Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More →
nano-memoize
Advanced tools
nano-memoize - npm Package Compare versions
Comparing version 1.1.4 to 1.1.5
| { | ||
| "name": "nano-memoize", | ||
| "version": "v1.1.4", | ||
| "version": "v1.1.5", | ||
| "description": "Faster than fast, smaller than micro ... a nano speed and nano size memoizer.", | ||
@@ -8,3 +8,3 @@ "engines": {}, | ||
| "scripts": { | ||
| "test": "mocha ./test/index.js", | ||
| "test": "mocha ./test/index.js", | ||
| "prepare": "cp ./src/nano-memoize.js ./index.js && cp ./src/nano-memoize.js dist/nano-memoize.js && npx bread-compressor dist && browserify ./src/nano-memoize.js -o browser/nano-memoize.js && uglifyjs browser/nano-memoize.js -o browser/nano-memoize.min.js && uglifyjs src/nano-memoize.js -o dist/nano-memoize.min.js" | ||
@@ -31,3 +31,3 @@ }, | ||
| "blanket": "^1.2.3", | ||
| "bread-compressor-cli": "^1.0.6", | ||
| "bread-compressor-cli": "^1.0.7", | ||
| "chai": "^3.4.1", | ||
@@ -37,3 +37,3 @@ "cli-table2": "^0.2.0", | ||
| "codeclimate-test-reporter": "^0.2.0", | ||
| "fast-equals": "^1.6.2", | ||
| "fast-equals": "^1.6.3", | ||
| "fast-memoize": "^2.5.1", | ||
@@ -45,10 +45,10 @@ "hash-it": "^4.0.4", | ||
| "lru-memoize": "^1.1.0", | ||
| "memoizee": "^0.4.11", | ||
| "memoizerific": "^1.11.2", | ||
| "micro-memoize": "^3.0.1", | ||
| "memoizee": "^0.4.14", | ||
| "memoizerific": "^1.11.3", | ||
| "micro-memoize": "^4.0.8", | ||
| "mocha": "^2.5.3", | ||
| "moize": "^5.4.2", | ||
| "ora": "^1.3.0", | ||
| "moize": "^5.4.4", | ||
| "ora": "^1.4.0", | ||
| "ramda": "^0.26.1", | ||
| "uglify-es": "^3.1.6", | ||
| "uglify-es": "^3.3.9", | ||
| "underscore": "^1.9.1" | ||
@@ -55,0 +55,0 @@ }, |
106
README.md
@@ -12,15 +12,15 @@ [](https://www.codacy.com/app/syblackwell/nano-memoize?utm_source=github.com&utm_medium=referral&utm_content=anywhichway/nano-memoize&utm_campaign=Badge_Grade) | ||
| The minified/brotli size is 654 bytes for `nano-memoize` v1.1.3 vs 1,356 bytes for `micro-memoize` v3.0.1. And, `nano-memoize` has slightly more functionality. | ||
| The minified/brotli size is 660 bytes for `nano-memoize` v1.1.5 vs 1,356 bytes for `micro-memoize` v4.08. And, `nano-memoize` has slightly more functionality. | ||
| The speed tests are below. | ||
| The speed tests are below. At the time of testing the most recent version of `fast-memoize` 2.5.1 was a year old. The most recent version of `micro-memoize` 4.0.8 was 14 days old. | ||
| * For single primitive argument functions it is typically 5-10% faster than `fast-memoize` and 3x faster than `micro-memoize`. | ||
| * For single primitive argument functions `nano-memoize` runs neck-and-neck with `fast-memoize` and 3-4x faster than `micro-memoize`. | ||
| * For single object argument functions it is typically 10-15% faster than `fast-memoize` and 15-20% faster than `micro-memoize`. | ||
| * For single object argument functions `nano-memoize` is typically 10% faster than `fast-memoize` and 1.75x faster than `micro-memoize`. | ||
| * For multiple primitive argument functions `nano-memoize` and `micro-memoize` will trade-off first position across multiple test runs with `nano-memoize` winning slightly more frequently. They are 60x faster than `fast-memoize`. | ||
| * For multiple primitive argument functions `nano-memoize` is about 20% faster than `micro-memoize`. They are 60x faster than `fast-memoize`. | ||
| * For multiple object argument functions `nano-memoize` and `micro-memoize` will trade-off first position across multiple test runs with `nano-memoize` winning slightly more frequently. They are 60x faster than `fast-memoize`. | ||
| * For multiple object argument functions `nano-memoize` is typically 20% faster than `micro-memoize` and 60x faster than `fast-memoize`. | ||
| * When `deepEquals` tests are used, `micro-memoize` rules the day. | ||
| * When `deepEquals` tests are used, `nano-memoize` is 33% faster than micro-memoize. `fast-memoize` is by default deep equals and `nano-memoize` is 60x faster. | ||
@@ -35,23 +35,23 @@ We have found that benchmarks can vary dramatically from O/S to O/S or Node version to Node version. These tests were run on a Windows 10 Pro 64bit 1.8ghz i7 machine with 16GB RAM and Node v11.6.0. Also, even with multiple samplings, garbage collection can have a substative impact and multiple runs in different orders are really required for apples-to-apples comparisons. | ||
| +----------------------------------------------------------------------+ | ||
| � nano-memoize � 408,626,233 � � 1.86% � 81 � | ||
| � nano-memoize � 429,266,986 � 0.53% � 95 � | ||
| +----------------------------------------------------------------------+ | ||
| � fast-memoize � 368,639,842 � � 1.79% � 81 � | ||
| � fast-memoize � 423,833,441 � 0.62% � 94 � | ||
| +----------------------------------------------------------------------+ | ||
| � micro-memoize � 102,964,021 � � 1.39% � 84 � | ||
| � moize � 95,351,935 � 1.54% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � moize � 93,623,511 � � 1.70% � 83 � | ||
| � iMemoized � 82,908,646 � 0.76% � 89 � | ||
| +----------------------------------------------------------------------+ | ||
| � iMemoized � 83,667,946 � � 1.58% � 83 � | ||
| � micro-memoize � 74,658,533 � 2.16% � 86 � | ||
| +----------------------------------------------------------------------+ | ||
| � lru-memoize � 71,258,447 � � 1.90% � 82 � | ||
| � lru-memoize � 73,747,331 � 0.59% � 89 � | ||
| +----------------------------------------------------------------------+ | ||
| � lodash � 46,706,263 � � 1.87% � 82 � | ||
| � lodash � 48,098,010 � 1.79% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � memoizee � 36,960,053 � � 1.67% � 81 � | ||
| � memoizee � 39,111,373 � 0.53% � 95 � | ||
| +----------------------------------------------------------------------+ | ||
| � underscore � 34,650,172 � � 1.67% � 79 � | ||
| � underscore � 34,623,228 � 1.22% � 95 � | ||
| +----------------------------------------------------------------------+ | ||
| � memoizerific � 6,854,333 � � 2.14% � 79 � | ||
| � memoizerific � 6,905,607 � 2.16% � 91 � | ||
| +----------------------------------------------------------------------+ | ||
| � addy-osmani � 6,076,478 � � 1.80% � 80 � | ||
| � addy-osmani � 6,319,914 � 0.94% � 91 � | ||
| +----------------------------------------------------------------------+ | ||
@@ -66,23 +66,23 @@ ``` | ||
| +----------------------------------------------------------------------+ | ||
| � nano-memoize � 120,054,209 � � 1.77% � 86 � | ||
| � nano-memoize � 124,264,741 � 0.61% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � micro-memoize � 88,968,257 � � 1.13% � 84 � | ||
| � fast-memoize � 111,267,506 � 0.74% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � moize � 85,218,895 � � 1.42% � 84 � | ||
| � moize � 95,260,557 � 0.88% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � fast-memoize � 73,730,097 � � 5.40% � 71 � | ||
| � iMemoized � 73,937,479 � 0.67% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
| � iMemoized � 58,513,510 � � 1.26% � 80 � | ||
| � micro-memoize � 66,863,547 � 4.08% � 80 � | ||
| +----------------------------------------------------------------------+ | ||
| � lodash � 46,264,060 � � 1.88% � 80 � | ||
| � lodash � 47,881,566 � 1.41% � 90 � | ||
| +----------------------------------------------------------------------+ | ||
| � lru-memoize � 30,648,600 � � 1.61% � 81 � | ||
| � underscore � 34,777,812 � 0.79% � 92 � | ||
| +----------------------------------------------------------------------+ | ||
| � underscore � 28,901,663 � � 2.98% � 75 � | ||
| � lru-memoize � 31,919,125 � 0.33% � 98 � | ||
| +----------------------------------------------------------------------+ | ||
| � memoizee � 17,213,563 � � 1.68% � 80 � | ||
| � memoizee � 18,033,950 � 0.55% � 89 � | ||
| +----------------------------------------------------------------------+ | ||
| � addy-osmani � 6,379,759 � � 1.75% � 81 � | ||
| � memoizerific � 6,600,328 � 1.28% � 95 � | ||
| +----------------------------------------------------------------------+ | ||
| � memoizerific � 5,789,710 � � 3.67% � 74 � | ||
| � addy-osmani � 6,346,356 � 1.02% � 93 � | ||
| +----------------------------------------------------------------------+ | ||
@@ -97,19 +97,19 @@ ``` | ||
| +---------------------------------------------------------------------+ | ||
| � nano-memoize � 64,477,579 � � 1.77% � 83 � | ||
| � nano-memoize � 64,862,221 � 0.98% � 91 � | ||
| +---------------------------------------------------------------------+ | ||
| � moize � 56,501,764 � � 2.20% � 79 � | ||
| � moize � 62,050,114 � 0.46% � 95 � | ||
| +---------------------------------------------------------------------+ | ||
| � micro-memoize � 39,469,612 � � 6.47% � 72 � | ||
| � micro-memoize � 53,790,249 � 0.42% � 93 � | ||
| +---------------------------------------------------------------------+ | ||
| � lru-memoize � 19,361,408 � � 6.19% � 70 � | ||
| � lru-memoize � 25,083,521 � 0.43% � 97 � | ||
| +---------------------------------------------------------------------+ | ||
| � memoizee � 11,381,474 � � 4.35% � 73 � | ||
| � memoizee � 16,817,318 � 1.67% � 94 � | ||
| +---------------------------------------------------------------------+ | ||
| � iMemoized � 5,733,044 � � 9.82% � 71 � | ||
| � iMemoized � 9,893,933 � 0.53% � 93 � | ||
| +---------------------------------------------------------------------+ | ||
| � addy-osmani � 3,258,073 � � 2.34% � 86 � | ||
| � memoizerific � 5,214,455 � 1.49% � 89 � | ||
| +---------------------------------------------------------------------+ | ||
| � memoizerific � 1,965,125 � � 7.60% � 64 � | ||
| � addy-osmani � 3,331,201 � 0.81% � 94 � | ||
| +---------------------------------------------------------------------+ | ||
| � fast-memoize � 834,173 � � 7.38% � 65 � | ||
| � fast-memoize � 1,370,977 � 1.01% � 90 � | ||
| +---------------------------------------------------------------------+ | ||
@@ -124,17 +124,17 @@ ``` | ||
| +---------------------------------------------------------------------+ | ||
| � nano-memoize � 63,382,702 � � 1.88% � 83 � | ||
| � nano-memoize � 63,382,702 � 1.88% � 83 � | ||
| +---------------------------------------------------------------------+ | ||
| � moize � 61,349,765 � � 1.78% � 82 � | ||
| � moize � 61,349,765 � 1.78% � 82 � | ||
| +---------------------------------------------------------------------+ | ||
| � micro-memoize � 54,322,737 � � 4.53% � 72 � | ||
| � micro-memoize � 54,322,737 � 4.53% � 72 � | ||
| +---------------------------------------------------------------------+ | ||
| � lru-memoize � 23,824,559 � � 2.34% � 81 � | ||
| � lru-memoize � 23,824,559 � 2.34% � 81 � | ||
| +---------------------------------------------------------------------+ | ||
| � memoizee � 11,161,431 � � 1.97% � 84 � | ||
| � memoizee � 11,161,431 � 1.97% � 84 � | ||
| +---------------------------------------------------------------------+ | ||
| � memoizerific � 5,416,184 � � 3.89% � 79 � | ||
| � memoizerific � 5,416,184 � 3.89% � 79 � | ||
| +---------------------------------------------------------------------+ | ||
| � addy-osmani � 1,199,529 � � 2.78% � 84 � | ||
| � addy-osmani � 1,199,529 � 2.78% � 84 � | ||
| +---------------------------------------------------------------------+ | ||
| � fast-memoize � 1,057,876 � � 1.75% � 83 � | ||
| � fast-memoize � 1,057,876 � 1.75% � 83 � | ||
| +---------------------------------------------------------------------+ | ||
@@ -149,11 +149,11 @@ ``` | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
| � micro-memoize deep equals (lodash isEqual) � 12,400,181 � � 19.08% � 61 � | ||
| � nanomemoize deep equals (lodash isEqual) � 66,440,153 � 2.02% � 92 � | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
| � micro-memoize deep equals (fast-equals deepEqual) � 12,082,145 � � 14.66% � 47 � | ||
| � nanomemoize deep equals (fast-equals deepEqual) � 53,056,118 � 2.48% � 74 � | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
| � nanomemoize deep equals (lodash isEqual) � 6,136,579 � � 82.87% � 51 � | ||
| � micro-memoize deep equals (hash-it isEqual) � 47,502,261 � 1.73% � 85 � | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
| � micro-memoize deep equals (hash-it isEqual) � 4,010,002 � � 42.97% � 44 � | ||
| � micro-memoize deep equals (lodash isEqual) � 41,636,743 � 2.88% � 84 � | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
| � nanomemoize deep equals (fast-equals deepEqual) � 3,539,280 � � 43.70% � 43 � | ||
| � micro-memoize deep equals (fast-equals deepEqual) � 39,346,248 � 2.18% � 85 � | ||
| +---------------------------------------------------------------------------------------------------------+ | ||
@@ -206,4 +206,6 @@ ``` | ||
| 2019-05-31 v1.3.4 [Fixed Issue 7](https://github.com/anywhichway/nano-memoize/issues/7). | ||
| 2019-06-28 v1.1.5 Improved documentation. Updated version of `micro-memoize` used for benchmark testing. No code changes. | ||
| 2019-05-31 v1.1.4 [Fixed Issue 7](https://github.com/anywhichway/nano-memoize/issues/7). | ||
| 2019-04-09 v1.1.3 [Fixed Issue 6](https://github.com/anywhichway/nano-memoize/issues/6). Minor speed and size improvements. | ||
@@ -210,0 +212,0 @@ |
New alerts
License Policy Violation
LicenseThis package is not allowed per your license policy. Review the package's license to ensure compliance.
Found 1 instance in 1 package
Manifest confusion
Supply chain riskThis package has inconsistent metadata. This could be malicious or caused by an error when publishing the package.
Found 1 instance in 1 package
Fixed alerts
License Policy Violation
LicenseThis package is not allowed per your license policy. Review the package's license to ensure compliance.
Found 1 instance in 1 package
Manifest confusion
Supply chain riskThis package has inconsistent metadata. This could be malicious or caused by an error when publishing the package.
Found 1 instance in 1 package
Improved metrics
- Total package byte prevSize
- increased by0.29%
71238
- Number of lines in readme file
- increased by0.81%
249
No dependency changes