BadGzipFile get_progeny

[thommetz]

Describe the bug
When using any other organism than 'human', a BadGzipFile error occurs. I tried using different species (mouse, rat, pig, dog,...) and different names and IDs (e.g. mouse, mus musculus, NCBI ID '10090' for mouse).

To Reproduce
import decoupler as dc
progeny = dc.get_progeny(organism="mus musculus", top=500)

Expected behavior
Return of a DataFrame as noted in the documentation of decoupler.get_progeny

System

• OS: Windows 11
• Python version: 3.11.8
• Versions of libraries involved: decoupler 1.8.0

[deeenes]

Hello, Could you please include a full traceback? A corrupted gzip file suggests an accidental download issue. I recommend wiping the cache of omnipath or pypath (depending on where the traceback leads us):

# omnipath:
rm ~/.cache/omnipathdb/*

# pypath:
rm ~/.cache/pypath/*

...and try loading the dataset again. It's also good to make sure you perform the downloads with a good network connection. Edit: I see you use Windows, in this case change ~/.cache according to your system, you can find it by from pypath.share import cache; cache.get_cachedir().

[thommetz]

Hi, thanks for the prompt answer!
Unfortunately even after whiping the cache, the problem still occurs. If using 'human' as organism, it works fine.
Here you can find the full traceback.

Downloading data from `https://omnipathdb.org/queries/enzsub?format=json`
Downloading data from `https://omnipathdb.org/queries/interactions?format=json`
Downloading data from `https://omnipathdb.org/queries/complexes?format=json`
Downloading data from `https://omnipathdb.org/queries/annotations?format=json`
Downloading data from `https://omnipathdb.org/queries/intercell?format=json`
Downloading data from `https://omnipathdb.org/about?format=text`
Downloading annotations for all proteins from the following resources: `['PROGENy']`
Downloading data from `https://omnipathdb.org/annotations?format=tsv&resources=PROGENy`
 39.0M/? [00:04<00:00, 14.4MB/s]
---------------------------------------------------------------------------
BadGzipFile                               Traceback (most recent call last)
Cell In[5], line 1
----> 1 progeny = dc.get_progeny(organism="mus musculus", top=500)

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:250, in get_progeny(organism, top, genesymbol_resource, **kwargs)
    248 p = p.drop('record_id', axis=1)
    249 p.columns.name = None
--> 250 p = _annotation_identifiers(p, organism, genesymbol_resource)
    251 p = p[['pathway', 'genesymbol', 'weight', 'p_value']]
    252 p = p[~p.duplicated(['pathway', 'genesymbol'])]

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:919, in _annotation_identifiers(net, organism, genesymbol_resource)
    906 def _annotation_identifiers(
    907         net: pd.DataFrame,
    908         organism: str | int,
   (...)
    914         ) = None,
    915         ) -> pd.DataFrame:
    917     if not _is_human(organism):
--> 919         net = translate_net(
    920             net,
    921             columns='uniprot',
    922             id_type='uniprot',
    923             source_organism=9606,
    924             target_organism=organism,
    925         )
    927     if genesymbol_resource is False:
    929         net['genesymbol'] = net['uniprot']

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:758, in translate_net(net, columns, source_organism, target_organism, id_type, unique_by, **kwargs)
    755 hom_net = net.copy()
    757 # Translate
--> 758 hom_net = orthology.translate_df(
    759     df=hom_net,
    760     target=_target_organism,
    761     cols=columns,
    762     source=_source_organism,
    763 )
    765 unique_by = common.to_list(unique_by)
    767 if unique_by and all(c in hom_net.columns for c in unique_by):
    768 
    769     # Remove duplicated based on source and target

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:2262, in translate_df(df, target, source, cols, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, **kwargs)
   2259 args.pop('manager')
   2260 args.pop('kwargs')
-> 2262 return manager.translate_df(**args, **kwargs)

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:620, in OrthologyManager.translate_df(self, df, target, source, cols, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, **kwargs)
    618 args.pop('self')
    619 args['id_type'] = _id_type
--> 620 ortho_df = self.get_df(**args)
    622 table = self.which_table(
    623     target = target,
    624     source = source,
   (...)
    627     resource = 'oma',
    628 )
    630 df = table.translate_df(
    631     df = df,
    632     cols = [c for c, i in cols.items() if i == _id_type],
    633     ortho_df = ortho_df,
    634 )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:515, in OrthologyManager.get_df(self, target, source, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, full_records, **kwargs)
    511     if not param[resource]:
    513         continue
--> 515     table = self.which_table(
    516         target = target,
    517         source = source,
    518         only_swissprot = only_swissprot,
    519         id_type = id_type,
    520         resource = resource,
    521     )
    523     result.append(
    524         table.df(
    525             full_records = full_records,
   (...)
    531         )
    532     )
    534 return pd.concat(result)

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:233, in OrthologyManager.which_table(self, target, source, only_swissprot, resource, id_type)
    229 self.expiry[key] = time.time()
    231 if key not in self.tables:
--> 233     self.load(key)
    235 if key in self.tables:
    237     return self.tables[key]

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:242, in OrthologyManager.load(self, key)
    240 def load(self, key):
--> 242     self.tables[key] = globals()[f'{key.resource.capitalize()}Orthology'](
    243         target = key.target,
    244         source = key.source,
    245         only_swissprot = key.only_swissprot,
    246         id_type = key.id_type,
    247     )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:1492, in OmaOrthology.__init__(self, target, source, id_type, only_swissprot, rel_type, score)
   1462 def __init__(
   1463         self,
   1464         target: int | str,
   (...)
   1472         score: float | None = None,
   1473     ):
   1474     """
   1475     Orthology translation with Ensembl data.
   1476 
   (...)
   1489             Lower threshold for similarity metric.
   1490     """
-> 1492     ProteinOrthology.__init__(**locals())

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:869, in ProteinOrthology.__init__(self, target, source, id_type, only_swissprot, **kwargs)
    867 self.load_proteome(self.source)
    868 self._set_param(kwargs, *self._param)
--> 869 self.load()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:1506, in OmaOrthology.load(self)
   1502 if self._from_pickle():
   1504     return
-> 1506 oma_data = oma_input.oma_orthologs(
   1507     organism_a = self.source,
   1508     organism_b = self.target,
   1509     id_type = self.id_type,
   1510 )
   1511 self.data = collections.defaultdict(set)
   1513 for rec in oma_data:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:125, in oma_orthologs(organism_a, organism_b, id_type, rel_type, score, return_df)
    119     if (
    120         (score and rec['score'] < score) or
    121         (rel_type and rec['rel_type'] not in rel_type)
    122     ):
    123         continue
--> 125     a, b = (
    126         [
    127             OmaGene(
    128                 id = id_,
    129                 oma_group = e['oma_group'],
    130                 hog = e['oma_hog_id'],
    131                 taxon = e['species']['taxon_id'],
    132                 chr = e['chromosome'],
    133                 start = int(e['locus']['start']),
    134                 end = int(e['locus']['end']),
    135                 strand = int(e['locus']['strand']),
    136                 main_isoform = e['is_main_isoform'],
    137 
    138             )
    139             for id_ in _id_translate(
    140                 id_ = e['canonicalid'],
    141                 taxon = e['species']['taxon_id'],
    142                 id_type = id_type,
    143             )
    144         ]
    145         for e in (rec[f'entry_{ei}'] for ei in (1, 2))
    146     )
    149     result.update(
    150         {
    151             OmaOrthology(
   (...)
    159         }
    160     )
    162 if page > n_pages: break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:139, in <genexpr>(.0)
    119     if (
    120         (score and rec['score'] < score) or
    121         (rel_type and rec['rel_type'] not in rel_type)
    122     ):
    123         continue
    125     a, b = (
    126         [
    127             OmaGene(
    128                 id = id_,
    129                 oma_group = e['oma_group'],
    130                 hog = e['oma_hog_id'],
    131                 taxon = e['species']['taxon_id'],
    132                 chr = e['chromosome'],
    133                 start = int(e['locus']['start']),
    134                 end = int(e['locus']['end']),
    135                 strand = int(e['locus']['strand']),
    136                 main_isoform = e['is_main_isoform'],
    137 
    138             )
--> 139             for id_ in _id_translate(
    140                 id_ = e['canonicalid'],
    141                 taxon = e['species']['taxon_id'],
    142                 id_type = id_type,
    143             )
    144         ]
    145         for e in (rec[f'entry_{ei}'] for ei in (1, 2))
    146     )
    149     result.update(
    150         {
    151             OmaOrthology(
   (...)
    159         }
    160     )
    162 if page > n_pages: break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:244, in _id_translate(id_, taxon, id_type)
    234 if not id_type: return {id_}
    236 s_id_type = (
    237     'ensg'
    238         if id_.startswith('ENS') else
   (...)
    241     'uniprot'
    242 )
--> 244 uniprots = mapping.map_name(
    245     id_,
    246     s_id_type,
    247     'uniprot',
    248     ncbi_tax_id = taxon,
    249 )
    251 return mapping.map_names(
    252     uniprots,
    253     'uniprot',
    254     id_type,
    255     ncbi_tax_id = taxon,
    256 ) if uniprots else set()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:3551, in map_name(name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
   3498 """
   3499 Translates one instance of one ID type to a different one.
   3500 Returns set of the target ID type.
   (...)
   3546         ID, call the `uniprot_cleanup` function at the end.
   3547 """
   3549 mapper = get_mapper()
-> 3551 return mapper.map_name(
   3552     name = name,
   3553     id_type = id_type,
   3554     target_id_type = target_id_type,
   3555     ncbi_tax_id = ncbi_tax_id,
   3556     strict = strict,
   3557     expand_complexes = expand_complexes,
   3558     uniprot_cleanup = uniprot_cleanup,
   3559 )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath_common\_misc.py:2953, in ignore_unhashable.<locals>.wrapper(*args, **kwargs)
   2950 @functools.wraps(func, assigned = attributes)
   2951 def wrapper(*args, **kwargs):
   2952     try:
-> 2953         return func(*args, **kwargs)
   2954     except TypeError as error:
   2955         if 'unhashable type' in str(error):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2193, in Mapper.map_name(self, name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
   2189 # for UniProt IDs we do a few more steps to
   2190 # try to find out the primary SwissProt ID
   2191 if uniprot_cleanup and target_id_type == 'uniprot':
-> 2193     mapped_names = self.uniprot_cleanup(
   2194         uniprots = mapped_names,
   2195         ncbi_tax_id = ncbi_tax_id,
   2196     )
   2198 return mapped_names

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2227, in Mapper.uniprot_cleanup(self, uniprots, ncbi_tax_id)
   2224 # step 2: translate TrEMBL to SwissProt by gene symbols
   2225 if self._trembl_swissprot_by_genesymbol:
-> 2227     uniprots = self.trembl_swissprot(
   2228         uniprots,
   2229         ncbi_tax_id = ncbi_tax_id,
   2230     )
   2232 # step 3: translate deleted IDs by gene symbols
   2233 if self._translate_deleted_uniprot:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2868, in Mapper.trembl_swissprot(self, uniprots, ncbi_tax_id)
   2865 for uniprot in uniprots:
   2867     swissprot = None
-> 2868     genesymbols = self.map_name(
   2869         name = uniprot,
   2870         id_type = 'trembl',
   2871         target_id_type = 'genesymbol',
   2872         ncbi_tax_id = ncbi_tax_id,
   2873     )
   2875     this_swissprots = self.map_names(
   2876         names = genesymbols,
   2877         id_type = 'genesymbol',
   2878         target_id_type = 'swissprot',
   2879         ncbi_tax_id = ncbi_tax_id,
   2880     )
   2882     if not this_swissprots:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath_common\_misc.py:2953, in ignore_unhashable.<locals>.wrapper(*args, **kwargs)
   2950 @functools.wraps(func, assigned = attributes)
   2951 def wrapper(*args, **kwargs):
   2952     try:
-> 2953         return func(*args, **kwargs)
   2954     except TypeError as error:
   2955         if 'unhashable type' in str(error):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:1978, in Mapper.map_name(self, name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
   1964     mapped_names = self.chain_map(
   1965         name = name,
   1966         id_type = id_type,
   (...)
   1972         uniprot_cleanup = uniprot_cleanup,
   1973     )
   1975 else:
   1976 
   1977     # all the other ID types
-> 1978     mapped_names = self._map_name(
   1979         name = name,
   1980         id_type = id_type,
   1981         target_id_type = target_id_type,
   1982         ncbi_tax_id = ncbi_tax_id,
   1983     )
   1985 # as ID translation tables for PRO IDs are not organism specific
   1986 # we need an extra step to limit the results to the target organism
   1987 if id_type == 'pro' and target_id_type == 'uniprot':

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2510, in Mapper._map_name(self, name, id_type, target_id_type, ncbi_tax_id)
   2503 """
   2504 Once we have defined the name type and the target name type,
   2505 this function looks it up in the most suitable dictionary.
   2506 """
   2508 ncbi_tax_id = ncbi_tax_id or self.ncbi_tax_id
-> 2510 tbl = self.which_table(
   2511     id_type,
   2512     target_id_type,
   2513     ncbi_tax_id = ncbi_tax_id,
   2514 )
   2516 return tbl[name] if tbl else set()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:1562, in Mapper.which_table(self, id_type, target_id_type, load, ncbi_tax_id)
   1551 if resource:
   1553     self._log(
   1554         'Chosen built-in defined ID translation table: '
   1555         'resource=%s, id_type_a=%s, id_type_b=%s' % (
   (...)
   1559         )
   1560     )
-> 1562     self.load_mapping(
   1563         resource = resource,
   1564         load_a_to_b = load_a_to_b,
   1565         load_b_to_a = load_b_to_a,
   1566         ncbi_tax_id = ncbi_tax_id,
   1567     )
   1569     tbl = check_loaded()
   1571     break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:3208, in Mapper.load_mapping(self, resource, **kwargs)
   3195 ncbi_tax_id = kwargs.get('ncbi_tax_id', resource.ncbi_tax_id)
   3197 self._log(
   3198     'Loading mapping table for organism `%s` '
   3199     'with identifiers `%s` and `%s`, '
   (...)
   3205     )
   3206 )
-> 3208 reader = MapReader(param = resource, **kwargs)
   3210 a_to_b = reader.mapping_table_a_to_b
   3211 b_to_a = reader.mapping_table_b_to_a

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:258, in MapReader.__init__(self, param, ncbi_tax_id, entity_type, load_a_to_b, load_b_to_a, uniprots, lifetime, resource_id_types)
    255 self.uniprots = uniprots
    256 self._resource_id_types = resource_id_types
--> 258 self.load()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:288, in MapReader.load(self)
    283     self.read_cache()
    285 if not self.tables_loaded():
    286 
    287     # read from the original source
--> 288     self.read()
    290     if self.tables_loaded():
    291 
    292         # write cache only at successful loading
    293         self.write_cache()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:450, in MapReader.read(self)
    446 method = 'read_mapping_%s' % self.source_type
    448 if hasattr(self, method):
--> 450     getattr(self, method)()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:893, in MapReader.read_mapping_uniprot(self)
    891 protein_name = self.param.field == 'protein names'
    892 query.name_process = not protein_name and not trembl
--> 893 data = query.perform()
    895 if not query.name_process:
    897     def maybe_split(v):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\uniprot.py:681, in UniprotQuery.perform(self)
    669 def perform(self) -> list[str] | dict[str, str] | dict[str, dict[str, str]]:
    670     """
    671     Perform the query and preprocess the result.
    672 
   (...)
    678           kind described in the previous point as values.
    679     """
--> 681     _id, *variables = zip(*self)
    682     _id = list(map(common.sfirst, _id))
    684     if variables:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\uniprot.py:660, in UniprotQuery.__iter__(self)
    657 _proc0 = functools.partial(self._FIELDEND.sub, '')
    658 _proc1 = self._FIELDSEP.split if self.name_process else common.identity
--> 660 for line in result:
    662     line = line.strip('\n\r')
    664     if line.strip():

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\share\curl.py:766, in FileOpener.iterfile(fileobj)
    763 @staticmethod
    764 def iterfile(fileobj):
--> 766     for line in fileobj:
    768         yield line

File ~\miniconda3\envs\thomas\Lib\gzip.py:314, in GzipFile.read1(self, size)
    312 if size < 0:
    313     size = io.DEFAULT_BUFFER_SIZE
--> 314 return self._buffer.read1(size)

File ~\miniconda3\envs\thomas\Lib\_compression.py:68, in DecompressReader.readinto(self, b)
     66 def readinto(self, b):
     67     with memoryview(b) as view, view.cast("B") as byte_view:
---> 68         data = self.read(len(byte_view))
     69         byte_view[:len(data)] = data
     70     return len(data)

File ~\miniconda3\envs\thomas\Lib\gzip.py:490, in _GzipReader.read(self, size)
    484 while True:
    485     if self._decompressor.eof:
    486         # Ending case: we've come to the end of a member in the file,
    487         # so finish up this member, and read a new gzip header.
    488         # Check the CRC and file size, and set the flag so we read
    489         # a new member
--> 490         self._read_eof()
    491         self._new_member = True
    492         self._decompressor = self._decomp_factory(
    493             **self._decomp_args)

File ~\miniconda3\envs\thomas\Lib\gzip.py:536, in _GzipReader._read_eof(self)
    534 crc32, isize = struct.unpack("<II", _read_exact(self._fp, 8))
    535 if crc32 != self._crc:
--> 536     raise BadGzipFile("CRC check failed %s != %s" % (hex(crc32),
    537                                                      hex(self._crc)))
    538 elif isize != (self._stream_size & 0xffffffff):
    539     raise BadGzipFile("Incorrect length of data produced")

BadGzipFile: CRC check failed 0x6036a815 != 0x17d2a1ca

[deeenes]

Apparently a simple query to the basic UniProt API fails. We should check in the logs what was that query. In the directory where you run your session above, probably the bottom of the last log file contains the relevant information:

ls -ltra ./pypath_log/ | tail

Or you can reproduce the error and see the log file from Python:

import decoupler as dc
import pypath

mpg = dc.get_progeny(organism = 'mouse')

# error happens

pypath.log()

In the log there should be the path to the affected cache file, you can check locally what's the actual content of that file, is it indeed a truncated gzip, or is it a HTML error page? And if you could post here the last few dozens of lines from the log, it would be very helpful for me to find out about this error.

[thommetz]

I run it again trying to reproduce the error. For some reason it now gives a different error:

Downloading data from https://omnipathdb.org/queries/enzsub?format=json
Downloading data from https://omnipathdb.org/queries/interactions?format=json
Downloading data from https://omnipathdb.org/queries/complexes?format=json
Downloading data from https://omnipathdb.org/queries/annotations?format=json
Downloading data from https://omnipathdb.org/queries/intercell?format=json
Downloading data from https://omnipathdb.org/about?format=text
Downloading annotations for all proteins from the following resources: ['PROGENy']

error Traceback (most recent call last)
Cell In[5], line 1
----> 1 progeny = dc.get_progeny(organism="mouse", top=500)

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:250, in get_progeny(organism, top, genesymbol_resource, **kwargs)
248 p = p.drop('record_id', axis=1)
249 p.columns.name = None
--> 250 p = _annotation_identifiers(p, organism, genesymbol_resource)
251 p = p[['pathway', 'genesymbol', 'weight', 'p_value']]
252 p = p[~p.duplicated(['pathway', 'genesymbol'])]

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:919, in _annotation_identifiers(net, organism, genesymbol_resource)
906 def _annotation_identifiers(
907 net: pd.DataFrame,
908 organism: str | int,
(...)
914 ) = None,
915 ) -> pd.DataFrame:
917 if not _is_human(organism):
--> 919 net = translate_net(
920 net,
921 columns='uniprot',
922 id_type='uniprot',
923 source_organism=9606,
924 target_organism=organism,
925 )
927 if genesymbol_resource is False:
929 net['genesymbol'] = net['uniprot']

File ~\miniconda3\envs\thomas\Lib\site-packages\decoupler\omnip.py:758, in translate_net(net, columns, source_organism, target_organism, id_type, unique_by, **kwargs)
755 hom_net = net.copy()
757 # Translate
--> 758 hom_net = orthology.translate_df(
759 df=hom_net,
760 target=_target_organism,
761 cols=columns,
762 source=_source_organism,
763 )
765 unique_by = common.to_list(unique_by)
767 if unique_by and all(c in hom_net.columns for c in unique_by):
768
769 # Remove duplicated based on source and target

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:2262, in translate_df(df, target, source, cols, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, **kwargs)
2259 args.pop('manager')
2260 args.pop('kwargs')
-> 2262 return manager.translate_df(**args, **kwargs)

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:620, in OrthologyManager.translate_df(self, df, target, source, cols, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, **kwargs)
618 args.pop('self')
619 args['id_type'] = _id_type
--> 620 ortho_df = self.get_df(**args)
622 table = self.which_table(
623 target = target,
624 source = source,
(...)
627 resource = 'oma',
628 )
630 df = table.translate_df(
631 df = df,
632 cols = [c for c, i in cols.items() if i == _id_type],
633 ortho_df = ortho_df,
634 )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:515, in OrthologyManager.get_df(self, target, source, id_type, only_swissprot, oma, homologene, ensembl, oma_rel_type, oma_score, ensembl_hc, ensembl_types, full_records, **kwargs)
511 if not param[resource]:
513 continue
--> 515 table = self.which_table(
516 target = target,
517 source = source,
518 only_swissprot = only_swissprot,
519 id_type = id_type,
520 resource = resource,
521 )
523 result.append(
524 table.df(
525 full_records = full_records,
(...)
531 )
532 )
534 return pd.concat(result)

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:233, in OrthologyManager.which_table(self, target, source, only_swissprot, resource, id_type)
229 self.expiry[key] = time.time()
231 if key not in self.tables:
--> 233 self.load(key)
235 if key in self.tables:
237 return self.tables[key]

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:242, in OrthologyManager.load(self, key)
240 def load(self, key):
--> 242 self.tables[key] = globals()[f'{key.resource.capitalize()}Orthology'](
243 target = key.target,
244 source = key.source,
245 only_swissprot = key.only_swissprot,
246 id_type = key.id_type,
247 )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:1492, in OmaOrthology.init(self, target, source, id_type, only_swissprot, rel_type, score)
1462 def init(
1463 self,
1464 target: int | str,
(...)
1472 score: float | None = None,
1473 ):
1474 """
1475 Orthology translation with Ensembl data.
1476
(...)
1489 Lower threshold for similarity metric.
1490 """
-> 1492 ProteinOrthology.init(**locals())

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:869, in ProteinOrthology.init(self, target, source, id_type, only_swissprot, **kwargs)
867 self.load_proteome(self.source)
868 self._set_param(kwargs, *self._param)
--> 869 self.load()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\orthology.py:1506, in OmaOrthology.load(self)
1502 if self._from_pickle():
1504 return
-> 1506 oma_data = oma_input.oma_orthologs(
1507 organism_a = self.source,
1508 organism_b = self.target,
1509 id_type = self.id_type,
1510 )
1511 self.data = collections.defaultdict(set)
1513 for rec in oma_data:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:125, in oma_orthologs(organism_a, organism_b, id_type, rel_type, score, return_df)
119 if (
120 (score and rec['score'] < score) or
121 (rel_type and rec['rel_type'] not in rel_type)
122 ):
123 continue
--> 125 a, b = (
126 [
127 OmaGene(
128 id = id_,
129 oma_group = e['oma_group'],
130 hog = e['oma_hog_id'],
131 taxon = e['species']['taxon_id'],
132 chr = e['chromosome'],
133 start = int(e['locus']['start']),
134 end = int(e['locus']['end']),
135 strand = int(e['locus']['strand']),
136 main_isoform = e['is_main_isoform'],
137
138 )
139 for id_ in id_translate(
140 id = e['canonicalid'],
141 taxon = e['species']['taxon_id'],
142 id_type = id_type,
143 )
144 ]
145 for e in (rec[f'entry_{ei}'] for ei in (1, 2))
146 )
149 result.update(
150 {
151 OmaOrthology(
(...)
159 }
160 )
162 if page > n_pages: break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:139, in (.0)
119 if (
120 (score and rec['score'] < score) or
121 (rel_type and rec['rel_type'] not in rel_type)
122 ):
123 continue
125 a, b = (
126 [
127 OmaGene(
128 id = id_,
129 oma_group = e['oma_group'],
130 hog = e['oma_hog_id'],
131 taxon = e['species']['taxon_id'],
132 chr = e['chromosome'],
133 start = int(e['locus']['start']),
134 end = int(e['locus']['end']),
135 strand = int(e['locus']['strand']),
136 main_isoform = e['is_main_isoform'],
137
138 )
--> 139 for id_ in id_translate(
140 id = e['canonicalid'],
141 taxon = e['species']['taxon_id'],
142 id_type = id_type,
143 )
144 ]
145 for e in (rec[f'entry_{ei}'] for ei in (1, 2))
146 )
149 result.update(
150 {
151 OmaOrthology(
(...)
159 }
160 )
162 if page > n_pages: break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\oma.py:244, in id_translate(id, taxon, id_type)
234 if not id_type: return {id_}
236 s_id_type = (
237 'ensg'
238 if id_.startswith('ENS') else
(...)
241 'uniprot'
242 )
--> 244 uniprots = mapping.map_name(
245 id_,
246 s_id_type,
247 'uniprot',
248 ncbi_tax_id = taxon,
249 )
251 return mapping.map_names(
252 uniprots,
253 'uniprot',
254 id_type,
255 ncbi_tax_id = taxon,
256 ) if uniprots else set()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:3551, in map_name(name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
3498 """
3499 Translates one instance of one ID type to a different one.
3500 Returns set of the target ID type.
(...)
3546 ID, call the uniprot_cleanup function at the end.
3547 """
3549 mapper = get_mapper()
-> 3551 return mapper.map_name(
3552 name = name,
3553 id_type = id_type,
3554 target_id_type = target_id_type,
3555 ncbi_tax_id = ncbi_tax_id,
3556 strict = strict,
3557 expand_complexes = expand_complexes,
3558 uniprot_cleanup = uniprot_cleanup,
3559 )

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath_common_misc.py:2953, in ignore_unhashable..wrapper(*args, **kwargs)
2950 @functools.wraps(func, assigned = attributes)
2951 def wrapper(*args, **kwargs):
2952 try:
-> 2953 return func(*args, **kwargs)
2954 except TypeError as error:
2955 if 'unhashable type' in str(error):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2193, in Mapper.map_name(self, name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
2189 # for UniProt IDs we do a few more steps to
2190 # try to find out the primary SwissProt ID
2191 if uniprot_cleanup and target_id_type == 'uniprot':
-> 2193 mapped_names = self.uniprot_cleanup(
2194 uniprots = mapped_names,
2195 ncbi_tax_id = ncbi_tax_id,
2196 )
2198 return mapped_names

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2227, in Mapper.uniprot_cleanup(self, uniprots, ncbi_tax_id)
2224 # step 2: translate TrEMBL to SwissProt by gene symbols
2225 if self._trembl_swissprot_by_genesymbol:
-> 2227 uniprots = self.trembl_swissprot(
2228 uniprots,
2229 ncbi_tax_id = ncbi_tax_id,
2230 )
2232 # step 3: translate deleted IDs by gene symbols
2233 if self._translate_deleted_uniprot:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2868, in Mapper.trembl_swissprot(self, uniprots, ncbi_tax_id)
2865 for uniprot in uniprots:
2867 swissprot = None
-> 2868 genesymbols = self.map_name(
2869 name = uniprot,
2870 id_type = 'trembl',
2871 target_id_type = 'genesymbol',
2872 ncbi_tax_id = ncbi_tax_id,
2873 )
2875 this_swissprots = self.map_names(
2876 names = genesymbols,
2877 id_type = 'genesymbol',
2878 target_id_type = 'swissprot',
2879 ncbi_tax_id = ncbi_tax_id,
2880 )
2882 if not this_swissprots:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath_common_misc.py:2953, in ignore_unhashable..wrapper(*args, **kwargs)
2950 @functools.wraps(func, assigned = attributes)
2951 def wrapper(*args, **kwargs):
2952 try:
-> 2953 return func(*args, **kwargs)
2954 except TypeError as error:
2955 if 'unhashable type' in str(error):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:1978, in Mapper.map_name(self, name, id_type, target_id_type, ncbi_tax_id, strict, expand_complexes, uniprot_cleanup)
1964 mapped_names = self.chain_map(
1965 name = name,
1966 id_type = id_type,
(...)
1972 uniprot_cleanup = uniprot_cleanup,
1973 )
1975 else:
1976
1977 # all the other ID types
-> 1978 mapped_names = self._map_name(
1979 name = name,
1980 id_type = id_type,
1981 target_id_type = target_id_type,
1982 ncbi_tax_id = ncbi_tax_id,
1983 )
1985 # as ID translation tables for PRO IDs are not organism specific
1986 # we need an extra step to limit the results to the target organism
1987 if id_type == 'pro' and target_id_type == 'uniprot':

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:2510, in Mapper._map_name(self, name, id_type, target_id_type, ncbi_tax_id)
2503 """
2504 Once we have defined the name type and the target name type,
2505 this function looks it up in the most suitable dictionary.
2506 """
2508 ncbi_tax_id = ncbi_tax_id or self.ncbi_tax_id
-> 2510 tbl = self.which_table(
2511 id_type,
2512 target_id_type,
2513 ncbi_tax_id = ncbi_tax_id,
2514 )
2516 return tbl[name] if tbl else set()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:1562, in Mapper.which_table(self, id_type, target_id_type, load, ncbi_tax_id)
1551 if resource:
1553 self._log(
1554 'Chosen built-in defined ID translation table: '
1555 'resource=%s, id_type_a=%s, id_type_b=%s' % (
(...)
1559 )
1560 )
-> 1562 self.load_mapping(
1563 resource = resource,
1564 load_a_to_b = load_a_to_b,
1565 load_b_to_a = load_b_to_a,
1566 ncbi_tax_id = ncbi_tax_id,
1567 )
1569 tbl = check_loaded()
1571 break

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:3208, in Mapper.load_mapping(self, resource, **kwargs)
3195 ncbi_tax_id = kwargs.get('ncbi_tax_id', resource.ncbi_tax_id)
3197 self._log(
3198 'Loading mapping table for organism %s '
3199 'with identifiers %s and %s, '
(...)
3205 )
3206 )
-> 3208 reader = MapReader(param = resource, **kwargs)
3210 a_to_b = reader.mapping_table_a_to_b
3211 b_to_a = reader.mapping_table_b_to_a

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:258, in MapReader.init(self, param, ncbi_tax_id, entity_type, load_a_to_b, load_b_to_a, uniprots, lifetime, resource_id_types)
255 self.uniprots = uniprots
256 self._resource_id_types = resource_id_types
--> 258 self.load()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:288, in MapReader.load(self)
283 self.read_cache()
285 if not self.tables_loaded():
286
287 # read from the original source
--> 288 self.read()
290 if self.tables_loaded():
291
292 # write cache only at successful loading
293 self.write_cache()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:450, in MapReader.read(self)
446 method = 'read_mapping_%s' % self.source_type
448 if hasattr(self, method):
--> 450 getattr(self, method)()

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\utils\mapping.py:893, in MapReader.read_mapping_uniprot(self)
891 protein_name = self.param.field == 'protein names'
892 query.name_process = not protein_name and not trembl
--> 893 data = query.perform()
895 if not query.name_process:
897 def maybe_split(v):

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\uniprot.py:681, in UniprotQuery.perform(self)
669 def perform(self) -> list[str] | dict[str, str] | dict[str, dict[str, str]]:
670 """
671 Perform the query and preprocess the result.
672
(...)
678 kind described in the previous point as values.
679 """
--> 681 _id, *variables = zip(*self)
682 _id = list(map(common.sfirst, _id))
684 if variables:

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\inputs\uniprot.py:656, in UniprotQuery.iter(self)
648 c = curl.Curl(
649 self._baseurl,
650 get = self._get,
(...)
653 compr = 'gz',
654 )
655 result = c.result if c.result or self.fail_on_empty else [0].iter()
--> 656 _ = next(result)
657 _proc0 = functools.partial(self._FIELDEND.sub, '')
658 _proc1 = self._FIELDSEP.split if self.name_process else common.identity

File ~\miniconda3\envs\thomas\Lib\site-packages\pypath\share\curl.py:766, in FileOpener.iterfile(fileobj)
763 @staticmethod
764 def iterfile(fileobj):
--> 766 for line in fileobj:
768 yield line

File ~\miniconda3\envs\thomas\Lib\gzip.py:314, in GzipFile.read1(self, size)
312 if size < 0:
313 size = io.DEFAULT_BUFFER_SIZE
--> 314 return self._buffer.read1(size)

File ~\miniconda3\envs\thomas\Lib_compression.py:68, in DecompressReader.readinto(self, b)
66 def readinto(self, b):
67 with memoryview(b) as view, view.cast("B") as byte_view:
---> 68 data = self.read(len(byte_view))
69 byte_view[:len(data)] = data
70 return len(data)

File ~\miniconda3\envs\thomas\Lib\gzip.py:507, in _GzipReader.read(self, size)
504 # Read a chunk of data from the file
505 buf = self._fp.read(io.DEFAULT_BUFFER_SIZE)
--> 507 uncompress = self._decompressor.decompress(buf, size)
508 if self._decompressor.unconsumed_tail != b"":
509 self._fp.prepend(self._decompressor.unconsumed_tail)

error: Error -3 while decompressing data: invalid block type