diff --git a/CI/prepare_documentation_precommit.sh b/CI/prepare_documentation_precommit.sh
index 373e6ba4a7b7028451aea47ee53bb0f5309160dd..e653861d5f09a246c3c4041d5f5b4114ce9fca61 100755
--- a/CI/prepare_documentation_precommit.sh
+++ b/CI/prepare_documentation_precommit.sh
@@ -7,6 +7,14 @@ python3 prepare_openapi_json.py toardb_fastapi.yaml
# convert OpenAPI format to Markdown
openapi-markdown --skip-info -i sample.json
+# also get controlled_vocabulary
+curl "http://127.0.0.1:8000/controlled_vocabulary" >controlled_vocabulary.json
+# giving credit to torsimany (although it was not working, it was a good starting point)
+torsimany controlled_vocabulary.json
+# some more pretty printing for the "tables"
+cat controlled_vocabulary.markdown | sed -E 's/\], \[/\], \n \[/g' | sed -E 's/\[\[/\[ \n \[/g' | sed -E 's/#/####/g' >controlled_vocabulary.md
+
+
# last pretty print changes for pages
(
cat <<'EOF'
@@ -26,6 +34,14 @@ EOF
) > sample_rest_header.md
sed '1,/^### Models$/d' sample.md >sample_models.md
sed '/^### Models$/Q' sample.md >sample_rest.md
+(
+cat <<'EOF'
+
+
+## controlled vocabulary
+
+EOF
+) > controlled_vocabulary_header.md
-cat sample_header.md sample_models.md sample_rest_header.md sample_rest.md >../docs/toardb_fastapi.md
-rm sample* toardb_fastapi.yaml
+cat sample_header.md sample_models.md controlled_vocabulary_header.md controlled_vocabulary.md sample_rest_header.md sample_rest.md >../docs/toardb_fastapi.md
+rm sample* controlled* toardb_fastapi.yaml
diff --git a/docs/toardb_fastapi.md b/docs/toardb_fastapi.md
index d00df760fdc00e176cf1bf03ae13989bccf95d35..2ed6e9ba0d818858e212300b722068ed2309d90c 100644
--- a/docs/toardb_fastapi.md
+++ b/docs/toardb_fastapi.md
@@ -236,8 +236,188 @@
| chemical_formula | string | Chemical formula. Chemical formula of variable(if applicable) | Yes |
| id | integer | | Yes |
+## controlled vocabulary
+
+#### Rc_Vocabulary ####
+ * RC_vocabulary: [
+ [0, 'PointOfContact', 'point of contact'],
+ [1, 'PrincipalInvestigator', 'principal investigator'],
+ [2, 'Originator', 'originator'],
+ [3, 'Contributor', 'contributor'],
+ [4, 'Collaborator', 'collaborator'],
+ [5, 'ResourceProvider', 'resource provider']]
+#### Rs_Vocabulary ####
+ * RS_vocabulary: [
+ [0, 'active', 'active'],
+ [1, 'inactive', 'inactive'],
+ [2, 'unknown', 'unknown']]
+#### Ok_Vocabulary ####
+ * OK_vocabulary: [
+ [1, 'Government', 'government'],
+ [2, 'Research', 'research'],
+ [3, 'International', 'international'],
+ [4, 'NonProfit', 'non-profit'],
+ [5, 'Commercial', 'commercial'],
+ [6, 'Individual', 'individual'],
+ [7, 'Other', 'other']]
+#### Da_Vocabulary ####
+ * DA_vocabulary: [
+ [0, 'ByAttribution', 'by attribution'],
+ [1, 'ShareAlike', 'share alike'],
+ [2, 'Restricted', 'restricted']]
+#### Sf_Vocabulary ####
+ * SF_vocabulary: [
+ [0, 'Hourly', 'hourly'],
+ [1, 'ThreeHourly', '3-hourly'],
+ [2, 'SixHourly', '6-hourly'],
+ [3, 'Daily', 'daily'],
+ [4, 'Weekly', 'weekly'],
+ [5, 'Monthly', 'monthly'],
+ [6, 'Yearly', 'yearly'],
+ [7, 'Irregular', 'irregular data samples of constant length'],
+ [8, 'Irregular2', 'irregular data samples of varying length']]
+#### At_Vocabulary ####
+ * AT_vocabulary: [
+ [0, 'Mean', 'mean'],
+ [1, 'Mean1Of2', 'mean of two values'],
+ [2, 'Mean1OfWeek', 'weekly mean'],
+ [3, 'Mean4Samples', 'mean out of 4 samples'],
+ [4, 'MeanMonth', 'monthly mean'],
+ [5, 'None', 'none'],
+ [6, 'Unknown', 'unknown']]
+#### Ds_Vocabulary ####
+ * DS_vocabulary: [
+ [0, 'Model', 'model'],
+ [1, 'Measurement', 'measurement']]
+#### Mm_Vocabulary ####
+ * MM_vocabulary: [
+ [0, 'UVAbsorption', 'UV absorption'],
+ [1, 'UnknownInstrument', 'unknown instrument']]
+#### Cz_Vocabulary ####
+ * CZ_vocabulary: [
+ [-1, 'Undefined', 'undefined'],
+ [0, 'Unclassified', 'unclassified'],
+ [1, 'WarmTemperateMoist', 'warm temperate moist'],
+ [2, 'WarmTemperateDry', 'warm temperate dry'],
+ [3, 'CoolTemperateMoist', 'cool temperate moist'],
+ [4, 'CoolTemperateDry', 'cool temperate dry'],
+ [5, 'PolarMoist', 'polar moist'],
+ [6, 'PolarDry', 'polar dry'],
+ [7, 'BorealMoist', 'boreal moist'],
+ [8, 'BorealDry', 'boreal dry'],
+ [9, 'TropicalMontane', 'tropical montane'],
+ [10, 'TropicalWet', 'tropical wet'],
+ [11, 'TropicalMoist', 'tropical moist'],
+ [12, 'TropicalDry', 'tropical dry']]
+#### Cv_Vocabulary ####
+ * CV_vocabulary: [
+ [0, 'NotChecked', 'not checked'],
+ [1, 'Verified', 'verified'],
+ [2, 'Plausible', 'plausible'],
+ [3, 'Doubtful', 'doubtful'],
+ [4, 'Unverifyable', 'not verifyable']]
+#### St_Vocabulary ####
+ * ST_vocabulary: [
+ [0, 'Unknown', 'unknown'],
+ [1, 'Background', 'background'],
+ [2, 'Traffic', 'traffic'],
+ [3, 'Industrial', 'industrial'],
+ [4, 'Other', 'other']]
+#### Ta_Vocabulary ####
+ * TA_vocabulary: [
+ [0, 'Unknown', 'unknown'],
+ [1, 'Urban', 'urban'],
+ [2, 'Suburban', 'suburban'],
+ [3, 'Rural', 'rural'],
+ [4, 'Remote', 'remote']]
+#### Tc_Vocabulary ####
+ * TC_vocabulary: [
+ [-1, 'Unknown', 'unknown'],
+ [0, 'Unclassified', 'unclassified'],
+ [1, 'RuralLowElevation', 'rural low elevation'],
+ [2, 'RuralHighElevation', 'rural high elevation'],
+ [3, 'Urban', 'urban']]
+#### Tr_Vocabulary ####
+ * TR_vocabulary: [
+ [-1, 'HTAPTier1Undefined', '-1 (undefined)'],
+ [1, 'HTAPTier1World', '1 (World)'],
+ [2, 'HTAPTier1OCN', '2 (OCN Non-arctic/Antarctic Ocean)'],
+ [3, 'HTAPTier1NAM', '3 (NAM US+Canada (upto 66 N; polar circle))'],
+ [4, 'HTAPTier1EUR', '4 (EUR Western + Eastern EU+Turkey (upto 66 N polar circle))'],
+ [5, 'HTAPTier1SAS', '5 (SAS South Asia: India, Nepal, Pakistan, Afghanistan, Bangadesh, Sri Lanka)'],
+ [6, 'HTAPTier1EAS', '6 (EAS East Asia: China, Korea, Japan)'],
+ [7, 'HTAPTier1SEA', '7 (SEA South East Asia)'],
+ [8, 'HTAPTier1PAN', '8 (PAN Pacific, Australia+ New Zealand)'],
+ [9, 'HTAPTier1NAF', '9 (NAF Northern Africa+Sahara+Sahel)'],
+ [10, 'HTAPTier1SAF', '10 (SAF Sub Saharan/sub Sahel Africa)'],
+ [11, 'HTAPTier1MDE', '11 (MDE Middle East: S. Arabia, Oman, etc, Iran, Iraq)'],
+ [12, 'HTAPTier1MCA', '12 (MCA Mexico, Central America, Caribbean, Guyanas, Venezuela, Columbia)'],
+ [13, 'HTAPTier1SAM', '13 (SAM S. America)'],
+ [14, 'HTAPTier1RBU', '14 (RBU Russia, Belarussia, Ukraine)'],
+ [15, 'HTAPTier1CAS', '15 (CAS Central Asia)'],
+ [16, 'HTAPTier1NPO', '16 (NPO Arctic Circle (North of 66 N) + Greenland)'],
+ [17, 'HTAPTier1SPO', '17 (SPO Antarctic)']]
+#### Dl_Vocabulary ####
+ * DL_vocabulary: [
+ [-1, 'Undefined', '-1 (undefined)'],
+ [0, 'Water', '0 (Water)'],
+ [1, 'EGNeedleleaf', '1 (Evergreen Needleleaf forest)'],
+ [2, 'EGBroadleaf', '2 (Evergreen Broadleaf forest)'],
+ [3, 'DCNeedleleaf', '3 (Deciduous Needleleaf forest)'],
+ [4, 'DCBroadleaf', '4 (Deciduous Broadleaf forest)'],
+ [5, 'MixedForest', '5 (Mixed forest)'],
+ [6, 'ClosedShrublands', '6 (Closed shrublands)'],
+ [7, 'OpenShrublands', '7 (Open shrublands)'],
+ [8, 'WoodySavannas', '8 (Woody savannas)'],
+ [9, 'Savannas', '9 (Savannas)'],
+ [10, 'Grasslands', '10 (Grasslands)'],
+ [11, 'Wetlands', '11 (Permanent wetlands)'],
+ [12, 'Croplands', '12 (Croplands)'],
+ [13, 'Urban', '13 (Urban and built-up)'],
+ [14, 'Mosaic', '14 (Cropland/Natural vegetation mosaic)'],
+ [15, 'Snow', '15 (Snow and ice)'],
+ [16, 'Barren', '16 (Barren or sparsely vegetated)'],
+ [255, 'Fill', '255 (Fill Value/Unclassified)']]
+#### Rt_Vocabulary ####
+ * RT_vocabulary: [
+ [0, 'String', 'str'],
+ [1, 'Integer', 'int'],
+ [2, 'Float', 'float']]
+#### Df_Vocabulary ####
+ * DF_vocabulary: [
+ [0, 'OK', 'OK'],
+ [1, 'OKPreliminary', 'OK preliminary'],
+ [2, 'OKModified', 'OK modified'],
+ [3, 'OKPreliminaryModified', 'OK preliminary modified'],
+ [4, 'Inconsistent', 'inconsistent'],
+ [5, 'InconsistentPreliminary', 'inconsistent preliminary'],
+ [6, 'Doubtful', 'doubtful'],
+ [7, 'DoubtfulPreliminary', 'doubtful preliminary'],
+ [8, 'DoubtfulModified', 'doubtful modified'],
+ [9, 'DoubtfulPreliminaryModified', 'doubtful preliminary modified'],
+ [10, 'Wrong', 'wrong'],
+ [11, 'WrongPreliminary', 'wrong preliminary'],
+ [12, 'NotCheckedPreliminary', 'not checked preliminary'],
+ [13, 'Changed', 'changed'],
+ [14, 'Estimated', 'estimated'],
+ [15, 'MissingValue', 'missing value']]
+
+
## REST API
+### /controlled_vocabulary
+
+#### GET
+##### Summary:
+
+Info
+
+##### Responses
+
+| Code | Description |
+| ---- | ----------- |
+| 200 | Successful Response |
+
### /variables/
#### GET
diff --git a/docs/toardb_v2.pdf b/docs/toardb_v2.pdf
index 9eb95458ad937b9a2f91f83d7e17895c2fe7a523..cc8f817211c638a398c2032ed1945abe28439d49 100644
Binary files a/docs/toardb_v2.pdf and b/docs/toardb_v2.pdf differ
diff --git a/toardb/test_toardb.py b/toardb/test_toardb.py
new file mode 100644
index 0000000000000000000000000000000000000000..48b9f3b4838a1cf36f2556c613c40cf07475c360
--- /dev/null
+++ b/toardb/test_toardb.py
@@ -0,0 +1,151 @@
+import pytest
+import json
+# Required imports 'create_test_database'
+from toardb.test_base import (
+ client,
+ get_test_db,
+ create_test_database,
+ url,
+ get_test_engine,
+ test_db_session as db,
+)
+
+class TestApps:
+ def setup(self):
+ self.application_url = "/controlled_vocabulary"
+
+ def test_get_controlled_vocabulary(self, client, db):
+ response = client.get("/controlled_vocabulary")
+ expected_status_code = 200
+ assert response.status_code == expected_status_code
+ expected_resp = {"RC_vocabulary":[[0,"PointOfContact","point of contact"],
+ [1,"PrincipalInvestigator","principal investigator"],
+ [2,"Originator","originator"],
+ [3,"Contributor","contributor"],
+ [4,"Collaborator","collaborator"],
+ [5,"ResourceProvider","resource provider"]],
+ "RS_vocabulary":[[0,"active","active"],
+ [1,"inactive","inactive"],
+ [2,"unknown","unknown"]],
+ "OK_vocabulary":[[1,"Government","government"],
+ [2,"Research","research"],
+ [3,"International","international"],
+ [4,"NonProfit","non-profit"],
+ [5,"Commercial","commercial"],
+ [6,"Individual","individual"],
+ [7,"Other","other"]],
+ "DA_vocabulary":[[0,"ByAttribution","by attribution"],
+ [1,"ShareAlike","share alike"],
+ [2,"Restricted","restricted"]],
+ "SF_vocabulary":[[0,"Hourly","hourly"],
+ [1,"ThreeHourly","3-hourly"],
+ [2,"SixHourly","6-hourly"],
+ [3,"Daily","daily"],
+ [4,"Weekly","weekly"],
+ [5,"Monthly","monthly"],
+ [6,"Yearly","yearly"],
+ [7,"Irregular","irregular data samples of constant length"],
+ [8,"Irregular2","irregular data samples of varying length"]],
+ "AT_vocabulary":[[0,"Mean","mean"],
+ [1,"Mean1Of2","mean of two values"],
+ [2,"Mean1OfWeek","weekly mean"],
+ [3,"Mean4Samples","mean out of 4 samples"],
+ [4,"MeanMonth","monthly mean"],
+ [5,"None","none"],
+ [6,"Unknown","unknown"]],
+ "DS_vocabulary":[[0,"Model","model"],
+ [1,"Measurement","measurement"]],
+ "MM_vocabulary":[[0,"UVAbsorption","UV absorption"],
+ [1,"UnknownInstrument","unknown instrument"]],
+ "CZ_vocabulary":[[-1,"Undefined","undefined"],
+ [0,"Unclassified","unclassified"],
+ [1,"WarmTemperateMoist","warm temperate moist"],
+ [2,"WarmTemperateDry","warm temperate dry"],
+ [3,"CoolTemperateMoist","cool temperate moist"],
+ [4,"CoolTemperateDry","cool temperate dry"],
+ [5,"PolarMoist","polar moist"],
+ [6,"PolarDry","polar dry"],
+ [7,"BorealMoist","boreal moist"],
+ [8,"BorealDry","boreal dry"],
+ [9,"TropicalMontane","tropical montane"],
+ [10,"TropicalWet","tropical wet"],
+ [11,"TropicalMoist","tropical moist"],
+ [12,"TropicalDry","tropical dry"]],
+ "CV_vocabulary":[[0,"NotChecked","not checked"],
+ [1,"Verified","verified"],
+ [2,"Plausible","plausible"],
+ [3,"Doubtful","doubtful"],
+ [4,"Unverifyable","not verifyable"]],
+ "ST_vocabulary":[[0,"Unknown","unknown"],
+ [1,"Background","background"],
+ [2,"Traffic","traffic"],
+ [3,"Industrial","industrial"],
+ [4,"Other","other"]],
+ "TA_vocabulary":[[0,"Unknown","unknown"],
+ [1,"Urban","urban"],
+ [2,"Suburban","suburban"],
+ [3,"Rural","rural"],
+ [4,"Remote","remote"]],
+ "TC_vocabulary":[[-1,"Unknown","unknown"],
+ [0,"Unclassified","unclassified"],
+ [1,"RuralLowElevation","rural low elevation"],
+ [2,"RuralHighElevation","rural high elevation"],
+ [3,"Urban","urban"]],
+ "TR_vocabulary":[[-1,"HTAPTier1Undefined","-1 (undefined)"],
+ [1,"HTAPTier1World","1 (World)"],
+ [2,"HTAPTier1OCN","2 (OCN Non-arctic/Antarctic Ocean)"],
+ [3,"HTAPTier1NAM","3 (NAM US+Canada (upto 66 N; polar circle))"],
+ [4,"HTAPTier1EUR","4 (EUR Western + Eastern EU+Turkey (upto 66 N polar circle))"],
+ [5,"HTAPTier1SAS","5 (SAS South Asia: India, Nepal, Pakistan, Afghanistan, Bangadesh, Sri Lanka)"],
+ [6,"HTAPTier1EAS","6 (EAS East Asia: China, Korea, Japan)"],
+ [7,"HTAPTier1SEA","7 (SEA South East Asia)"],
+ [8,"HTAPTier1PAN","8 (PAN Pacific, Australia+ New Zealand)"],
+ [9,"HTAPTier1NAF","9 (NAF Northern Africa+Sahara+Sahel)"],
+ [10,"HTAPTier1SAF","10 (SAF Sub Saharan/sub Sahel Africa)"],
+ [11,"HTAPTier1MDE","11 (MDE Middle East: S. Arabia, Oman, etc, Iran, Iraq)"],
+ [12,"HTAPTier1MCA","12 (MCA Mexico, Central America, Caribbean, Guyanas, Venezuela, Columbia)"],
+ [13,"HTAPTier1SAM","13 (SAM S. America)"],
+ [14,"HTAPTier1RBU","14 (RBU Russia, Belarussia, Ukraine)"],
+ [15,"HTAPTier1CAS","15 (CAS Central Asia)"],
+ [16,"HTAPTier1NPO","16 (NPO Arctic Circle (North of 66 N) + Greenland)"],
+ [17,"HTAPTier1SPO","17 (SPO Antarctic)"]],
+ "DL_vocabulary":[[-1,"Undefined","-1 (undefined)"],
+ [0,"Water","0 (Water)"],
+ [1,"EGNeedleleaf","1 (Evergreen Needleleaf forest)"],
+ [2,"EGBroadleaf","2 (Evergreen Broadleaf forest)"],
+ [3,"DCNeedleleaf","3 (Deciduous Needleleaf forest)"],
+ [4,"DCBroadleaf","4 (Deciduous Broadleaf forest)"],
+ [5,"MixedForest","5 (Mixed forest)"],
+ [6,"ClosedShrublands","6 (Closed shrublands)"],
+ [7,"OpenShrublands","7 (Open shrublands)"],
+ [8,"WoodySavannas","8 (Woody savannas)"],
+ [9,"Savannas","9 (Savannas)"],
+ [10,"Grasslands","10 (Grasslands)"],
+ [11,"Wetlands","11 (Permanent wetlands)"],
+ [12,"Croplands","12 (Croplands)"],
+ [13,"Urban","13 (Urban and built-up)"],
+ [14,"Mosaic","14 (Cropland/Natural vegetation mosaic)"],
+ [15,"Snow","15 (Snow and ice)"],
+ [16,"Barren","16 (Barren or sparsely vegetated)"],
+ [255,"Fill","255 (Fill Value/Unclassified)"]],
+ "RT_vocabulary":[[0,"String","str"],
+ [1,"Integer","int"],
+ [2,"Float","float"]],
+ "DF_vocabulary":[[0,"OK","OK"],
+ [1,"OKPreliminary","OK preliminary"],
+ [2,"OKModified","OK modified"],
+ [3,"OKPreliminaryModified","OK preliminary modified"],
+ [4,"Inconsistent","inconsistent"],
+ [5,"InconsistentPreliminary","inconsistent preliminary"],
+ [6,"Doubtful","doubtful"],
+ [7,"DoubtfulPreliminary","doubtful preliminary"],
+ [8,"DoubtfulModified","doubtful modified"],
+ [9,"DoubtfulPreliminaryModified","doubtful preliminary modified"],
+ [10,"Wrong","wrong"],
+ [11,"WrongPreliminary","wrong preliminary"],
+ [12,"NotCheckedPreliminary","not checked preliminary"],
+ [13,"Changed","changed"],
+ [14,"Estimated","estimated"],
+ [15,"MissingValue","missing value"]]}
+ assert response.json() == expected_resp
+
diff --git a/toardb/toardb.py b/toardb/toardb.py
index 8dbeed5feca994c2ee2652ce168a809e728c004c..e2f53b23713e316c1547c8c9f5d6c2a34d417d2f 100644
--- a/toardb/toardb.py
+++ b/toardb/toardb.py
@@ -15,10 +15,32 @@ from toardb.timeseries import timeseries
from toardb.data import data
from collections import namedtuple
-
+from pydantic import BaseSettings
app = FastAPI()
+@app.get("/controlled_vocabulary")
+async def info():
+ return {
+ "RC_vocabulary": settings.RC_vocab,
+ "RS_vocabulary": settings.RS_vocab,
+ "OK_vocabulary": settings.OK_vocab,
+ "DA_vocabulary": settings.DA_vocab,
+ "SF_vocabulary": settings.SF_vocab,
+ "AT_vocabulary": settings.AT_vocab,
+ "DS_vocabulary": settings.DS_vocab,
+ "MM_vocabulary": settings.MM_vocab,
+ "CZ_vocabulary": settings.CZ_vocab,
+ "CV_vocabulary": settings.CV_vocab,
+ "ST_vocabulary": settings.ST_vocab,
+ "TA_vocabulary": settings.TA_vocab,
+ "TC_vocabulary": settings.TC_vocab,
+ "TR_vocabulary": settings.TR_vocab,
+ "DL_vocabulary": settings.DL_vocab,
+ "RT_vocabulary": settings.RT_vocab,
+ "DF_vocabulary": settings.DF_vocab,
+ }
+
# Dependency
def get_db():
try:
@@ -73,3 +95,48 @@ async def startup_event():
RT_vocabulary = __get_enum_dict(fake_cur, "rt_vocabulary")
DF_vocabulary = __get_enum_dict(fake_cur, "df_vocabulary")
+
+Enumdict=namedtuple("Dict",["value","string","display_str"])
+fake_conn = engine.raw_connection()
+fake_cur = fake_conn.cursor()
+RC_vocabulary = __get_enum_dict(fake_cur, "rc_vocabulary")
+RS_vocabulary = __get_enum_dict(fake_cur, "rs_vocabulary")
+OK_vocabulary = __get_enum_dict(fake_cur, "ok_vocabulary")
+DA_vocabulary = __get_enum_dict(fake_cur, "da_vocabulary")
+SF_vocabulary = __get_enum_dict(fake_cur, "sf_vocabulary")
+AT_vocabulary = __get_enum_dict(fake_cur, "at_vocabulary")
+DS_vocabulary = __get_enum_dict(fake_cur, "ds_vocabulary")
+MM_vocabulary = __get_enum_dict(fake_cur, "mm_vocabulary")
+CZ_vocabulary = __get_enum_dict(fake_cur, "cz_vocabulary")
+CV_vocabulary = __get_enum_dict(fake_cur, "cv_vocabulary")
+ST_vocabulary = __get_enum_dict(fake_cur, "st_vocabulary")
+TA_vocabulary = __get_enum_dict(fake_cur, "ta_vocabulary")
+TC_vocabulary = __get_enum_dict(fake_cur, "tc_vocabulary")
+TR_vocabulary = __get_enum_dict(fake_cur, "tr_vocabulary")
+DL_vocabulary = __get_enum_dict(fake_cur, "dl_vocabulary")
+RT_vocabulary = __get_enum_dict(fake_cur, "rt_vocabulary")
+DF_vocabulary = __get_enum_dict(fake_cur, "df_vocabulary")
+
+
+class Settings(BaseSettings):
+ Enumdict=namedtuple("Dict",["value","string","display_str"])
+ RC_vocab = RC_vocabulary
+ RS_vocab = RS_vocabulary
+ OK_vocab = OK_vocabulary
+ DA_vocab = DA_vocabulary
+ SF_vocab = SF_vocabulary
+ AT_vocab = AT_vocabulary
+ DS_vocab = DS_vocabulary
+ MM_vocab = MM_vocabulary
+ CZ_vocab = CZ_vocabulary
+ CV_vocab = CV_vocabulary
+ ST_vocab = ST_vocabulary
+ TA_vocab = TA_vocabulary
+ TC_vocab = TC_vocabulary
+ TR_vocab = TR_vocabulary
+ DL_vocab = DL_vocabulary
+ RT_vocab = RT_vocabulary
+ DF_vocab = DF_vocabulary
+
+settings = Settings()
+