A static site translation monitoring tool
Project description
rumi
Not the ones speaking the same language, but the ones sharing the same feeling understand each other. —Rumi
Rumi is a static site translation monitoring tool designed to support the localization (l10n) and internationalization (i18n) of documentation, and to facilitation the long-term maintenance of translated documentation.
Rumi currently supports two workflows for translation monitoring: file-based monitoring and message-based monitoring, both of which are described below.
File-based Translation Monitoring Workflow
File-based translation flow exemplified with Hugo site
1. Create reader
reader = GitReader(
repo_path="",
branch="main,
content_path=["content/"],
file_ext=["md"],
pattern="folder/",
langs=""
)
Parameters:
repo_path
: Path to the repository for translation monitoring.
branch
: Name of the branch to read the github history from.
content_path
: List of paths from the root of the repository to the directory that contains contents that require translation.
file_ext
: List of extensions of the target files for translation monitoring.
pattern
: Two types of patterns in which the static site repository is organized: "folder/" (organizing contents from each locale into one folder of the locale name, e.g. en/filename.md, fr/filename.md) and ".lang" (organizing contents from each locale by tagging the file name with the locale name, e.g. filename.en.md, filename.fr.md)
langs
: Language codes joint by a white space as specified by the user. If not provided, will monitor languages currently contained in the repository.
2. Set Target
The target files for translation monitoring are initialized using content_path
and file_ext
, and it can also be specified by adding or deleting single filename.
reader.add_target(filename)
reader.del_target(filename)
3. Calculate commits, origins, langs
commits = reader.parse_commits() # Structured commit history
origins = reader.get_origins(commits) # Original target files
langs = reader.get_langs(commits) # Target languages
4. Create reporter
reporter = StatusReporter(
repo_path=reader.repo_path,
src_lang=detail_src_lang,
tgt_lang=detail_tgt_lang
)
src_lang
: Language code of the source language (the original language of contents) to be reported. If not specified, all source language will be reported.
tgt_lang
: Language code of the target language (language to translate contents
into) to be reported. If not specified, all target language will be reported.
5. Report stats and details
stats mode: displays the number of Open (hasn't been translated), Updated (source file has been updated after translation), and Completed (source file has been translated for all target languages) for each Language. E.g.:
reporter.stats(commits, origins, langs)
"""
| Language | Origin | Open | Updated | Completed |
|------------+----------+--------+-----------+-------------|
| fr | 0 | 0 | 0 | 0 |
| en | 17 | 12 | 1 | 4 |
| zh | 0 | 0 | 0 | 0 |
"""
detail mode: displays translation work required for each source file together with the word count and percent change. E.g.:
reporter.detail(commits, origins, langs)
"""
| File | Status| Source Language| Target Language| Word Count| Percent Change|
|----------+-------+----------------+----------------+-----------+---------------|
| filename1| Update| en | zh | ? | 50% |
| filename2| Open | en | fr | 404 | 100% |
| filename2| Open | en | zh | 404 | 100% |
"""
6. Github Action
To setup your repository with Rumi github action so that stats and details are automated on push, include the following code in .github/workflow/rumi.yaml
:
name: Rumi action
on: push
jobs:
rumi:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v2
- name: Run Action
# Directory path that contains action.yaml
uses: ./
# Pass user input as arguments
with:
repo_url: "https://github.com/rotationalio/rotational.io.git"
pattern: "folder/"
7. Additional resources for the SDE steps
For more about setting up a Hugo site, check out the documentation about Hugo in multilingual mode.
Message-based Translation Monitoring Workflow
Message-based translation flow exemplified with React App
1. Create reporter
reporter = ReactReporter(
repo_path=config.repo_path,
content_path=config.content_path
)
2. Calculate needs
needs, msg_cnt = reporter.get_needs()
3. Report stats and details
stats mode: Print out a summary of the translation status including number of message missing and word count.
reporter.stats(needs, msg_cnt)
"""
| Language | Total | Missing | Word Count |
|------------+---------+-----------+--------------|
| ja | 175 | 174 | 1204 |
| zh | 175 | 1 | 41 |
| de | 175 | 1 | 41 |
| fr | 175 | 1 | 41 |
| en | 175 | 0 | 0 |
"""
detail mode: Print out the details of messages needing translations for each language and provide word count.
reporter.detail(needs)
"""
----------------------------------------------------------------------
ja Missing: 2
msgid1
msgid2
----------------------------------------------------------------------
zh Missing: 0
----------------------------------------------------------------------
de Missing: 0
----------------------------------------------------------------------
fr Missing: 1
msgid1
----------------------------------------------------------------------
en Missing: 0
----------------------------------------------------------------------
"""
4. Github Action
To setup your repository with Rumi github action so that stats and details are automated on push, include the following code in .github/workflow/rumi.yaml
:
5. Rumi Download
Rumi can help you download the new messages from Lingui Extract
results:
reporter.download_needs()
6. Rumi Insert Translated
Rumi can also insert the new translations back into the old ones, to support the next Lingui Compile
step.
reporter.insert_done("new_translations.txt", "old_messages.po", language_code)
7. Additional Resources for the SDE steps
Here are some additional resources for getting set up with Lingui on your React project:
- UI Dev: Setup Lingui.js
- Installation: Setup Lingui with React project
- Wrap Messages: Wrap UI text message according to Lingui patterns
- Lingui Extract:
npm run extract
oryarn extract
- Lingui Compile:
npm run compile
oryarn compile
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