How GFF3 attributes (9th column) varies from one gene prediction algorithm to another
The first place to start is the GFF3 specification. This is the official word on what is and is not allowed in a GFF3 file. For example, users can define arbitrary attribute keys, so long as they do not begin with an uppercase letter (these are reserved for "official" use).

But your question doesn't seem to be about what is allowed, but what is commonly used. I have a question for you: which gene predictors are YOU using? Or are you using gene annotations produced by others?

Here are a few examples.

NCBI RefSeq

If you're using GFF3 from NCBI, chances are it looks something like this.

NC_007070.3     Gnomon  gene    329235  331223  .       +       .       ID=gene14;Dbxref=BEEBASE:GB42168,GeneID:551678;Name=LOC551678;gbkey=Gene;gene=LOC551678;gene_biotype=protein_coding
NC_007070.3     Gnomon  mRNA    329235  331223  .       +       .       ID=rna27;Parent=gene14;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;Name=XM_624067.4;gbkey=mRNA;gene=LOC551678;model_evidence=Supporting evidence includes similarity to: 66 ESTs%2C 24 Proteins%2C and 99%25 coverage of the annotated genomic feature by RNAseq alignments%2C including 113 samples with support for all annotated introns;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3     Gnomon  exon    329235  329459  .       +       .       ID=id117;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3     Gnomon  exon    329850  330082  .       +       .       ID=id118;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3     Gnomon  exon    330166  330301  .       +       .       ID=id119;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3     Gnomon  exon    330376  331223  .       +       .       ID=id120;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3     Gnomon  CDS     329333  329459  .       +       0       ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3     Gnomon  CDS     329850  330082  .       +       2       ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3     Gnomon  CDS     330166  330301  .       +       0       ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3     Gnomon  CDS     330376  330416  .       +       2       ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1


MAKER

The MAKER annotation workflow (paper, software) is a pretty commonly used gene annotation tool, and produces GFF3 output like this.

scaffold_12     maker   gene    652527  655343  .       +       .       ID=maker-scaffold_12-augustus-gene-0.959;Name=maker-scaffold_12-augustus-gene-0.959
scaffold_12     maker   mRNA    652527  655343  .       +       .       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1;Parent=maker-scaffold_12-augustus-gene-0.959;Name=maker-scaffold_12-augustus-gene-0.959-mRNA-1;_AED=0.24;_eAED=0.18;_QI=0|0|0|0.66|0.5|0.33|3|0|218
scaffold_12     maker   exon    652527  652817  .       +       .       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1203;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   exon    654877  655170  .       +       .       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1204;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   exon    655272  655343  .       +       .       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1205;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   CDS     652527  652817  .       +       0       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   CDS     654877  655170  .       +       0       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   CDS     655272  655343  .       +       0       ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12     maker   gene    941547  943897  .       +       .       ID=snap-scaffold_12-processed-gene-0.851;Name=snap-scaffold_12-processed-gene-0.851
scaffold_12     maker   mRNA    941547  943897  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1;Parent=snap-scaffold_12-processed-gene-0.851;Name=snap-scaffold_12-processed-gene-0.851-mRNA-1;_AED=0.22;_eAED=0.22;_QI=0|0|0.25|0.25|1|1|4|661|95
scaffold_12     maker   exon    941547  941631  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1206;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   exon    942343  942367  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1207;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   exon    942780  942920  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1208;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   exon    943200  943897  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1209;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   CDS     941547  941631  .       +       0       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   CDS     942343  942367  .       +       2       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   CDS     942780  942920  .       +       1       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   CDS     943200  943236  .       +       1       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12     maker   three_prime_UTR 943237  943897  .       +       .       ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:three_prime_utr;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1


GeneMark, SNAP, Augustus

If we look at the output of several common ab initio gene prediction tools, none of them actually produces GFF3 by default. Here is some output from GeneMark (paper, software).

543   1   +  Initial         799051     799097         47          1 2 - -
543   2   +  Terminal        799236     799266         31          3 3 - -

544   3   -  Terminal        802357     802514        158          3 2 - -
544   2   -  Internal        802607     802685         79          1 1 - -
544   1   -  Initial         802829     802843         15          3 1 - -


Here is some output from SNAP (paper, software).

Einit   8230    8239    +       9.329   0       1       0       scaffold_12-snap.4
Exon    8848    8869    +       2.484   2       2       2       scaffold_12-snap.4
Exon    10121   10208   +       15.302  1       0       2       scaffold_12-snap.4
Exon    11361   11420   +       5.969   0       0       2       scaffold_12-snap.4
Exon    11471   11535   +       0.921   0       2       1       scaffold_12-snap.4
Eterm   12169   12187   +       18.163  1       0       1       scaffold_12-snap.4
Einit   14569   14668   +       -6.918  0       1       0       scaffold_12-snap.5
Exon    15029   15203   +       -1.023  2       2       0       scaffold_12-snap.5
Exon    16171   16307   +       -9.230  1       1       1       scaffold_12-snap.5
Eterm   16667   16698   +       9.829   2       0       0       scaffold_12-snap.5
Einit   17809   17898   -       -5.390  0       0       0       scaffold_12-snap.6
Exon    17299   17350   -       6.978   0       1       2       scaffold_12-snap.6
Eterm   17029   17129   -       -2.857  2       0       0       scaffold_12-snap.6


Both of these formats appear to be tab-delimited, but that's where the similarity with GFF3 ends.

The output of Augustus (paper, software) looks like GTF (a variant of the GFF format) once you lose all the lines beginning with a # symbol, but Augustus also has a GFF3 output mode.

# Predicted genes for sequence number 1 on both strands
# start gene g1
scaffold_12     AUGUSTUS        gene    2841    3400    1       +       .       g1
scaffold_12     AUGUSTUS        transcript      2841    3400    1       +       .       g1.t1
scaffold_12     AUGUSTUS        start_codon     2841    2843    .       +       0       transcript_id "g1.t1"; gene_id "g1";
scaffold_12     AUGUSTUS        intron  3027    3097    1       +       .       transcript_id "g1.t1"; gene_id "g1";
scaffold_12     AUGUSTUS        CDS     2841    3026    1       +       0       transcript_id "g1.t1"; gene_id "g1";
scaffold_12     AUGUSTUS        CDS     3098    3400    1       +       0       transcript_id "g1.t1"; gene_id "g1";
scaffold_12     AUGUSTUS        stop_codon      3398    3400    .       +       0       transcript_id "g1.t1"; gene_id "g1";
# protein sequence = [MAIKNAEHDLRVIVDAIEGLGLKVAPHKTEAMAFPASALCGRRGAAPPKIRLGGSSILVGSRSRWYISGHSENSSKSP
# RTEGKETTPLQQRDPLDAPLWVSGVVAHCCGGPEGQEGCPGLAAQGSDQGVLRIRDGLLCGYDGCGDHRPRPSDSSAGGGLCRP]
# end gene g1
###
# start gene g2
scaffold_12     AUGUSTUS        gene    4712    15229   0.21    +       .       g2
scaffold_12     AUGUSTUS        transcript      4712    15229   0.21    +       .       g2.t1
scaffold_12     AUGUSTUS        start_codon     4712    4714    .       +       0       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        intron  4858    5591    0.74    +       .       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        intron  5686    15028   0.23    +       .       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        CDS     4712    4857    0.72    +       0       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        CDS     5592    5685    0.42    +       1       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        CDS     15029   15229   0.43    +       0       transcript_id "g2.t1"; gene_id "g2";
scaffold_12     AUGUSTUS        stop_codon      15227   15229   .       +       0       transcript_id "g2.t1"; gene_id "g2";
# protein sequence = [MGRNSHRSCCVVNCKITSAKSDCKFYKFPTAKWKINQRKMWVAAVKRQKYIKDEISHAETQTEITEVTGATKVNYANK
# KYICLLFVRTYVLRMLVDVALSNLRFSLFGIRKSLEIFGQSEKADQTRWRLPSCEMEWIESRKGKMRE]
# end gene g2
###


Parsing attributes

So...how should YOU handle attributes in GFF3's 9th column? That depends a lot on what you want to do with the data.

The most important attributes are ID and Parent, which are used to define relationships between features and subfeatures. (These relationships implicitly define a directed acyclic graph of features, although most GFF3 parsers don't directly support traversal of this graph.)

But not only do you have to handle the pre-defined attributes discussed in the GFF3 specification, you also have to be able to handle any number of arbitrary attributes whose keys you may not know beforehand.

The simplest way to handle this would be to parse the attribute column into a dictionary of key/value pairs. Once it's in this form, it's trivial to see what attributes are there and how to access them.

For example, if we have a feature with the following attributes...

ID=mRNA42;Parent=gene19;integrity=0.95;foo=bar


...we would want it in a dictionary like so.

attributes = {
    'ID': 'mrna42',
    'Parent': 'gene19',
    'integrity': '0.95',
    'foo': 'bar',
}


Python code to parse that might look something like this.

attributes = dict()
for keyvaluepair in attributestring.split(';'):
    for key, value in keyvaluepair.split('='):
        attributes[key] = value


One thing to consider is that it's possible for an attribute to have multiple values (separated by commas). It's not commonly used, but it is valid and something that should be handled or at least checked for.