corrlib/find.py

@@ -6,7 +6,6 @@ import numpy as np
 from .input.implementations import codes
 from .tools import k2m, get_db_file
 from .tracker import get
-from .integrity import check_time_validity
 from typing import Any, Optional, Union
 from pathlib import Path
 import datetime as dt
@@ -71,9 +70,6 @@ def _time_filter(results: pd.DataFrame,  created_before: Optional[str]=None, cre
         result = results.iloc[ind]
         created_at = dt.datetime.fromisoformat(result['created_at'])
         updated_at = dt.datetime.fromisoformat(result['updated_at'])
-        db_times_valid = check_time_validity(created_at=created_at, updated_at=updated_at)
-        if not db_times_valid:
-            raise ValueError('Time stamps not valid for result with path', result["path"])
 
         if created_before is not None:
             date_created_before = dt.datetime.fromisoformat(created_before)

corrlib/integrity.py

@@ -1,5 +0,0 @@
-import datetime as dt
-
-
-def check_time_validity(created_at: dt.datetime, updated_at: dt.datetime) -> bool:
-    return not (created_at > updated_at)

corrlib/meas_io.py

@@ -175,7 +175,7 @@ def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] =
                 if cache_enabled(path):
                     if not os.path.exists(cache_dir(path, file)):
                         os.makedirs(cache_dir(path, file))
-                    dump_object(preloaded[file][key], str(cache_path(path, file, key)))
+                    dump_object(preloaded[file][key], cache_path(path, file, key))
     return returned_data
 
 
@@ -195,7 +195,7 @@ def cache_dir(path: Path, file: str) -> Path:
         The path holding the cached data for the given file.
     """
     cache_path_list = file.split("/")[1:]
-    cache_path = Path(path) / CACHE_DIR
+    cache_path = path / CACHE_DIR
     for directory in cache_path_list:
         cache_path /= directory
     return cache_path
@@ -238,7 +238,7 @@ def preload(path: Path, file: Path) -> dict[str, Any]:
         The data read from the file.
     """
     get(path, file)
-    filedict: dict[str, Any] = pj.load_json_dict(str(path / file))
+    filedict: dict[str, Any] = pj.load_json_dict(path / file)
     print("> read file")
     return filedict
 

tests/find_test.py

@@ -3,8 +3,6 @@ import sqlite3
 from pathlib import Path
 import corrlib.initialization as cinit
 import pytest
-import pandas as pd
-import datalad.api as dl
 
 
 def make_sql(path: Path) -> Path:
@@ -36,34 +34,6 @@ def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
     conn.close()
 
 
-def test_find_project(tmp_path: Path) -> None:
-    cinit.create(tmp_path)
-    db = tmp_path / "backlogger.db"
-    dl.unlock(str(db), dataset=str(tmp_path))
-    conn = sqlite3.connect(db)
-    c = conn.cursor()
-    uuid = "test_uuid"
-    alias_str = "fun_project"
-    tag_str = "tt"
-    owner = "tester"
-    code = "test_code"
-    c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
-              (uuid, alias_str, tag_str, owner, code))
-    conn.commit()
-
-    assert uuid == find.find_project(tmp_path, "fun_project")
-
-    uuid = "test_uuid2"
-    alias_str = "fun_project"
-    c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
-              (uuid, alias_str, tag_str, owner, code))
-    conn.commit()
-
-    with pytest.raises(Exception):
-        assert uuid == find._project_lookup_by_alias(tmp_path, "fun_project")
-    conn.close()
-
-
 def test_find_lookup_by_id(tmp_path: Path) -> None:
     db = make_sql(tmp_path)
     conn = sqlite3.connect(db)
@@ -152,89 +122,3 @@ def test_db_lookup(tmp_path: Path) -> None:
     assert len(results) == 1
 
     conn.close()
-
-
-def test_time_filter() -> None:
-    record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-            '2025-03-26 12:55:18.229966', '2025-03-26 12:55:18.229966'] # only created
-    record_B = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-                '2025-03-26 12:55:18.229966', '2025-04-26 12:55:18.229966'] # created and updated
-    record_C = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-                '2026-03-26 12:55:18.229966', '2026-05-26 12:55:18.229966'] # created and updated later
-    record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-                '2026-03-26 12:55:18.229966', '2026-03-27 12:55:18.229966']
-    record_E = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-                '2024-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # only created, earlier
-    record_F = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf", "SF_A", '{par_A: 5.0, par_B: 5.0}', "projects/SF_A/input.in",
-                '2026-03-26 12:55:18.229966', '2024-03-26 12:55:18.229966'] # this is invalid...
-
-    data = [record_A, record_B, record_C, record_D, record_E]
-    cols = ["name",
-            "ensemble",
-            "code",
-            "path",
-            "project",
-            "parameters",
-            "parameter_file",
-            "created_at",
-            "updated_at"]
-    df = pd.DataFrame(data,columns=cols)
-
-    results = find._time_filter(df, created_before='2023-03-26 12:55:18.229966')
-    assert results.empty
-    results = find._time_filter(df, created_before='2027-03-26 12:55:18.229966')
-    assert len(results) == 5
-    results = find._time_filter(df, created_before='2026-03-25 12:55:18.229966')
-    assert len(results) == 3
-    results = find._time_filter(df, created_before='2026-03-26 12:55:18.229965')
-    assert len(results) == 3
-    results = find._time_filter(df, created_before='2025-03-04 12:55:18.229965')
-    assert len(results) == 1
-
-    results = find._time_filter(df, created_after='2023-03-26 12:55:18.229966')
-    assert len(results) == 5
-    results = find._time_filter(df, created_after='2027-03-26 12:55:18.229966')
-    assert results.empty
-    results = find._time_filter(df, created_after='2026-03-25 12:55:18.229966')
-    assert len(results) == 2
-    results = find._time_filter(df, created_after='2026-03-26 12:55:18.229965')
-    assert len(results) == 2
-    results = find._time_filter(df, created_after='2025-03-04 12:55:18.229965')
-    assert len(results) == 4
-
-    results = find._time_filter(df, updated_before='2023-03-26 12:55:18.229966')
-    assert results.empty
-    results = find._time_filter(df, updated_before='2027-03-26 12:55:18.229966')
-    assert len(results) == 5
-    results = find._time_filter(df, updated_before='2026-03-25 12:55:18.229966')
-    assert len(results) == 3
-    results = find._time_filter(df, updated_before='2026-03-26 12:55:18.229965')
-    assert len(results) == 3
-    results = find._time_filter(df, updated_before='2025-03-04 12:55:18.229965')
-    assert len(results) == 1
-
-    results = find._time_filter(df, updated_after='2023-03-26 12:55:18.229966')
-    assert len(results) == 5
-    results = find._time_filter(df, updated_after='2027-03-26 12:55:18.229966')
-    assert results.empty
-    results = find._time_filter(df, updated_after='2026-03-25 12:55:18.229966')
-    assert len(results) == 2
-    results = find._time_filter(df, updated_after='2026-03-26 12:55:18.229965')
-    assert len(results) == 2
-    results = find._time_filter(df, updated_after='2025-03-04 12:55:18.229965')
-    assert len(results) == 4
-
-    data = [record_A, record_B, record_C, record_D, record_F]
-    cols = ["name",
-            "ensemble",
-            "code",
-            "path",
-            "project",
-            "parameters",
-            "parameter_file",
-            "created_at",
-            "updated_at"]
-    df = pd.DataFrame(data,columns=cols)
-
-    with pytest.raises(ValueError):
-        results = find._time_filter(df, created_before='2023-03-26 12:55:18.229966')