[hanzi-flash] single mode + misc modifications

- indexing changed
- readme updated
- output is now stdout

hanzi-flash/README.md

@@ -1,10 +1,74 @@
 # hanzi-flash
 
-Generate flashcards for a range of frequent hanzi characters.
+Generate flashcards in CSV format for a range of frequent hanzi words.
 
-There are multiple sources for words:
+This is based on the
+[hsk CSV](https://github.com/plaktos/hsk_csv)
+repo, including common usage words graded by difficulty.
+These form the vocabulary of the HSK (hanzi proficiency exam).
 
-- [hanziDB CSV](https://github.com/ruddfawcett/hanziDB.csv) (purely frequency based)
-- [hsk CSV](https://github.com/plaktos/hsk_csv) (common usage words, graded by difficulty)
+## usage
 
-Be careful to keep the filenames as `hanzi_db.csv` and `hsk*.csv` because the script tries to recognize these.
+This script requires the HSK vocabulary in a CSV file.
+The expected format is word, pronunciation in pinyin, and definition.
+You may combine all levels into a single file as such:
+
+```
+git clone https://github.com/plaktos/hsk_csv
+cd hsk_csv
+cat hsk*.csv > all_hsk.csv
+```
+
+To use the script, put this `all_hsk.csv` file in the same directory, or pass the path explicitly with the `-i/--input` flag.
+CSV output goes to stdout, which can be redirected to a file.
+For example, this generates a flashcard deck for the entire HSK vocabulary:
+
+```
+python hanzi_flash.py -i ./all_hsk.csv > output.csv
+```
+
+## ranges
+
+HSK's 6 levels have increasingly large vocabulary.
+This script can help you divide this into more digestible chunks.
+Specify the `-s/--start` and `-e/--end` options to only output a range of characters.
+For example, the first 50 characters:
+
+```
+python hanzi_flash.py -s 1 -e 50
+```
+
+Or, the next 50:
+
+```
+python hanzi_flash.py -s 51 -e 100
+```
+
+Once generated, use your flashcard app's merge feature after importing both these decks.
+
+## single character mode
+
+HSK's vocabulary is in words, not in individual characters.
+Pass the `-S/--single` flag to break up the words into characters.
+The flashcard will have a single character, and the answer will be its pronunciations and example words containing it.
+This is intended as a supplement to the regular word flashcard decks.
+
+Single mode respects the range options above,
+and only outputs new, unique, characters
+that appear first in the given range.
+It will also not duplicate flashcards for words that are single characters.
+
+For example, take the following invocations, with and without single mode:
+
+```
+$ python hanzi_flash.py -s 17 -e 19
+电脑,diàn nǎo (computer)
+电视,diàn shì (television)
+电影,diàn yǐng (movie)
+$ python hanzi_flash.py -s 17 -e 19 --single
+脑,nǎo / 电脑
+视,shì / 电视
+影,yǐng / 电影
+```
+
+Single mode only picks out the new characters (电 was learned before the given range `17-19`).

hanzi-flash/hanzi_flash.py

@@ -2,31 +2,64 @@
 """
 Generate flashcards for a range of frequent hanzi characters.
 
-Based on https://github.com/ruddfawcett/hanziDB.csv
+See attached README for more information.
 """
 
 import csv
 import itertools
 import argparse
-import re
+import sys
 from pathlib import Path
 
 parser = argparse.ArgumentParser()
-parser.add_argument("-s", "--start", default=0, type=int)
+parser.add_argument("-s", "--start", default=1, type=int)
 parser.add_argument("-e", "--end", default=99999999, type=int)
-parser.add_argument("-O", "--output", default="hanzi_flash.csv", type=Path)
-parser.add_argument("-i", "--input", default="hanzi_db.csv", type=Path)
+parser.add_argument("-i", "--input", default="all_hsk.csv", type=Path)
+parser.add_argument(
+    "-S",
+    "--single",
+    action="store_true",
+    help="Output unique single characters instead of words.",
+)
 args = parser.parse_args()
 
-offset = 1
+prev: set[str] = set()
+"""Characters from previous single character card decks."""
 
-fname: str = args.input.stem
-if fname.startswith("hsk"):
-    offset = 0
+single: set[str] = set()
+"""Already single characters."""
+
+uniq: dict[str, set[str]] = {}
+"""Character to words mapping."""
+
+prons: dict[str, set[str]] = {}
+"""Character to pronunciations mapping."""
 
 with open(args.input) as csv_file:
     reader = csv.reader(csv_file)
-    with open(args.output, "w") as outp_file:
-        writer = csv.writer(outp_file)
-        for row in itertools.islice(reader, args.start, args.end + 1):
-            writer.writerow([row[offset], f"{row[offset+1]} ({row[offset+2]})"])
+    writer = csv.writer(sys.stdout)
+    start = 0 if args.single else args.start - 1
+    for i, row in enumerate(itertools.islice(reader, start, args.end)):
+        word, pron, mean = row[:3]
+        if args.single:
+            if len(word) > 1:
+                for sound, char in zip(pron.lower().split(), word):
+                    if i < args.start - 1:
+                        prev.add(char)
+                    elif char not in prev:
+                        if char not in uniq:
+                            uniq[char] = set()
+                            prons[char] = set()
+                        uniq[char].add(word)
+                        prons[char].add(sound)
+            else:
+                single.add(word[0])
+        else:
+            writer.writerow([word, f"{pron} ({mean})"])
+
+    if args.single:
+        for char in uniq:
+            if char not in single:
+                writer.writerow(
+                    [char, f"{', '.join(prons[char])} / {' '.join(uniq[char])}"]
+                )