Spaces:
Running
Running
ZeroCommand
commited on
Commit
•
a2810d6
1
Parent(s):
97c6f8e
add closing files
Browse files- io_utils.py +12 -0
io_utils.py
CHANGED
@@ -28,6 +28,7 @@ def read_scanners(uid):
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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scanners = config.get("detectors", [])
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return scanners
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@@ -37,9 +38,12 @@ def write_scanners(scanners, uid):
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config = yaml.load(f, Loader=yaml.FullLoader)
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if config:
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config["detectors"] = scanners
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# save scanners to detectors in yaml
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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# read model_type from yaml file
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@@ -48,6 +52,7 @@ def read_inference_type(uid):
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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inference_type = config.get("inference_type", "")
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return inference_type
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@@ -62,9 +67,11 @@ def write_inference_type(use_inference, inference_token, uid):
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config["inference_type"] = "hf_pipeline"
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# FIXME: A quick and temp fix for missing token
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config["inference_token"] = ""
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# save inference_type to inference_type in yaml
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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@@ -75,6 +82,7 @@ def read_column_mapping(uid):
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config = yaml.load(f, Loader=yaml.FullLoader)
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if config:
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column_mapping = config.get("column_mapping", dict())
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return column_mapping
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@@ -82,6 +90,7 @@ def read_column_mapping(uid):
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def write_column_mapping(mapping, uid):
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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if config is None:
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return
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@@ -92,6 +101,8 @@ def write_column_mapping(mapping, uid):
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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# convert column mapping dataframe to json
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@@ -114,6 +125,7 @@ def get_logs_file(uid):
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def write_log_to_user_file(id, log):
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with open(f"./tmp/{id}_log", "a") as f:
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f.write(log)
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def save_job_to_pipe(id, job, lock):
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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scanners = config.get("detectors", [])
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f.close()
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return scanners
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config = yaml.load(f, Loader=yaml.FullLoader)
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if config:
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config["detectors"] = scanners
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f.close()
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# save scanners to detectors in yaml
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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f.close()
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+
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# read model_type from yaml file
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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inference_type = config.get("inference_type", "")
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f.close()
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return inference_type
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config["inference_type"] = "hf_pipeline"
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# FIXME: A quick and temp fix for missing token
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config["inference_token"] = ""
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f.close()
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# save inference_type to inference_type in yaml
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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f.close()
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config = yaml.load(f, Loader=yaml.FullLoader)
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if config:
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column_mapping = config.get("column_mapping", dict())
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f.close()
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return column_mapping
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def write_column_mapping(mapping, uid):
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with open(get_yaml_path(uid), "r") as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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f.close()
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if config is None:
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return
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with open(get_yaml_path(uid), "w") as f:
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yaml.dump(config, f, Dumper=Dumper)
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f.close()
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+
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# convert column mapping dataframe to json
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def write_log_to_user_file(id, log):
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with open(f"./tmp/{id}_log", "a") as f:
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f.write(log)
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f.close()
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def save_job_to_pipe(id, job, lock):
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