Merge pull request #103 from expertanalytics/norwegian-fields

Norwegian fields

cvcreator/data/tech_skills.toml

@@ -23,6 +23,25 @@ allowed_labels = [
   "GUI",                      # Creating graphical user interfaces
 ]
 
+[norwegian_labels]
+
+"Tools" = "Verktøy"
+"Languages" = "Språk" # Note that "Programeringsspråk" breaks the table columns
+# because it is too long
+"ML" = "Maskinlæring"
+"Modelling" = "Modellering"
+"Organize" = "Organisering"
+"Cloud" = "Sky"
+"Databases" = "Databaser"
+"Web" = "Nett"
+"Platforms" = "Platformer"
+"Testing" = "Testing"
+"Visualization" = "Visualisering"
+"Office" = "Office"
+"Math" = "Matematikk"
+"File formats" = "Filformater"
+"Editors" = "Editors"
+"GUI" = "GUI"
 
 # If we want to group some labels together.
 [short_map]

cvcreator/templates/vitae.tex

@@ -95,10 +95,10 @@
   \begin{tabular}{LR}
     \BLOCK{for s in education}
       \BLOCK{if s.start}\VAR{s.start} -- \VAR{s.end}\BLOCK{else}\VAR{s.end}\BLOCK{endif} &
-      \BLOCK{if s.degree}{\bf \VAR{s.degree} in \BLOCK{if s.specialization}\VAR{s.specialization}\BLOCK{else}\VAR{s.topic}\BLOCK{endif}}\
-        \BLOCK{else}\VAR{s.specialization} -- \VAR{s.description}\BLOCK{endif} \
-      \BLOCK{if s.department or s.university or s.country} at \VAR{[s.department, s.university, s.country]|select()|join(", ")}.\BLOCK{endif} \
-      \BLOCK{if s.thesis_title}Thesis title: ``\VAR{s.thesis_title}''.\BLOCK{endif} \
+      \BLOCK{if s.degree}{\bf \VAR{s.degree} \VAR{s.what} \BLOCK{if s.specialization}\VAR{s.specialization}\BLOCK{else}\VAR{s.topic}\BLOCK{endif}}\
+      \BLOCK{else}\VAR{s.specialization} -- \VAR{s.description}\BLOCK{endif}\
+      \BLOCK{if s.department or s.university or s.country} \VAR{s.fromwhere} \VAR{[s.department, s.university, s.country]|select()|join(", ")}.\BLOCK{endif} \
+      \BLOCK{if s.thesis_title}\VAR{s.title}: ``\VAR{s.thesis_title}''.\BLOCK{endif} \
       \BLOCK{if s.degree}\VAR{s.description}\BLOCK{endif} \\
     \BLOCK{endfor}
   \end{tabular}

cvcreator/vitae/content.py

@@ -2,8 +2,9 @@
 from typing import Any, List, Sequence
 
 import toml
-from .schema import VitaeContent, SectionTitles, ProjectSubtitles, PublicationSubtitles, Titles
-from .tech_skills import make_skill_groups
+from .schema import VitaeContent, NorwegianVitaeContent
+from .schema import TechnicalSkill
+from .tech_skills import make_skill_groups, get_skills_data
 
 CURDIR = f"{os.path.dirname(__file__)}{os.path.sep}"
 
@@ -62,20 +63,29 @@ def load_vitae(
     assert str(path).endswith(".toml"), (
         "must be TOML files with .toml extension.")
     with open(path) as src:
-        content = VitaeContent(**toml.load(src))
+        if norwegian:
+            content = NorwegianVitaeContent(**toml.load(src))
+        else:
+            content = VitaeContent(**toml.load(src))
 
     # filter projects and publications (as this can not be done in template)
     content.project = filter_(projects, content.project)
     content.publication = filter_(publications, content.publication)
-    if norwegian:
-        content.change_to_norwegian_titles()
 
     # remove potential duplicates from technical skills
     content.technical_skill = list(set(content.technical_skill))
 
     # place technical skills into groups
     content.technical_skill = make_skill_groups(content.technical_skill)
 
+    if norwegian:
+        norwegian_labels = get_skills_data()["norwegian_labels"]
+        norwegian_skills = []
+        for skill in content.technical_skill:
+            norwegian_skills.append(TechnicalSkill(title=norwegian_labels[skill.title], values=skill.values))
+
+        content.technical_skill = norwegian_skills
+
     if badges:
         for skill in content.technical_skill:
             for idx, value in enumerate(skill.values):

cvcreator/vitae/schema.py

@@ -77,6 +77,24 @@ class LanguageSkill(StrictModel):
     language: Language
     proficiency: Literal["Native", "Fluent", "Intermediate", "Basic"]
 
+class NorwegianLanguageSkill(StrictModel):
+    """Language skill and proficiency."""
+
+    # In principal, it should be possible to map a language name from english to norwegian
+    # using the following code snippet (which generates a list of language names in norwegian):
+    # no = gettext.translation("iso639-3", pycountry.LOCALES_DIR,languages=["nb"])
+    # exceptions = {"English": "Engelsk"}
+    # LANGUAGE_NAMES_NO = tuple(exceptions[language.name] if language.name in exceptions \
+    #                     else no.gettext(language.name)
+    #                     for language in pycountry.languages if not no.gettext(language.name) == language.name)
+    # LanguagesNorwegian = Literal[LANGUAGE_NAMES_NO]
+    # The problem, however, is that not all language names are translated in the data base, and hence one would have to 
+    # treat that. Thus for now, the user has to enter the correct norwegian name for the language in the toml file
+    # and type(language) is str.
+    language: str
+    proficiency: Literal["Morsmål", "Flytende", "Middels", "Grunnleggende"]
+
+
 
 class PersonalSkill(StrictModel):
     """A personal skill and description."""
@@ -110,8 +128,32 @@ class Education(StrictModel):
     university: str = ""
     country: Country = ""
     description: str = ""
+    title: str = "Thesis title" # used for printing the education in latex
+    what : str = "in" # used for printing the education in latex
+    fromwhere : str = "at" # used for printing the education in latex
 
 
+class NorwegianEducation(StrictModel):
+    """Completed educational degree."""
+
+    start: int = 0
+    end: int = 0
+    degree: Literal["Mastergrad", "PhD",
+                    ""] = ""
+    topic: Literal["Fysikk", "Scientific Computing", "Mekanikk",
+                   "Matematikk", "Engineering", "Kjemi",
+                   "Geologi og Geofysikk", "informatikk", "Musikk", 
+                   ] = ""
+    specialization: str = ""
+    thesis_title: str = ""
+    department: str = ""
+    university: str = ""
+    country: Country = ""
+    description: str = ""
+    title: str = "Avhandlingens tittel" # used for printing the education in latex
+    what : str = "innen" # used for printing the education in latex
+    fromwhere : str = "fra" # used for printing the education in latex
+
 class Work(StrictModel):
     """Previous work experience."""
 
@@ -169,8 +211,8 @@ class SectionTitles(StrictModel):
     technical_skills: str = "Technical Skills"
     languages: str = "Languages"
     personal_skills: str = "Personal Skills"
-    hobbies: str = "Interests and hobbies"
-    projects: str = "Extended description of selected projects"
+    hobbies: str = "Interests and Hobbies"
+    projects: str = "Extended Description of Selected Projects"
     publications: str = "Publications"
 
 
@@ -234,12 +276,14 @@ class VitaeContent(StrictModel):
     project: List[Project] = Field(default_factory=list)
     publication: List[Publications] = Field(default_factory=list)
 
-    def change_to_norwegian_titles(self):
-        self.titles = _create_norwegian_titles()
 
+class NorwegianVitaeContent(VitaeContent):
+
+    language_skill: List[NorwegianLanguageSkill] = Field(default_factory=list)
+
+    education: List[NorwegianEducation] = Field(default_factory=list)
 
-def _create_norwegian_titles() -> Titles:
-    return Titles(
+    titles: Titles = Titles(
         section_titles=SectionTitles(
             professional_experience="Arbeidserfaring",
             education="Utdanning",

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cvcreator"
-version = "1.1.12"
+version = "1.1.14"
 description = "An automated tool for creating CVs on the fly."
 authors = ["Jonathan Feinberg <jonathf@gmail.com>"]
 license = "mit"

test/test_tech_skills.py

@@ -34,3 +34,9 @@ def test_short_maps(skills_data):
     unknown_vals = set(skills_data["short_map"].values()).difference(skills_data["skills"])
     assert not unknown_vals, f"Shortmap value not recognized: {unknown_vals}"
 
+
+def test_skill_translation(skills_data):
+
+    norwegian_labels = get_skills_data()["norwegian_labels"]
+    for label in skills_data["allowed_labels"]:
+        assert label in norwegian_labels.keys()