File Converter

Convert between data, document, image, audio formats, and ZIP archives. One-liners for each conversion pair.

Tool Map

pandas

pip install pandas openpyxl pyarrow

pyyaml

pip install pyyaml

xmltodict

pip install xmltodict

apt install pandoc

pip install pypandoc_binary

markdown

pip install markdown

markdownify

pip install markdownify

python-docx

pip install python-docx

pdfplumber

pip install pdfplumber

pdf2image

pip install pdf2image

apt install poppler-utils

pypdf

pip install pypdf

Pillow

pip install Pillow

cairosvg

pip install cairosvg

pillow-heif

pip install pillow-heif

pydub

pip install pydub

apt install ffmpeg

ebooklib

pip install ebooklib

weasyprint

pip install weasyprint

Pillow

imageio

pip install imageio[ffmpeg]

pdf2image

potrace

pymupdf

pip install pymupdf

zipfile

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 inserts
• Auto-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:

• pdf2image

  needs

  poppler-utils

  installed system-wide (not a pip package)
• Scanned PDFs have no text layer — pdfplumber returns

  None

  . Use

  pytesseract

  OCR on pdf2image output.

• PyPDF2

  is deprecated → use

  pypdf

  (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 save

• quality

  for PNG is meaningless (lossless) — use

  optimize=True, compress_level=9

• Pillow can't open

  .svg

  natively — use

  cairosvg

  or

  svglib

• GIF → 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:

• pydub

  requires

  ffmpeg

  installed system-wide for non-WAV formats
• Bitrate 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:

• zipfile

  is in Python's standard library — no install needed
• Always use

  ZIP_DEFLATED

  compression (default is

  ZIP_STORED

  = no compression)
• For password-protected ZIPs, stdlib

  zipfile

  can only read (not write) — use

  pyzipper

  for encrypted writes
• Max file size in standard ZIP is 4 GB; use

  allowZip64=True

  (default in Python 3) for larger files

• shutil.make_archive

  is 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:

• pandoc

  is the simplest for format-to-format EPUB conversion
• Always add

  --metadata title="..."

  when creating EPUB — readers require a title
• EPUB is essentially a ZIP of HTML files —

  ebooklib

  gives you fine-grained control
• For EPUB → PDF, pandoc needs a LaTeX engine (

  texlive-xetex

  )
• Cover images: use

  --epub-cover-image=cover.jpg

  with 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:

• weasyprint

  supports CSS3 including flexbox, grid, and

  @page

  rules — best for styled documents

• weasyprint

  does NOT run JavaScript — for JS-heavy pages, use

  playwright

  or

  pyppeteer

  instead
• For JS-rendered pages:

  playwright

  →

  page.pdf()

  is the most reliable option
• pandoc 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=True

  to reduce file size, but large GIFs are still huge compared to MP4

• duration

  is per-frame in milliseconds (100ms = 10 FPS, 40ms = 25 FPS)

• loop=0

  means infinite loop;

  loop=1

  plays once then stops
• For video → GIF, consider downscaling first — full-resolution GIFs are enormous
• Pillow GIF output doesn't support transparency well — use

  imageio

  for better results
• For 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 as

  fitz

  ) produces true vector SVGs — text stays as text, paths stay as paths
• Scanned PDFs produce SVGs with embedded raster images (no vector data to extract)
• Large PDFs with complex graphics produce very large SVG files

• pdf2svg

  CLI 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()