Merge branch 'develop' of ssh://kuhl-mann.de/jkuhl/corrlib into develop

corrlib/cli.py

@@ -1,15 +1,16 @@
 from typing import Optional
 import typer
 from corrlib import __app_name__
+
 from .initialization import create
 from .toml import import_tomls, update_project, reimport_project
-from .find import find_record, list_projects
+from .find import find_record, list_projects, list_ensembles, get_stat
 from .tools import str2list
 from .main import update_aliases
 from .meas_io import drop_cache as mio_drop_cache
-from .meas_io import load_record as mio_load_record
+from .integrity import full_integrity_check
+
 import os
-from pyerrors import Corr
 from importlib.metadata import version
 from pathlib import Path
 
@@ -26,7 +27,7 @@ def _version_callback(value: bool) -> None:
 @app.command()
 def update(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -42,7 +43,7 @@ def update(
 @app.command()
 def lister(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
     ),
@@ -53,15 +54,15 @@ def lister(
     """
     if entities in ['ensembles', 'Ensembles','ENSEMBLES']:
         print("Ensembles:")
-        for item in os.listdir(path / "archive"):
+        ensemble_results = list_ensembles(path)
-            if os.path.isdir(path / "archive" / item):
+        for e in ensemble_results:
-                print(item)
+            print(e)
     elif entities == 'projects':
-        results = list_projects(path)
+        project_results = list_projects(path)
         print("Projects:")
         header = "UUID".ljust(37) + "| Aliases"
         print(header)
-        for project in results:
+        for project in project_results:
             if project[1] is not None:
                 aliases = " | ".join(str2list(project[1]))
             else:
@@ -73,7 +74,7 @@ def lister(
 @app.command()
 def alias_add(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -91,7 +92,7 @@ def alias_add(
 @app.command()
 def find(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -105,12 +106,19 @@ def find(
     ),
     ) -> None:
     """
-    Find a record in the backlog at hand. Through specifying it's ensemble and the measured correlator.
+    Find a record in the given backlog.
     """
     results = find_record(path, ensemble, corr, code)
+    if results.empty:
+        return
     if arg == 'all':
         print(results)
     else:
+        if arg == 'stat':
+            for r in results['path'].values:
+                stat = get_stat(path, r)
+                print(stat)
+                return
         for r in results[arg].values:
             print(r)
 
@@ -118,7 +126,7 @@ def find(
 @app.command()
 def stat(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -127,18 +135,28 @@ def stat(
     """
     Show the statistics of a given record.
     """
-    record = mio_load_record(path, record_id)
+    statistics = get_stat(path, record_id)
-    if isinstance(record, (list, Corr)):
-        record = record[0]
-    statistics = record.idl
     print(statistics)
     return
 
 
+@app.command()
+def check(path: Path = typer.Option(
+        Path('.'),
+        "--dataset",
+        "-d",
+        ),
+    ) -> None:
+    """
+    Check the integrity of the repository.
+    """
+    full_integrity_check(path)
+
+
 @app.command()
 def importer(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -155,13 +173,14 @@ def importer(
     """
     file_list = files.split(",")
     import_tomls(path, file_list, copy_file)
+    mio_drop_cache(path)
     return
 
 
 @app.command()
 def reimporter(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -179,13 +198,14 @@ def reimporter(
             raise Exception("This file is not known for this project.")
     else:
         reimport_project(path, uuid)
+    mio_drop_cache(path)
     return
 
 
 @app.command()
 def init(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),
@@ -205,7 +225,7 @@ def init(
 @app.command()
 def drop_cache(
     path: Path = typer.Option(
-        Path('./corrlib'),
+        Path('.'),
         "--dataset",
         "-d",
         ),

corrlib/find.py

@@ -6,11 +6,18 @@ import numpy as np
 from .input.implementations import codes
 from .tools import k2m, get_db_file
 from .tracker import get
+from .integrity import has_valid_times
+from .sql import thin_sql_wrapper
 from typing import Any, Optional
 from pathlib import Path
+import datetime as dt
+from collections.abc import Callable
+import warnings
+from .meas_io import load_record
+from pyerrors import Corr, Obs
 
 
-def _project_lookup_by_alias(db: Path, alias: str) -> str:
+def _project_lookup_by_alias(path: Path, alias: str) -> str:
     """
     Lookup a projects UUID by its (human-readable) alias.
 
@@ -26,11 +33,8 @@ def _project_lookup_by_alias(db: Path, alias: str) -> str:
     uuid: str
         The UUID of the project with the given alias.
     """
-    conn = sqlite3.connect(db)
+    stmt = f"SELECT * FROM 'projects' WHERE aliases = '{alias}'"
-    c = conn.cursor()
+    results = thin_sql_wrapper(path, stmt)
-    c.execute(f"SELECT * FROM 'projects' WHERE aliases = '{alias}'")
-    results = c.fetchall()
-    conn.close()
     if len(results)>1:
         print("Error: multiple projects found with alias " + alias)
     elif len(results) == 0:
@@ -38,7 +42,7 @@ def _project_lookup_by_alias(db: Path, alias: str) -> str:
     return str(results[0][0])
 
 
-def _project_lookup_by_id(db: Path, uuid: str) -> list[tuple[str, str]]:
+def _project_lookup_by_id(path: Path, uuid: str) -> list[tuple[str, ...]]:
     """
     Return the project information available in the database by UUID.
 
@@ -54,16 +58,61 @@ def _project_lookup_by_id(db: Path, uuid: str) -> list[tuple[str, str]]:
     results: list
         The row of the project in the database.
     """
-    conn = sqlite3.connect(db)
+    stmt = f"SELECT * FROM 'projects' WHERE id = '{uuid}'"
-    c = conn.cursor()
+    results = thin_sql_wrapper(path, stmt)
-    c.execute(f"SELECT * FROM 'projects' WHERE id = '{uuid}'")
-    results = c.fetchall()
-    conn.close()
     return results
 
 
-def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None,  parameters: Optional[str]=None,
+def _time_filter(results: pd.DataFrame,  created_before: Optional[str]=None, created_after: Optional[Any]=None, updated_before: Optional[Any]=None, updated_after: Optional[Any]=None) -> pd.DataFrame:
-               created_before: Optional[str]=None, created_after: Optional[Any]=None, updated_before: Optional[Any]=None, updated_after: Optional[Any]=None) -> pd.DataFrame:
+    """
+    Filter the results from the database in terms of the creation and update times.
+
+    Parameters
+    ----------
+    results: pd.DataFrame
+        The dataframe holding the unfilteres results from the database.
+    created_before: str
+        Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The creation date has to be truly before the date and time given.
+    created_after: str
+        Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The creation date has to be truly after the date and time given.
+    updated_before: str
+        Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The date of the last update has to be truly before the date and time given.
+    updated_after: str
+        Contraint on the creation date in datetime.datetime.isoformat. Note that this is exclusive. The date of the last update has to be truly after the date and time given.
+    """
+    drops = []
+    for ind in range(len(results)):
+        result = results.iloc[ind]
+        created_at = dt.datetime.fromisoformat(result['created_at'])
+        updated_at = dt.datetime.fromisoformat(result['updated_at'])
+        db_times_valid = has_valid_times(result)
+        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)
+            if date_created_before < created_at:
+                drops.append(ind)
+                continue
+        if created_after is not None:
+            date_created_after = dt.datetime.fromisoformat(created_after)
+            if date_created_after > created_at:
+                drops.append(ind)
+                continue
+        if updated_before is not None:
+            date_updated_before = dt.datetime.fromisoformat(updated_before)
+            if date_updated_before < updated_at:
+                drops.append(ind)
+                continue
+        if updated_after is not None:
+            date_updated_after = dt.datetime.fromisoformat(updated_after)
+            if date_updated_after > updated_at:
+                drops.append(ind)
+                continue
+    return results.drop(drops)
+
+
+def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None,  parameters: Optional[str]=None) -> pd.DataFrame:
     """
     Look up a correlator record in the database by the data given to the method.
 
@@ -105,20 +154,84 @@ def _db_lookup(db: Path, ensemble: str, correlator_name: str, code: str, project
         search_expr += f" AND code = '{code}'"
     if parameters:
         search_expr += f" AND parameters = '{parameters}'"
-    if created_before:
-        search_expr += f" AND created_at < '{created_before}'"
-    if created_after:
-        search_expr += f" AND created_at > '{created_after}'"
-    if updated_before:
-        search_expr += f" AND updated_at < '{updated_before}'"
-    if updated_after:
-        search_expr += f" AND updated_at > '{updated_after}'"
     conn = sqlite3.connect(db)
     results = pd.read_sql(search_expr, conn)
     conn.close()
     return results
 
 
+def _sfcf_drop(param: dict[str, Any], **kwargs: Any) -> bool:
+        if 'offset' in kwargs:
+            if kwargs.get('offset') != param['offset']:
+                return True
+        if 'quark_kappas' in kwargs:
+            kappas = kwargs['quark_kappas']
+            if (not np.isclose(kappas[0], param['quarks'][0]['mass']) or not np.isclose(kappas[1], param['quarks'][1]['mass'])):
+                return True
+        if 'quark_masses' in kwargs:
+            masses = kwargs['quark_masses']
+            if (not np.isclose(masses[0], k2m(param['quarks'][0]['mass'])) or not np.isclose(masses[1], k2m(param['quarks'][1]['mass']))):
+                return True
+        if 'qk1' in kwargs:
+            quark_kappa1 = kwargs['qk1']
+            if not isinstance(quark_kappa1, list):
+                if (not np.isclose(quark_kappa1, param['quarks'][0]['mass'])):
+                    return True
+            else:
+                if len(quark_kappa1) == 2:
+                    if (quark_kappa1[0] > param['quarks'][0]['mass']) or (quark_kappa1[1] < param['quarks'][0]['mass']):
+                        return True
+                else:
+                    raise ValueError("quark_kappa1 has to have length 2")
+        if 'qk2' in kwargs:
+            quark_kappa2 = kwargs['qk2']
+            if not isinstance(quark_kappa2, list):
+                if (not np.isclose(quark_kappa2, param['quarks'][1]['mass'])):
+                    return True
+            else:
+                if len(quark_kappa2) == 2:
+                    if (quark_kappa2[0] > param['quarks'][1]['mass']) or (quark_kappa2[1] < param['quarks'][1]['mass']):
+                        return True
+                else:
+                    raise ValueError("quark_kappa2 has to have length 2")
+        if 'qm1' in kwargs:
+            quark_mass1 = kwargs['qm1']
+            if not isinstance(quark_mass1, list):
+                if (not np.isclose(quark_mass1, k2m(param['quarks'][0]['mass']))):
+                    return True
+            else:
+                if len(quark_mass1) == 2:
+                    if (quark_mass1[0] > k2m(param['quarks'][0]['mass'])) or (quark_mass1[1] < k2m(param['quarks'][0]['mass'])):
+                        return True
+                else:
+                    raise ValueError("quark_mass1 has to have length 2")
+        if 'qm2' in kwargs:
+            quark_mass2 = kwargs['qm2']
+            if not isinstance(quark_mass2, list):
+                if (not np.isclose(quark_mass2, k2m(param['quarks'][1]['mass']))):
+                    return True
+            else:
+                if len(quark_mass2) == 2:
+                    if (quark_mass2[0] > k2m(param['quarks'][1]['mass'])) or (quark_mass2[1] < k2m(param['quarks'][1]['mass'])):
+                        return True
+                else:
+                    raise ValueError("quark_mass2 has to have length 2")
+        if 'quark_thetas' in kwargs:
+            quark_thetas = kwargs['quark_thetas']
+            if (quark_thetas[0] != param['quarks'][0]['thetas'] and quark_thetas[1] != param['quarks'][1]['thetas']) or (quark_thetas[0] != param['quarks'][1]['thetas'] and quark_thetas[1] != param['quarks'][0]['thetas']):
+                return True
+        # careful, this is not save, when multiple contributions are present!
+        if 'wf1' in kwargs:
+            wf1 = kwargs['wf1']
+            if not (np.isclose(wf1[0][0], param['wf1'][0][0], 1e-8) and np.isclose(wf1[0][1][0], param['wf1'][0][1][0], 1e-8) and np.isclose(wf1[0][1][1], param['wf1'][0][1][1], 1e-8)):
+                return True
+        if 'wf2' in kwargs:
+            wf2 = kwargs['wf2']
+            if not (np.isclose(wf2[0][0], param['wf2'][0][0], 1e-8) and np.isclose(wf2[0][1][0], param['wf2'][0][1][0], 1e-8) and np.isclose(wf2[0][1][1], param['wf2'][0][1][1], 1e-8)):
+                return True
+        return False
+
+
 def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
     r"""
     Filter method for the Database entries holding SFCF calculations.
@@ -136,9 +249,9 @@ def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
     qk2: float, optional
         Mass parameter $\kappa_2$ of the first quark.
     qm1: float, optional
-        Bare quak mass $m_1$ of the first quark.
+        Bare quark mass $m_1$ of the first quark.
     qm2: float, optional
-        Bare quak mass $m_1$ of the first quark.
+        Bare quark mass $m_2$ of the first quark.
     quarks_thetas: list[list[float]], optional
     wf1: optional
     wf2: optional
@@ -148,101 +261,81 @@ def sfcf_filter(results: pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
     results: pd.DataFrame
         The filtered DataFrame, only holding the records that fit to the parameters given.
     """
+
     drops = []
     for ind in range(len(results)):
         result = results.iloc[ind]
         param = json.loads(result['parameters'])
-        if 'offset' in kwargs:
+        if _sfcf_drop(param, **kwargs):
-            if kwargs.get('offset') != param['offset']:
             drops.append(ind)
-                continue
-        if 'quark_kappas' in kwargs:
-            kappas = kwargs['quark_kappas']
-            if (not np.isclose(kappas[0], param['quarks'][0]['mass']) or not np.isclose(kappas[1], param['quarks'][1]['mass'])):
-                drops.append(ind)
-                continue
-        if 'quark_masses' in kwargs:
-            masses = kwargs['quark_masses']
-            if (not np.isclose(masses[0], k2m(param['quarks'][0]['mass'])) or not np.isclose(masses[1], k2m(param['quarks'][1]['mass']))):
-                drops.append(ind)
-                continue
-        if 'qk1' in kwargs:
-            quark_kappa1 = kwargs['qk1']
-            if not isinstance(quark_kappa1, list):
-                if (not np.isclose(quark_kappa1, param['quarks'][0]['mass'])):
-                    drops.append(ind)
-                    continue
-            else:
-                if len(quark_kappa1) == 2:
-                    if (quark_kappa1[0] > param['quarks'][0]['mass']) or (quark_kappa1[1] < param['quarks'][0]['mass']):
-                        drops.append(ind)
-                        continue
-        if 'qk2' in kwargs:
-            quark_kappa2 = kwargs['qk2']
-            if not isinstance(quark_kappa2, list):
-                if (not np.isclose(quark_kappa2, param['quarks'][1]['mass'])):
-                    drops.append(ind)
-                    continue
-            else:
-                if len(quark_kappa2) == 2:
-                    if (quark_kappa2[0] > param['quarks'][1]['mass']) or (quark_kappa2[1] < param['quarks'][1]['mass']):
-                        drops.append(ind)
-                        continue
-        if 'qm1' in kwargs:
-            quark_mass1 = kwargs['qm1']
-            if not isinstance(quark_mass1, list):
-                if (not np.isclose(quark_mass1, k2m(param['quarks'][0]['mass']))):
-                    drops.append(ind)
-                    continue
-            else:
-                if len(quark_mass1) == 2:
-                    if (quark_mass1[0] > k2m(param['quarks'][0]['mass'])) or (quark_mass1[1] < k2m(param['quarks'][0]['mass'])):
-                        drops.append(ind)
-                        continue
-        if 'qm2' in kwargs:
-            quark_mass2 = kwargs['qm2']
-            if not isinstance(quark_mass2, list):
-                if (not np.isclose(quark_mass2, k2m(param['quarks'][1]['mass']))):
-                    drops.append(ind)
-                    continue
-            else:
-                if len(quark_mass2) == 2:
-                    if (quark_mass2[0] > k2m(param['quarks'][1]['mass'])) or (quark_mass2[1] < k2m(param['quarks'][1]['mass'])):
-                        drops.append(ind)
-                        continue
-        if 'quark_thetas' in kwargs:
-            quark_thetas = kwargs['quark_thetas']
-            if (quark_thetas[0] != param['quarks'][0]['thetas'] and quark_thetas[1] != param['quarks'][1]['thetas']) or (quark_thetas[0] != param['quarks'][1]['thetas'] and quark_thetas[1] != param['quarks'][0]['thetas']):
-                drops.append(ind)
-                continue
-        # careful, this is not save, when multiple contributions are present!
-        if 'wf1' in kwargs:
-            wf1 = kwargs['wf1']
-            if not (np.isclose(wf1[0][0], param['wf1'][0][0], 1e-8) and np.isclose(wf1[0][1][0], param['wf1'][0][1][0], 1e-8) and np.isclose(wf1[0][1][1], param['wf1'][0][1][1], 1e-8)):
-                drops.append(ind)
-                continue
-        if 'wf2' in kwargs:
-            wf2 = kwargs['wf2']
-            if not (np.isclose(wf2[0][0], param['wf2'][0][0], 1e-8) and np.isclose(wf2[0][1][0], param['wf2'][0][1][0], 1e-8) and np.isclose(wf2[0][1][1], param['wf2'][0][1][1], 1e-8)):
-                drops.append(ind)
-                continue
     return results.drop(drops)
 
 
+def openQCD_filter(results:pd.DataFrame, **kwargs: Any) -> pd.DataFrame:
+    """
+    Filter for parameters of openQCD.
+
+    Parameters
+    ----------
+    results: pd.DataFrame
+        The unfiltered list of results from the database.
+
+    Returns
+    -------
+    results: pd.DataFrame
+        The filtered results.
+
+    """
+    warnings.warn("A filter for openQCD parameters is no implemented yet.", Warning)
+
+    return results
+
+
+def _code_filter(results: pd.DataFrame, code: str, **kwargs: Any) -> pd.DataFrame:
+    """
+    Abstraction of the filters for the different codes that are available.
+    At the moment, only openQCD and SFCF are known.
+    The possible key words for the parameters can be seen in the descriptionso f the code-specific filters.
+
+    Parameters
+    ----------
+    results: pd.DataFrame
+        The unfiltered list of results from the database.
+    code: str
+        The name of the code that produced the record at hand.
+    kwargs:
+        The keyworkd args that are handed over to the code-specific filters.
+
+    Returns
+    -------
+    results: pd.DataFrame
+        The filtered results.
+    """
+    if code == "sfcf":
+        return sfcf_filter(results, **kwargs)
+    elif code == "openQCD":
+        return openQCD_filter(results, **kwargs)
+    else:
+        raise ValueError(f"Code {code} is not known.")
+
+
 def find_record(path: Path, ensemble: str, correlator_name: str, code: str, project: Optional[str]=None, parameters: Optional[str]=None,
-                created_before: Optional[str]=None, created_after: Optional[str]=None, updated_before: Optional[str]=None, updated_after: Optional[str]=None, revision: Optional[str]=None, **kwargs: Any) -> pd.DataFrame:
+                created_before: Optional[str]=None, created_after: Optional[str]=None, updated_before: Optional[str]=None, updated_after: Optional[str]=None,
+                revision: Optional[str]=None,
+                customFilter: Optional[Callable[[pd.DataFrame], pd.DataFrame]] = None,
+                **kwargs: Any) -> pd.DataFrame:
+    path = Path(path)
     db_file = get_db_file(path)
     db = path / db_file
     if code not in codes:
         raise ValueError("Code " + code + "unknown, take one of the following:" + ", ".join(codes))
     get(path, db_file)
-    results = _db_lookup(db, ensemble, correlator_name,code, project, parameters=parameters, created_before=created_before, created_after=created_after, updated_before=updated_before, updated_after=updated_after)
+    results = _db_lookup(db, ensemble, correlator_name,code, project, parameters=parameters)
-    if code == "sfcf":
+    if any([arg is not None for arg in [created_before, created_after, updated_before, updated_after]]):
-        results = sfcf_filter(results, **kwargs)
+        results = _time_filter(results, created_before, created_after, updated_before, updated_after)
-    elif code == "openQCD":
+    results = _code_filter(results, code, **kwargs)
-        pass
+    if customFilter is not None:
-    else:
+        results =  customFilter(results)
-        raise Exception
     print("Found " + str(len(results)) + " result" + ("s" if len(results)>1 else ""))
     return results.reset_index()
 
@@ -265,7 +358,7 @@ def find_project(path: Path, name: str) -> str:
     """
     db_file = get_db_file(path)
     get(path, db_file)
-    return _project_lookup_by_alias(path / db_file, name)
+    return _project_lookup_by_alias(path, name)
 
 
 def list_projects(path: Path) -> list[tuple[str, str]]:
@@ -291,3 +384,19 @@ def list_projects(path: Path) -> list[tuple[str, str]]:
     conn.close()
     return results
 
+
+def list_ensembles(path: Path) -> list[str]:
+    res = []
+    for item in os.listdir(path / "archive"):
+        if os.path.isdir(path / "archive" / item):
+            res.append(item)
+    return res
+
+
+def get_stat(path: Path, record_id: str) -> Any:
+    loaded_record: Obs = load_record(path, record_id)
+    if isinstance(loaded_record, (list, Corr)):
+        record: Obs = loaded_record[0]
+    else:
+        record = loaded_record
+    return record.idl

corrlib/initialization.py

@@ -3,6 +3,7 @@ import sqlite3
 import os
 from .tracker import save, init
 from pathlib import Path
+from .tools import CONFIG_FILENAME
 
 
 def _create_db(db: Path) -> None:
@@ -87,7 +88,7 @@ def _write_config(path: Path, config: ConfigParser) -> None:
     config: ConfigParser
         The configuration to be used as a ConfigParser, e.g. generated by _create_config.
     """
-    with open(os.path.join(path, '.corrlib'), 'w') as configfile:
+    with open(os.path.join(path, CONFIG_FILENAME), 'w') as configfile:
         config.write(configfile)
     return
 

corrlib/input/openQCD.py

@@ -4,9 +4,12 @@ import os
 import fnmatch
 from typing import Any, Optional
 from pathlib import Path
+from ..pars.openQCD import ms1
+from ..pars.openQCD import qcd2
 
 
-def read_ms1_param(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
+
+def load_ms1_infile(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
     """
     Read the parameters for ms1 measurements from a parameter file in the project.
 
@@ -70,7 +73,7 @@ def read_ms1_param(path: Path, project: str, file_in_project: str) -> dict[str,
     return param
 
 
-def read_ms3_param(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
+def load_ms3_infile(path: Path, project: str, file_in_project: str) -> dict[str, Any]:
     """
     Read the parameters for ms3 measurements from a parameter file in the project.
 
@@ -161,7 +164,8 @@ def read_rwms(path: Path, project: str, dir_in_project: str, param: dict[str, An
     return rw_dict
 
 
-def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str="", names: Optional[list[str]]=None, files: Optional[list[str]]=None) -> dict[str, Any]:
+def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str="", names: Optional[list[str]]=None, files: Optional[list[str]]=None,
+               r_start: list[int]=[], r_stop: list[int]=[], r_step:int=1) -> dict[str, Any]:
     """
     Extract t0 measurements from the project.
 
@@ -215,6 +219,11 @@ def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, A
     if postfix is not None:
         kwargs['postfix'] = postfix
     kwargs['plot_fit'] = False
+    if not r_start == []:
+        kwargs['r_start'] = r_start
+    if not r_stop == []:
+        kwargs['r_stop'] = r_stop
+    kwargs['r_step'] = r_step
 
     t0 = input.extract_t0(directory,
                             prefix,
@@ -235,7 +244,8 @@ def extract_t0(path: Path, project: str, dir_in_project: str, param: dict[str, A
     return t0_dict
 
 
-def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str = "", names: Optional[list[str]]=None, files: Optional[list[str]]=None) -> dict[str, Any]:
+def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, Any], prefix: str, dtr_read: int, xmin: int, spatial_extent: int, fit_range: int = 5, postfix: str = "", names: Optional[list[str]]=None, files: Optional[list[str]]=None,
+               r_start: list[int]=[], r_stop: list[int]=[], r_step:int=1) -> dict[str, Any]:
     """
     Extract t1 measurements from the project.
 
@@ -287,6 +297,11 @@ def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, A
     if postfix is not None:
         kwargs['postfix'] = postfix
     kwargs['plot_fit'] = False
+    if not r_start == []:
+        kwargs['r_start'] = r_start
+    if not r_stop == []:
+        kwargs['r_stop'] = r_stop
+    kwargs['r_step'] = r_step
     t0 = input.extract_t0(directory,
                             prefix,
                             dtr_read,
@@ -304,3 +319,51 @@ def extract_t1(path: Path, project: str, dir_in_project: str, param: dict[str, A
     t1_dict[param["type"]] = {}
     t1_dict[param["type"]][pars] = t0
     return t1_dict
+
+
+def load_qcd2_pars(path: Path, project: str, file_in_project: str)  -> dict[str, Any]:
+    """
+    Thin wrapper around read_qcd2_par_file, getting the file before reading.
+
+    Parameters
+    ----------
+    path: Path
+        Path of the corrlib repository.
+    project: str
+        UUID of the project of the parameter-file.
+    file_in_project: str
+        The loaction of the file in the project directory.
+
+    Returns
+    -------
+    par_dict: dict
+        The dict with the parameters read from the .par-file.
+    """
+    fname = path / "projects" / project / file_in_project
+    ds = os.path.join(path, "projects", project)
+    dl.get(fname, dataset=ds)
+    return qcd2.read_qcd2_par_file(fname)
+
+
+def load_ms1_parfile(path: Path, project: str, file_in_project: str)  -> dict[str, Any]:
+    """
+    Thin wrapper around read_qcd2_ms1_par_file, getting the file before reading.
+
+    Parameters
+    ----------
+    path: Path
+        Path of the corrlib repository.
+    project: str
+        UUID of the project of the parameter-file.
+    file_in_project: str
+        The loaction of the file in the project directory.
+
+    Returns
+    -------
+    par_dict: dict
+        The dict with the parameters read from the .par-file.
+    """
+    fname = path / "projects" / project / file_in_project
+    ds = os.path.join(path, "projects", project)
+    dl.get(fname, dataset=ds)
+    return ms1.read_qcd2_ms1_par_file(fname)

corrlib/integrity.py

@@ -0,0 +1,295 @@
+import datetime as dt
+from pathlib import Path
+from .tools import get_db_file, CONFIG_FILENAME
+import pandas as pd
+import sqlite3
+from .tracker import get
+import pyerrors.input.json as pj
+import os
+from configparser import ConfigParser
+from typing import Any
+
+
+path_opts = ['db', 'projects_path', 'archive_path', 'toml_imports_path', 'import_scripts_path']
+
+
+def has_valid_times(result: pd.Series) -> bool:
+    """
+    Check, whether the result at hand has time-stamps that are sensible:
+    A recored is created first, then updated, with both times laying in the past.
+
+    Parameters
+    ----------
+    result: pd.Series
+        The result to check
+
+    Returns
+    -------
+    b: bool
+        True, if the timestamps make sense.
+    """
+    # we expect created_at <= updated_at <= now
+    created_at = dt.datetime.fromisoformat(result['created_at'])
+    updated_at = dt.datetime.fromisoformat(result['updated_at'])
+    if created_at > updated_at:
+        return False
+    if updated_at > dt.datetime.now():
+        return False
+    return True
+
+def are_keys_unique(db: Path, table: str, col: str) -> bool:
+    """
+    Check whether the strings listed in a column of a given table are unique.
+
+    Parameters
+    ----------
+    db: Path
+        The database to check.
+    table: str
+        The table to check.
+    col: str
+        The column to be checked for uniqueness.
+
+    Returns
+    -------
+    b: bool
+        True, if the strings are unique.
+    """
+    conn = sqlite3.connect(db)
+    c = conn.cursor()
+    c.execute(f"SELECT COUNT( DISTINCT CAST({col} AS nvarchar(4000))), COUNT({col}) FROM {table};")
+    results = c.fetchall()[0]
+    conn.close()
+    res = bool(results[0] == results[1])
+    if not res:
+        print("Unique:", results[0], "All:", results[1])
+    return res
+
+
+def _list_projects(path: Path) -> list[tuple[str, str]]:
+    """
+    List all projects known to the library.
+
+    Parameters
+    ----------
+    path: str
+        The path of the library.
+
+    Returns
+    -------
+    results: list[Any]
+        The projects known to the library.
+    """
+    db_file = get_db_file(path)
+    get(path, db_file)
+    conn = sqlite3.connect(os.path.join(path, db_file))
+    c = conn.cursor()
+    c.execute("SELECT id,aliases FROM projects")
+    results = c.fetchall()
+    conn.close()
+    return results
+
+
+def _list_ensembles(path: Path) -> list[str]:
+    res = []
+    for item in os.listdir(path / "archive"):
+        if os.path.isdir(path / "archive" / item):
+            res.append(item)
+    return res
+
+
+def check_path_format(result: pd.Series, ensembles: list[str], projects: list[str]) -> None:
+    """
+    Check whether the path of the given result has the right format.
+
+    Parameters
+    ----------
+    result: pd.Series
+        The result to be checked.
+    """
+    p = result['path']
+    if not p.startswith('archive'):
+        raise ValueError(f'The path {p} does not start correctly')
+
+    meas_key = p.split('::')[1]
+    ensemble = p.split('/')[1]
+    project = p.split('/')[3].split('.')[0]
+    if not len(meas_key) == 64:
+        raise ValueError(f'meas_key of {p} is scrambled')
+    if ensemble not in ensembles:
+        raise ValueError(f'meas_key of {p} points to an unknown ensemble')
+    if project not in projects:
+        raise ValueError(f'meas_key of {p} points to an unknown project id ({project})')
+    if not ensemble == result['ensemble']:
+        raise ValueError(f'Ensemble in database and file does not match for path {p}.')
+
+
+
+def check_db_integrity(path: Path) -> None:
+    """
+    Check intergrity of the database by checking the uniqueness of the record keys used to load the records
+    and ensuring that the timestamps of each record is sensible. Throws an error, if issues are detected.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    db = get_db_file(path)
+
+    if not are_keys_unique(path / db, 'backlogs', 'path'):
+        raise Exception("The paths the backlog table of the database links are not unique.")
+
+    search_expr = "SELECT * FROM 'backlogs'"
+    conn = sqlite3.connect(path / db)
+    results = pd.read_sql(search_expr, conn)
+    ensembles = _list_ensembles(path)
+    projects = [p[0] for p in _list_projects(path)]
+
+    for _, result in results.iterrows():
+        if not has_valid_times(result):
+            raise ValueError(f"Result with id {result[id]} has wrong time signatures.")
+        check_path_format(result, ensembles, projects)
+    return
+
+
+def _check_db2paths(path: Path, meas_paths: list[str]) -> None:
+    """
+    Check whether for each record in the given by meas_paths, we can find the data in the file as we expect.
+    Also check, whether there are unreachable records in the files. If either of the issues arise, throws an error.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    meas_paths: list[str]
+        List of measurement paths to check.
+    """
+    needed_data: dict[str, list[str]] = {}
+    for mpath in meas_paths:
+        file = mpath.split("::")[0]
+        if file not in needed_data.keys():
+            needed_data[file] = []
+        key = mpath.split("::")[1]
+        needed_data[file].append(key)
+
+    totf = len(needed_data.keys())
+    for i, file in enumerate(needed_data.keys()):
+        print(f"Check against file {i}/{totf}: {file}")
+        get(path, Path(file))
+        filedict: dict[str, Any] = pj.load_json_dict(str(path / file))
+        if not set(filedict.keys()).issubset(needed_data[file]):
+            for key in filedict.keys():
+                if key not in needed_data[file]:
+                    raise ValueError(f"Found unintended key {key} in file {file}.")
+        if not set(needed_data[file]).issubset(filedict.keys()):
+            for key in needed_data[file]:
+                if key not in filedict.keys():
+                    raise ValueError(f"Did not find data for key {key} that should be in file {file}.")
+    return
+
+
+def check_db_file_links(path: Path) -> None:
+    """
+    Check whether for each record in the given correlator library, we can find the data in the file as we expect.
+    Also check, whether there are unreachable records in the files. If either of the issues arise, throws an error.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    db = get_db_file(path)
+    search_expr = "SELECT path FROM 'backlogs'"
+    conn = sqlite3.connect(path / db)
+    results = pd.read_sql(search_expr, conn)['path'].values
+    _check_db2paths(path, list(results))
+
+
+def check_path_and_config(path: Path) -> None:
+    """
+    Check whether the given path exists and the cinfigureation file can be found.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    if not os.path.exists(path):
+        raise FileNotFoundError(f"Corrlib path {path} does not exist.")
+    config_path = path / CONFIG_FILENAME
+    if not os.path.exists(config_path):
+        raise FileNotFoundError(f"Configuration file {config_path} not found.")
+
+
+def check_config_validity(path: Path) -> None:
+    """
+    Check whether the configuration file of the given corrlib-dataset path is valid.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    config = ConfigParser()
+    config_path = path / CONFIG_FILENAME
+    if os.path.exists(config_path):
+        config.read(config_path)
+    else:
+        raise FileNotFoundError("Configuration file not found.")
+
+    if config.has_section('core'):
+        core_opts = ['version', 'tracker', 'cached']
+        has_core_opts = [config.has_option('core', opt) for opt in core_opts]
+        if not all(has_core_opts):
+            raise ValueError("One of the options in the 'core' section  ('version', 'tracker', 'cached') is missing.")
+
+    if config.has_section('paths'):
+        has_path_opts = [config.has_option('paths', opt) for opt in path_opts]
+        if not all(has_path_opts):
+            raise ValueError("One of the options in the 'path' section  ('db', 'projects_path', 'archive_path', 'toml_imports_path', 'import_scripts_path') is missing.")
+
+
+def check_paths(path: Path) -> None:
+    """
+    Check whether all paths demanded by the 'paths' section of the configuration-file exist.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    config = ConfigParser()
+    config_path = path / CONFIG_FILENAME
+    if os.path.exists(config_path):
+        config.read(config_path)
+    else:
+        raise FileNotFoundError("Configuration file not found.")
+    has_paths = [os.path.exists(path / config.get('paths', opt)) for opt in path_opts]
+    if not all(has_paths):
+        raise FileNotFoundError("One of the paths specified in the configuration file is not present.")
+
+
+def full_integrity_check(path: Path) -> None:
+    """
+    Aggregate all checks for easy validation of the backlog-library.
+
+    Parameters
+    ----------
+    path: Path
+        Path to the backlog-library to check.
+    """
+    print("Run full integrity check...")
+    check_path_and_config(path)
+    print("(1/5) Path and config-file exist: ✅")
+    check_config_validity(path)
+    print("(2/5) Configuration is valid: ✅")
+    check_paths(path)
+    print("(3/5) Needed paths exist: ✅")
+    check_db_integrity(path)
+    print("(4/5) Database is sane: ✅")
+    check_db_file_links(path)
+    print("(5/5) DB2File and File2DB-links are sound: ✅")
+    print("Full integrity check: ✅")
+
+

corrlib/main.py

@@ -27,7 +27,7 @@ def create_project(path: Path, uuid: str, owner: Union[str, None]=None, tags: Un
         The code that was used to create the measurements.
     """
     db_file = get_db_file(path)
-    db = os.path.join(path, db_file)
+    db = path / db_file
     get(path, db_file)
     conn = sqlite3.connect(db)
     c = conn.cursor()
@@ -67,7 +67,7 @@ def update_project_data(path: Path, uuid: str, prop: str, value: Union[str, None
     """
     db_file = get_db_file(path)
     get(path, db_file)
-    conn = sqlite3.connect(os.path.join(path, db_file))
+    conn = sqlite3.connect(path / db_file)
     c = conn.cursor()
     c.execute(f"UPDATE projects SET '{prop}' = '{value}' WHERE id == '{uuid}'")
     conn.commit()
@@ -77,9 +77,8 @@ def update_project_data(path: Path, uuid: str, prop: str, value: Union[str, None
 
 def update_aliases(path: Path, uuid: str, aliases: list[str]) -> None:
     db_file = get_db_file(path)
-    db = path / db_file
     get(path, db_file)
-    known_data = _project_lookup_by_id(db, uuid)[0]
+    known_data = _project_lookup_by_id(path, uuid)[0]
     known_aliases = known_data[1]
 
     if aliases is None:

corrlib/meas_io.py

@@ -11,6 +11,7 @@ from .tracker import get, save, unlock
 import shutil
 from typing import Any
 from pathlib import Path
+from .integrity import _check_db2paths
 
 
 CACHE_DIR = ".cache"
@@ -36,6 +37,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
     parameter_file: str
         The parameter file used for the measurement.
     """
+    path = Path(path)
     db_file = get_db_file(path)
     db = path / db_file
 
@@ -49,7 +51,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
     c = conn.cursor()
     for corr in measurement.keys():
         file_in_archive = Path('.') / 'archive' / ensemble / corr / str(uuid + '.json.gz')
-        file = path / file_in_archive
+        file = Path(path) / file_in_archive
         known_meas = {}
         if not os.path.exists(path / 'archive' / ensemble / corr):
             os.makedirs(path / 'archive' / ensemble / corr)
@@ -59,7 +61,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
                 if file not in files_to_save:
                     unlock(path, file_in_archive)
                     files_to_save.append(file_in_archive)
-                known_meas = pj.load_json_dict(file, verbose=False)
+                known_meas = pj.load_json_dict(str(file), verbose=False)
         if code == "sfcf":
             if parameter_file is not None:
                 parameters = sfcf.read_param(path, uuid, parameter_file)
@@ -74,9 +76,24 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
             ms_type = list(measurement.keys())[0]
             if ms_type == 'ms1':
                 if parameter_file is not None:
-                    parameters = openQCD.read_ms1_param(path, uuid, parameter_file)
+                    if parameter_file.endswith(".ms1.in"):
+                        parameters = openQCD.load_ms1_infile(path, uuid, parameter_file)
+                    elif parameter_file.endswith(".ms1.par"):
+                        parameters = openQCD.load_ms1_parfile(path, uuid, parameter_file)
                 else:
-                    raise Exception("Need parameter file for this code!")
+                    # Temporary solution
+                    parameters = {}
+                    parameters["rand"] = {}
+                    parameters["rw_fcts"] = [{}]
+                    for nrw in range(1):
+                        if "nsrc" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["nsrc"] = 1
+                        if "mu" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["mu"] = "None"
+                        if "np" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["np"] = "None"
+                        if "irp" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["irp"] = "None"
                 pars = {}
                 subkeys = []
                 for i in range(len(parameters["rw_fcts"])):
@@ -88,7 +105,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
                     pars[subkey] = json.dumps(parameters["rw_fcts"][i])
             elif ms_type in ['t0', 't1']:
                 if parameter_file is not None:
-                    parameters = openQCD.read_ms3_param(path, uuid, parameter_file)
+                    parameters = openQCD.load_ms3_infile(path, uuid, parameter_file)
                 else:
                     parameters = {}
                     for rwp in ["integrator", "eps", "ntot", "dnms"]:
@@ -113,7 +130,7 @@ def write_measurement(path: Path, ensemble: str, measurement: dict[str, dict[str
                 c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
                                                 (corr, ensemble, code, meas_path, uuid, pars[subkey], parameter_file))
         conn.commit()
-        pj.dump_dict_to_json(known_meas, file)
+        pj.dump_dict_to_json(known_meas, str(file))
     conn.close()
     save(path, message="Add measurements to database", files=files_to_save)
     return
@@ -138,7 +155,7 @@ def load_record(path: Path, meas_path: str) -> Union[Corr, Obs]:
     return load_records(path, [meas_path])[0]
 
 
-def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] = {}) -> list[Union[Corr, Obs]]:
+def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] = {}, dry_run: bool = False) -> list[Union[Corr, Obs]]:
     """
     Load a list of records by their paths.
 
@@ -148,14 +165,20 @@ def load_records(path: Path, meas_paths: list[str], preloaded: dict[str, Any] =
         Path of the correlator library.
     meas_paths: list[str]
         A list of the paths to the correlator in the backlog system.
-    perloaded: dict[str, Any]
+    preloaded: dict[str, Any]
-        The data that is already prelaoded. Of interest if data has alread been loaded in the same script.
+        The data that is already preloaded. Of interest if data has alread been loaded in the same script.
+    dry_run: bool
+        Do not load datda, just check whether we can reach the data we are interested in.
 
     Returns
     -------
-    retruned_data: list
+    returned_data: list
         The loaded records.
     """
+    path = Path(path)
+    if dry_run:
+        _check_db2paths(path, meas_paths)
+        return []
     needed_data: dict[str, list[str]] = {}
     for mpath in meas_paths:
         file = mpath.split("::")[0]
@@ -175,7 +198,7 @@ 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], cache_path(path, file, key))
+                    dump_object(preloaded[file][key], str(cache_path(path, file, key)))
     return returned_data
 
 
@@ -195,7 +218,7 @@ 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 / CACHE_DIR
+    cache_path = Path(path) / CACHE_DIR
     for directory in cache_path_list:
         cache_path /= directory
     return cache_path
@@ -217,6 +240,7 @@ def cache_path(path: Path, file: str, key: str) -> Path:
     cache_path: str
         The path at which the measurement of the given file and key is cached.
     """
+    path = Path(path)
     cache_path = cache_dir(path, file) / key
     return cache_path
 
@@ -237,8 +261,9 @@ def preload(path: Path, file: Path) -> dict[str, Any]:
     filedict: dict[str, Any]
         The data read from the file.
     """
+    path = Path(path)
     get(path, file)
-    filedict: dict[str, Any] = pj.load_json_dict(path / file)
+    filedict: dict[str, Any] = pj.load_json_dict(str(path / file))
     print("> read file")
     return filedict
 
@@ -255,7 +280,7 @@ def drop_record(path: Path, meas_path: str) -> None:
         The measurement path as noted in the database.
     """
     file_in_archive = meas_path.split("::")[0]
-    file = path / file_in_archive
+    file = Path(path) / file_in_archive
     db_file = get_db_file(path)
     db = path / db_file
     get(path, db_file)
@@ -269,11 +294,11 @@ def drop_record(path: Path, meas_path: str) -> None:
         raise ValueError("This measurement does not exist as an entry!")
 
     conn.commit()
-    known_meas = pj.load_json_dict(file)
+    known_meas = pj.load_json_dict(str(file))
     if sub_key in known_meas:
         del known_meas[sub_key]
         unlock(path, Path(file_in_archive))
-        pj.dump_dict_to_json(known_meas, file)
+        pj.dump_dict_to_json(known_meas, str(file))
         save(path, message="Drop measurements to database", files=[db, file])
         return
     else:
@@ -289,6 +314,7 @@ def drop_cache(path: Path) -> None:
     path: str
         The path of the library.
     """
+    path = Path(path)
     cache_dir = path / ".cache"
     for f in os.listdir(cache_dir):
         shutil.rmtree(cache_dir / f)

corrlib/pars/openQCD/__init__.py

@@ -0,0 +1,3 @@
+
+from . import ms1 as ms1
+from . import qcd2 as qcd2

corrlib/pars/openQCD/flags.py

@@ -0,0 +1,59 @@
+"""
+Reconstruct the outputs of flags.
+"""
+
+import struct
+from typing import Any, BinaryIO
+
+# lat_parms.c
+def lat_parms_write_lat_parms(fp: BinaryIO) -> dict[str, Any]:
+        """
+        NOTE: This is a duplcation from qcd2.
+        Unpack the lattice parameters written by write_lat_parms.
+        """
+        lat_pars = {}
+        t = fp.read(16)
+        lat_pars["N"] = list(struct.unpack('iiii', t)) # lattice extends
+        t = fp.read(8)
+        nk, isw = struct.unpack('ii', t) # number of kappas and isw parameter
+        lat_pars["nk"] = nk
+        lat_pars["isw"] = isw
+        t = fp.read(8)
+        lat_pars["beta"] = struct.unpack('d', t)[0] # beta
+        t = fp.read(8)
+        lat_pars["c0"] = struct.unpack('d', t)[0]
+        t = fp.read(8)
+        lat_pars["c1"] = struct.unpack('d', t)[0]
+        t = fp.read(8)
+        lat_pars["csw"] = struct.unpack('d', t)[0] # csw factor
+        kappas = []
+        m0s = []
+        # read kappas
+        for ik in range(nk):
+            t = fp.read(8)
+            kappas.append(struct.unpack('d', t)[0])
+            t = fp.read(8)
+            m0s.append(struct.unpack('d', t)[0])
+        lat_pars["kappas"] = kappas
+        lat_pars["m0s"] = m0s
+        return lat_pars
+
+
+def lat_parms_write_bc_parms(fp: BinaryIO) -> dict[str, Any]:
+        """
+        NOTE: This is a duplcation from qcd2.
+        Unpack the boundary parameters written by write_bc_parms.
+        """
+        bc_pars: dict[str, Any] = {}
+        t = fp.read(4)
+        bc_pars["type"] = struct.unpack('i', t)[0] # type of hte boundaries
+        t = fp.read(104)
+        bc_parms = struct.unpack('d'*13, t)
+        bc_pars["cG"] = list(bc_parms[:2]) # boundary gauge field improvement
+        bc_pars["cF"] = list(bc_parms[2:4]) # boundary fermion field improvement
+        phi: list[list[float]] = [[], []]
+        phi[0] = list(bc_parms[4:7])
+        phi[1] = list(bc_parms[7:10])
+        bc_pars["phi"] = phi
+        bc_pars["theta"] = list(bc_parms[10:])
+        return bc_pars

corrlib/pars/openQCD/ms1.py

@@ -0,0 +1,30 @@
+from . import flags
+
+from typing import Any
+from pathlib import Path
+
+
+def read_qcd2_ms1_par_file(fname: Path) -> dict[str, dict[str, Any]]:
+    """
+    The subroutines written here have names according to the openQCD programs and functions that write out the data.
+    Parameters
+    ----------
+    fname: Path
+        Location of the parameter file.
+
+    Returns
+    -------
+    par_dict: dict
+        Dictionary holding the parameters specified in the given file.
+    """
+
+    with open(fname, "rb") as fp:
+        lat_par_dict = flags.lat_parms_write_lat_parms(fp)
+        bc_par_dict = flags.lat_parms_write_bc_parms(fp)
+        fp.close()
+    par_dict = {}
+    par_dict["lat"] = lat_par_dict
+    par_dict["bc"] = bc_par_dict
+    return par_dict
+
+

corrlib/pars/openQCD/qcd2.py

@@ -0,0 +1,29 @@
+from . import flags
+
+from pathlib import Path
+from typing import Any
+
+
+def read_qcd2_par_file(fname: Path) -> dict[str, dict[str, Any]]:
+    """
+    The subroutines written here have names according to the openQCD programs and functions that write out the data.
+
+    Parameters
+    ----------
+    fname: Path
+        Location of the parameter file.
+
+    Returns
+    -------
+    par_dict: dict
+        Dictionary holding the parameters specified in the given file.
+    """
+
+    with open(fname, "rb") as fp:
+        lat_par_dict = flags.lat_parms_write_lat_parms(fp)
+        bc_par_dict = flags.lat_parms_write_bc_parms(fp)
+        fp.close()
+    par_dict = {}
+    par_dict["lat"] = lat_par_dict
+    par_dict["bc"] = bc_par_dict
+    return par_dict

corrlib/sql.py

@@ -0,0 +1,17 @@
+import sqlite3
+from .tools import get_db_file
+from pathlib import Path
+from typing import Any
+
+
+def thin_sql_wrapper(path: Path, stmt: str) -> list[Any]:
+    db_file = get_db_file(path)
+    db = path / db_file
+    conn = sqlite3.connect(db)
+    c = conn.cursor()
+
+    c.execute(stmt)
+    results = c.fetchall()
+    conn.commit()
+    conn.close()
+    return results

corrlib/toml.py

@@ -158,6 +158,10 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
     copy_file: bool, optional
         Whether the toml-files will be copied into the library. Default is True.
     """
+    if not os.path.exists(path):
+        raise FileNotFoundError(f"Corrlib path {path} does not exist.")
+    if not os.path.exists(file):
+        raise FileNotFoundError(f".toml-file {file} does not exist.")
     print("Import project as decribed in " + file)
     with open(file, 'rb') as fp:
         toml_dict = toml.load(fp)
@@ -178,8 +182,10 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
             update_aliases(path, uuid, aliases)
     else:
         uuid = import_project(path, project['url'], aliases=aliases)
+    imeas = 1
+    nmeas = len(measurements.keys())
     for mname, md in measurements.items():
-        print("Import measurement: " + mname)
+        print(f"Import measurement {imeas}/{nmeas}: {mname}")
         ensemble = md['ensemble']
         if project['code'] == 'sfcf':
             param = sfcf.read_param(path, uuid, md['param_file'])
@@ -192,26 +198,49 @@ def import_toml(path: Path, file: str, copy_file: bool=True) -> None:
 
         elif project['code'] == 'openQCD':
             if md['measurement'] == 'ms1':
-                param = openQCD.read_ms1_param(path, uuid, md['param_file'])
+                if 'param_file' in md.keys():
+                    parameter_file = md['param_file']
+                    if parameter_file.endswith(".ms1.in"):
+                        param = openQCD.load_ms1_infile(path, uuid, parameter_file)
+                    elif parameter_file.endswith(".ms1.par"):
+                        param = openQCD.load_ms1_parfile(path, uuid, parameter_file)
+                else:
+                    # Temporary solution
+                    parameters: dict[str, Any] = {}
+                    parameters["rand"] = {}
+                    parameters["rw_fcts"] = [{}]
+                    for nrw in range(1):
+                        if "nsrc" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["nsrc"] = 1
+                        if "mu" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["mu"] = "None"
+                        if "np" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["np"] = "None"
+                        if "irp" not in parameters["rw_fcts"][nrw]:
+                            parameters["rw_fcts"][nrw]["irp"] = "None"
+                    param = parameters
                 param['type'] = 'ms1'
                 measurement = openQCD.read_rwms(path, uuid, md['path'], param, md["prefix"], version=md["version"], names=md['names'], files=md['files'])
             elif md['measurement'] == 't0':
                 if 'param_file' in md:
-                    param = openQCD.read_ms3_param(path, uuid, md['param_file'])
+                    param = openQCD.load_ms3_infile(path, uuid, md['param_file'])
                 else:
                     param = {}
                     for rwp in ["integrator", "eps", "ntot", "dnms"]:
                         param[rwp] = "Unknown"
                 param['type'] = 't0'
                 measurement = openQCD.extract_t0(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
-                                                 fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []))
+                                                 fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []),
+                                                 r_start=md.get('r_start', []), r_stop=md.get('r_stop', []), r_step=md.get('r_step', 1))
             elif md['measurement'] == 't1':
                 if 'param_file' in md:
-                    param = openQCD.read_ms3_param(path, uuid, md['param_file'])
+                    param = openQCD.load_ms3_infile(path, uuid, md['param_file'])
                 param['type'] = 't1'
                 measurement = openQCD.extract_t1(path, uuid, md['path'], param, str(md["prefix"]), int(md["dtr_read"]), int(md["xmin"]), int(md["spatial_extent"]),
-                                                 fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []))
+                                                 fit_range=int(md.get('fit_range', 5)), postfix=str(md.get('postfix', '')), names=md.get('names', []), files=md.get('files', []),
+                                                 r_start=md.get('r_start', []), r_stop=md.get('r_stop', []), r_step=md.get('r_step', 1))
         write_measurement(path, ensemble, measurement, uuid, project['code'], (md['param_file'] if 'param_file' in md else None))
+        imeas += 1
         print(mname + " imported.")
 
     if not os.path.exists(path / "toml_imports" / uuid):

corrlib/tools.py

@@ -89,7 +89,8 @@ def set_config(path: Path, section: str, option: str, value: Any) -> None:
     value: Any
         The value we set the option to.
     """
-    config_path = os.path.join(path, CONFIG_FILENAME)
+    path = Path(path)
+    config_path = path / CONFIG_FILENAME
     config = ConfigParser()
     if os.path.exists(config_path):
         config.read(config_path)
@@ -115,7 +116,10 @@ def get_db_file(path: Path) -> Path:
     db_file: str
         The file holding the database.
     """
-    config_path = os.path.join(path, CONFIG_FILENAME)
+    path = Path(path)
+    if not os.path.exists(path):
+        raise FileNotFoundError(f"Corrlib path {path} does not exist.")
+    config_path = path / CONFIG_FILENAME
     config = ConfigParser()
     if os.path.exists(config_path):
         config.read(config_path)
@@ -140,7 +144,8 @@ def cache_enabled(path: Path) -> bool:
     cached_bool: bool
         Whether the given library is cached.
     """
-    config_path = os.path.join(path, CONFIG_FILENAME)
+    path = Path(path)
+    config_path = path / CONFIG_FILENAME
     config = ConfigParser()
     if os.path.exists(config_path):
         config.read(config_path)

corrlib/tracker.py

@@ -3,7 +3,7 @@ from configparser import ConfigParser
 import datalad.api as dl
 from typing import Optional
 import shutil
-from .tools import get_db_file
+from .tools import get_db_file, CONFIG_FILENAME
 from pathlib import Path
 
 
@@ -21,7 +21,8 @@ def get_tracker(path: Path) -> str:
     tracker: str
         The tracker used in the dataset.
     """
-    config_path = os.path.join(path, '.corrlib')
+    path = Path(path)
+    config_path = path / CONFIG_FILENAME
     config = ConfigParser()
     if os.path.exists(config_path):
         config.read(config_path)
@@ -42,6 +43,7 @@ def get(path: Path, file: Path) -> None:
     file: str
         The file to get.
     """
+    path = Path(path)
     tracker = get_tracker(path)
     if tracker == 'datalad':
         if file == get_db_file(path):
@@ -70,6 +72,7 @@ def save(path: Path, message: str, files: Optional[list[Path]]=None) -> None:
     files: list[str], optional
         The files to save. If None, all changes are saved.
     """
+    path = Path(path)
     tracker = get_tracker(path)
     if tracker == 'datalad':
         if files is not None:
@@ -93,6 +96,7 @@ def init(path: Path, tracker: str='datalad') -> None:
     tracker: str
         The tracker to use. Currently only 'datalad' and 'None' are supported.
     """
+    path = Path(path)
     if tracker == 'datalad':
         dl.create(path)
     elif tracker == 'None':
@@ -113,6 +117,7 @@ def unlock(path: Path, file: Path) -> None:
     file    : str
         The file to unlock.
     """
+    path = Path(path)
     tracker = get_tracker(path)
     if tracker == 'datalad':
         dl.unlock(os.path.join(path, file), dataset=path)
@@ -136,6 +141,7 @@ def clone(path: Path, source: str, target: str) -> None:
     target: str
         The target path to clone the dataset to.
     """
+    path = Path(path)
     tracker = get_tracker(path)
     if tracker == 'datalad':
         dl.clone(target=target, source=source, dataset=path)
@@ -159,6 +165,7 @@ def drop(path: Path, reckless: Optional[str]=None) -> None:
     reckless: Optional[str]
         The datalad's reckless option for dropping data.
     """
+    path = Path(path)
     tracker = get_tracker(path)
     if tracker == 'datalad':
         dl.drop(path, reckless=reckless)

corrlib/version.py

@@ -1,5 +1,6 @@
-# file generated by setuptools-scm
+# file generated by vcs-versioning
 # don't change, don't track in version control
+from __future__ import annotations
 
 __all__ = [
     "__version__",
@@ -10,25 +11,14 @@ __all__ = [
     "commit_id",
 ]
 
-TYPE_CHECKING = False
-if TYPE_CHECKING:
-    from typing import Tuple
-    from typing import Union
-
-    VERSION_TUPLE = Tuple[Union[int, str], ...]
-    COMMIT_ID = Union[str, None]
-else:
-    VERSION_TUPLE = object
-    COMMIT_ID = object
-
 version: str
 __version__: str
-__version_tuple__: VERSION_TUPLE
+__version_tuple__: tuple[int | str, ...]
-version_tuple: VERSION_TUPLE
+version_tuple: tuple[int | str, ...]
-commit_id: COMMIT_ID
+commit_id: str | None
-__commit_id__: COMMIT_ID
+__commit_id__: str | None
 
-__version__ = version = '0.2.4.dev71+g5e712b64c.d20260213'
+__version__ = version = '0.3.1.dev0+g08de17e6b.d20260507'
-__version_tuple__ = version_tuple = (0, 2, 4, 'dev71', 'g5e712b64c.d20260213')
+__version_tuple__ = version_tuple = (0, 3, 1, 'dev0', 'g08de17e6b.d20260507')
 
-__commit_id__ = commit_id = 'g5e712b64c'
+__commit_id__ = commit_id = 'g08de17e6b'

tests/find_test.py

@@ -3,14 +3,23 @@ import sqlite3
 from pathlib import Path
 import corrlib.initialization as cinit
 import pytest
+import pandas as pd
+import datalad.api as dl
+import datetime as dt
 
 
 def make_sql(path: Path) -> Path:
-    db = path / "test.db"
+    db = path / "backlogger.db"
     cinit._create_db(db)
     return db
 
+
+def make_config(path: Path) -> None:
+    cinit._write_config(path,  cinit._create_config(path, "datalad", False))
+
+
 def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
+    make_config(tmp_path)
     db = make_sql(tmp_path)
     conn = sqlite3.connect(db)
     c = conn.cursor()
@@ -22,7 +31,7 @@ def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
     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._project_lookup_by_alias(db, "fun_project")
+    assert uuid == find._project_lookup_by_alias(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'))",
@@ -31,3 +40,400 @@ def test_find_lookup_by_one_alias(tmp_path: Path) -> None:
     with pytest.raises(Exception):
         assert uuid == find._project_lookup_by_alias(db, "fun_project")
     conn.close()
+
+
+def test_find_lookup_by_id(tmp_path: Path) -> None:
+    make_config(tmp_path)
+    db = make_sql(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()
+    conn.close()
+    result = find._project_lookup_by_id(tmp_path, uuid)[0]
+    assert uuid == result[0]
+    assert alias_str == result[1]
+    assert tag_str == result[2]
+    assert owner == result[3]
+    assert code == result[4]
+
+
+def test_time_filter() -> None:
+    record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "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::asdfasdfasdf1", "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::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
+    record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "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::asdfasdfasdf4", "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::asdfasdfasdf5", "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...
+    record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
+
+    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')
+
+    data = [record_A, record_B, record_C, record_D, record_G]
+    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')
+
+
+def test_db_lookup(tmp_path: Path) -> None:
+    db = make_sql(tmp_path)
+    conn = sqlite3.connect(db)
+    c = conn.cursor()
+
+    corr = "f_A"
+    ensemble = "SF_A"
+    code = "openQCD"
+    meas_path = "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf"
+    uuid = "Project_A"
+    pars = "{par_A: 3.0, par_B: 5.0}"
+    parameter_file = "projects/Project_A/myinput.in"
+    c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
+                                                (corr, ensemble, code, meas_path, uuid, pars, parameter_file))
+    conn.commit()
+
+    results = find._db_lookup(db, ensemble, corr, code)
+    assert len(results) == 1
+    results = find._db_lookup(db, "SF_B", corr, code)
+    assert results.empty
+    results = find._db_lookup(db, ensemble, "g_A", code)
+    assert results.empty
+    results = find._db_lookup(db, ensemble, corr, "sfcf")
+    assert results.empty
+    results = find._db_lookup(db, ensemble, corr, code, project = "Project_A")
+    assert len(results) == 1
+    results = find._db_lookup(db, ensemble, corr, code, project = "Project_B")
+    assert results.empty
+    results = find._db_lookup(db, ensemble, corr, code, parameters = pars)
+    assert len(results) == 1
+    results = find._db_lookup(db, ensemble, corr, code, parameters = '{"par_A": 3.0, "par_B": 4.0}')
+    assert results.empty
+
+    corr = "g_A"
+    ensemble = "SF_A"
+    code = "openQCD"
+    meas_path = "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf"
+    uuid = "Project_A"
+    pars = '{"par_A": 3.0, "par_B": 4.0}'
+    parameter_file = "projects/Project_A/myinput.in"
+    c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
+                                                (corr, ensemble, code, meas_path, uuid, pars, parameter_file))
+    conn.commit()
+
+    corr = "f_A"
+    results = find._db_lookup(db, ensemble, corr, code)
+    assert len(results) == 1
+    results = find._db_lookup(db, "SF_B", corr, code)
+    assert results.empty
+    results = find._db_lookup(db, ensemble, "g_A", code)
+    assert len(results) == 1
+    results = find._db_lookup(db, ensemble, corr, "sfcf")
+    assert results.empty
+    results = find._db_lookup(db, ensemble, corr, code, project = "Project_A")
+    assert len(results) == 1
+    results = find._db_lookup(db, ensemble, "g_A", code, project = "Project_A")
+    assert len(results) == 1
+    results = find._db_lookup(db, ensemble, corr, code, project = "Project_B")
+    assert results.empty
+    results = find._db_lookup(db, ensemble, "g_A", code, project = "Project_B")
+    assert results.empty
+    results = find._db_lookup(db, ensemble, corr, code, parameters = pars)
+    assert results.empty
+    results = find._db_lookup(db, ensemble, "g_A", code, parameters = '{"par_A": 3.0, "par_B": 4.0}')
+    assert len(results) == 1
+
+    conn.close()
+
+
+def test_sfcf_drop() -> None:
+    parameters0 = {
+                    'offset': [0,0,0],
+                    'quarks': [{'mass': 1, 'thetas': [0,0,0]}, {'mass': 2, 'thetas': [0,0,1]}], # m0s = -3.5, -3.75
+                    'wf1': [[1, [0, 0]], [0.5, [1, 0]], [.75, [.5, .5]]],
+                    'wf2': [[1, [2, 1]], [2, [0.5, -0.5]], [.5, [.75, .72]]],
+                   }
+
+    assert not find._sfcf_drop(parameters0, offset=[0,0,0])
+    assert find._sfcf_drop(parameters0, offset=[1,0,0])
+
+    assert not find._sfcf_drop(parameters0, quark_kappas = [1, 2])
+    assert find._sfcf_drop(parameters0, quark_kappas = [-3.1, -3.72])
+
+    assert not find._sfcf_drop(parameters0, quark_masses = [-3.5, -3.75])
+    assert find._sfcf_drop(parameters0, quark_masses = [-3.1, -3.72])
+
+    assert not find._sfcf_drop(parameters0, qk1 = 1)
+    assert not find._sfcf_drop(parameters0, qk2 = 2)
+    assert find._sfcf_drop(parameters0, qk1 = 2)
+    assert find._sfcf_drop(parameters0, qk2 = 1)
+
+    assert not find._sfcf_drop(parameters0, qk1 = [0.5,1.5])
+    assert not find._sfcf_drop(parameters0, qk2 = [1.5,2.5])
+    assert find._sfcf_drop(parameters0, qk1 = 2)
+    assert find._sfcf_drop(parameters0, qk2 = 1)
+    with pytest.raises(ValueError):
+        assert not find._sfcf_drop(parameters0, qk1 = [0.5,1,5])
+    with pytest.raises(ValueError):
+        assert not find._sfcf_drop(parameters0, qk2 = [1,5,2.5])
+
+    assert find._sfcf_drop(parameters0, qm1 = 1.2)
+    assert find._sfcf_drop(parameters0, qm2 = 2.2)
+    assert not find._sfcf_drop(parameters0, qm1 = -3.5)
+    assert not find._sfcf_drop(parameters0, qm2 = -3.75)
+
+    assert find._sfcf_drop(parameters0, qm2 = 1.2)
+    assert find._sfcf_drop(parameters0, qm1 = 2.2)
+    with pytest.raises(ValueError):
+        assert not find._sfcf_drop(parameters0, qm1 = [0.5,1,5])
+    with pytest.raises(ValueError):
+        assert not find._sfcf_drop(parameters0, qm2 = [1,5,2.5])
+
+
+def test_openQCD_filter() -> None:
+    record_0 = ["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']
+    record_1 = ["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']
+    record_2 = ["f_P", "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']
+    record_3 = ["f_P", "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']
+    data = [
+        record_0,
+        record_1,
+        record_2,
+        record_3,
+    ]
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+    df = pd.DataFrame(data,columns=cols)
+
+    with pytest.warns(Warning):
+        find.openQCD_filter(df, a = "asdf")
+
+
+def test_code_filter() -> None:
+    record_0 = ["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']
+    record_1 = ["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']
+    record_2 = ["f_P", "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']
+    record_3 = ["f_P", "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']
+    record_4 = ["f_A", "ensA", "openQCD", "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']
+    record_5 = ["f_A", "ensA", "openQCD", "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']
+    record_6 = ["f_P", "ensA", "openQCD", "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']
+    record_7 = ["f_P", "ensA", "openQCD", "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']
+    record_8 = ["f_P", "ensA", "openQCD", "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']
+    data = [
+        record_0,
+        record_1,
+        record_2,
+        record_3,
+    ]
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+    df = pd.DataFrame(data,columns=cols)
+
+    res = find._code_filter(df, "sfcf")
+    assert len(res) == 4
+
+    data = [
+        record_4,
+        record_5,
+        record_6,
+        record_7,
+        record_8,
+    ]
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+    df = pd.DataFrame(data,columns=cols)
+
+    res = find._code_filter(df, "openQCD")
+    assert len(res) == 5
+    with pytest.raises(ValueError):
+        res = find._code_filter(df, "asdf")
+
+
+def test_find_record() -> None:
+    assert True
+
+
+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_list_projects(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))
+    uuid = "test_uuid2"
+    alias_str = "fun_project2"
+    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))
+    uuid = "test_uuid3"
+    alias_str = "fun_project3"
+    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))
+    uuid = "test_uuid4"
+    alias_str = "fun_project4"
+    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()
+    conn.close()
+    results = find.list_projects(tmp_path)
+    assert len(results) == 4
+    for i in range(4):
+        assert len(results[i]) == 2

tests/integrity_test.py

@@ -0,0 +1,189 @@
+import corrlib.integrity as integ
+import corrlib.find as find
+import datalad.api as dl
+import corrlib.initialization as cinit
+import sqlite3
+from pathlib import Path
+import os
+import pandas as pd
+import datetime as dt
+import pytest
+
+
+def test_list_ensembles(tmp_path: Path) -> None:
+    """
+    Check against the implementation in find to check if they are the same.
+    """
+    os.mkdir(tmp_path / 'archive')
+    os.mkdir(tmp_path / 'archive' / 'A')
+    os.mkdir(tmp_path / 'archive' / 'B')
+    os.mkdir(tmp_path / 'archive' / 'C')
+    integ_results = integ._list_ensembles(tmp_path)
+    assert len(integ_results) == 3
+    find_results = find.list_ensembles(tmp_path)
+    assert len(find_results) == 3
+    for f,i in zip(find_results, integ_results):
+        assert f == i
+
+
+def test_list_projects(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()
+
+    customTags = ""
+    owner = "owner"
+    code = "sfcf"
+    created_at = "today"
+    updated_at = "today"
+
+    id = "asdf1"
+    aliases = "a1,s1,d1,f1"
+    c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
+    id = "asdf2"
+    aliases = "a2,s2,d2,f2"
+    c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
+    id = "asdf3"
+    aliases = "a3,s3,d3,f3"
+    c.execute("INSERT INTO projects (id, aliases, customTags, owner, code, created_at, updated_at) VALUES (?,?,?,?,?,?,?)", (id, aliases, customTags, owner, code , created_at, updated_at))
+    conn.commit()
+    conn.close
+    integ_results = integ._list_projects(tmp_path)
+    assert len(integ_results) == 3
+    find_results = find.list_projects(tmp_path)
+    assert len(find_results) == 3
+    for f,i in zip(find_results, integ_results):
+        assert f == i
+
+
+def test_has_valid_time() -> None:
+    record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "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::asdfasdfasdf1", "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::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
+    record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "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::asdfasdfasdf4", "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::asdfasdfasdf5", "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...
+    record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+    data = [record_A, record_B, record_C, record_D, record_E]
+
+    df = pd.DataFrame(data,columns=cols)
+    for _, result in df.iterrows():
+        assert integ.has_valid_times(result)
+    data = [record_F, record_G]
+    df = pd.DataFrame(data,columns=cols)
+    for _, result in df.iterrows():
+        assert not integ.has_valid_times(result)
+
+
+def test_are_keys_unique(tmp_path: Path) -> None:
+    db = tmp_path / 'test_success.db'
+
+    record_A = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf0", "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::asdfasdfasdf1", "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::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
+    record_D = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf3", "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::asdfasdfasdf4", "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::asdfasdfasdf5", "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...
+    record_G = ["f_A", "ensA", "sfcf", "archive/SF_A/f_A/Project_A.json.gz::asdfasdfasdf2", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
+
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+
+    data = [record_A, record_B, record_C, record_D, record_E, record_F]
+    df = pd.DataFrame(data,columns=cols)
+    conn = sqlite3.connect(db)
+    df.to_sql('backlogs', conn)
+    conn.close()
+    assert integ.are_keys_unique(db, 'backlogs', 'path')
+
+    db = tmp_path / 'test_fail.db'
+    data = [record_A, record_B, record_C, record_D, record_E, record_F, record_G]
+
+    df = pd.DataFrame(data,columns=cols)
+    conn = sqlite3.connect(db)
+    df.to_sql('backlogs', conn)
+    conn.close()
+    assert not integ.are_keys_unique(db, 'backlogs', 'path')
+
+
+def test_check_path_format() -> None:
+    record_A = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "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/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "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/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', '2026-04-14 12:55:18.229966'] # created and updated later
+    record_D = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "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/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "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/ensA/f_A/Project_B.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdf", "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...
+    record_G = ["f_A", "ensA", "sfcf", "archive/ensA/f_A/Project_A.json.gz::asdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfasdfas", "SF_A", '{"par_A": 5.0, "par_B": 5.0}', "projects/SF_A/input.in",
+                '2026-03-26 12:55:18.229966', str(dt.datetime.now() + dt.timedelta(days=2, hours=3, minutes=5, seconds=30))] # created and updated later
+
+    projects = ['Project_A', 'Project_B']
+    ensembles = ['ensA']
+    cols = ["name",
+            "ensemble",
+            "code",
+            "path",
+            "project",
+            "parameters",
+            "parameter_file",
+            "created_at",
+            "updated_at"]
+
+    data = [record_A, record_B, record_C, record_D, record_E, record_F]
+    df = pd.DataFrame(data,columns=cols)
+    for _, result in df.iterrows():
+        integ.check_path_format(result, ensembles, projects)
+
+    projects = ['Project_A', 'Project_B']
+    ensembles = ['ensB']
+    for _, result in df.iterrows():
+        with pytest.raises(ValueError):
+            integ.check_path_format(result, ensembles, projects)
+
+    projects = ['Project_A', 'Project_B']
+    ensembles = ['ensA', 'ensB']
+    for _, result in df.iterrows():
+        integ.check_path_format(result, ensembles, projects)
+
+    data = [record_G]
+    df = pd.DataFrame(data,columns=cols)
+    for _, result in df.iterrows():
+        with pytest.raises(ValueError):
+            integ.check_path_format(result, ensembles, projects)

tests/tools_test.py

@@ -69,6 +69,8 @@ def test_get_db_file(tmp_path: Path) -> None:
     # config is not yet available
     tl.set_config(tmp_path, section, option, value)
     assert tl.get_db_file(tmp_path) == Path("test_value")
+    with pytest.raises(FileNotFoundError):
+        tl.get_db_file(tmp_path / "doesnotexist")
 
 
 def test_cache_enabled(tmp_path: Path) -> None:
@@ -82,3 +84,5 @@ def test_cache_enabled(tmp_path: Path) -> None:
     tl.set_config(tmp_path, section, option, "lalala")
     with pytest.raises(ValueError):
         tl.cache_enabled(tmp_path)
+    with pytest.raises(FileNotFoundError):
+        tl.cache_enabled(tmp_path / "doesnotexist")