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11 changed files with 138 additions and 67 deletions
1
.gitignore
vendored
1
.gitignore
vendored
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@ -2,3 +2,4 @@ pyerrors_corrlib.egg-info
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__pycache__
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*.egg-info
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test.ipynb
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test_ds
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@ -5,3 +5,12 @@ This is done in a reproducible way using `datalad`.
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In principle, a dataset is created, that is automatically administered by the backlogger, in which data from differnt projects are held together.
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Everything is catalogued by a searchable SQL database, which holds the paths to the respective measurements.
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The original projects can be linked to the dataset and the data may be imported using wrapper functions around the read methonds of pyerrors.
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We work with the following nomenclature in this project:
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- Measurement
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A setis of Observables, including the appropriate metadata.
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- Project
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A series of measurements that was done by one person as part of their research.
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- Record
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An entry of a single Correlator in the database of the backlogger.
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-
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25
TODO.md
25
TODO.md
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@ -1,14 +1,21 @@
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# TODO
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## Features
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- implement import of non-datalad projects
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- implement a way to use another backlog repo as a project
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- find a way to convey the mathematical structure of what EXACTLY is the form of the correlator in a specific project
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- this could e.g. be done along the lines of mandatory documentation
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- keep better track of the versions of the code, that was used for a specific measurement.
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- maybe let this be an input in the project file?
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- git repo and commit hash/version tag
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- [ ] implement import of non-datalad projects
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- [ ] implement a way to use another backlog repo as a project
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- [ ] make cache deadlock resistent (no read while writing)
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- [ ] find a way to convey the mathematical structure of what EXACTLY is the form of the correlator in a specific project
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- [ ] this could e.g. be done along the lines of mandatory documentation
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- [ ] keep better track of the versions of the code, that was used for a specific measurement.
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- [ ] maybe let this be an input in the project file?
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- [ ] git repo and commit hash/version tag
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- [ ] implement a code table?
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- [ ] parallel processing of measurements
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- [ ] extra SQL table for ensembles with UUID and aliases
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## Bugfixes
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- [ ] revisit the reimport function for single files
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- [ ] drop record needs to look if no records are left in a json file.
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## Rough Ideas
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- [ ] multitable could provide a high speed implementation of an HDF5 based format
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- [ ] implement also a way to include compiled binaries in the archives.
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@ -19,5 +19,6 @@ from .main import *
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from .import input as input
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from .initialization import *
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from .meas_io import *
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from .cache_io import *
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from .find import *
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from .version import __version__
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58
corrlib/cache_io.py
Normal file
58
corrlib/cache_io.py
Normal file
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@ -0,0 +1,58 @@
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from typing import Union, Optional
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import os
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import shutil
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from .tools import record2name_key
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from pyerrors import dump_object
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import datalad.api as dl
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import sqlite3
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def get_version_hash(path, record):
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db = os.path.join(path, "backlogger.db")
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dl.get(db, dataset=path)
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conn = sqlite3.connect(db)
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c = conn.cursor()
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c.execute(f"SELECT current_version FROM 'backlogs' WHERE path = '{record}'")
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return c.fetchall()[0][0]
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def drop_cache_files(path: str, fs: Optional[list[str]]=None):
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cache_dir = os.path.join(path, ".cache")
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if fs is None:
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fs = os.listdir(cache_dir)
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for f in fs:
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shutil.rmtree(os.path.join(cache_dir, f))
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def cache_dir(path, file):
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cache_path_list = [path]
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cache_path_list.append(".cache")
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cache_path_list.extend(file.split("/")[1:])
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cache_path = "/".join(cache_path_list)
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return cache_path
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def cache_path(path, file, sha_hash, key):
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cache_path = os.path.join(cache_dir(path, file), key + "_" + sha_hash)
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return cache_path
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def is_old_version(path, record):
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version_hash = get_version_hash(path, record)
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file, key = record2name_key(record)
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meas_cache_path = os.path.join(cache_dir(path, file))
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ls = []
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for p, ds, fs in os.walk(meas_cache_path):
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ls.extend(fs)
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for filename in ls:
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if key == filename.split("_")[0]:
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if not version_hash == filename.split("_")[1][:-2]:
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return True
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else:
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return False
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def is_in_cache(path, record):
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version_hash = get_version_hash(path, record)
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file, key = record2name_key(record)
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return os.path.exists(cache_path(path, file, version_hash, key) + ".p")
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@ -6,7 +6,7 @@ from .toml import import_tomls, update_project, reimport_project
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from .find import find_record, list_projects
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from .tools import str2list
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from .main import update_aliases
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from .meas_io import drop_cache as mio_drop_cache
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from .cache_io import drop_cache_files as cio_drop_cache_files
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import os
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@ -171,7 +171,7 @@ def drop_cache(
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"""
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Drop the currect cache directory of the dataset.
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"""
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mio_drop_cache(path)
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cio_drop_cache_files(path)
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return
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@ -21,7 +21,8 @@ def _create_db(db):
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parameters TEXT,
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parameter_file TEXT,
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created_at TEXT,
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updated_at TEXT)''')
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updated_at TEXT,
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current_version TEXT)''')
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c.execute('''CREATE TABLE IF NOT EXISTS projects
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(id TEXT PRIMARY KEY,
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aliases TEXT,
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@ -4,14 +4,14 @@ import datalad.api as dl
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import sqlite3
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from .input import sfcf,openQCD
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import json
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from typing import Union
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from pyerrors import Obs, Corr, dump_object, load_object
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from hashlib import sha256
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from .tools import cached, get_file
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import shutil
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from typing import Union, Optional
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from pyerrors import Obs, Corr, load_object, dump_object
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from hashlib import sha256, sha1
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from .tools import cached, get_file, record2name_key, name_key2record, make_version_hash
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from .cache_io import is_in_cache, cache_path, cache_dir, get_version_hash
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def write_measurement(path, ensemble, measurement, uuid, code, parameter_file=None):
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def write_measurement(path, ensemble, measurement, uuid, code, parameter_file: Optional[str]=None):
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"""
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Write a measurement to the backlog.
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If the file for the measurement already exists, update the measurement.
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@ -79,20 +79,21 @@ def write_measurement(path, ensemble, measurement, uuid, code, parameter_file=No
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subkey = "/".join(par_list)
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subkeys = [subkey]
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pars[subkey] = json.dumps(parameters)
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for subkey in subkeys:
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parHash = sha256(str(pars[subkey]).encode('UTF-8')).hexdigest()
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meas_path = file_in_archive + "::" + parHash
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known_meas[parHash] = measurement[corr][subkey]
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if c.execute("SELECT * FROM backlogs WHERE path = ?", (meas_path,)).fetchone() is not None:
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c.execute("UPDATE backlogs SET updated_at = datetime('now') WHERE path = ?", (meas_path, ))
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else:
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c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at, updated_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'), datetime('now'))",
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meas_paths = []
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for subkey in subkeys:
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par_hash = sha256(str(pars[subkey]).encode('UTF-8')).hexdigest()
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meas_path = name_key2record(file_in_archive, par_hash)
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meas_paths.append(meas_path)
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known_meas[par_hash] = measurement[corr][subkey]
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data_hash = make_version_hash(path, meas_path)
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if c.execute("SELECT * FROM backlogs WHERE path = ?", (meas_path,)).fetchone() is None:
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c.execute("INSERT INTO backlogs (name, ensemble, code, path, project, parameters, parameter_file, created_at) VALUES (?, ?, ?, ?, ?, ?, ?, datetime('now'))",
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(corr, ensemble, code, meas_path, uuid, pars[subkey], parameter_file))
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conn.commit()
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c.execute("UPDATE backlogs SET current_version = ?, updated_at = datetime('now') WHERE path = ?", (data_hash, meas_path))
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pj.dump_dict_to_json(known_meas, file)
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files.append(path + '/backlogger.db')
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conn.commit()
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files.append(db)
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conn.close()
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dl.save(files, message="Add measurements to database", dataset=path)
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@ -116,7 +117,7 @@ def load_record(path: str, meas_path: str):
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return load_records(path, [meas_path])[0]
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def load_records(path: str, meas_paths: list[str], preloaded = {}) -> list[Union[Corr, Obs]]:
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def load_records(path: str, record_paths: list[str], preloaded = {}) -> list[Union[Corr, Obs]]:
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"""
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Load a list of records by their paths.
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@ -132,41 +133,32 @@ def load_records(path: str, meas_paths: list[str], preloaded = {}) -> list[Union
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List
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"""
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needed_data: dict[str, list[str]] = {}
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for mpath in meas_paths:
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file = mpath.split("::")[0]
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for rpath in record_paths:
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file, key = record2name_key(rpath)
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if file not in needed_data.keys():
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needed_data[file] = []
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key = mpath.split("::")[1]
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needed_data[file].append(key)
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returned_data: list = []
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for file in needed_data.keys():
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for key in list(needed_data[file]):
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if os.path.exists(cache_path(path, file, key) + ".p"):
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returned_data.append(load_object(cache_path(path, file, key) + ".p"))
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record = name_key2record(file, key)
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current_version = get_version_hash(path, record)
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if is_in_cache(path, record):
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returned_data.append(load_object(cache_path(path, file, current_version, key) + ".p"))
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else:
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if file not in preloaded:
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preloaded[file] = preload(path, file)
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returned_data.append(preloaded[file][key])
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if cached:
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if not os.path.exists(cache_dir(path, file)):
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os.makedirs(cache_dir(path, file))
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dump_object(preloaded[file][key], cache_path(path, file, key))
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if not is_in_cache(path, record):
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file, key = record2name_key(record)
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if not os.path.exists(cache_dir(path, file)):
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os.makedirs(cache_dir(path, file))
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current_version = get_version_hash(path, record)
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dump_object(preloaded[file][key], cache_path(path, file, current_version, key))
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return returned_data
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def cache_dir(path, file):
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cache_path_list = [path]
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cache_path_list.append(".cache")
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cache_path_list.extend(file.split("/")[1:])
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cache_path = "/".join(cache_path_list)
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return cache_path
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def cache_path(path, file, key):
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cache_path = os.path.join(cache_dir(path, file), key)
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return cache_path
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def preload(path: str, file: str):
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get_file(path, file)
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filedict = pj.load_json_dict(os.path.join(path, file))
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@ -175,11 +167,10 @@ def preload(path: str, file: str):
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def drop_record(path: str, meas_path: str):
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file_in_archive = meas_path.split("::")[0]
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file_in_archive, sub_key = record2name_key(meas_path)
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file = os.path.join(path, file_in_archive)
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db = os.path.join(path, 'backlogger.db')
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get_file(path, 'backlogger.db')
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sub_key = meas_path.split("::")[1]
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dl.unlock(db, dataset=path)
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conn = sqlite3.connect(db)
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c = conn.cursor()
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@ -199,7 +190,3 @@ def drop_record(path: str, meas_path: str):
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else:
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raise ValueError("This measurement does not exist as a file!")
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def drop_cache(path: str):
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cache_dir = os.path.join(path, ".cache")
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for f in os.listdir(cache_dir):
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shutil.rmtree(os.path.join(cache_dir, f))
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@ -1,6 +1,6 @@
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import os
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import datalad.api as dl
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import hashlib
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def str2list(string):
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return string.split(",")
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@ -19,11 +19,18 @@ def k2m(k):
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return (1/(2*k))-4
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def get_file(path, file):
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if file == "backlogger.db":
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print("Downloading database...")
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else:
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print("Downloading data...")
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dl.get(os.path.join(path, file), dataset=path)
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print("> downloaded file")
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def record2name_key(record_path: str):
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file = record_path.split("::")[0]
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key = record_path.split("::")[1]
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return file, key
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def name_key2record(name: str, key: str):
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return name + "::" + key
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def make_version_hash(path, record):
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file, key = record2name_key(record)
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with open(os.path.join(path, file), 'rb') as fp:
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file_hash = hashlib.file_digest(fp, 'sha1').hexdigest()
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return file_hash
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2
setup.py
2
setup.py
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@ -10,7 +10,7 @@ setup(name='pycorrlib',
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version=version['__version__'],
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author='Justus Kuhlmann',
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author_email='j_kuhl19@uni-muenster.de',
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install_requires=['pyerrors>=2.11.1', 'datalad>=1.1.0', 'typer>=0.12.5'],
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install_requires=['pyerrors>=2.11.1', 'datalad>=1.1.0', 'typer>=0.12.5', 'gitpython>=3.1.45'],
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entry_points = {
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'console_scripts': ['pcl=corrlib.cli:app'],
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},
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Loading…
Add table
Add a link
Reference in a new issue