion of a "top-level" directory on which all paths are based.
A useful convention is to create a main.t schema that simply imports all the other schemas, directly or indirectly. Then it's clear which schema to use for code generation. Alternatively, in a large organization, you might have a separate top-level schema per project that imports only the types needed by that project. However, these are merely conventions, and Typical has no intrinsic notion of "project".
If you import two schemas with the same name from different directories, you'll need to disambiguate usages of those schemas. Suppose, for example, you attempted the following:
```perl import 'apis/email.t' import 'util/email.t'
struct Employee { name: String = 0 email: email.Address = 1 # Uh oh! Which schema is this type from? } ```
Fortunately, Typical will tell you about this problem and ask you to clarify what you mean. You can do so with import aliases as follows:
```perl import 'apis/email.t' as emailapi import 'util/email.t' as emailutil
struct Employee { name: String = 0 email: email_util.Address = 1 } ```
Every user-defined type is either a struct or a choice, and they have the same abstract syntax: a name, an optional list of indices of deleted fields, and a list of fields. Here's are some examples of user-defined types:
```perl import 'apis/email.t' import 'net/ip.t'
choice DeviceIpAddress { staticv4: ip.V4Address = 0 staticv6: ip.V6Address = 1 dynamic = 2 }
struct Device { hostname: String = 0 asymmetric ip_address: DeviceIpAddress = 1 optional owner: email.Address = 2 } ```
A field consists of an optional rule, a human-readable name, an optional type, and an index.
The rule, if present, is either optional or asymmetric. The absence of a rule indicates that the field is required.
The name is a human-readable identifier for the field. It's used to refer to the field in code, but it's never encoded on the wire and can be safely renamed at will. The size of the name doesn't affect the size of the encoded messages, so be as descriptive as you want.
The type, if present, is either a built-in type (e.g., String), the name of a user-defined type in the same schema (e.g., Server), or the name of an import and the name of a type from the schema corresponding to that import (e.g., email.Address). If the type is missing, it defaults to Unit. This can be used to create traditional enumerated types:
perl
choice Weekday {
monday = 0
tuesday = 1
wednesday = 2
thursday = 3
friday = 4
}
The index is a non-negative integer which is required to be unique within the type. The indices aren't required to be consecutive or in any particular order, but starting with consecutive indices is a good convention.
If you delete a field, you must be careful not to reuse that field's index for any new fields as long as there are messages still containing the deleted field. Otherwise, the old field would be decoded as the new field, which is likely to result in deserialization errors and is almost certainly not what you want. To avoid this, you can reserve the indices of deleted fields to prevent them from being reused. For example, if we delete the ip_address and owner fields from the Device struct above, we can reserve their indices as follows:
```perl struct Device { deleted 1 2
hostname: String = 0
} ```
Typical will then prevent us from introducing new fields with those indices.
The following built-in types are supported:
Unit is a type which holds no information. It's mainly used for the fields of choices which represent enumerated types.F64 is the type of double-precision floating-point numbers as defined by IEEE 754.U64 is the type of unsigned 64-bit integers.S64 is the type of signed 64-bit integers.Bool is the type of Booleans.
choice with two fields, and it would use the exact same space on the wire. However, the built-in Bool type is often more convenient to use, since it corresponds to the native Boolean type of the programming language targeted by the generated code.Bytes is the type of binary blobs with no further structure.String is the type of Unicode strings.[U64]) are the types of sequences of some other type. Any type may be used for the elements, including nested arrays (e.g., [[String]]).Comments can be used to add helpful context to your schemas. A comment begins with a # and continues to the end of the line, as with Python, Ruby, Perl, etc.
An identifier (the name of a type, field, or import) must start with a letter or an underscore (_), and every subsequent character must be a letter, an underscore, or a digit. If you want to use a keyword (e.g., choice) as an identifier, you can do so by prefixing it with a $ (e.g., $choice).
Typical doesn't require any particular naming convention or formatting style. However, it's valuable to establish conventions for consistency. We recommend being consistent with the examples given in this guide. For example:
UpperCamelCase for the names of types.lower_snake_case for the names of everything else: fields, import aliases, and schema files.Note that Typical generates code that uses the most popular naming convention for the target programming language, regardless of what convention is used for the type definitions. For example, a struct named email_address will be called EmailAddressOut/EmailAddressIn in the code generated for Rust, since idiomatic Rust uses UpperCamelCase for the names of user-defined types.
The generated deserialization code is designed to be safe from malicious inputs in the sense that it protects against unsafe memory accesses like buffer over-reading, buffer overflowing, and arbitrary code execution.
There is currently no way to configure resource limits, so it's good practice to reject implausibly large messages before attempting to deserialize them. It's also good practice to apply techniques like rate limiting to mitigate denial-of-service attacks.
In general, you can expect the size of a deserialized message in memory to be within the same order of magnitude as the size of the corresponding serialized message on the wire. However, there is one exception: for values of type [Unit] (array of units), only the number of elements is encoded, since the Unit values themselves take up zero bytes on the wire. That means an attacker can force the deserialization logic to reconstruct arbitrarily large arrays of units given only the number of elements (cf. billion laughs attack). For this reason, we strongly recommend avoiding the use of [Unit] in your schema if you intend to consume untrusted inputs. This isn't a major loss, however, since that type is generally useless anyway. It's only supported for the uniformity of the type system; the array type constructor accepts any type for its argument, even if some combinations have no practical purpose.
The following sections describe how Typical serializes your data.
Many situations require Typical to serialize integer values, e.g., field indices, user-provided integers, etc. Typical uses a variable-width encoding that allows smaller integers to use fewer bytes. With the distributions that occur in practice, most integers end up consuming only a single byte.
For unsigned integers, the valid range is [0, 2^64).
Let n be the integer to be encoded. The encoding scheme described below is little-endian, so the last byte contains the most significant bits.
0 <= n < 128, embed the 7 bits of n in 1 byte as follows: xxxxxxx1.128 <= n < 16,512, embed the 14 bits of n - 128 in 2 bytes as follows: xxxxxx10 xxxxxxxx.16,512 <= n < 2,113,664, embed the 21 bits of n - 16,512 in 3 bytes as follows: xxxxx100 xxxxxxxx xxxxxxxx.2,113,664 <= n < 270,549,120, embed the 28 bits of n - 2,113,664 in 4 bytes as follows: xxxx1000 xxxxxxxx xxxxxxxx xxxxxxxx.270,549,120 <= n < 34,630,287,488, embed the 35 bits of n - 270,549,120 in 5 bytes as follows: xxx10000 xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx.34,630,287,488 <= n < 4,432,676,798,592, embed the 42 bits of n - 34,630,287,488 in 6 bytes as follows: xx100000 xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx.4,432,676,798,592 <= n < 567,382,630,219,904, embed the 49 bits of n - 4,432,676,798,592 in 6 bytes as follows: x1000000 xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx.567,382,630,219,904 <= n < 72,624,976,668,147,840, embed the 56 bits of n - 567,382,630,219,904 in 8 bytes as follows: 10000000 xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx.72,624,976,668,147,840 <= n < 18,446,744,073,709,551,616, embed the 64 bits of n - 72,624,976,668,147,840 in 9 bytes as follows: 00000000 xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx xxxxxxxx.The number of trailing zeros in the first byte indicates how many subsequent bytes there are. This allows the number of bytes in an encoded integer to be efficiently determined with a single instruction (e.g., BSF or TZCNT) on most modern processors.
The encoding is similar to the "base 128 varints" used by Protocol Buffers and Thrift's compact protocol. However, Typical's encoding differs in two ways:
16,511 uses two bytes in Typical's encoding, but 3 bytes in the encoding used by Protocol Buffers and Thrift's compact protocol.To represent signed integers, Typical converts them into an unsigned "ZigZag" representation, and then encodes the unsigned result as described above. The ZigZag representation converts signed integers with small magnitudes into unsigned integers with small magnitudes, and signed integers with large magnitudes into unsigned integers with large magnitudes. This allows signed integers with small magnitudes to be encoded using fewer bytes.
Specifically, the ZigZag representation of a two's complement 64-bit integer n is (n >> 63) ^ (n << 1), where >> is an arithmetic shift. The inverse operation is (n >> 1) ^ -(n & 1), where >> is a logical shift.
To give you a sense of how it works, the ZigZag representations of the numbers (0, -1, 1, -2, 2) are (0, 1, 2, 3, 4), respectively.
The conversion of signed integers to their ZigZag representations before their subsequent encoding as variable-width integers is also used by Protocol Buffers and Thrift's compact protocol.
structsA struct is encoded as the contiguous arrangement of (header, value) pairs, one pair per field, where the value is encoded according to its type and the header is encoded as one or two contiguous parts:
0: The size of the value is 0 bytes.1: The size of the value is 8 bytes.2: The size of the value is given by the second part of the header (below).3: The value is encoded as a variable-width integer, so its size can be determined from its first byte.2.For fields of type Unit, F64, U64, S64, or Bool for which the index is less than 32, the header is encoded as a single byte.
A struct must follow these rules:
asymmetric fields must be present.optional and asymmetric fields may be missing.choicesA choice is encoded in the same way as a struct, but with different rules:
asymmetric field must be present.For a simple enumerated type (such as Weekday above), a field with an index less than 32 takes up a single byte.
Unit takes 0 bytes to encode.F64 is normally encoded in the little-endian double-precision floating-point format defined by IEEE 754. Thus, it normally takes 8 bytes to encode. However, for field values (rather than, say, elements of an array), positive zero is encoded as 0 bytes.U64 is normally encoded as a variable-width integer. Thus, it normally takes 1-9 bytes to encode, depending on the value. However, for field values (rather than, say, elements of an array), 0 is encoded as 0 bytes, and values equal to or greater than 567,382,630,219,904 are encoded as fixed-width 8-byte little-endian integers.S64 is normally first converted into an unsigned "ZigZag" representation, which is then encoded as a variable-width integer. Thus, it normally takes 1-9 bytes to encode, depending on the magnitude of the value. However, for field values (rather than, say, elements of an array), 0 is encoded as 0 bytes, and values for which the ZigZag representation is equal to or greater than 567,382,630,219,904 are encoded as fixed-width 8-byte two's complement little-endian integers (verbatim, not with a ZigZag representation).Bool is first converted into an integer with 0 representing false and 1 representing true. The value is then encoded in the same way as a U64, including the special behavior in the case of field values if applicable. false takes 0 bytes to encode, and true takes 1 byte.Bytes is encoded verbatim, with zero additional space overhead.String is encoded as UTF-8.[U64]) are encoded in one of three ways:
Unit are represented by the number of elements encoded the same way as a U64, including the special behavior in the case of field values if applicable. Since the elements (of type Unit) take 0 bytes to encode, there's no way to infer the number of elements from the size of the buffer. Thus, it's encoded explicitly.F64, U64, S64, or Bool are represented as the contiguous arrangement of the respective encodings of the elements. The number of elements is not explicitly encoded.Bytes, String, nested arrays, or nested messages) are encoded as the contiguous arrangement of (size, element) pairs, where size is the number of bytes of the encoded element and is encoded as a variable-width integer. The element is encoded according to its type. The number of elements is not explicitly encoded.Notice that several types can take advantage of a more compact representation when they are used for the values of fields. For example, a variable-width integer takes 1-9 bytes to encode, but an integer field takes 0-8 bytes to encode, not including the field header. This may seem impossible—the resolution to this paradox is that the extra information comes from the size mode in the field header.
Once Typical is installed, you can use it to generate code for a schema called main.t with the following:
sh
typical generate main.t --rust-out types.rs --typescript-out types.ts
Here are the supported command-line options:
```
USAGE:
typical
OPTIONS: -h, --help Prints help information
-v, --version
Prints version information
SUBCOMMANDS: generate Generate code for a schema and its transitive dependencies
help
Prints this message or the help of the given subcommand(s)
```
In particular, the generate subcommand has the following options:
```
USAGE:
typical generate [OPTIONS]
FLAGS: -h, --help Prints help information
OPTIONS:
--rust-out
ARGS:
If you're running macOS or Linux on an x86-64 CPU, you can install Typical with this command:
sh
curl https://raw.githubusercontent.com/stepchowfun/typical/main/install.sh -LSfs | sh
The same command can be used again to update to the latest version.
The installation script supports the following optional environment variables:
VERSION=x.y.z (defaults to the latest version)PREFIX=/path/to/install (defaults to /usr/local/bin)For example, the following will install Typical into the working directory:
sh
curl https://raw.githubusercontent.com/stepchowfun/typical/main/install.sh -LSfs | PREFIX=. sh
If you prefer not to use this installation method, you can download the binary from the releases page, make it executable (e.g., with chmod), and place it in some directory in your PATH (e.g., /usr/local/bin).
If you're running Windows on an x86-64 CPU, download the latest binary from the releases page and rename it to typical (or typical.exe if you have file extensions visible). Create a directory called Typical in your %PROGRAMFILES% directory (e.g., C:\Program Files\Typical), and place the renamed binary in there. Then, in the "Advanced" tab of the "System Properties" section of Control Panel, click on "Environment Variables..." and add the full path to the new Typical directory to the PATH variable under "System variables". Note that the Program Files directory might have a different name if Windows is configured for language other than English.
To update to an existing installation, simply replace the existing binary.
If you have Cargo, you can install Typical as follows:
sh
cargo install typical
You can run that command with --force to update an existing installation.