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A Python library for maintaining grammatically correct i18n (internationalization) of texts used inthe program: translation of messages, formatting dates and numbers to provide multi-language support.




Pyslate i18n library

A Python library for maintaining grammatically correct i18n
(internationalization) of texts used in the program: translation of
messages, formatting dates and numbers to provide multi-language

What is it for?

As you probably know, there already are quite many i18n libraries for
Python, mostly based on Gettext. The reason I decided to prepare my own
library was because I wasn't satisfied with any of them. I needed
full-features library, having similar capabilities as `Rails
i18n <>`__. But it's not just a
port. I included all features I found necessary, but also many more:

| - i18n of text (tag values) based on their unique names (tag keys)
| - possibility to use different backends where translation texts are stored
| - support for special structures to use by translator directly in translation text
| - powerful fallback capabilities in case some variant of tag is missing
| - possibility of injecting Python code into translations using decorators and custom functions
| - support for languages significantly different than English, based on practical knowledge and years of experience

What is it not for?

| All advanced features are optional, but it's surely not intended to be used when:
| - you are sure you don't need anything except literal text i18n
| - you'd like to use it as a templating engine
| - you'd like to make some lexical analysis
| - you'd like to create a natural language generator or a chatterbot

Simple example

Define a translation file ``translations.json``:

.. code:: json

        "hello_world": {
            "en": "Hello world!",
            "pl": "Witaj świecie!"

Then you can check that it works in an interactive Python session:


    >>> from pyslate.pyslate import Pyslate
    >>> from pyslate.backends.json_backend import JsonBackend
    >>> pys_en = Pyslate("en", backend=JsonBackend("translations.json"))
    >>> pys_en.translate("hello_world")
    Hello world!
    >>> pys_pl = Pyslate("pl", backend=JsonBackend("translations.json"))
    >>> pys_pl.translate("hello_world")
    Witaj świecie!

It works!

So the most basic use is to create a Pyslate object for a selected
language and then request translation of a specific tag using a
``Pyslate.translate()`` method. To make it more handy you can use
``Pyslate.t`` abbreviation. The JSON backend is used as an example,
there are other storage options available.

More complicated example

Change translation file into:

.. code:: json

        "introduction": {
            "en": "Hello! %{m?His|f?Her} name is %{name}."

Then in your Python interpreter you can write:


    >>> pys = Pyslate("en", backend=JsonBackend("translations.json"))
    >>> pys.t("introduction", name="John", variant="m")
    Hello! His name is John.
    >>> pys.t("introduction", name="Judy", variant="f")
    Hello! Her name is Judy.

There are two new things here: ``%{name}`` is a variable field where
actual name (specified as a keyword argument for ``t()`` method) is
interpolated. The second is ``%{m?His|f?Her}`` structure, called a
switch field, which means: if ``variant`` keyword argument is "m", then
print "His", if ``variant`` keyword argument is "f" then print "Her". If
none of these is true, then the first one is used as fallback. It's
easily possible to change pieces of translation based on context
variables. That's great for English, but it's often even more important
for `fusional
languages <>`__ (like
Polish) where word suffixes can vary in different forms.

Even more complicated example

Change translation file into:

.. code:: json

        "show_off": {
            "en": "Hello! I'd like to show you ${toy@article}"
        "toy": {
            "en": "wooden toy"

Then you can write:


    >>> pys.t("show_off")
    Hello! I'd like to show you a wooden toy.

Two new things here: ``${}`` specifies an inner tag field. It means
evaluating a "toy" tag and interpolating the contents directly into the
main tag value. At the end of the inner tag key there's a ``@article``.
It's a decorator, which means "take the tag value of tag it's used on,
and then transform the string into something else". Decorator "article"
is included as specific for English and simply adds a/an article. There
are also "upper" "lower" and "capitalize" decorators included right
away. In addition, you can define any new decorator as you like, which is
`described in the documentation


.. code:: json

        "show_off": {
            "en": "Hello! I'd like to show you ${%{toy_name}@article}"
        "horse": {
            "en": "rocking horse"

Then you can write:


    >>> pys.t("show_off", toy_name="horse")
    Hello! I'd like to show you a rocking horse.

How does it work? It's simply evaluating ``%{toy_name}`` variable field
into "horse", which produces ``${horse@article}`` inner tag field, which
is evaluated to "rocking horse" which is decorated using ``article``,
and in the end we get "a rocking horse".

Grammatical forms

.. code:: json

        "announcement": {
            "en": "Hello! ${pol:%{policeperson}@article@capitalize} is here. %{pol:m?He|f?She} is going to help us."
        "john": {
            "en": ["policeman", "m"]
        "judy": {
            "en": ["policewoman", "f"]

Then you can write:


    >>> pys.t("announcement", policeperson="john")
    Hello! A policeman is here. He is going to help us.

For "john" key in specified JSON data there's a list instead of a single
string. The first element of the list is a value used for this key, the
second is a grammatical form.

Another new thing is a "pol" identifier followed by a colon - both in an
inner tag and a switch field. The first is tag's ID, which then can be
used to specify some special tag options (which will be explained
later), but it can also be used as identifier of grammatical form which
can be used in switch field. So, in short, "m" form is taken from an
inner tag and used in switch field to print "He". The use-case for such
mechanism look quite slim for English, however it's very important in
many languages, where every noun has a grammatical form which can, for
example, affect form of adjectives.

Tag variants

It may happen that one tag is available in more than one form, which can
for example mean different suffix based on its context in the sentence.
It's hard to be shown in English, so I'll put an example in Polish:

.. code:: json

        "having": {
            "en": "I have ${item_stone}.",
            "pl": "Mam ${item_stone}."
        "not_having": {
            "en": "I don't have ${item_stone}",
            "pl": "Nie mam ${item_stone#g}"
        "item_stone": {
            "en": "a stone",
            "pl": "kamień"
        "item_stone#g": {
            "pl": "kamienia"


    >>> pys_en.t("not_having")
    I don't have a stone.
    >>> pys_pl.t("having")
    Mam kamień.
    >>> pys_pl.t("not_having")
    Nie mam kamienia.

Let's take a look at the tag value of "not\_having". In English it looks
almost the same as "having", but in Polish inner tag for item\_stone has
"#g" suffix, which makes it point at different tag. That is the tag's
variant, whose value has different suffix. What's the advantage of doing
it instead of having own tag naming convention (e.g. "stone\_g")? The
first thing is previously highlighted fallback ability. When some tag
key contains variant which is unavailable in the database, then the more
basic form is used. That's why the most basic form (singular nominative)
should be defined without any variant. In case of lack of tag key and
its basic form for a specified language, the tag or its base form is
searched for in the fallback language. Fallback mechanism is big and
details can be found
`here <>`__.
As you see, it's possible to adapt translations to the specified
language without any programmer's knowledge what language is going to be
introduced. All can be managed in translation system by creating tags
with correct variants.

Formatting numbers

When you translate number being an interpolated variable then you must
decide if the used noun should be singular or plural. Pyslate supports
that easily by a special ``number`` variable:

.. code:: json

        "having_flower": {
            "en": "I have a flower"
        "having_flower#p": {
            "en": "I have %{number} flowers"


    >>> pys.t("having_flower", number=1)
    I have a flower.
    >>> pys.t("having_flower", number=5)
    I have 5 flowers.

These two forms are sufficient for English, but for many other languages
it's not enough. For example words can have different suffixes when
there's a few of them and there's many of them. In Polish there are
three possibilities: singular (1), a few (2, 3, 4, 102, 103, 104...) and
many (all the rest). The word "kwiat*ka*" (genitive form of "kwiat*ek*"
["a flower"]) has the following plural forms: "kwiatka", "kwiatki",

.. code:: json

        "having_flower": {
            "pl": "Mam kwiatka"
        "having_flower#w": {
            "pl": "Mam %{number} kwiatki."
        "having_flower#p": {
            "pl": "Mam %{number} kwiatków."

`Every language can have different
rules <>`__,
so they are already configured for around 80 languages in ````

Custom functions

If none of previously mentioned options was a solution for your problem,
then custom functions come to the rescue. It's possible to create a
meta-tag being in fact a custom python function which can do almost
everything and then return a translated tag.

.. code:: json

        "product_presentation": {
            "en": "I'd like to present you a new product. It's ${product}."
        "car_personal": {
            "en": "a personal car"
        "car_van": {
            "en": "a delivery van"
        "product_template": {
            "en": "${%{type}} produced by %{producer}"

Then we have to create a custom function for a "product" inner tag

.. code:: python

    def product_fun(helper, name, params):
        product_id = params["product_id"]
        product_db = {
            1: dict(producer='BMW', capacity=1200),
            7: dict(producer='Audi', capacity=2000)
        product = product_db[product_id]
        if product["capacity"] >= 1000:
            car_type = "car_van"
            car_type = "car_personal"
        return helper.translation(

It gets keyword argument "product\_id", query the database for a product
and print some data related to it. Then it uses special helper object
supplied by Pyslate to translate a "product\_template" tag, whose
variable fields are set by data got inside of the function. This way you
can almost be sure that you'll never have to alter custom functions to
make it work for some language. In general, every custom function should
return a string which is a value of this pseudo-tag. Let's register that


    >>> pys.register_function("product", product_fun)

Now let's use it:


    >>> pys.t("product_presentation", product_id=7)
    I'd like to present you a new product. It's a delivery van produced by Audi.

It works great. Note that if you need lots of custom functions in your
code, then probably you should not use a translation library for this
task. You also shouldn't misuse Pyslate as a templating engine, if you
need to interpolate variables into large documents, use Jinja2 or
similar library.

Integration with templating engines

If you use a templating engine, there are probably lots of static
messages in your template files that need to be translated and you need
a way to call Pyslate directly from them. Considering short tag keys and
easy to use interface it's very simple to integrate with any template
language. I'll show how to get Pyslate work with Jinja2 and
Flask-Jinja2, but it's just as easy for any other templating language
which allows defining custom functions.

Jinja2 integration

For Jinja integration you need to get access to Jinja's env globals and
register two new functions there:

.. code:: python

    env = Environment(loader=FileSystemLoader('/path/to/templates'))
    env.globals["t"] = pyslate.t
    env.globals["l"] = pyslate.l

In Flask it's just as easy. ``app.jinja_env.globals`` contains the dict
of all global variables of jinja2 being used by Flask application
``app``. So all you need to do, assuming instance of Pyslate is stored
in ``g.pys`` is:


    app.jinja_env.globals.update(t=lambda *args, **kwargs: g.pys.t(*args, **kwargs))
    app.jinja_env.globals.update(l=lambda *args, **kwargs: g.pys.l(*args, **kwargs))

It registers functions "t" and "l" which are lambdas delegating all the
translations to pyslate object. I've used lambda, because flask's ``g``
is accessible only when processing the request while the function
registration is better to be done during the application startup.


Did you know?

Socket installs a GitHub app to automatically flag issues on every pull request and report the health of your dependencies. Find out what is inside your node modules and prevent malicious activity before you update the dependencies.


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