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Create KGTK augment command #638

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Create KGTK augment command #638

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GrantXie
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@pep8speaks
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pep8speaks commented Feb 10, 2022

Hello @GrantXie! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2022-02-22 10:12:53 UTC

@GrantXie GrantXie closed this Feb 14, 2022
@GrantXie GrantXie reopened this Feb 15, 2022
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Every function should have augmented parameters. Lot of changes required. Some repeated mistakes from previous PRs. Please update

@@ -0,0 +1,177 @@
## Summary

This command will augmented graph from a KGTK Edge file with numeric value in float (or date) on node2. This command will automatically detect date in wikidata format and transform it to float in year
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Please fix the grammar. Also I can't understand what this command will do from this description. Please update


### The Output File

The output file is an edge file for each mode that contains the following columns:
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what extra edges will be added? Example?

-o OUTPUT_FILE, --output-file OUTPUT_FILE
The KGTK output file. (May be omitted or '-' for
stdout.)
--dataset DATASET Specify the location of dataset.
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what exactly is the location of dataset?

The KGTK output file. (May be omitted or '-' for
stdout.)
--dataset DATASET Specify the location of dataset.
--train-file-name TRAIN_FILE_NAME
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All these new parameters need to have longer descriptions

Specify name for training file
--numerical-literal-name NUM_LITERAL_NAME
Specify name for numerical literal file
--valid-file-name VALID_FILE_NAME
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?? I will only add this comment here, add longer description help messages

collections_raw = defaultdict(list)

if train_edges_raw is not None:
for i, row in train_edges_raw.iterrows():
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remove df.iterrows(), it is the most inefficient function

import pandas as pd
from tqdm import tqdm
from bisect import bisect
from kgtk.augment.utils import *
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import * again


def gen_plabel(pnode, unit=None):
if not unit:
return pnode + ' (Interval)'
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use f strings everywhere, be consistent

parser.add_output_file()

parser.add_argument('--dataset', dest='dataset', type=str,
default=None,
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add longer meaningful help messages

from kgtk.cli_entry import cli_entry
from kgtk.exceptions import KGTKArgumentParseException
import glob

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for all of unit tests, you have to test on content also, instead of only length

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3 participants