Added predetermined headers feature

.vscode/extensions.json

@@ -1,5 +1,6 @@
 {
     "recommendations": [
-        "piotrpalarz.vscode-gitignore-generator"
+        "piotrpalarz.vscode-gitignore-generator",
+        "gruntfuggly.todo-tree"
     ]
 }

src/autobigs/engine/analysis/bigsdb.py

@@ -9,7 +9,7 @@ import shutil
 import tempfile
 from typing import Any, AsyncGenerator, AsyncIterable, Coroutine, Iterable, Mapping, Sequence, Set, Union
 
-from aiohttp import ClientSession, ClientTimeout
+from aiohttp import ClientOSError, ClientSession, ClientTimeout, ServerDisconnectedError
 
 from autobigs.engine.reading import read_fasta
 from autobigs.engine.structures.alignment import PairwiseAlignment
@@ -43,11 +43,12 @@ class BIGSdbMLSTProfiler(AbstractAsyncContextManager):
 
 class RemoteBIGSdbMLSTProfiler(BIGSdbMLSTProfiler):
 
-    def __init__(self, database_api: str, database_name: str, scheme_id: int):
+    def __init__(self, database_api: str, database_name: str, scheme_id: int, retry_requests: int = 5):
+        self._retry_limit = retry_requests
         self._database_name = database_name
         self._scheme_id = scheme_id
         self._base_url = f"{database_api}/db/{self._database_name}/schemes/{self._scheme_id}/"
-        self._http_client = ClientSession(self._base_url, timeout=ClientTimeout(60))
+        self._http_client = ClientSession(self._base_url, timeout=ClientTimeout(300))
 
     async def __aenter__(self):
         return self
@@ -57,11 +58,19 @@ class RemoteBIGSdbMLSTProfiler(BIGSdbMLSTProfiler):
         uri_path = "sequence"
         if isinstance(query_sequence_strings, str) or isinstance(query_sequence_strings, NamedString):
             query_sequence_strings = [query_sequence_strings]
+        
         for sequence_string in query_sequence_strings:
-            async with self._http_client.post(uri_path, json={
+            attempts = 0
+            success = False
+            last_error = None
+            while not success and attempts < self._retry_limit:
+                attempts += 1
+                request = self._http_client.post(uri_path, json={
                     "sequence": sequence_string if isinstance(sequence_string, str) else sequence_string.sequence,
                     "partial_matches": True
-            }) as response:
+                })
+                try:
+                    async with request as response:
                         sequence_response: dict = await response.json()
 
                         if "exact_matches" in sequence_response:
@@ -91,6 +100,17 @@ class RemoteBIGSdbMLSTProfiler(BIGSdbMLSTProfiler):
                                 yield result_allele if isinstance(sequence_string, str) else (sequence_string.name, result_allele)
                         else:
                             raise NoBIGSdbMatchesException(self._database_name, self._scheme_id, sequence_string.name if isinstance(sequence_string, NamedString) else None)
+                except (ConnectionError, ServerDisconnectedError, ClientOSError) as e: # Errors we will retry
+                    last_error = e
+                    success = False
+                    await asyncio.sleep(5) # In case the connection issue is due to rate issues
+                else:
+                    success = True
+            if not success and last_error is not None:
+                try:
+                    raise last_error
+                except (ConnectionError, ServerDisconnectedError, ClientOSError) as e: # Non-fatal errors
+                    yield Allele("error", "error", None)
 
     async def determine_mlst_st(self, alleles: Union[AsyncIterable[Union[Allele, tuple[str, Allele]]], Iterable[Union[Allele, tuple[str, Allele]]]]) -> Union[MLSTProfile, NamedMLSTProfile]:
         uri_path = "designations"
@@ -113,6 +133,13 @@ class RemoteBIGSdbMLSTProfiler(BIGSdbMLSTProfiler):
         request_json = {
             "designations": allele_request_dict
         }
+
+        attempts = 0
+        success = False
+        last_error = None
+        while attempts < self._retry_limit and not success:
+            attempts += 1
+            try:
                 async with self._http_client.post(uri_path, json=request_json) as response:
                     response_json: dict = await response.json()
                     allele_set: Set[Allele] = set()
@@ -129,6 +156,19 @@ class RemoteBIGSdbMLSTProfiler(BIGSdbMLSTProfiler):
                     if len(names_list) > 0:
                         result_mlst_profile = NamedMLSTProfile(str(tuple(names_list)) if len(set(names_list)) > 1 else names_list[0], result_mlst_profile)
                     return result_mlst_profile
+            except (ConnectionError, ServerDisconnectedError, ClientOSError) as e:
+                last_error = e
+                success = False
+                await asyncio.sleep(5)
+            else:
+                success = True
+        try:
+            if last_error is not None:
+                raise last_error
+        except (ConnectionError, ServerDisconnectedError, ClientOSError) as e:
+                result_mlst_profile = NamedMLSTProfile((str(tuple(names_list)) if len(set(names_list)) > 1 else names_list[0]) + ":Error", None)
+        raise ValueError("Last error was not recorded.")
+
                     
     async def profile_string(self, query_sequence_strings: Iterable[Union[NamedString, str]]) -> Union[NamedMLSTProfile, MLSTProfile]:
         alleles = self.determine_mlst_allele_variants(query_sequence_strings)
@@ -212,6 +252,16 @@ class BIGSdbIndex(AbstractAsyncContextManager):
     async def build_profiler_from_seqdefdb(self, local: bool, dbseqdef_name: str, scheme_id: int) -> BIGSdbMLSTProfiler:
         return get_BIGSdb_MLST_profiler(local, await self.get_bigsdb_api_from_seqdefdb(dbseqdef_name), dbseqdef_name, scheme_id)
     
+    async def get_scheme_loci(self, dbseqdef_name: str, scheme_id: int) -> list[str]:
+        uri_path = f"{await self.get_bigsdb_api_from_seqdefdb(dbseqdef_name)}/db/{dbseqdef_name}/schemes/{scheme_id}"
+        async with self._http_client.get(uri_path) as response:
+            response_json = await response.json()
+            loci = response_json["loci"]
+            results = []
+            for locus in loci:
+                results.append(path.basename(locus))
+            return results
+
     async def close(self):
         await self._http_client.close()
 

src/autobigs/engine/writing.py

@@ -1,7 +1,7 @@
 from collections import defaultdict
 import csv
 from os import PathLike
-from typing import AsyncIterable, Collection, Mapping, Sequence, Union
+from typing import AsyncIterable, Collection, Iterable, Mapping, Sequence, Union
 
 from autobigs.engine.structures.mlst import Allele, MLSTProfile, NamedMLSTProfile
 
@@ -17,7 +17,7 @@ def alleles_to_text_map(alleles: Collection[Allele]) -> Mapping[str, Union[Seque
             result[locus] = tuple(result[locus]) # type: ignore
     return dict(result)
 
-async def write_mlst_profiles_as_csv(mlst_profiles_iterable: AsyncIterable[NamedMLSTProfile], handle: Union[str, bytes, PathLike[str], PathLike[bytes]]) -> Sequence[str]:
+async def write_mlst_profiles_as_csv(mlst_profiles_iterable: AsyncIterable[NamedMLSTProfile], handle: Union[str, bytes, PathLike[str], PathLike[bytes]], allele_names: Iterable[str]) -> Sequence[str]:
     failed = list()
     with open(handle, "w", newline='') as filehandle:
         header = None
@@ -30,7 +30,7 @@ async def write_mlst_profiles_as_csv(mlst_profiles_iterable: AsyncIterable[Named
                 continue
             allele_mapping = alleles_to_text_map(mlst_profile.alleles)
             if writer is None:
-                header = ["id", "st", "clonal-complex", *sorted(allele_mapping.keys())]
+                header = ["id", "st", "clonal-complex", *sorted(allele_names)]
                 writer = csv.DictWriter(filehandle, fieldnames=header)
                 writer.writeheader()
             row_dictionary = {

tests/autobigs/engine/analysis/test_bigsdb.py

@@ -222,3 +222,12 @@ class TestBIGSdbIndex:
                 assert isinstance(profile, MLSTProfile)
                 assert profile.clonal_complex == "ST-2 complex"
                 assert profile.sequence_type == "1"
+
+
+    @pytest.mark.parametrize(["bigsdb_name", "scheme_id", "expected"], [
+        ("pubmlst_bordetella_seqdef", 3, ["adk", "fumC", "glyA", "tyrB", "icd", "pepA", "pgm"])
+    ])
+    async def test_bigsdb_index_fetches_loci_names(self, bigsdb_name, scheme_id, expected):
+        async with BIGSdbIndex() as bigsdb_index:
+            loci = await bigsdb_index.get_scheme_loci(bigsdb_name, scheme_id)
+            assert set(loci) == set(expected)

tests/autobigs/engine/test_writing.py

@@ -27,7 +27,7 @@ async def test_column_order_is_same_as_expected_file(dummy_alphabet_mlst_profile
     dummy_profiles = [dummy_alphabet_mlst_profile]
     with tempfile.TemporaryDirectory() as temp_dir:
         output_path = path.join(temp_dir, "out.csv")
-        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path)
+        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path, ["A", "D", "B", "C"])
         with open(output_path) as csv_handle:
             csv_reader = reader(csv_handle)
             lines = list(csv_reader)
@@ -38,7 +38,7 @@ async def test_csv_writing_sample_name_not_repeated_when_single_sequence(dummy_a
     dummy_profiles = [dummy_alphabet_mlst_profile]
     with tempfile.TemporaryDirectory() as temp_dir:
         output_path = path.join(temp_dir, "out.csv")
-        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path)
+        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path, ["A", "D", "B", "C"])
         with open(output_path) as csv_handle:
             csv_reader = reader(csv_handle)
             lines = list(csv_reader)
@@ -63,7 +63,7 @@ async def test_csv_writing_includes_asterisk_for_non_exact(dummy_alphabet_mlst_p
     dummy_profiles = [dummy_alphabet_mlst_profile]
     with tempfile.TemporaryDirectory() as temp_dir:
         output_path = path.join(temp_dir, "out.csv")
-        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path)
+        await write_mlst_profiles_as_csv(iterable_to_asynciterable(dummy_profiles), output_path, ["A", "D", "B", "C"])
         with open(output_path) as csv_handle:
             csv_reader = reader(csv_handle)
             lines = list(csv_reader)