From 07e41a0b556ea08cfd44a16a5a6ea312c9efe45a Mon Sep 17 00:00:00 2001
From: Anderson Banihirwe <axbanihirwe@ualr.edu>
Date: Wed, 15 Nov 2023 21:56:53 -0800
Subject: [PATCH] add gold-standard

---
 offsets_db_data/gs.py | 106 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 106 insertions(+)
 create mode 100644 offsets_db_data/gs.py

diff --git a/offsets_db_data/gs.py b/offsets_db_data/gs.py
new file mode 100644
index 0000000..170cd48
--- /dev/null
+++ b/offsets_db_data/gs.py
@@ -0,0 +1,106 @@
+import ast
+
+import numpy as np  # noqa: F401
+import pandas as pd
+import pandas_flavor as pf
+
+from offsets_db_data.common import (
+    CREDIT_SCHEMA_UPATH,
+    PROJECT_SCHEMA_UPATH,
+    load_column_mapping,
+    load_inverted_protocol_mapping,
+    load_protocol_mapping,
+    load_registry_project_column_mapping,
+)
+from offsets_db_data.credits import *  # noqa: F403
+from offsets_db_data.models import credit_without_id_schema, project_schema
+from offsets_db_data.projects import *  # noqa: F403
+
+
+@pf.register_dataframe_method
+def determine_gs_transaction_type(df: pd.DataFrame, *, download_type: str) -> pd.DataFrame:
+    transaction_type_mapping = {'issuances': 'issuance', 'retirements': 'retirement'}
+    df['transaction_type'] = transaction_type_mapping[download_type]
+    return df
+
+
+@pf.register_dataframe_method
+def add_gs_project_id_from_credits(df: pd.DataFrame) -> pd.DataFrame:
+    df['project'] = df['project'].apply(lambda x: x if isinstance(x, dict) else ast.literal_eval(x))
+    df['project_id'] = 'GS' + df['project'].apply(lambda x: x.get('sustaincert_id', np.nan)).astype(
+        str
+    )
+    return df
+
+
+@pf.register_dataframe_method
+def process_gs_credits(
+    df: pd.DataFrame, *, download_type: str, registry_name: str = 'gold-standard'
+) -> pd.DataFrame:
+    df = df.copy()
+    column_mapping = load_column_mapping(
+        registry_name=registry_name, download_type=download_type, mapping_path=CREDIT_SCHEMA_UPATH
+    )
+
+    columns = {v: k for k, v in column_mapping.items()}
+    data = (
+        df.rename(columns=columns)
+        .set_registry(registry_name=registry_name)
+        .determine_gs_transaction_type(download_type=download_type)
+        .add_gs_project_id_from_credits()
+    )
+
+    if download_type == 'issuances':
+        data = data.aggregate_issuance_transactions()
+
+    data = data.convert_to_datetime(columns=['transaction_date']).validate(
+        schema=credit_without_id_schema
+    )
+
+    return data
+
+
+@pf.register_dataframe_method
+def add_gs_project_url(df: pd.DataFrame) -> pd.DataFrame:
+    df['project_url'] = 'https://registry.goldstandard.org/projects/details/' + df[
+        'project_id'
+    ].apply(str)
+    return df
+
+
+@pf.register_dataframe_method
+def add_gs_project_id(df: pd.DataFrame) -> pd.DataFrame:
+    df['project_id'] = df['project_id'].apply(lambda x: f'GS{str(x)}')
+    return df
+
+
+@pf.register_dataframe_method
+def process_gs_projects(
+    df: pd.DataFrame, *, credits: pd.DataFrame, registry_name: str = 'gold-standard'
+) -> pd.DataFrame:
+    df = df.copy()
+    credits = credits.copy()
+
+    registry_project_column_mapping = load_registry_project_column_mapping(
+        registry_name=registry_name, file_path=PROJECT_SCHEMA_UPATH
+    )
+    inverted_column_mapping = {value: key for key, value in registry_project_column_mapping.items()}
+    protocol_mapping = load_protocol_mapping()
+    inverted_protocol_mapping = load_inverted_protocol_mapping()
+    data = (
+        df.rename(columns=inverted_column_mapping)
+        .set_registry(registry_name=registry_name)
+        .add_gs_project_id()
+        .add_gs_project_url()
+        .harmonize_country_names()
+        .harmonize_status_codes()
+        .map_protocol(inverted_protocol_mapping=inverted_protocol_mapping)
+        .add_category(protocol_mapping=protocol_mapping)
+        .add_is_compliance_flag()
+        .add_retired_and_issued_totals(credits=credits)
+        .add_first_issuance_and_retirement_dates(credits=credits)
+        .add_missing_columns(columns=project_schema.columns.keys())
+        .convert_to_datetime(columns=['listed_at'])
+        .validate(schema=project_schema)
+    )
+    return data