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added is_benchmark to logbook #49

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Nov 21, 2024
Merged

added is_benchmark to logbook #49

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10 changes: 5 additions & 5 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ To download your logbook entries for a given board:
This outputs a CSV file with the following fields:

```json
["board", "angle", "climb_name", "date", "logged_grade", "displayed_grade", "difficulty", "tries", "is_mirror", "sessions_count", "tries_total", "is_repeat", "is_ascent", "comment"]
["board", "angle", "climb_name", "date", "logged_grade", "displayed_grade", "difficulty", "is_benchmark", "tries", "is_mirror", "sessions_count", "tries_total", "is_repeat", "is_ascent", "comment"]
```

For example, the command
Expand All @@ -41,10 +41,10 @@ For example, the command
would output a file named `tension.csv` with the following contents:

```
board,angle,climb_name,date,logged_grade,displayed_grade,difficulty,tries,is_mirror,sessions_count,tries_total,is_repeat,is_ascent,comment
tension,40,trash bag better,2024-06-17 16:21:23,V3,V3,16.0,3,False,1,3,False,True,
tension,40,Bumble,2024-06-17 16:28:23,V3,V3,16.0,1,True,1,1,False,True,
tension,40,sender2,2024-06-17 16:38:06,V5,V5,20.0,2,False,1,2,False,True,
board,angle,climb_name,date,logged_grade,displayed_grade,difficulty,is_benchmark,tries,is_mirror,sessions_count,tries_total,is_repeat,is_ascent,comment
tension,40,trash bag better,2024-06-17 16:21:23,V3,V3,16.0,False,3,False,1,3,False,True,
tension,40,Bumble,2024-06-17 16:28:23,V3,V3,16.0,True,1,True,1,1,False,True,
tension,40,sender2,2024-06-17 16:38:06,V5,V5,20.0,False,2,False,1,2,False,True,
...
```
When no local database is provided, displayed_grade and difficulty remain empty.
Expand Down
2 changes: 1 addition & 1 deletion src/boardlib/__main__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
import boardlib.db.aurora


LOGBOOK_FIELDS = ("board", "angle", "climb_name", "date", "logged_grade", "displayed_grade", "difficulty", "tries", "is_mirror", "sessions_count", "tries_total", "is_repeat", "is_ascent", "comment")
LOGBOOK_FIELDS = ("board", "angle", "climb_name", "date", "logged_grade", "displayed_grade", "difficulty", "is_benchmark", "tries", "is_mirror", "sessions_count", "tries_total", "is_repeat", "is_ascent", "comment")


def logbook_entries(board, username, password, grade_type="font", database=None):
Expand Down
25 changes: 22 additions & 3 deletions src/boardlib/api/aurora.py
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Expand Up @@ -434,6 +434,17 @@ def get_difficulty_from_db(database, climb_uuid, angle):
return row[0]
return None

def get_benchmark_from_db(database, climb_uuid, angle):
conn = sqlite3.connect(database)
cursor = conn.cursor()
cursor.execute(
"SELECT benchmark_difficulty FROM climb_stats WHERE climb_uuid = ? AND angle = ?",
(climb_uuid, angle)
)
row = cursor.fetchone()
conn.close()
return row[0] is not None if row else False


def convert_difficulty_to_grade(difficulty, grades_dict, grade_type):
grade_info = grades_dict.get(round(difficulty) if difficulty is not None else None, {})
Expand All @@ -449,10 +460,12 @@ def process_raw_ascent_entries(raw_ascents_entries, board, db_path, grades_dict,
climb_name = get_climb_name_from_db(db_path, raw_entry["climb_uuid"])
difficulty = get_difficulty_from_db(db_path, raw_entry["climb_uuid"], raw_entry["angle"])
displayed_grade = convert_difficulty_to_grade(difficulty, grades_dict, grade_type)
is_benchmark = get_benchmark_from_db(db_path, raw_entry["climb_uuid"], raw_entry["angle"])
else:
climb_name = get_climb_name(board, raw_entry["climb_uuid"])
difficulty = None
displayed_grade = None
is_benchmark = None

logged_grade = convert_difficulty_to_grade(raw_entry["difficulty"], grades_dict, grade_type)

Expand All @@ -465,6 +478,7 @@ def process_raw_ascent_entries(raw_ascents_entries, board, db_path, grades_dict,
"logged_grade": logged_grade,
"difficulty": difficulty,
"displayed_grade": displayed_grade,
"is_benchmark": is_benchmark,
"tries": raw_entry["attempt_id"] if raw_entry["attempt_id"] else raw_entry["bid_count"],
"is_mirror": raw_entry["is_mirror"],
"comment": raw_entry["comment"]
Expand Down Expand Up @@ -515,6 +529,7 @@ def combine_ascents_and_bids(ascents_df, bids_summary, db_path, grades_dict, gra
'logged_grade': ascent_row['logged_grade'],
'displayed_grade': ascent_row.get('displayed_grade', None),
'difficulty': ascent_row['difficulty'],
'is_benchmark': ascent_row.get('is_benchmark', None),
'tries': total_tries,
'is_mirror': ascent_row['is_mirror'],
'is_ascent': True,
Expand All @@ -532,6 +547,7 @@ def combine_ascents_and_bids(ascents_df, bids_summary, db_path, grades_dict, gra
'logged_grade': ascent_row['logged_grade'],
'displayed_grade': ascent_row.get('displayed_grade', None),
'difficulty': ascent_row['difficulty'],
'is_benchmark': ascent_row['is_benchmark'],
'tries': ascent_row['tries'],
'is_mirror': ascent_row['is_mirror'],
'is_ascent': True,
Expand All @@ -544,9 +560,11 @@ def combine_ascents_and_bids(ascents_df, bids_summary, db_path, grades_dict, gra
if db_path:
difficulty = get_difficulty_from_db(db_path, bid_row["climb_uuid"], bid_row["angle"])
displayed_grade = convert_difficulty_to_grade(difficulty, grades_dict, grade_type)
is_benchmark = get_benchmark_from_db(db_path, bid_row["climb_uuid"], bid_row["angle"])
else:
displayed_grade = None
difficulty = None
is_benchmark = None

final_logbook.append({
'climb_angle_uuid': climb_angle_uuid,
Expand All @@ -558,6 +576,7 @@ def combine_ascents_and_bids(ascents_df, bids_summary, db_path, grades_dict, gra
'logged_grade': None,
'displayed_grade': displayed_grade,
'difficulty': difficulty,
'is_benchmark': is_benchmark,
'tries': bid_row['tries'],
'is_mirror': bid_row['is_mirror'],
'is_ascent': False,
Expand Down Expand Up @@ -586,7 +605,7 @@ def logbook_entries(board, user_id, token, grade_type="font", db_path=None):
raw_ascents_entries = get_logbook(board, token, user_id)

if not bids_entries and not raw_ascents_entries:
return pd.DataFrame(columns=['climb_uuid', 'board', 'angle', 'climb_name', 'date', 'logged_grade', 'displayed_grade', 'difficulty', 'tries', 'is_mirror', 'is_ascent', 'comment'])
return pd.DataFrame(columns=['climb_uuid', 'board', 'angle', 'climb_name', 'date', 'logged_grade', 'displayed_grade', 'difficulty', 'is_benchmark', 'tries', 'is_mirror', 'is_ascent', 'comment'])

if bids_entries:
bids_df = pd.DataFrame(bids_entries)
Expand All @@ -601,11 +620,11 @@ def logbook_entries(board, user_id, token, grade_type="font", db_path=None):
ascents_entries = process_raw_ascent_entries(raw_ascents_entries, board, db_path, grades_dict, grade_type)
ascents_df = pd.DataFrame(ascents_entries)
else:
ascents_df = pd.DataFrame(columns=['board', 'angle', 'climb_uuid', 'name', 'date', 'logged_grade', 'difficulty', 'displayed_grade', 'tries', 'is_mirror', 'comment'])
ascents_df = pd.DataFrame(columns=['board', 'angle', 'climb_uuid', 'name', 'date', 'logged_grade', 'difficulty', 'displayed_grade', 'is_benchmark', 'tries', 'is_mirror', 'comment'])

final_logbook = combine_ascents_and_bids(ascents_df, bids_summary, db_path, grades_dict, grade_type)

full_logbook_df = pd.DataFrame(final_logbook, columns=['climb_angle_uuid', 'board', 'angle', 'climb_name', 'date', 'logged_grade', 'displayed_grade', 'difficulty', 'tries', 'is_mirror', 'is_ascent', 'comment'])
full_logbook_df = pd.DataFrame(final_logbook, columns=['climb_angle_uuid', 'board', 'angle', 'climb_name', 'date', 'logged_grade', 'displayed_grade', 'is_benchmark', 'difficulty', 'tries', 'is_mirror', 'is_ascent', 'comment'])
full_logbook_df['date'] = pd.to_datetime(full_logbook_df['date'])

full_logbook_df = full_logbook_df.groupby(['climb_name', 'is_mirror', 'angle']).apply(calculate_sessions_count).reset_index(drop=True)
Expand Down