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""" |
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2
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Caching. |
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""" |
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5
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from __future__ import annotations |
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import abc |
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import shutil |
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from pathlib import Path |
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from typing import Union |
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import pandas as pd |
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import requests |
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from pocketutils.core.hashers import Hasher |
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from mandos import logger |
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from mandos.model import MandosResources |
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from mandos.model.taxonomy import Taxonomy |
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hasher = Hasher("sha1") |
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class TaxonomyFactory(metaclass=abc.ABCMeta): |
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def load(self, taxon: int) -> Taxonomy: |
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raise NotImplementedError() |
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class UniprotTaxonomyCache(TaxonomyFactory, metaclass=abc.ABCMeta): |
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""" |
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Preps a new taxonomy file for use in mandos. |
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Just returns if a corresponding file already exists in the resources dir or mandos cache (``~/.mandos``). |
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32
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Otherwise, downloads a tab-separated file from UniProt. |
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(To find manually, follow the ``All lower taxonomy nodes`` link and click ``Download``.) |
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Then applies fixes and reduces the file size, creating a new file alongside. |
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Puts both the raw data and fixed data in the cache under ``~/.mandos/taxonomy/``. |
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""" |
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def load_by_name(self, taxon: str) -> Taxonomy: |
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39
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vertebrata = Taxonomy.from_path(MandosResources.path("7742.tab.gz")) |
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only = vertebrata.req_only_by_name(taxon) |
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return vertebrata.subtree(only.id) |
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def load(self, taxon: Union[int, str]) -> Taxonomy: |
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""" |
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Tries, in order: |
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1. A cached file exactly matching the taxon ID |
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2. A taxon ID under vertebrata |
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3. The UNIQUE name of a taxon under vertebrata |
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4. Downloads the taxonomy with the specified ID |
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""" |
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if isinstance(taxon, str) and taxon.isdigit(): |
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taxon = int(taxon) |
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if isinstance(taxon, int): |
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path = self._resolve_non_vertebrate_final(taxon) |
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if path.exists(): |
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return Taxonomy.from_path(path) |
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vertebrata = Taxonomy.from_path(MandosResources.path("7742.tab.gz")) |
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if isinstance(taxon, int) and taxon in vertebrata: |
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return vertebrata.subtree(taxon) |
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elif isinstance(taxon, str): |
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match = vertebrata.req_only_by_name(taxon).id |
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return vertebrata.subtree(match) |
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if isinstance(taxon, int): |
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raw_path = self._resolve_non_vertebrate_raw(taxon) |
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if not raw_path.exists(): |
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self._download(raw_path, taxon) |
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self._fix(raw_path, taxon, path) |
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return Taxonomy.from_path(path) |
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else: |
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raise LookupError(f"Could not find taxon {taxon}; try passing an ID instead") |
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def _resolve_non_vertebrate_final(self, taxon: int) -> Path: |
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raise NotImplementedError() |
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76
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def _resolve_non_vertebrate_raw(self, taxon: int) -> Path: |
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raise NotImplementedError() |
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79
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def _download(self, raw_path: Path, taxon: int) -> None: |
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80
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# this is faster and safer than using pd.read_csv(url) |
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# https://uniprot.org/taxonomy/?query=ancestor:7742&format=tab&force=true&columns=id&compress=yes |
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url = f"https://uniprot.org/taxonomy/?query=ancestor:{taxon}&format=tab&force=true&columns=id&compress=yes" |
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with requests.get(url, stream=True) as r: |
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with raw_path.open("wb") as f: |
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shutil.copyfileobj(r.raw, f) |
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hasher.to_write(raw_path).write() |
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def _fix(self, raw_path: Path, taxon: int, final_path: Path): |
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# now process it! |
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# unfortunately it won't include an entry for the root ancestor (`taxon`) |
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# so, we'll add it in |
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df = pd.read_csv(raw_path, sep="\t") |
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93
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# find the scientific name of the parent |
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scientific_name = self._determine_name(df, taxon) |
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# now fix the columns |
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df = df[["Taxon", "Scientific name", "Parent"]] |
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df.columns = ["taxon", "scientific_name", "parent"] |
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# now add the ancestor back in |
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df = df.append( |
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pd.Series(dict(taxon=taxon, scientific_name=scientific_name, parent=0)), |
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ignore_index=True, |
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) |
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# write it to a csv.gz |
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df["parent"] = df["parent"].astype(int) |
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df.to_csv(final_path, index=False, sep="\t") |
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def _determine_name(self, df: pd.DataFrame, taxon: int) -> str: |
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got = df[df["Parent"] == taxon] |
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if len(got) == 0: |
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raise ValueError(f"Could not infer scientific name for {taxon}") |
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z = str(list(got["Lineage"])[0]) |
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return z.split("; ")[-1].strip() |
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114
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115
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class FixedTaxonomyFactory(TaxonomyFactory): |
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def __init__(self, tax: Taxonomy): |
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self._tax = tax |
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def load(self, taxon: Union[int, str]) -> Taxonomy: |
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if isinstance(taxon, str): |
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taxon = self._tax.req_only_by_name(taxon).id |
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return self._tax.subtree(taxon) |
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124
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125
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class FixedFileTaxonomyFactory(TaxonomyFactory): |
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def __init__(self, path: Path): |
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self._path = path |
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def load(self, taxon: Union[int, str]) -> Taxonomy: |
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taxonomy = Taxonomy.from_path(self._path) |
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if isinstance(taxon, str): |
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taxon = taxonomy.req_only_by_name(taxon).id |
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return taxonomy.subtree(taxon) |
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135
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136
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class CacheDirTaxonomyCache(UniprotTaxonomyCache): |
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def __init__(self, cache_dir: Path): |
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self.cache_dir = cache_dir |
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def _resolve_non_vertebrate_final(self, taxon: int) -> Path: |
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return self._get_resource(f"{taxon}.tab.gz") |
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143
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def _resolve_non_vertebrate_raw(self, taxon: int) -> Path: |
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return self._get_resource(f"taxonomy-ancestor_{taxon}.tab.gz") |
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146
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def _get_resource(self, *nodes: Union[Path, str]) -> Path: |
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path = MandosResources.path(*nodes) |
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if path.exists(): |
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return path |
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self.cache_dir.mkdir(parents=True, exist_ok=True) |
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return Path(self.cache_dir, *nodes) |
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153
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154
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class TaxonomyFactories: |
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""" |
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156
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Collection of static factory methods. |
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157
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""" |
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158
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159
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@classmethod |
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160
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def from_vertebrata(cls) -> TaxonomyFactory: |
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161
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return CacheDirTaxonomyCache(MandosResources.path("7742.tab.gz")) |
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163
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@classmethod |
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164
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def from_uniprot(cls, cache_dir: Path) -> TaxonomyFactory: |
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165
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return CacheDirTaxonomyCache(cache_dir) |
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166
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167
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@classmethod |
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168
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def from_fixed_file(cls, cache_dir: Path) -> TaxonomyFactory: |
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169
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return FixedFileTaxonomyFactory(cache_dir) |
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171
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172
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__all__ = ["TaxonomyFactory", "TaxonomyFactories"] |
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dmyersturnbull /
mandos
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