Fill template files with structured data
Project description
NAME
kera — Fill template files with structured data
SYNOPSIS
kera plate_files... data_files...
OPTIONS
-o, --out-dir : The directory in which to write all files. Defaults to the current directory.
INSTALL
kera can be installed using the pip package manager.
pipx install kera
DESCRIPTION
This program takes a collection of template files (.plate) and a collection of data files (.json or .yaml) and then uses the data to fill placeholder "slots" in the templates. Each individual data file produces an output for each individual template file.
To represent a simple slot in a template file, surround it in double hashes:
= ##title##
by ##name## on ##date##
##content##
And provide the data in your format of choice:
{
"title": "kera",
"name": "C Wiebe",
"date": "JAN 01 1970",
"content": "Fill template files with structured data."
}
This results in:
= kera
by C Wiebe on JAN 01 1970
Fill template files with structured data.
GLOSSARY
plate file : A file containing a template; optionally can have the extension .plate
data file : A file containing structured data; can be either a JSON file or a YAML file
slot : A string in a plate file that will be replaced with data from a data file
key : The identifier used to select which value from a data file is used to fill any given slot; the key in a key / value pair
conditional slot : A slot that has a condition attached to it
collection slot : A slot whose key points to a collection of nested data
FILENAMES
Template files can have the extension .plate, but any file that isn't a data file will be read as a template by default.
Supported data filetypes are:
- JSON
- YAML
If you want to use a data file as a template file, it must have the .plate extension, e.g. .json.plate
The default filename of the filled template is the name of the data file (minus extension), an underscore, and the name of the template file (with extension, minus .plate if present). These output files can be redirected to a different directory with the --out option.
As an example:
$ ls
> 123.sql 456.sql.plate abc.json def.yml
$ kera --out output 123.sql 456.sql.plate abc.json def.yml
$ ls output
> abc_123.sql abc_456.sql def_123.sql def_456.sql
CONDITIONAL SLOTS
kera also supports other types of slots. Conditional slots (analogous to if statements) can be represented as such:
##[ condition ]{{ if true }}{{ if false (optional) }}
The condition is simply a key found in the data, and it is true if the value of the key is truthy according to Python. If the key is not found, it is automatically false. The "body" of the conditional slot is treated the same as the rest of the text; you can include other slots inside it and nest slots as much as you wish.
An example of conditional slots in use:
<div class="profile">
<h3>##name##</h3>
<ul class="inline">
##[pronouns]{{ <li>##pronouns##</li> }}
##[language]{{ <li>##language##</li> }}
##[join-date]{{ <li>Joined ##join-date##</li> }}
</ul>
##[desc]{{
##desc##
}}{{
<p>No bio provided.</p>
}}
</div>
With this, you can process both full profiles:
name: Scofflaw Saxwulf
pronouns: he/him
language: ENG | FIN
join-date: AUG 23 2025
desc: <p>INSERT INTERESTING BIO HERE</p>
<div class="profile">
<h3>Scofflaw Saxwulf</h3>
<ul class="inline">
<li>he/him</li>
<li>ENG | FIN</li>
<li>Joined AUG 23 2025</li>
</ul>
<p>INSERT INTERESTING BIO HERE</p>
</div>
And partial profiles:
name: Lusaka Hernesto
pronouns: she/her
<div class="profile">
<h3>Lusaka Hernesto</h3>
<ul class="inline">
<li>she/her</li>
</ul>
<p>No bio provided.</p>
</div>
COLLECTION SLOTS
Collection slots (analogous to for loops) are represented as:
##collection{{ body for each collection member }}
In a collection body, the "scope" that contains available keys is not the original data, but rather the keys nested inside the collection key. This is easier shown than explained:
table: Person
joins:
- table: Place
alias: a
join-on: addressId
- table: Place
alias: w
join-on: workAddressId
- table: Job
alias: j
join-on: workId
SELECT *
FROM ##table##
##joins{{
JOIN ##table## ##alias## ON ##join-on## = ##alias##.id
}};
SELECT *
FROM Person
JOIN Place a ON addressId = a.id
JOIN Place w ON workAddressId = w.id
JOIN Job j ON workId = j.id;
By default each member of the collection is joined with a newline, but you can alter this by providing a join string before the collection body that is surrounded by parenthesis:
table: Record
columns:
- name: create_date
type: DATE
- name: update_date
type: DATE
- name: id
type: INTEGER
- name: content
type: TEXT
CREATE PROCEDURE insert_into_##table##
( ##columns(\n, ){{
p_##name## IN ##type##
}}
)
BEGIN
INSERT
INTO ##table##
( ##columns(\n , ){{
##name##
}}
)
VALUES ( ##columns(\n , ){{
p_##name##
}}
);
END insert_into_##table##;
CREATE PROCEDURE insert_into_Record
( p_create_date IN DATE
, p_update_date IN DATE
, p_id IN INTEGER
, p_content IN TEXT
)
BEGIN
INSERT
INTO Record
( create_date
, update_date
, id
, content
)
VALUES ( p_create_date
, p_update_date
, p_id
, p_content
);
END insert_into_Record;
RETURN CODES
0 : Code execution was successful.
1 : Unable to create or find the given output directory.
BUGS
-
If a key in YAML is made up of numbers and only numbers, the YAML parser will store it as an integer, which won't be resolved properly when kera tries to retrieve it as a string. To prevent this, surround such keys with double quotes:
# bad: 1: this won't be resolved # good: "1": this WILL be resolved
SEE ALSO
Source code can be found at https://github.com/ctwiebe23/kera.
Changelog can be found at https://ctwiebe23.github.io/kera/changelog.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file kera-1.2.0.tar.gz.
File metadata
- Download URL: kera-1.2.0.tar.gz
- Upload date:
- Size: 7.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4cc1e1329eb2b4dc1a62844dcdbfcda6e9bebf31d2460ab8622f1ff9dac43c4e
|
|
| MD5 |
485a79d52568b2bc285e4c3362c890c1
|
|
| BLAKE2b-256 |
673ddf7c49c401fcaf0b949b7ea319011c5a35abb9a6bdbea7bbe2769e031ead
|
File details
Details for the file kera-1.2.0-py2.py3-none-any.whl.
File metadata
- Download URL: kera-1.2.0-py2.py3-none-any.whl
- Upload date:
- Size: 7.8 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a2954dc0376e044c3311da1d390b1f78a138590aab0a7cbbd9d47960c390f78f
|
|
| MD5 |
0a56e952ec3ac61c88e3f489ab5bc983
|
|
| BLAKE2b-256 |
2755e14947c9e5100380f3e61453210fae7f99026be239e07c1f309f1ec2bba0
|