File Converter
OpenClawd Operator Adaptation
Run this skill as part of the OpenClawd operator deck. Preserve the skill-specific workflow below, but frame outputs for Solana-native agents when relevant: prefer OpenClawd language, note whether the work can support autonomous agent operations, and keep financial, legal, tax, hiring, medical, or other regulated outputs informational unless the skill already requires a stricter disclaimer. Use the Llobster Legend persona only as light operator framing; do not let branding override accuracy, safety, or the user's stated domain.
Convert between data, document, image, audio formats, and ZIP archives. One-liners for each conversion pair.
Tool Map
| Domain | Tool | Install |
|---|---|---|
| CSV/JSON/Excel/Parquet | pandas | pip install pandas openpyxl pyarrow |
| YAML | pyyaml | pip install pyyaml |
| XML ↔ dict | xmltodict | pip install xmltodict |
| Any doc format ↔ any | pandoc (CLI) | apt install pandoc or pip install pypandoc_binary |
| Markdown → HTML | markdown | pip install markdown |
| HTML → Markdown | markdownify | pip install markdownify |
| .docx read/write | python-docx | pip install python-docx |
| PDF → text/tables | pdfplumber | pip install pdfplumber |
| PDF → images | pdf2image | pip install pdf2image + apt install poppler-utils |
| PDF manipulation | pypdf | pip install pypdf |
| Images | Pillow | pip install Pillow |
| SVG → PNG | cairosvg | pip install cairosvg |
| HEIC → JPG | pillow-heif | pip install pillow-heif |
| Audio formats | pydub | pip install pydub + apt install ffmpeg |
| EPUB ↔ other | pandoc or ebooklib | pip install ebooklib |
| HTML → PDF | weasyprint | pip install weasyprint |
| GIF creation | Pillow or imageio | pip install imageio[ffmpeg] |
| PDF → SVG | pdf2image + potrace or pymupdf | pip install pymupdf |
| ZIP archives | zipfile (stdlib) | built-in, no install needed |
File Input Handling
When a user wants to convert a file that can't be attached directly in the chat (e.g., .heic, .flac, .epub, .psd, .m4a, .wma, .parquet), ask them to upload it to the project's file system. Uploaded files typically appear in attached_assets/ or the project root. Always check both locations. If the file isn't found, ask the user where they saved it.
Common unsupported-in-chat but convertible formats: .heic, .avif, .webp, .flac, .ogg, .m4a, .wma, .aiff, .epub, .parquet, .psd, .svg, .zip
Data Formats
import pandas as pd, json, yaml, xmltodict
# --- CSV ↔ JSON ---
pd.read_csv("in.csv").to_json("out.json", orient="records", indent=2)
pd.read_json("in.json").to_csv("out.csv", index=False)
# --- CSV → Excel / Excel → CSV ---
pd.read_csv("in.csv").to_excel("out.xlsx", index=False, engine="openpyxl")
pd.read_excel("in.xlsx", sheet_name="Sheet1").to_csv("out.csv", index=False)
# All sheets: pd.read_excel("in.xlsx", sheet_name=None) → dict of DataFrames
# --- CSV → Parquet (columnar, compressed) ---
pd.read_csv("in.csv").to_parquet("out.parquet", engine="pyarrow", compression="snappy")
# --- YAML ↔ JSON ---
data = yaml.safe_load(open("in.yaml")) \# ALWAYS safe_load, never load()
json.dump(data, open("out.json", "w"), indent=2)
yaml.safe_dump(json.load(open("in.json")), open("out.yaml", "w"), sort_keys=False)
# --- XML ↔ JSON ---
data = xmltodict.parse(open("in.xml").read())
json.dump(data, open("out.json", "w"), indent=2)
open("out.xml", "w").write(xmltodict.unparse(data, pretty=True))
# --- JSONL (one JSON object per line) ---
pd.read_json("in.jsonl", lines=True).to_csv("out.csv", index=False)
Encoding gotchas:
pd.read_csv("f.csv", encoding="utf-8-sig")strips the BOM that Excel insertsAuto-detect:
import chardet; enc = chardet.detect(open("f.csv","rb").read())["encoding"]CSV delimiter sniffing:
pd.read_csv("f.csv", sep=None, engine="python")
Nested JSON → flat CSV:
pd.json_normalize(data, sep=".").to_csv("out.csv", index=False) \# {"a":{"b":1}} → column "a.b"
Document Formats — pandoc is the Swiss Army knife
# Markdown → PDF (requires LaTeX: apt install texlive-xetex)
pandoc input.md -o output.pdf --pdf-engine=xelatex
# Markdown → DOCX
pandoc input.md -o output.docx
# DOCX → Markdown (extracts images to ./media/)
pandoc input.docx -o output.md --extract-media=.
# HTML → Markdown
pandoc input.html -o output.md -t gfm
# Any → Any (pandoc supports ~40 formats)
pandoc -f docx -t rst input.docx -o output.rst
# From Python
import pypandoc
pypandoc.convert_file("in.md", "docx", outputfile="out.docx")
Without pandoc (pure Python):
# Markdown → HTML
import markdown
html = markdown.markdown(open("in.md").read(), extensions=["tables", "fenced_code", "toc"])
# HTML → Markdown
from markdownify import markdownify
md = markdownify(html, heading_style="ATX") \# ATX = \# headers, not underlines
PDF Operations
# --- Extract text + tables ---
import pdfplumber
with pdfplumber.open("in.pdf") as pdf:
text = "\n".join(p.extract_text() or "" for p in pdf.pages)
tables = pdf.pages[0].extract_tables() \# list of list-of-rows
# --- PDF → images (one PNG per page) ---
from pdf2image import convert_from_path
for i, img in enumerate(convert_from_path("in.pdf", dpi=200)):
img.save(f"page_{i+1}.png")
# --- Merge / split / rotate ---
from pypdf import PdfReader, PdfWriter
writer = PdfWriter()
for path in ["a.pdf", "b.pdf"]:
for page in PdfReader(path).pages:
writer.add_page(page)
writer.write("merged.pdf")
# Extract pages 2–5
reader = PdfReader("in.pdf")
writer = PdfWriter()
for p in reader.pages[1:5]:
writer.add_page(p)
writer.write("pages_2-5.pdf")
PDF gotchas:
pdf2imageneedspoppler-utilsinstalled system-wide (not a pip package)Scanned PDFs have no text layer — pdfplumber returns
None. UsepytesseractOCR on pdf2image output.PyPDF2is deprecated → usepypdf(same API, maintained fork)
Image Formats
from PIL import Image
# --- Basic conversion ---
Image.open("in.png").convert("RGB").save("out.jpg", quality=90)
# convert("RGB") is REQUIRED: JPEG can't store alpha channel, will raise OSError
# --- WebP (best web format) ---
Image.open("in.jpg").save("out.webp", quality=85, method=6) \# method 0-6, 6=best compression
# --- AVIF (smallest, Pillow 11+) ---
Image.open("in.jpg").save("out.avif", quality=75)
# --- HEIC (iPhone photos) → JPG ---
from pillow_heif import register_heif_opener
register_heif_opener()
Image.open("in.heic").convert("RGB").save("out.jpg", quality=90)
# --- SVG → PNG ---
import cairosvg
cairosvg.svg2png(url="in.svg", write_to="out.png", output_width=1024)
# --- Batch convert directory ---
from pathlib import Path
for p in Path("imgs").glob("*.png"):
Image.open(p).convert("RGB").save(p.with_suffix(".jpg"), quality=85)
Image gotchas:
PNG → JPG: must
convert("RGB")first or transparency crashes the savequalityfor PNG is meaningless (lossless) — useoptimize=True, compress_level=9Pillow can't open
.svgnatively — usecairosvgorsvglibGIF → MP4 is a video operation:
ffmpeg -i in.gif -pix_fmt yuv420p out.mp4
Audio Formats
from pydub import AudioSegment
# --- MP3 ↔ WAV ---
AudioSegment.from_mp3("in.mp3").export("out.wav", format="wav")
AudioSegment.from_wav("in.wav").export("out.mp3", format="mp3", bitrate="192k")
# --- FLAC → MP3 ---
AudioSegment.from_file("in.flac", format="flac").export("out.mp3", format="mp3", bitrate="320k")
# --- OGG → MP3 ---
AudioSegment.from_ogg("in.ogg").export("out.mp3", format="mp3", bitrate="192k")
# --- M4A / AAC → MP3 ---
AudioSegment.from_file("in.m4a", format="m4a").export("out.mp3", format="mp3", bitrate="256k")
# --- Any → Any (pydub supports mp3, wav, ogg, flac, m4a, aac, wma, aiff) ---
AudioSegment.from_file("in.wma", format="wma").export("out.flac", format="flac")
# --- Trim audio (first 30 seconds) ---
audio = AudioSegment.from_file("in.mp3")
audio[:30000].export("first_30s.mp3", format="mp3") \# milliseconds
# --- Merge / concatenate ---
combined = AudioSegment.from_file("a.mp3") + AudioSegment.from_file("b.mp3")
combined.export("merged.mp3", format="mp3")
# --- Adjust volume ---
audio = AudioSegment.from_file("in.mp3")
louder = audio + 6 \# +6 dB
quieter = audio - 6 \# -6 dB
louder.export("louder.mp3", format="mp3")
# --- Get audio info ---
audio = AudioSegment.from_file("in.mp3")
print(f"Duration: {len(audio)/1000:.1f}s, Channels: {audio.channels}, "
f"Sample rate: {audio.frame_rate}Hz, Sample width: {audio.sample_width*8}bit")
# --- Batch convert directory ---
from pathlib import Path
for p in Path("audio").glob("*.wav"):
AudioSegment.from_wav(str(p)).export(p.with_suffix(".mp3"), format="mp3", bitrate="192k")
Audio gotchas:
pydubrequiresffmpeginstalled system-wide for non-WAV formatsBitrate options: "128k" (small/low quality), "192k" (balanced), "256k" (high), "320k" (max for MP3)
WAV files are uncompressed — expect 10x larger file sizes than MP3
For sample rate conversion:
audio.set_frame_rate(44100).export("out.wav", format="wav")Mono to stereo:
audio.set_channels(2)/ Stereo to mono:audio.set_channels(1)
ZIP Archives
import zipfile
from pathlib import Path
# --- Create ZIP from files ---
with zipfile.ZipFile("archive.zip", "w", zipfile.ZIP_DEFLATED) as zf:
zf.write("file1.txt")
zf.write("file2.csv")
zf.write("images/photo.jpg")
# --- Create ZIP from entire directory ---
import shutil
shutil.make_archive("archive", "zip", root_dir="my_folder") \# creates archive.zip
# --- Extract all ---
with zipfile.ZipFile("archive.zip", "r") as zf:
zf.extractall("output_dir")
# --- Extract single file ---
with zipfile.ZipFile("archive.zip", "r") as zf:
zf.extract("file1.txt", "output_dir")
# --- List contents without extracting ---
with zipfile.ZipFile("archive.zip", "r") as zf:
for info in zf.infolist():
print(f"{info.filename} {info.file_size:,} bytes {info.compress_size:,} compressed")
# --- Read file from ZIP without extracting ---
with zipfile.ZipFile("archive.zip", "r") as zf:
content = zf.read("file1.txt").decode("utf-8")
# --- Add files to existing ZIP ---
with zipfile.ZipFile("archive.zip", "a") as zf:
zf.write("new_file.txt")
# --- Create ZIP with password (read-only, use pyzipper for write) ---
# pip install pyzipper
import pyzipper
with pyzipper.AESZipFile("secure.zip", "w", compression=pyzipper.ZIP_DEFLATED,
encryption=pyzipper.WZ_AES) as zf:
zf.setpassword(b"my_password")
zf.write("secret.txt")
# --- Batch: ZIP all PDFs in a directory ---
with zipfile.ZipFile("all_pdfs.zip", "w", zipfile.ZIP_DEFLATED) as zf:
for p in Path(".").glob("**/*.pdf"):
zf.write(p)
ZIP gotchas:
zipfileis in Python's standard library — no install neededAlways use
ZIP_DEFLATEDcompression (default isZIP_STORED= no compression)For password-protected ZIPs, stdlib
zipfilecan only read (not write) — usepyzipperfor encrypted writesMax file size in standard ZIP is 4 GB; use
allowZip64=True(default in Python 3) for larger filesshutil.make_archiveis the simplest way to ZIP an entire directory tree
EPUB Formats
# --- EPUB → other formats (via pandoc) ---
# pandoc is the easiest way to convert EPUB
import pypandoc
# EPUB → Markdown
pypandoc.convert_file("in.epub", "markdown", outputfile="out.md")
# EPUB → HTML
pypandoc.convert_file("in.epub", "html", outputfile="out.html")
# EPUB → DOCX
pypandoc.convert_file("in.epub", "docx", outputfile="out.docx")
# EPUB → plain text
pypandoc.convert_file("in.epub", "plain", outputfile="out.txt")
# --- Other formats → EPUB ---
# Markdown → EPUB
pypandoc.convert_file("in.md", "epub", outputfile="out.epub",
extra_args=["--metadata", "title=My Book"])
# HTML → EPUB
pypandoc.convert_file("in.html", "epub", outputfile="out.epub",
extra_args=["--metadata", "title=My Book"])
# DOCX → EPUB
pypandoc.convert_file("in.docx", "epub", outputfile="out.epub")
# --- CLI equivalents ---
pandoc in.epub -o out.md
pandoc in.epub -o out.pdf --pdf-engine=xelatex
pandoc in.md -o out.epub --metadata title="My Book"
pandoc in.html -o out.epub --metadata title="My Book" --epub-cover-image=cover.jpg
# --- Pure Python: read/write EPUB with ebooklib ---
from ebooklib import epub
# Read EPUB
book = epub.read_epub("in.epub")
for item in book.get_items_of_type(9): \# 9 = ITEM_DOCUMENT (HTML chapters)
print(item.get_name())
html_content = item.get_content().decode("utf-8")
# Create EPUB from scratch
book = epub.EpubBook()
book.set_identifier("id123")
book.set_title("My Book")
book.set_language("en")
book.add_author("Author Name")
ch1 = epub.EpubHtml(title="Chapter 1", file_name="ch1.xhtml", lang="en")
ch1.content = "<h1>Chapter 1</h1><p>Hello world.</p>"
book.add_item(ch1)
book.toc = [epub.Link("ch1.xhtml", "Chapter 1", "ch1")]
book.add_item(epub.EpubNcx())
book.add_item(epub.EpubNav())
book.spine = ["nav", ch1]
epub.write_epub("out.epub", book)
EPUB gotchas:
pandocis the simplest for format-to-format EPUB conversionAlways add
--metadata title="..."when creating EPUB — readers require a titleEPUB is essentially a ZIP of HTML files —
ebooklibgives you fine-grained controlFor EPUB → PDF, pandoc needs a LaTeX engine (
texlive-xetex)Cover images: use
--epub-cover-image=cover.jpgwith pandoc
HTML to PDF
# --- weasyprint (best CSS support, no browser needed) ---
from weasyprint import HTML
# Simple file conversion
HTML("in.html").write_pdf("out.pdf")
# From URL
HTML("https://example.com").write_pdf("page.pdf")
# From HTML string
HTML(string="<h1>Hello</h1><p>World</p>").write_pdf("out.pdf")
# With custom CSS
HTML("in.html").write_pdf("out.pdf", stylesheets=["custom.css"])
# With page size and margins
from weasyprint import CSS
HTML("in.html").write_pdf("out.pdf", stylesheets=[
CSS(string="@page { size: A4; margin: 2cm; }")
])
# Landscape orientation
HTML("in.html").write_pdf("out.pdf", stylesheets=[
CSS(string="@page { size: A4 landscape; margin: 1.5cm; }")
])
# --- CLI alternatives ---
# pandoc (simpler, less CSS fidelity)
pandoc in.html -o out.pdf --pdf-engine=xelatex
# weasyprint CLI
weasyprint in.html out.pdf
weasyprint https://example.com page.pdf
HTML to PDF gotchas:
weasyprintsupports CSS3 including flexbox, grid, and@pagerules — best for styled documentsweasyprintdoes NOT run JavaScript — for JS-heavy pages, useplaywrightorpyppeteerinsteadFor JS-rendered pages:
playwright→page.pdf()is the most reliable optionpandoc HTML → PDF goes through LaTeX, so complex CSS layouts may not render correctly
Large HTML files with many images: use
HTML(filename="in.html", base_url=".")so relative image paths resolve
GIF Creation
from PIL import Image
import imageio.v3 as iio
from pathlib import Path
# --- Images → animated GIF (Pillow) ---
frames = [Image.open(f"frame_{i}.png") for i in range(10)]
frames[0].save("out.gif", save_all=True, append_images=frames[1:],
duration=100, loop=0) \# duration in ms, loop=0 means infinite
# --- Images → GIF with optimization ---
frames = [Image.open(f"frame_{i}.png").convert("RGBA") for i in range(10)]
frames[0].save("out.gif", save_all=True, append_images=frames[1:],
duration=100, loop=0, optimize=True)
# --- Directory of images → GIF ---
frame_paths = sorted(Path("frames").glob("*.png"))
frames = [Image.open(p) for p in frame_paths]
frames[0].save("out.gif", save_all=True, append_images=frames[1:],
duration=100, loop=0)
# --- GIF → individual frames ---
gif = Image.open("in.gif")
for i in range(gif.n_frames):
gif.seek(i)
gif.save(f"frame_{i}.png")
# --- Resize GIF ---
gif = Image.open("in.gif")
resized_frames = []
for i in range(gif.n_frames):
gif.seek(i)
resized_frames.append(gif.copy().resize((320, 240), Image.LANCZOS))
resized_frames[0].save("small.gif", save_all=True, append_images=resized_frames[1:],
duration=gif.info.get("duration", 100), loop=0)
# --- Video → GIF (imageio + ffmpeg) ---
import imageio.v3 as iio
frames = iio.imread("in.mp4", plugin="pyav")
iio.imwrite("out.gif", frames, plugin="pillow", duration=40, loop=0)
# --- GIF → MP4 (ffmpeg CLI, much smaller file) ---
# ffmpeg -i in.gif -pix_fmt yuv420p -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2" out.mp4
GIF gotchas:
GIF is limited to 256 colors per frame — complex images lose quality
Use
optimize=Trueto reduce file size, but large GIFs are still huge compared to MP4durationis per-frame in milliseconds (100ms = 10 FPS, 40ms = 25 FPS)loop=0means infinite loop;loop=1plays once then stopsFor video → GIF, consider downscaling first — full-resolution GIFs are enormous
Pillow GIF output doesn't support transparency well — use
imageiofor better resultsFor best quality: create GIF from video with ffmpeg:
ffmpeg -i in.mp4 -vf "fps=15,scale=480:-1" out.gif
PDF to SVG
# --- PyMuPDF (fitz) — best quality, vector-preserving ---
import fitz \# pip install pymupdf
# Single page
doc = fitz.open("in.pdf")
page = doc[0]
svg_text = page.get_svg_image()
with open("page_1.svg", "w") as f:
f.write(svg_text)
# All pages
doc = fitz.open("in.pdf")
for i, page in enumerate(doc):
svg_text = page.get_svg_image()
with open(f"page_{i+1}.svg", "w") as f:
f.write(svg_text)
doc.close()
# With custom resolution (matrix scales the output)
doc = fitz.open("in.pdf")
page = doc[0]
mat = fitz.Matrix(2, 2) \# 2x scale for higher detail
svg_text = page.get_svg_image(matrix=mat)
with open("page_hires.svg", "w") as f:
f.write(svg_text)
# --- CLI alternatives ---
# pdf2svg (if installed)
pdf2svg in.pdf out.svg 1 \# page number
# Inkscape CLI
inkscape in.pdf --export-type=svg --export-filename=out.svg
# pdftocairo (from poppler-utils)
pdftocairo -svg in.pdf out.svg
PDF to SVG gotchas:
pymupdf(imported asfitz) produces true vector SVGs — text stays as text, paths stay as pathsScanned PDFs produce SVGs with embedded raster images (no vector data to extract)
Large PDFs with complex graphics produce very large SVG files
pdf2svgCLI tool is simple but must be installed separately (apt install pdf2svg)For rasterized SVG (simpler but not truly vector): render PDF to PNG first, then embed in SVG
Validation
Always verify output:
# Row count parity
assert len(pd.read_csv("out.csv")) == len(pd.read_json("in.json"))
# JSON well-formed
json.load(open("out.json"))
# Image opens
Image.open("out.jpg").verify()