argsearch 0.3.0

Run a command many times with different combinations of its inputs.

argsearch

argsearch is a simple and composable tool for sweeping over the arguments of another program. It aims to easily automate tasks like hyperparameter tuning and setting simulation parameters, while only requiring that your program accepts command-line arguments in some form.

Key features include:

• Easy integration with any program that takes command-line arguments.
• Support for searching over integer, floating-point, and categorical arguments with several search strategies.
• Smart search algorithms, including Bayesian optimization and low-discrepancy random search.
• The ability to produce JSON-structured output, making it composable with other command-line tools like jq.
• Multiprocessing, enabling running many experiments in parallel.

Examples

Basic usage

$ argsearch grid 3 "echo {a} {b}" --a 1 10 --b X Y
--- [0] echo 1 X
1 X
--- [1] echo 5 X
5 X
--- [2] echo 10 X
10 X
--- [3] echo 1 Y
1 Y
--- [4] echo 5 Y
5 Y
--- [5] echo 10 Y
10 Y
100%|██████████████████████████████| 6/6 [00:00<00:00, 220.49it/s]

Composing pipelines with argsearch and jq

$ argsearch --output-json repeat 2 "echo hello" | jq
[
  {
    "step": 0,
    "command": "echo hello",
    "stdout": "hello\n",
    "stderr": "",
    "returncode": 0
  },
  {
    "step": 1,
    "command": "echo hello",
    "stdout": "hello\n",
    "stderr": "",
    "returncode": 0
  }
]

$ argsearch --output-json random 5 "echo {x}" --x LOG 1e-3 1e3 | jq -j '.[] | .stdout' | sort
0.00346280772906192
0.026690253595621032
0.08766768693592873
0.24965066831702154
291.68909574884617

Black-box optimization

$ argsearch maximize 13 "echo {a}" --a 1 1000  | tail
--- [8] echo 249
249
--- [9] echo 116
116
--- [10] echo 999
999
--- [11] echo 1000
1000
--- [12] echo 1000
1000

Installation

pip install argsearch

Usage

argsearch has 3 mandatory arguments:

• A search strategy (random, quasirandom, grid, repeat, maximize, or minimize) and its configuration:
  • For random, quasirandom, maximize, and minimize: the number of trials to run.
  • For grid: the number of points to try in each numeric range.
  • For repeat: the number of times to repeat the command.
• A command string with templates designated by bracketed names (e.g. 'python my_script.py --flag {value}'.
• A range for each template in the command string (e.g. --value 1 100).

Then, argsearch runs the command string several times, each time replacing the templates with values from their associated ranges.

Any optional arguments (--num-workers, --output-json, or --disable-bar) must appear before these. I recommend you single-quote the command string to avoid shell expansion issues. Templates may appear multiple times in the command string (e.g. to name an experiment's output directory after its hyperparameters).

Search Strategies

The search strategy determines which commands get run by sampling from the ranges. The search strategies currently implemented are:

• Random search samples uniformly randomly from specified ranges for a fixed number of trials.
• Quasirandom search samples quasi-randomly according to a low-discrepancy Sobol sequence. This is recommended over random search in almost all cases because it fills the search space more effectively and avoids redundant experiments.
• Grid search divides each numeric range into a fixed number of evenly-spaced points and runs once for each possible combination of inputs.
• Repeat runs the same command a fixed number of times, and does not accept templates.
• Minimize tries to minimize the program's output with Bayesian black-box optimization.
• Maximize is like minimize, but for maximization.

Maximize and minimize both require that your program's last line of stdout is a single number, representing the quantity to optimize.

Ranges

For each template that appears in the command string, you must provide a range that determines what values may be substituted into the template. Three types of ranges are available:

• Floating-point ranges are specified by a minimum and maximum floating-point value (e.g. --value 0.0 1e3).
• Integer ranges are specified by a minimum and maximum integer (e.g. --value 1 100). Integer ranges are guaranteed to only yield integer values.
• Categorical ranges are specified by a list of non-numeric categories, or more than two numbers (e.g. --value A B C, --value 2 4 8 16). Categorical ranges only draw values from the listed categories, and are not divided up during a grid search.

Floating-point and integer ranges may be converted to logarithmic ranges by specifying LOG before their minimum and maximum (e.g. --value LOG 16 256). These ranges are gridded and sampled log-uniformly instead of uniformly, so that each order of magnitude appears roughly equally often.

Output

By default, argsearch streams each command's output to the standard output/error streams as soon as it's available. With the --output-json flag, argsearch will instead collect all output into a JSON string, printed to stdout at the end of the run. This JSON data can be pretty-printed or wrangled with jq for use in shell pipelines.

Multiprocessing

Providing --num-workers N runs commands in parallel with N worker processes. In this case, output will only appear on the standard streams once each command's done, to avoid mixing output from different runs. The format remains the same, but results are not guaranteed to come back in any particular order.

License

argsearch is licensed under the MIT License.