move to a class based thingy, make schema name specific

This commit is contained in:
gowthaman.b 2023-06-19 17:31:40 +05:30
parent 184ee74cda
commit 6082809715

295
main.py
View File

@ -26,14 +26,16 @@ class DBConn:
self.con = None
self.counter = 0
self.ts = ''
self.reinit_db()
self.table_col_map = {}
self.child_tables = {}
self.init_db()
def reinit_db(self):
def init_db(self):
self.counter += 1
self.ts = time.strftime('%Y%m%d_%H%M%S', time.localtime())
self.con = sqlite3.connect(args.output / f"data-{args.name}-{self.ts}-{self.counter}.db")
self.cur = self.con.cursor()
self.make_tables()
def make_table(self, tbl_name, cols):
syspk = "syspk integer primary key autoincrement"
@ -86,151 +88,152 @@ class DBConn:
clients = pd.read_sql(f"SELECT * FROM \"{tbl}\"", self.con)
clients.to_csv(args.output / f"{prefix}{tbl}.csv", index=False, sep=args.delimiter)
def extract_child(self, items_list, current_level, prev_step, existing, step):
attributes = existing.get("attributes", [args.join_column])
flat_attributes = existing.get("flat_attributes", [])
children = existing.get("children", {})
for child_idx in range(len(items_list)):
child = items_list[child_idx]
for (subKey, subValue) in child.items():
is_dict = isinstance(subValue, dict)
is_list = isinstance(subValue, list)
if is_dict:
if subKey not in flat_attributes:
flat_attributes.append(subKey)
for (sub2Key, sub2Value) in subValue.items():
composite_key = f"{current_level}_{sub2Key}"
if composite_key not in attributes:
attributes.append(composite_key)
if is_list:
if subKey not in children.keys():
existing_next_step = children.get(subKey, {})
children[subKey] = self.extract_child(subValue, subKey,
f"{prev_step}{current_level}_",
existing_next_step, step + 1)
else:
child_header = f"{current_level}_{subKey}"
if child_header not in attributes:
attributes.append(child_header)
self.child_tables[f"{prev_step}{current_level}"] = attributes
return {"flat_attributes": flat_attributes, "children": children, "attributes": attributes}
def extract_child_value(self, item, k, ext, prev_step, join_col_value):
child_value = {args.join_column: join_col_value}
for child in item[k]:
for (subKey, subValue) in child.items():
is_ext = subKey in ext.get("children", {}).keys()
if is_ext:
self.extract_child_value(child, subKey, ext["children"][subKey],
f"{prev_step}{k}_",
join_col_value)
else:
child_header = f"{k}_{subKey}"
child_value[child_header] = subValue
k_ = f"{prev_step}{k}"
dbConn.write_to_database(k_, child_value)
def make_tables(self):
for (mhKey, mhVal) in self.child_tables.items():
self.make_table(mhKey, mhVal)
def parse_json(self):
children = {}
flat_attributes = []
attributes = []
input_path = args.input
input_files = [x.name for x in input_path.iterdir() if
not x.is_dir() and x.is_file() and x.name.endswith(".json")]
print(f"found input file(s) {', '.join(input_files)} in path {args.input}")
if len(input_files) == 0:
print("could not find any input files, we shall stop")
return
parsed = 0
top_level = args.name
# first pass, collect all headers
print(f"parsing {input_files[0]} for metadata")
for topLevelItem in ijson.items(open(input_path / input_files[0]), "item"):
if parsed == args.metadata:
print(f"parsed {parsed} records for metadata")
break
for (key, value) in topLevelItem.items():
value_is_dict = isinstance(value, dict)
value_is_list = isinstance(value, list)
if value_is_dict:
if key not in flat_attributes:
flat_attributes.append(key)
for (subKey, subValue) in value.items():
child_attribute = f"{key}_{subKey}"
if child_attribute not in attributes:
attributes.append(child_attribute)
elif value_is_list:
existing = children.get(key, {})
children[key] = self.extract_child(value, key, f"{top_level}_", existing, 1)
else:
if key not in attributes:
attributes.append(key)
parsed += 1
open(f"schema-{args.name}.json", "w").write(
json.dumps({
"attributes": attributes,
"flat_attributes": flat_attributes,
"children": children
}, indent=2)
)
self.child_tables[top_level] = attributes
self.make_tables()
children_names = children.keys()
# second pass, make flat json from original-json, put to sqlite, use pandas to make csv
for inp_file in input_files:
if args.debug:
print(f"processing file {inp_file}")
for topLevelItem in ijson.items(open(input_path / inp_file), "item"):
keys = topLevelItem.keys()
flat_json = {}
for key in keys:
if key in flat_attributes:
for (subKey, subValue) in topLevelItem[key].items():
child_attribute = f"{key}_{subKey}"
flat_json[child_attribute] = subValue
elif key in children_names:
ext = children[key]
self.extract_child_value(topLevelItem, key, ext, f"{top_level}_",
topLevelItem[args.join_column])
else:
flat_json[key] = topLevelItem[key]
self.write_to_database(top_level, flat_json)
if not args.single:
self.con.commit()
self.make_csv_from_tables(prefix=f"{pathlib.Path(args.output / inp_file).stem}-")
self.init_db()
if args.single:
self.con.commit()
self.make_csv_from_tables()
dbConn = DBConn()
def extract_child(merge_headers, items_list, top_level, prev_step, existing, step):
headers = merge_headers.get(top_level, [args.join_column])
flat_keys = existing.get("flat_keys", [])
extract_keys = existing.get("extract_keys", {})
for child_idx in range(len(items_list)):
child = items_list[child_idx]
for (subKey, subValue) in child.items():
is_dict = isinstance(subValue, dict)
is_list = isinstance(subValue, list)
if is_dict:
if subKey not in flat_keys:
flat_keys.append(subKey)
for (sub2Key, sub2Value) in subValue.items():
composite_key = f"{top_level}_{sub2Key}"
if composite_key not in headers:
headers.append(composite_key)
if is_list:
if subKey not in extract_keys.keys():
existing_next_step = extract_keys.get(subKey, {})
extract_keys[subKey] = extract_child(merge_headers, subValue, subKey, f"{prev_step}{top_level}_",
existing_next_step, step + 1)
else:
child_header = f"{top_level}_{subKey}"
if child_header not in headers:
headers.append(child_header)
merge_headers[f"{prev_step}{top_level}"] = headers
return {"flat_keys": flat_keys, "extract_keys": extract_keys}
def extract_child_value(merge_headers, item, k, ext, prev_step, join_col_value):
child_value = {args.join_column: join_col_value}
for child in item[k]:
for (subKey, subValue) in child.items():
is_ext = subKey in ext.get("extract_keys", {}).keys()
if is_ext:
extract_child_value(merge_headers, child, subKey, ext["extract_keys"][subKey], f"{prev_step}{k}_",
join_col_value)
else:
child_header = f"{k}_{subKey}"
child_value[child_header] = subValue
k_ = f"{prev_step}{k}"
dbConn.write_to_database(k_, child_value)
def parse_json():
extract_keys = {}
flat_keys = []
headers = []
merge_headers = {}
input_path = args.input
input_files = [x.name for x in input_path.iterdir() if not x.is_dir() and x.is_file() and x.name.endswith(".json")]
print(f"found input file(s) {', '.join(input_files)} in path {args.input}")
if len(input_files) == 0:
print("could not find any input files, we shall stop")
return
parsed = 0
top_level = args.name
# first pass, collect all headers
print(f"parsing {input_files[0]} for metadata")
for topLevelItem in ijson.items(open(input_path / input_files[0]), "item"):
if parsed == args.metadata:
print(f"parsed {parsed} records for metadata")
break
for (key, value) in topLevelItem.items():
value_is_dict = isinstance(value, dict)
value_is_list = isinstance(value, list)
if value_is_dict:
if key not in flat_keys:
flat_keys.append(key)
for (subKey, subValue) in value.items():
composite_key = f"{key}_{subKey}"
if composite_key not in headers:
headers.append(composite_key)
elif value_is_list:
existing = extract_keys.get(key, {})
extract_keys[key] = extract_child(merge_headers, value, key, f"{top_level}_", existing, 1)
else:
if key not in headers:
headers.append(key)
parsed += 1
open("schema.json", "w").write(
json.dumps({
"flat_keys": flat_keys,
"extract_keys": extract_keys
}, indent=2)
)
dbConn.make_table(top_level, headers)
for (mhKey, mhVal) in merge_headers.items():
dbConn.make_table(mhKey, mhVal)
extract_keys_names = extract_keys.keys()
# second pass, make flat json from original-json, create csv ( we will use sqlite, as it is faster to write)
for inp_file in input_files:
for topLevelItem in ijson.items(open(input_path / inp_file), "item"):
keys = topLevelItem.keys()
flat_json = {}
for key in keys:
if key in flat_keys:
for (subKey, subValue) in topLevelItem[key].items():
composite_key = f"{key}_{subKey}"
flat_json[composite_key] = subValue
elif key in extract_keys_names:
ext = extract_keys[key]
extract_child_value(merge_headers, topLevelItem, key, ext, f"{top_level}_",
topLevelItem[args.join_column])
else:
flat_json[key] = topLevelItem[key]
dbConn.write_to_database(top_level, flat_json)
if not args.single:
dbConn.con.commit()
dbConn.make_csv_from_tables(prefix=f"{pathlib.Path(args.output / inp_file).stem}-")
dbConn.reinit_db()
dbConn.make_table(top_level, headers)
for (mhKey, mhVal) in merge_headers.items():
dbConn.make_table(mhKey, mhVal)
if args.single:
dbConn.con.commit()
dbConn.make_csv_from_tables()
if __name__ == '__main__':
parse_json()
dbConn.parse_json()