Improvements to summaries

README.md

@@ -58,7 +58,7 @@ The process is designed to be easily parallelized and interruptible, meaning tha
 
 ### 2. **Binning**
 
-To make the mapping to Dandisets more efficient, the reduced logs are binned by their object keys (asset blob IDs) for fast lookup.
+To make the mapping to Dandisets more efficient, the reduced logs are binned by their object keys (asset blob IDs) for fast lookup. Zarr assets specifically group by the parent blob ID, *e.g.*, a request for `zarr/abcdefg/group1/dataset1/0` will be binned by `zarr/abcdefg`.
 
 This step reduces the total file sizes from step (1) even further by reducing repeated object keys, though it does create a large number of small files.
 
@@ -126,7 +126,6 @@ The `--file_processing_limit < integer >` flag can be used to limit the number o
 bin_all_reduced_s3_logs_by_object_key \
   --reduced_s3_logs_folder_path /mnt/backup/dandi/dandiarchive-logs-reduced \
   --binned_s3_logs_folder_path /mnt/backup/dandi/dandiarchive-logs-binned \
-  --file_limit 20
 ```
 
 In the summer of 2024, this process took less than 5 hours to bin all 170 GB of reduced logs into the 80 GB of data per object key.

pyproject.toml

@@ -10,7 +10,7 @@ packages = ["src/dandi_s3_log_parser"]
 
 [project]
 name = "dandi_s3_log_parser"
-version="0.4.0"
+version="0.4.1"
 authors = [
   { name="Cody Baker", email="[email protected]" },
 ]

src/dandi_s3_log_parser/_bin_all_reduced_s3_logs_by_object_key.py

@@ -57,11 +57,12 @@ def bin_all_reduced_s3_logs_by_object_key(
     for reduced_s3_log_file in tqdm.tqdm(
         iterable=reduced_s3_log_files,
         total=len(reduced_s3_log_files),
-        desc="Binning reduced logs...",
+        desc="Binning reduced logs",
         position=0,
         leave=True,
         mininterval=3.0,
         smoothing=0,
+        unit="file",
     ):
         if reduced_s3_log_file.stat().st_size == 0:
             with open(file=started_tracking_file_path, mode="a") as io:
@@ -93,11 +94,12 @@ def bin_all_reduced_s3_logs_by_object_key(
         for object_key, data in tqdm.tqdm(
             iterable=object_keys_to_data.items(),
             total=len(object_keys_to_data),
-            desc="Writing binned logs...",
+            desc=f"Binning {reduced_s3_log_file}",
             position=1,
             leave=False,
             mininterval=3.0,
             smoothing=0,
+            unit="asset",
         ):
             object_key_as_path = pathlib.Path(object_key)
             binned_s3_log_file_path = (

src/dandi_s3_log_parser/_dandi_s3_log_file_reducer.py

@@ -85,15 +85,15 @@ def reduce_all_dandi_raw_s3_logs(
     fields_to_reduce = ["object_key", "timestamp", "bytes_sent", "ip_address"]
     object_key_parents_to_reduce = ["blobs", "zarr"]
     line_buffer_tqdm_kwargs = dict(position=1, leave=False)
-    # TODO: add better reporting units to all TQDMs (lines / s, files / s, etc.)
     if maximum_number_of_workers == 1:
         for relative_s3_log_file_path in tqdm.tqdm(
             iterable=relative_s3_log_file_paths_to_reduce,
             total=len(relative_s3_log_file_paths_to_reduce),
-            desc="Parsing log files...",
+            desc="Parsing log files",
             position=0,
             leave=True,
             smoothing=0,  # Use true historical average, not moving average since shuffling makes it more uniform
+            unit="file",
         ):
             raw_s3_log_file_path = raw_s3_logs_folder_path / relative_s3_log_file_path
             reduced_s3_log_file_path = (
@@ -144,6 +144,7 @@ def reduce_all_dandi_raw_s3_logs(
                 leave=True,
                 mininterval=3.0,
                 smoothing=0,  # Use true historical average, not moving average since shuffling makes it more uniform
+                unit="file",
             )
             for future in progress_bar_iterable:
                 future.result()  # This is the call that finally triggers the deployment to the workers
@@ -177,7 +178,10 @@ def _multi_worker_reduce_dandi_raw_s3_log(
         object_key_parents_to_reduce = ["blobs", "zarr"]
         object_key_handler = _get_default_dandi_object_key_handler()
         line_buffer_tqdm_kwargs = dict(
-            position=worker_index + 1, leave=False, desc=f"Parsing line buffers on worker {worker_index + 1}..."
+            position=worker_index + 1,
+            leave=False,
+            desc=f"Parsing line buffers on worker {worker_index + 1}...",
+            unit="buffer",
         )
 
         reduce_raw_s3_log(

src/dandi_s3_log_parser/_ip_utils.py

@@ -44,28 +44,39 @@ def get_region_from_ip_address(
         raise ValueError(message)  # pragma: no cover
     ip_hash_salt = bytes.fromhex(os.environ["IP_HASH_SALT"])
 
-    # Probably a legitimate user, so fetch the geographic region
+    # Hash for anonymization within the cache
     ip_hash = hashlib.sha1(string=bytes(ip_address, "utf-8") + ip_hash_salt).hexdigest()
 
-    # Early return for speed
+    # Early return from the cache for faster performance
     lookup_result = ip_hash_to_region.get(ip_hash, None)
     if lookup_result is not None:
         return lookup_result
 
     # Determine if IP address belongs to GitHub, AWS, Google, or known VPNs
     # Azure not yet easily doable; keep an eye on
     # https://learn.microsoft.com/en-us/answers/questions/1410071/up-to-date-azure-public-api-to-get-azure-ip-ranges
-    # and others, maybe it will change in the future
+    # maybe it will change in the future
     if ip_hash_not_in_services.get(ip_hash, None) is None:
         for service_name in _KNOWN_SERVICES:
-            cidr_addresses = _get_cidr_address_ranges(service_name=service_name)
-
-            if any(
-                ipaddress.ip_address(address=ip_address) in ipaddress.ip_network(address=cidr_address)
-                for cidr_address in cidr_addresses
-            ):
-                ip_hash_to_region[ip_hash] = service_name
-                return service_name
+            cidr_addresses_and_subregions = _get_cidr_address_ranges_and_subregions(service_name=service_name)
+
+            matched_cidr_address_and_subregion = next(
+                (
+                    (cidr_address, subregion)
+                    for cidr_address, subregion in cidr_addresses_and_subregions
+                    if ipaddress.ip_address(address=ip_address) in ipaddress.ip_network(address=cidr_address)
+                ),
+                None,
+            )
+            if matched_cidr_address_and_subregion is not None:
+                region_service_string = service_name
+
+                subregion = matched_cidr_address_and_subregion[1]
+                if subregion is not None:
+                    region_service_string += f"/{subregion}"
+
+                ip_hash_to_region[ip_hash] = region_service_string
+                return region_service_string
     ip_hash_not_in_services[ip_hash] = True
 
     # Log errors in IP fetching
@@ -105,49 +116,75 @@ def get_region_from_ip_address(
 
 
 @functools.lru_cache
-def _get_cidr_address_ranges(*, service_name: str) -> list[str]:
+def _get_cidr_address_ranges_and_subregions(*, service_name: str) -> list[tuple[str, str | None]]:
+    cidr_request = _request_cidr_range(service_name=service_name)
     match service_name:
         case "GitHub":
-            github_cidr_request = requests.get(url="https://api.github.com/meta").json()
             skip_keys = ["domains", "ssh_key_fingerprints", "verifiable_password_authentication", "ssh_keys"]
-            keys = set(github_cidr_request.keys()) - set(skip_keys)
-            github_cidr_addresses = [
-                cidr_address
+            keys = set(cidr_request.keys()) - set(skip_keys)
+            github_cidr_addresses_and_subregions = [
+                (cidr_address, None)
                 for key in keys
-                for cidr_address in github_cidr_request[key]
+                for cidr_address in cidr_request[key]
                 if "::" not in cidr_address
                 # Skip IPv6
             ]
 
-            return github_cidr_addresses
+            return github_cidr_addresses_and_subregions
         # Note: these endpoints also return the 'locations' of the specific subnet, such as 'us-east-2'
         case "AWS":
-            aws_cidr_request = requests.get(url="https://ip-ranges.amazonaws.com/ip-ranges.json").json()
-            aws_cidr_addresses = [prefix["ip_prefix"] for prefix in aws_cidr_request["prefixes"]]
+            aws_cidr_addresses_and_subregions = [
+                (prefix["ip_prefix"], prefix.get("region", None)) for prefix in cidr_request["prefixes"]
+            ]
 
-            return aws_cidr_addresses
+            return aws_cidr_addresses_and_subregions
         case "GCP":
-            gcp_cidr_request = requests.get(url="https://www.gstatic.com/ipranges/cloud.json").json()
-            gcp_cidr_addresses = [
-                prefix["ipv4Prefix"]
-                for prefix in gcp_cidr_request["prefixes"]
+            gcp_cidr_addresses_and_subregions = [
+                (prefix["ipv4Prefix"], prefix.get("scope", None))
+                for prefix in cidr_request["prefixes"]
                 if "ipv4Prefix" in prefix  # Not handling IPv6 yet
             ]
 
-            return gcp_cidr_addresses
+            return gcp_cidr_addresses_and_subregions
         case "Azure":
             raise NotImplementedError("Azure CIDR address fetching is not yet implemented!")  # pragma: no cover
+        case "VPN":
+            vpn_cidr_addresses_and_subregions = [(cidr_address, None) for cidr_address in cidr_request]
+
+            return vpn_cidr_addresses_and_subregions
+        case _:
+            raise ValueError(f"Service name '{service_name}' is not supported!")  # pragma: no cover
+
+
+@functools.lru_cache
+def _request_cidr_range(service_name: str) -> dict:
+    """Cache (in-memory) the requests to external services."""
+    match service_name:
+        case "GitHub":
+            github_cidr_request = requests.get(url="https://api.github.com/meta").json()
+
+            return github_cidr_request
+        case "AWS":
+            aws_cidr_request = requests.get(url="https://ip-ranges.amazonaws.com/ip-ranges.json").json()
+
+            return aws_cidr_request
+        case "GCP":
+            gcp_cidr_request = requests.get(url="https://www.gstatic.com/ipranges/cloud.json").json()
+
+            return gcp_cidr_request
+        case "Azure":
+            raise NotImplementedError("Azure CIDR address fetching is not yet implemented!")
         case "VPN":
             # Very nice public and maintained listing! Hope this stays stable.
-            vpn_cidr_addresses = (
+            vpn_cidr_request = (
                 requests.get(
                     url="https://raw.githubusercontent.com/josephrocca/is-vpn/main/vpn-or-datacenter-ipv4-ranges.txt"
                 )
                 .content.decode("utf-8")
                 .splitlines()
             )
 
-            return vpn_cidr_addresses
+            return vpn_cidr_request
         case _:
             raise ValueError(f"Service name '{service_name}' is not supported!")  # pragma: no cover
 
@@ -157,16 +194,16 @@ def _load_ip_hash_cache(*, name: Literal["region", "services"]) -> dict[str, str
     match name:
         case "region":
             if not _IP_HASH_TO_REGION_FILE_PATH.exists():
-                return {}  # pragma: no cover
+                return dict()  # pragma: no cover
 
             with open(file=_IP_HASH_TO_REGION_FILE_PATH) as stream:
-                return yaml.load(stream=stream, Loader=yaml.SafeLoader)
+                return yaml.load(stream=stream, Loader=yaml.SafeLoader) or dict()
         case "services":
             if not _IP_HASH_NOT_IN_SERVICES_FILE_PATH.exists():
-                return {}  # pragma: no cover
+                return dict()  # pragma: no cover
 
             with open(file=_IP_HASH_NOT_IN_SERVICES_FILE_PATH) as stream:
-                return yaml.load(stream=stream, Loader=yaml.SafeLoader)
+                return yaml.load(stream=stream, Loader=yaml.SafeLoader) or dict()
         case _:
             raise ValueError(f"Name '{name}' is not recognized!")  # pragma: no cover