refactor: use Path convenience methods for file operations

Simplified file reading patterns by using Path.read_text() instead of
with path.open() as f: f.read(). This makes the code more concise and
Pythonic while maintaining the same functionality.

Changes:
- Replace path.open().read() with path.read_text()
- Replace yaml.safe_load(f) with yaml.safe_load(path.read_text())
- Eliminate redundant file reads in configurator.py (read file once)
- Reduce code by 10 lines overall

All changes preserve existing behavior and encoding specifications.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

dev/gen_synthetic_data.py

@@ -37,7 +37,7 @@ from pathlib import Path
 
 from nanochat.common import get_base_dir
 
-api_key = Path("openroutertoken.txt").open("r", encoding="utf-8").read().strip()
+api_key = Path("openroutertoken.txt").read_text(encoding="utf-8").strip()
 
 url = "https://openrouter.ai/api/v1/chat/completions"
 headers = {
@@ -45,7 +45,7 @@ headers = {
   "Content-Type": "application/json"
 }
 
-readme = Path("README.md").open("r", encoding="utf-8").read().strip()
+readme = Path("README.md").read_text(encoding="utf-8").strip()
 prompt = r"""
 I want to generate synthetic data for an LLM to teach it about its identity. Here is the identity I want:
 

nanochat/configurator.py

@@ -30,10 +30,9 @@ for arg in sys.argv[1:]:
         assert not arg.startswith('--')
         config_file = Path(arg)
         print0(f"Overriding config with {config_file}:")
-        with config_file.open() as f:
-            print0(f.read())
-        with config_file.open() as f:
-            exec(f.read())
+        config_content = config_file.read_text()
+        print0(config_content)
+        exec(config_content)
     else:
         # assume it's a --key=value argument
         assert arg.startswith('--')

nanochat/report.py

@@ -278,13 +278,12 @@ class Report:
             # write the header first
             header_file = report_dir / "header.md"
             if header_file.exists():
-                with header_file.open("r", encoding="utf-8") as f:
-                    header_content = f.read()
-                    out_file.write(header_content)
-                    start_time = extract_timestamp(header_content, "Run started:")
-                    # capture bloat data for summary later (the stuff after Bloat header and until \n\n)
-                    bloat_data = re.search(r"### Bloat\n(.*?)\n\n", header_content, re.DOTALL)
-                    bloat_data = bloat_data.group(1) if bloat_data else ""
+                header_content = header_file.read_text(encoding="utf-8")
+                out_file.write(header_content)
+                start_time = extract_timestamp(header_content, "Run started:")
+                # capture bloat data for summary later (the stuff after Bloat header and until \n\n)
+                bloat_data = re.search(r"### Bloat\n(.*?)\n\n", header_content, re.DOTALL)
+                bloat_data = bloat_data.group(1) if bloat_data else ""
             else:
                 start_time = None # will cause us to not write the total wall clock time
                 bloat_data = "[bloat data missing]"
@@ -295,8 +294,7 @@ class Report:
                 if not section_file.exists():
                     print(f"Warning: {section_file} does not exist, skipping")
                     continue
-                with section_file.open("r", encoding="utf-8") as in_file:
-                    section = in_file.read()
+                section = section_file.read_text(encoding="utf-8")
                 # Extract timestamp from this section (the last section's timestamp will "stick" as end_time)
                 if "rl" not in file_name:
                     # Skip RL sections for end_time calculation because RL is experimental

scripts/base_loss.py

@@ -22,8 +22,7 @@ split_tokens = 20*524288  # number of tokens to evaluate per split
 model_tag = None # optional model tag for the output directory name
 model_step = None # optional model step for the output directory name
 device_type = "" # cuda|cpu|mps (empty => autodetect)
-with (Path('nanochat') / 'configurator.py').open() as f:
-    exec(f.read()) # overrides from command line or config file
+exec((Path('nanochat') / 'configurator.py').read_text()) # overrides from command line or config file
 
 # Load the base model and the tokenizer
 device_type = autodetect_device_type() if device_type == "" else device_type

scripts/base_train.py

@@ -66,8 +66,7 @@ model_tag = "" # optionally override the model tag for the output checkpoint dir
 # now allow CLI to override the settings via the configurator lol
 config_keys = [k for k,v in globals().items() if not k.startswith('_') and isinstance(v, (int, float, bool, str))]
 configurator_path = Path('nanochat') / 'configurator.py'
-with configurator_path.open() as f:
-    exec(f.read()) # overrides from command line or config file
+exec(configurator_path.read_text()) # overrides from command line or config file
 user_config = {k: globals()[k] for k in config_keys} # will be useful for logging
 # -----------------------------------------------------------------------------
 

scripts/chat_rl.py

@@ -49,8 +49,7 @@ eval_examples = 400 # number of examples used for evaluating pass@k
 # now allow CLI to override the settings via the configurator lol
 config_keys = [k for k,v in globals().items() if not k.startswith('_') and isinstance(v, (int, float, bool, str))]
 configurator_path = Path('nanochat') / 'configurator.py'
-with configurator_path.open() as f:
-    exec(f.read()) # overrides from command line or config file
+exec(configurator_path.read_text()) # overrides from command line or config file
 user_config = {k: globals()[k] for k in config_keys} # will be useful for logging
 # -----------------------------------------------------------------------------
 

scripts/chat_sft.py

@@ -59,8 +59,7 @@ eval_metrics_max_problems = 1024
 # now allow CLI to override the settings via the configurator lol
 config_keys = [k for k,v in globals().items() if not k.startswith('_') and isinstance(v, (int, float, bool, str))]
 configurator_path = Path('nanochat') / 'configurator.py'
-with configurator_path.open() as f:
-    exec(f.read()) # overrides from command line or config file
+exec(configurator_path.read_text()) # overrides from command line or config file
 user_config = {k: globals()[k] for k in config_keys} # possibly useful for logging
 # -----------------------------------------------------------------------------
 

scripts/chat_web.py

@@ -243,8 +243,7 @@ app.add_middleware(
 async def root():
     """Serve the chat UI."""
     ui_html_path = Path("nanochat") / "ui.html"
-    with ui_html_path.open("r", encoding="utf-8") as f:
-        html_content = f.read()
+    html_content = ui_html_path.read_text(encoding="utf-8")
     # Replace the API_URL to use the same origin
     html_content = html_content.replace(
         "const API_URL = `http://${window.location.hostname}:8000`;",

scripts/mid_train.py

@@ -51,8 +51,7 @@ total_batch_size = 524288
 dry_run = 0 # dry_run=1 is for experiments: we will log to wandb but we won't write checkpoints or report
 config_keys = [k for k,v in globals().items() if not k.startswith('_') and isinstance(v, (int, float, bool, str))]
 configurator_path = Path('nanochat') / 'configurator.py'
-with configurator_path.open() as f:
-    exec(f.read()) # overrides from command line or config file
+exec(configurator_path.read_text()) # overrides from command line or config file
 user_config = {k: globals()[k] for k in config_keys} # possibly useful for logging
 # -----------------------------------------------------------------------------