def _main(save: bool):
click.secho(cls.name, fg='green', bold=True)
inst = cls()
stmts = inst.extract_statements()
if save:
import pystow
stmts_path = pystow.join("indra", cls.name, name="stmts.pkl")
with stmts_path.open("wb") as file:
pickle.dump(stmts, file, protocol=pickle.HIGHEST_PROTOCOL)
print_stmt_summary(stmts)
def test_get(self):
"""Test the :func:`get` function."""
parts_examples = [
[n()],
[n(), n()],
[n(), n(), n()],
]
with self.mock_directory():
for parts in parts_examples:
with self.subTest(parts=parts):
self.assertEqual(self.join(*parts), join(*parts))
def assert_io(self, obj, ext: str, dump, load):
"""Test an object can be dumped and loaded.
:param obj: The object to dump
:param ext: The extension to use
:param dump: The dump function
:param load: The load function
"""
name = f"test.{ext}"
path = pystow.join("test", name=name)
if path.is_file():
path.unlink()
self.assertFalse(path.is_file())
dump("test", name=name, obj=obj)
self.assertTrue(path.is_file())
self.assertEqual(obj, load("test", name=name))
# -*- coding: utf-8 -*-
"""Constants for ComPath's resources."""
import os
from pathlib import Path
import pystow
COMPATH_HOME = pystow.join('compath')
HERE = os.path.abspath(os.path.dirname(__file__))
ROOT = Path(os.path.abspath(os.path.join(HERE, os.pardir, os.pardir)))
RESOURCES = Path(HERE) / 'resources'
DOCS_DIRECTORY = ROOT / 'docs'
IMG_DIRECTORY = DOCS_DIRECTORY / 'img'
DATA_DIRECTORY = DOCS_DIRECTORY / 'data'
DATA_DIRECTORY.mkdir(parents=True, exist_ok=True)
_BASE_URL = 'https://raw.githubusercontent.com/ComPath/resources/master/mappings'
# Inter-database mappings URLs
KEGG_WIKIPATHWAYS_URL = f'{_BASE_URL}/kegg_wikipathways.csv'
KEGG_REACTOME_URL = f'{_BASE_URL}/kegg_reactome.csv'
WIKIPATHWAYS_REACTOME_URL = f'{_BASE_URL}/wikipathways_reactome.csv'
PATHBANK_KEGG_URL = f'{_BASE_URL}/pathbank_kegg.csv'
PATHBANK_REACTOME_URL = f'{_BASE_URL}/pathbank_reactome.csv'
PATHBANK_WIKIPATHWAYS_URL = f'{_BASE_URL}/pathbank_wikipathways.csv'
# Intra-database mappings URLS
import os
import boto3
import pystow
import logging
import botocore
from gilda import __version__
logger = logging.getLogger(__name__)
HERE = os.path.abspath(os.path.dirname(__file__))
MESH_MAPPINGS_PATH = os.path.join(HERE, 'mesh_mappings.tsv')
resource_dir = pystow.join('gilda', __version__)
GROUNDING_TERMS_BASE_NAME = 'grounding_terms.tsv'
GROUNDING_TERMS_PATH = os.path.join(resource_dir, GROUNDING_TERMS_BASE_NAME)
# Popular organisms per UniProt, see
# https://www.uniprot.org/help/filter_options
popular_organisms = [
'9606', '10090', '10116', '9913', '7955', '7227', '6239', '44689', '3702',
'39947', '83333', '224308', '559292'
]
def _download_from_s3(path, base_name):
config = botocore.client.Config(signature_version=botocore.UNSIGNED)
s3 = boto3.client('s3', config=config)
tc = boto3.s3.transfer.TransferConfig(use_threads=False)
full_key = '%s/%s' % (__version__, base_name)
out_file = os.path.join(path, base_name)
import botocore
from ftplib import FTP
from io import BytesIO, StringIO
from collections import namedtuple
from urllib.request import urlretrieve
from xml.etree import ElementTree as ET
from . import __version__
logger = logging.getLogger('protmapper.resources')
logger.setLevel(logging.INFO)
# If the protmapper resource directory does not exist, try to create it using PyStow
# Can be specified with PROTMAPPER_HOME environment variable, otherwise defaults
# to $HOME/.data/protmapper/<__version__>. The location of $HOME can be overridden with
# the PYSTOW_HOME environment variable
resource_dir_path = pystow.join('protmapper', __version__)
resource_dir = resource_dir_path.as_posix()
def _download_from_s3(key, out_file):
s3 = boto3.client(
's3',
config=botocore.client.Config(signature_version=botocore.UNSIGNED))
tc = boto3.s3.transfer.TransferConfig(use_threads=False)
# Path to the versioned resource file
full_key = 'protmapper/%s/%s' % (__version__, key)
s3.download_file('bigmech', full_key, out_file, Config=tc)
def _download_ftp(ftp_host,
ftp_path,
# -*- coding: utf-8 -*-
"""Download registry information from N2T."""
import itertools as itt
from operator import itemgetter
import click
import pystow
import yaml
from more_itertools import pairwise
URL = 'https://n2t.net/e/cdl_ebi_prefixes.yaml'
PATH = pystow.join('bioregistry', name='n2t.json')
def _parse_1(file):
lines = (line.strip() for line in file
if not line.startswith('#') and line.strip())
it = itt.groupby(lines, lambda line: line.startswith('-'))
for a, grouped_lines in it:
if a:
k, v = [
part.strip()
for part in list(grouped_lines)[0].lstrip('-').lstrip().split(
':', 1)
]
yield [(k, v)]
else:
yield [[part.strip() for part in line.split(':', 1)]
for line in grouped_lines]
# -*- coding: utf-8 -*-
"""Connection configuration for PyBEL."""
import logging
import pystow
__all__ = [
'connection',
'PYBEL_MINIMUM_IMPORT_VERSION',
'PYBEL_HOME',
]
logger = logging.getLogger(__name__)
#: The last PyBEL version where the graph data definition changed
PYBEL_MINIMUM_IMPORT_VERSION = 0, 14, 0
PYBEL_HOME = pystow.join('pybel')
DEFAULT_CACHE_NAME = 'pybel_{}.{}.{}_cache.db'.format(
*PYBEL_MINIMUM_IMPORT_VERSION)
DEFAULT_CACHE_PATH = pystow.join('pybel', name=DEFAULT_CACHE_NAME)
#: The default cache connection string uses sqlite.
DEFAULT_CACHE_CONNECTION = 'sqlite:///' + DEFAULT_CACHE_PATH.as_posix()
connection = pystow.get_config(
'pybel',
'connection',
default=DEFAULT_CACHE_CONNECTION,
)
"""
Contains paths to locations on user's system where models and resources are
to be stored. These all live in adeft's home folder which defaults to the
hidden directory ".adeft" in the user's home directory but which can be
specified by setting the environment variable ADEFT_HOME in the user's profile.
"""
import os
import pystow
from adeft import __version__
# If the adeft resource directory does not exist, try to create it using PyStow
# Can be specified with ADEFT_HOME environment variable, otherwise defaults
# to $HOME/.data/adeft/<__version__>. The location of $HOME can be overridden with
# the PYSTOW_HOME environment variable
ADEFT_HOME = pystow.join('adeft')
ADEFT_PATH = os.path.join(ADEFT_HOME, __version__)
ADEFT_MODELS_PATH = os.path.join(ADEFT_PATH, 'models')
RESOURCES_PATH = os.path.join(ADEFT_PATH, 'resources')
GROUNDINGS_FILE_PATH = os.path.join(RESOURCES_PATH, 'groundings.csv')
TEST_RESOURCES_PATH = os.path.join(ADEFT_PATH, 'test_resources')
S3_BUCKET_URL = f'https://adeft.s3.amazonaws.com/{__version__}'
import pystow
# S3 bucket for raw data
S3_BUCKET = 'bigmech'
# Path to data within bucket
S3_DATA_PATH = 'causal_precedence'
# Path to where data is stored locally
LOCAL_DATA_HOME = pystow.join('causal_precedence_training')
# Path to SIGNOR pathways
SIGNOR_PATHWAYS_DIRECTORY = pystow.join('causal_precedence_training',
'SIGNOR_pathways')
# Path to triples used as input to generate causal precedence datasets
TRIPLES_DIRECTORY = pystow.join('causal_precedence_training',
'causal_triples')
TRAINING_DATA_EXPORT_DIRECTORY = pystow.join('causal_precedence_training',
'training_data')
import datetime
import enum
import ftplib
import os
from typing import Any, ClassVar, Mapping, Optional, Union
import bioregistry
import pydantic
import pystow
import requests
import requests_ftp
from bs4 import BeautifulSoup
from cachier import cachier
BIOVERSIONS_HOME = pystow.join("bioversions")
HERE = os.path.abspath(os.path.dirname(__file__))
DOCS = os.path.abspath(os.path.join(HERE, os.pardir, os.pardir, "docs"))
IMG = os.path.join(DOCS, "img")
requests_ftp.monkeypatch_session()
class VersionType(enum.Enum):
"""Different types of versions."""
semver = "SemVer (X.Y.Z)"
date = "CalVer (YYYY-MM-DD)"
month = "CalVer (YYYY-MM)"
year = "CalVer (YYYY)"
year_minor = "CalVer (YYYY.X)"