Naming Convention

dlt creates table and column identifiers from the data. The data source that ie. a stream of JSON documents may have identifiers (i.e. key names in a dictionary) with any Unicode characters, of any length and naming style. On the other hand, destinations require that you follow strict rules when you name tables, columns or collections. A good example is Redshift that accepts case-insensitive alphanumeric identifiers with maximum 127 characters.

dlt groups tables from a single source in a schema.

Each schema defines naming convention that tells dlt how to translate identifiers to the namespace that the destination understands. Naming conventions are in essence functions that map strings from the source identifier format into destination identifier format. For example our snake_case (default) naming convention will translate DealFlow into deal_flow identifier.

You can pick which naming convention to use. dlt provides a few to choose from or you can easily add your own.

tip

• Standard behavior of dlt is to use the same naming convention for all destinations so users see always the same tables and column names in their databases.
• Use simple, short small caps identifiers for everything so no normalization is needed

Use default naming convention (snake_case)

Case insensitive naming convention, converting source identifiers into lower case snake case with reduced alphabet.

• Spaces around identifier are trimmed
• Keeps ascii alphanumerics and underscores, replaces all other characters with underscores (with the exceptions below)
• Replaces + and * with x, - with _, @ with a and | with l
• Prepends _ if name starts with number.
• Multiples of _ are converted into single _.
• Replaces all trailing _ with x

Uses __ as patent-child separator for tables and flattened column names.

tip

If you do not like snake_case your next safe option is sql_ci which generates SQL-safe, lower-case, case-insensitive identifiers without any other transformations. To permanently change the default naming convention on a given machine:

1. set an environment variable SCHEMA__NAMING to sql_ci_v1 OR
2. add the following line to your global config.toml (the one in your home dir ie. ~/.dlt/config.toml)

[schema]
naming="sql_ci_v1"

Source identifiers vs destination identifiers

Pick the right identifier form when defining resources

dlt keeps source (not normalized) identifiers during data extraction and translates them during normalization. For you it means:

1. If you write a transformer or a mapping/filtering function, you will see the original data, without any normalization. Use the source key names to access the dicts!
2. If you define a primary_key or cursor that participate in cursor field incremental loading use the source identifiers (dlt uses them to inspect source data, Incremental class is a filtering function).
3. When defining any other hints ie. columns or merge_key you can pick source or destination identifiers. dlt normalizes all hints together with your data.
4. Schema object (ie. obtained from the pipeline or from dlt source via discover_schema) always contains destination (normalized) identifiers.

In the snippet below, we define a resource with various "illegal" unicode characters in table name and other hint and demonstrate how they get normalized in the schema object.

Understand the identifier normalization

Identifiers are translated from source to destination form in normalize step. Here's how dlt picks the right naming convention:

• Each destination may define a preferred naming convention (ie. Weaviate), otherwise snake case will be used
• This naming convention is used when new schemas are created. This happens when pipeline is run for a first time.
• Schemas preserve naming convention when saved. Your running pipelines will maintain existing naming conventions if not requested otherwise
• dlt applies final naming convention in normalize step. Naming convention comes from (1) explicit configuration (2) from destination capabilities.
• Naming convention will be used to put destination is case sensitive/insensitive mode and apply the right case folding function.

caution

If you change naming convention and dlt detects that it changes the destination identifiers for tables/collection/files that already exist and store data, the normalize process will fail.

Case sensitive and insensitive destinations

Naming conventions come in two types.

• case sensitive
• case insensitive

Case sensitive naming convention will put a destination in case sensitive mode. Identifiers that differ only in casing will not collide. Note that many destinations are exclusively case insensitive, of which some preserve casing of identifiers (ie. duckdb) and some will case-fold identifiers when creating tables (ie. Redshift, Athena do lower case on the names).

Identifier shortening

Identifier shortening happens during normalization. dlt takes the maximum length of the identifier from the destination capabilities and will trim the identifiers that are too long. The default shortening behavior generates short deterministic hashes of the source identifiers and places them in the middle of the destination identifier. This (with a high probability) avoids shortened identifier collisions.

Pick your own naming convention

Configure naming convention

tbd.

Available naming conventions

• snake_case
• duck_case - case sensitive, allows all unicode characters like emoji 💥
• direct - case sensitive, allows all unicode characters, does not contract underscores
• sql_cs_v1 - case sensitive, generates sql-safe identifiers
• sql_ci_v1 - case insensitive, generates sql-safe lower case identifiers

Set and adjust naming convention explicitly

tbd.

Avoid identifier collisions

dlt detects various types of collisions and ignores the others.

1. dlt detects collisions if case sensitive naming convention is used on case insensitive destination
2. dlt detects collisions if change of naming convention changes the identifiers of tables already created in the destination
3. dlt detects collisions when naming convention is applied to column names of arrow tables

dlt will not detect collision when normalizing source data. If you have a dictionary, keys will be merged if they collide after being normalized. You can use a naming convention that does not generate collisions, see examples below.

Write your own naming convention

Custom naming conventions are classes that derive from NamingConvention that you can import from dlt.common.normalizers.naming. We recommend the following module layout:

1. Each naming convention resides in a separate Python module (file)
2. The class is always named NamingConvention

In that case you can use a fully qualified module name in schema configuration or pass module explicitly.

We include two examples of naming conventions that you may find useful:

1. A variant of sql_ci that generates identifier collisions with a low (user defined) probability by appending a deterministic tag to each name.
2. A variant of sql_cs that allows for LATIN (ie. umlaut) characters

note

Note that a fully qualified name of your custom naming convention will be stored in the Schema and dlt will attempt to import it when schema is loaded from storage. You should distribute your custom naming conventions with your pipeline code via an installable package with a defined namespace.