Claude Opus 5

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      "text": "# Reading JSON Files in Python\n\nPython's built-in `json` module handles this. The key function is `json.load()`.\n\n## The basic pattern\n\n```python\nimport json\n\nwith open(\"data.json\", \"r\", encoding=\"utf-8\") as f:\n    data = json.load(f)\n\nprint(data)\n```\n\nThat's it. `json.load()` reads from a file object; the `with` statement ensures the file gets closed even if something goes wrong.\n\n## `load()` vs `loads()`\n\nThis trips people up constantly:\n\n| Function | Input | Use when |\n|---|---|---|\n| `json.load(f)` | file object | reading from a file |\n| `json.loads(s)` | string (or bytes) | you already have JSON text |\n\n```python\n# From a string\ntext = '{\"name\": \"Ada\", \"age\": 36}'\ndata = json.loads(text)\n\n# Equivalent to the file version\nwith open(\"data.json\", encoding=\"utf-8\") as f:\n    data = json.loads(f.read())   # works, but load(f) is cleaner\n```\n\n## What you get back\n\nJSON types map to Python types like this:\n\n```\nobject  -> dict\narray   -> list\nstring  -> str\nnumber  -> int / float\ntrue    -> True\nfalse   -> False\nnull    -> None\n```\n\nSo access it like any nested dict/list:\n\n```python\n# data.json: {\"users\": [{\"name\": \"Ada\", \"roles\": [\"admin\"]}]}\ndata[\"users\"][0][\"name\"]        # \"Ada\"\ndata[\"users\"][0][\"roles\"][0]    # \"admin\"\n```\n\nUse `.get()` for keys that might be missing:\n\n```python\nemail = data[\"users\"][0].get(\"email\", \"unknown\")\n```\n\n## Handling errors properly\n\nReal-world files are messy. Catch the two things that actually go wrong:\n\n```python\nimport json\nfrom pathlib import Path\n\ndef read_json(path):\n    try:\n        with open(path, \"r\", encoding=\"utf-8\") as f:\n            return json.load(f)\n    except FileNotFoundError:\n        print(f\"No such file: {path}\")\n    except json.JSONDecodeError as e:\n        print(f\"Invalid JSON in {path} at line {e.lineno}, column {e.colno}: {e.msg}\")\n    return None\n\ndata = read_json(\"data.json\")\n```\n\n`JSONDecodeError` is a subclass of `ValueError`, and it carries `lineno`, `colno`, and `pos` — genuinely useful for pinpointing a bad comma.\n\n## Using `pathlib` (slightly tidier)\n\n```python\nimport json\nfrom pathlib import Path\n\ndata = json.loads(Path(\"data.json\").read_text(encoding=\"utf-8\"))\n```\n\n## Common gotchas\n\n**Always specify `encoding=\"utf-8\"`.** Without it, Python uses the platform default, which on some Windows setups is cp1252 and will blow up on non-ASCII characters. JSON is UTF-8 by spec.\n\n**JSON Lines (`.jsonl`) is a different format.** One JSON object per line — `json.load()` will fail. Parse line by line:\n\n```python\nwith open(\"data.jsonl\", encoding=\"utf-8\") as f:\n    records = [json.loads(line) for line in f if line.strip()]\n```\n\n**Trailing commas and comments aren't valid JSON.** `{\"a\": 1,}` or `// comment` will raise `JSONDecodeError`. If you're stuck with such files, use the `json5` or `commentjson` package.\n\n**Huge files:** `json.load()` builds the whole structure in memory. For files that don't fit, use a streaming parser like [`ijson`](https://pypi.org/project/ijson/):\n\n```python\nimport ijson\n\nwith open(\"huge.json\", \"rb\") as f:\n    for record in ijson.items(f, \"users.item\"):\n        process(record)\n```\n\n## Writing it back out\n\nFor completeness:\n\n```python\nwith open(\"out.json\", \"w\", encoding=\"utf-8\") as f:\n    json.dump(data, f, indent=2, ensure_ascii=False)\n```\n\n`indent=2` makes it human-readable; `ensure_ascii=False` keeps non-ASCII characters as-is instead of escaping them to `\\uXXXX`."
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