diff --git a/build/Dockerfile b/build/Dockerfile
index a6f0deb..e632d84 100644
--- a/build/Dockerfile
+++ b/build/Dockerfile
@@ -1,6 +1,6 @@
FROM redis:8.6.1
-RUN apt update && apt install -y --no-install-recommends gettext && apt clean && rm -rf /var/lib/apt/lists/*
+RUN apt update && apt install -y --no-install-recommends gettext dnsutils && apt clean && rm -rf /var/lib/apt/lists/*
ADD ./entrypoint.sh /entrypoint.sh
ENTRYPOINT [ "/entrypoint.sh" ]
diff --git a/build/entrypoint.sh b/build/entrypoint.sh
old mode 100644
new mode 100755
index 4321ba7..7a50cea
--- a/build/entrypoint.sh
+++ b/build/entrypoint.sh
@@ -1,6 +1,10 @@
#!/bin/sh
set -e
+export CONTAINER_NAME=$(dig -x "$(hostname -i)" +short | cut -d . -f 1)
+mkdir -p /data/$CONTAINER_NAME
+cd /data/$CONTAINER_NAME
+
if [ "${1%.tmpl}" != "$1" ]; then
cat "$1" | envsubst > /etc/redis.conf
set -- /etc/redis.conf
diff --git a/compose.yml b/compose.yml
index 8ddf0cf..6ca9b8e 100644
--- a/compose.yml
+++ b/compose.yml
@@ -4,9 +4,9 @@ services:
ports:
- 5540:5540
redis:
- image: redis:8.6.1
+ image: golyalpha/redis:8.6.1
build: ./build
- command: ["/conf/redis.conf"]
+ command: ["/conf/redis.conf.tmpl"]
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 1m30s
@@ -15,7 +15,7 @@ services:
start_period: 30s
volumes:
- ./conf:/conf:ro
- - /data
+ - redis_data:/data
expose:
- 6379
- 16379
@@ -38,3 +38,6 @@ services:
userns_mode: keep-id
volumes:
- ./notebooks:/home/jovyan
+
+volumes:
+ redis_data:
diff --git a/conf/redis.conf b/conf/redis.conf.tmpl
similarity index 86%
rename from conf/redis.conf
rename to conf/redis.conf.tmpl
index 4537a79..4675d13 100644
--- a/conf/redis.conf
+++ b/conf/redis.conf.tmpl
@@ -1,4 +1,4 @@
-dir /data/
+dir /data/${CONTAINER_NAME}/
aclfile /conf/users.acl
diff --git a/notebooks/fill_test.ipynb b/notebooks/fill_test.ipynb
index 6749d6d..51b14ba 100644
--- a/notebooks/fill_test.ipynb
+++ b/notebooks/fill_test.ipynb
@@ -2,39 +2,17 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "05c0de49-0eb8-4cd2-89b2-c312111dda85",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: redis in /opt/conda/lib/python3.13/site-packages (7.4.0)\n",
- "Requirement already satisfied: hiredis in /opt/conda/lib/python3.13/site-packages (3.3.1)\n",
- "Requirement already satisfied: fastid in /opt/conda/lib/python3.13/site-packages (0.0.5)\n",
- "Requirement already satisfied: tqdm in /opt/conda/lib/python3.13/site-packages (4.67.3)\n",
- "Requirement already satisfied: kagglehub in /opt/conda/lib/python3.13/site-packages (1.0.0)\n",
- "Requirement already satisfied: kagglesdk<1.0,>=0.1.14 in /opt/conda/lib/python3.13/site-packages (from kagglehub) (0.1.16)\n",
- "Requirement already satisfied: packaging in /opt/conda/lib/python3.13/site-packages (from kagglehub) (26.0)\n",
- "Requirement already satisfied: pyyaml in /opt/conda/lib/python3.13/site-packages (from kagglehub) (6.0.3)\n",
- "Requirement already satisfied: requests in /opt/conda/lib/python3.13/site-packages (from kagglehub) (2.32.5)\n",
- "Requirement already satisfied: protobuf in /opt/conda/lib/python3.13/site-packages (from kagglesdk<1.0,>=0.1.14->kagglehub) (6.33.5)\n",
- "Requirement already satisfied: charset_normalizer<4,>=2 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.4.6)\n",
- "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.11)\n",
- "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2.6.3)\n",
- "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2026.2.25)\n",
- "Note: you may need to restart the kernel to use updated packages.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"%pip install redis hiredis fastid tqdm kagglehub"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "90326242-f141-4035-9053-d3aab6cc9224",
"metadata": {},
"outputs": [],
@@ -49,25 +27,10 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "50b9f473-8924-4d03-acf8-71ecf25e54a8",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "887890574a2048a587b6ed4dd8eef7c6",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- " 0%| | 0/1000000 [00:00, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"from fastid import ulid\n",
"from tqdm.notebook import trange\n",
@@ -80,20 +43,10 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "23933aa3-ff5d-45f9-b402-59e58c02a2b3",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "b'OK'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"schema = (\n",
" TextField(\"name\"),\n",
diff --git a/notebooks/r6_analysis.ipynb b/notebooks/r6_analysis.ipynb
index 1cb18df..a6ea7ca 100644
--- a/notebooks/r6_analysis.ipynb
+++ b/notebooks/r6_analysis.ipynb
@@ -12,7 +12,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "setup",
"metadata": {},
"outputs": [],
@@ -54,261 +54,10 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "task1-data-prep",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "
\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " GSG9-JAGER | \n",
- " SWAT-ASH | \n",
- " SAT-HIBANA | \n",
- " GSG9-BANDIT | \n",
- " GIGN-TWITCH | \n",
- " SWAT-THERMITE | \n",
- " SPETSNAZ-FUZE | \n",
- " BOPE-CAVEIRA | \n",
- " G.E.O.-JACKAL | \n",
- " NAVYSEAL-VALKYRIE | \n",
- " ... | \n",
- " GSG9-IQ | \n",
- " GIGN-MONTAGNE | \n",
- " SAT-ECHO | \n",
- " GSG9-BLITZ | \n",
- " GSG9-RESERVE | \n",
- " SPETSNAZ-TACHANKA | \n",
- " SAS-RESERVE | \n",
- " SWAT-RESERVE | \n",
- " GIGN-RESERVE | \n",
- " SPETSNAZ-RESERVE | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | total_kills | \n",
- " 5522 | \n",
- " 5446 | \n",
- " 3825 | \n",
- " 3802 | \n",
- " 3577 | \n",
- " 3441 | \n",
- " 3336 | \n",
- " 3293 | \n",
- " 3135 | \n",
- " 2926 | \n",
- " ... | \n",
- " 1027 | \n",
- " 777 | \n",
- " 775 | \n",
- " 425 | \n",
- " 386 | \n",
- " 202 | \n",
- " 183 | \n",
- " 112 | \n",
- " 89 | \n",
- " 84 | \n",
- "
\n",
- " \n",
- " | total_rounds | \n",
- " 6999 | \n",
- " 6519 | \n",
- " 4960 | \n",
- " 5257 | \n",
- " 4894 | \n",
- " 5001 | \n",
- " 4222 | \n",
- " 4586 | \n",
- " 4091 | \n",
- " 4319 | \n",
- " ... | \n",
- " 1570 | \n",
- " 1880 | \n",
- " 1207 | \n",
- " 782 | \n",
- " 618 | \n",
- " 436 | \n",
- " 375 | \n",
- " 206 | \n",
- " 173 | \n",
- " 145 | \n",
- "
\n",
- " \n",
- " | won_rounds | \n",
- " 3535 | \n",
- " 3370 | \n",
- " 2586 | \n",
- " 2684 | \n",
- " 2553 | \n",
- " 2603 | \n",
- " 2164 | \n",
- " 2321 | \n",
- " 2140 | \n",
- " 2177 | \n",
- " ... | \n",
- " 785 | \n",
- " 953 | \n",
- " 634 | \n",
- " 376 | \n",
- " 317 | \n",
- " 196 | \n",
- " 159 | \n",
- " 97 | \n",
- " 78 | \n",
- " 65 | \n",
- "
\n",
- " \n",
- " | dead_rounds | \n",
- " 5127 | \n",
- " 4555 | \n",
- " 3294 | \n",
- " 3833 | \n",
- " 3180 | \n",
- " 3394 | \n",
- " 2929 | \n",
- " 3362 | \n",
- " 2850 | \n",
- " 3150 | \n",
- " ... | \n",
- " 1128 | \n",
- " 1284 | \n",
- " 775 | \n",
- " 585 | \n",
- " 468 | \n",
- " 329 | \n",
- " 297 | \n",
- " 151 | \n",
- " 122 | \n",
- " 107 | \n",
- "
\n",
- " \n",
- " | survival_rate | \n",
- " 0.267466780969 | \n",
- " 0.301273201411 | \n",
- " 0.335887096774 | \n",
- " 0.270876926003 | \n",
- " 0.350224765018 | \n",
- " 0.321335732853 | \n",
- " 0.306252960682 | \n",
- " 0.266899258613 | \n",
- " 0.303348814471 | \n",
- " 0.270664505673 | \n",
- " ... | \n",
- " 0.28152866242 | \n",
- " 0.317021276596 | \n",
- " 0.357912178956 | \n",
- " 0.251918158568 | \n",
- " 0.242718446602 | \n",
- " 0.245412844037 | \n",
- " 0.208 | \n",
- " 0.266990291262 | \n",
- " 0.294797687861 | \n",
- " 0.262068965517 | \n",
- "
\n",
- " \n",
- " | win_rate | \n",
- " 0.505072153165 | \n",
- " 0.516950452523 | \n",
- " 0.521370967742 | \n",
- " 0.510557352102 | \n",
- " 0.521659174499 | \n",
- " 0.52049590082 | \n",
- " 0.512553292279 | \n",
- " 0.506105538596 | \n",
- " 0.523099486678 | \n",
- " 0.504051863857 | \n",
- " ... | \n",
- " 0.5 | \n",
- " 0.506914893617 | \n",
- " 0.525269262635 | \n",
- " 0.480818414322 | \n",
- " 0.512944983819 | \n",
- " 0.449541284404 | \n",
- " 0.424 | \n",
- " 0.470873786408 | \n",
- " 0.450867052023 | \n",
- " 0.448275862069 | \n",
- "
\n",
- " \n",
- "
\n",
- "
6 rows × 35 columns
\n",
- "
"
- ],
- "text/plain": [
- " GSG9-JAGER SWAT-ASH SAT-HIBANA GSG9-BANDIT \\\n",
- "total_kills 5522 5446 3825 3802 \n",
- "total_rounds 6999 6519 4960 5257 \n",
- "won_rounds 3535 3370 2586 2684 \n",
- "dead_rounds 5127 4555 3294 3833 \n",
- "survival_rate 0.267466780969 0.301273201411 0.335887096774 0.270876926003 \n",
- "win_rate 0.505072153165 0.516950452523 0.521370967742 0.510557352102 \n",
- "\n",
- " GIGN-TWITCH SWAT-THERMITE SPETSNAZ-FUZE BOPE-CAVEIRA \\\n",
- "total_kills 3577 3441 3336 3293 \n",
- "total_rounds 4894 5001 4222 4586 \n",
- "won_rounds 2553 2603 2164 2321 \n",
- "dead_rounds 3180 3394 2929 3362 \n",
- "survival_rate 0.350224765018 0.321335732853 0.306252960682 0.266899258613 \n",
- "win_rate 0.521659174499 0.52049590082 0.512553292279 0.506105538596 \n",
- "\n",
- " G.E.O.-JACKAL NAVYSEAL-VALKYRIE ... GSG9-IQ \\\n",
- "total_kills 3135 2926 ... 1027 \n",
- "total_rounds 4091 4319 ... 1570 \n",
- "won_rounds 2140 2177 ... 785 \n",
- "dead_rounds 2850 3150 ... 1128 \n",
- "survival_rate 0.303348814471 0.270664505673 ... 0.28152866242 \n",
- "win_rate 0.523099486678 0.504051863857 ... 0.5 \n",
- "\n",
- " GIGN-MONTAGNE SAT-ECHO GSG9-BLITZ GSG9-RESERVE \\\n",
- "total_kills 777 775 425 386 \n",
- "total_rounds 1880 1207 782 618 \n",
- "won_rounds 953 634 376 317 \n",
- "dead_rounds 1284 775 585 468 \n",
- "survival_rate 0.317021276596 0.357912178956 0.251918158568 0.242718446602 \n",
- "win_rate 0.506914893617 0.525269262635 0.480818414322 0.512944983819 \n",
- "\n",
- " SPETSNAZ-TACHANKA SAS-RESERVE SWAT-RESERVE GIGN-RESERVE \\\n",
- "total_kills 202 183 112 89 \n",
- "total_rounds 436 375 206 173 \n",
- "won_rounds 196 159 97 78 \n",
- "dead_rounds 329 297 151 122 \n",
- "survival_rate 0.245412844037 0.208 0.266990291262 0.294797687861 \n",
- "win_rate 0.449541284404 0.424 0.470873786408 0.450867052023 \n",
- "\n",
- " SPETSNAZ-RESERVE \n",
- "total_kills 84 \n",
- "total_rounds 145 \n",
- "won_rounds 65 \n",
- "dead_rounds 107 \n",
- "survival_rate 0.262068965517 \n",
- "win_rate 0.448275862069 \n",
- "\n",
- "[6 rows x 35 columns]"
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -348,182 +97,10 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "task2-weapons",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " 416-C CARBINE | \n",
- " L85A2 | \n",
- " MP7 | \n",
- " R4-C | \n",
- " 556XI | \n",
- " TYPE-89 | \n",
- " UMP45 | \n",
- " MP5 | \n",
- " F2 | \n",
- " MPX | \n",
- " ... | \n",
- " SPAS-12 | \n",
- " SASG-12 | \n",
- " HK417 | \n",
- " SUPER 90 | \n",
- " SG-CQB | \n",
- " SuperNova | \n",
- " SR-25 | \n",
- " G8A1 | \n",
- " M249 | \n",
- " ITA12L | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | primaryweapon | \n",
- " 416-C CARBINE | \n",
- " L85A2 | \n",
- " MP7 | \n",
- " R4-C | \n",
- " 556XI | \n",
- " TYPE-89 | \n",
- " UMP45 | \n",
- " MP5 | \n",
- " F2 | \n",
- " MPX | \n",
- " ... | \n",
- " SPAS-12 | \n",
- " SASG-12 | \n",
- " HK417 | \n",
- " SUPER 90 | \n",
- " SG-CQB | \n",
- " SuperNova | \n",
- " SR-25 | \n",
- " G8A1 | \n",
- " M249 | \n",
- " ITA12L | \n",
- "
\n",
- " \n",
- " | total_kills | \n",
- " 5541 | \n",
- " 3767 | \n",
- " 3790 | \n",
- " 4209 | \n",
- " 3418 | \n",
- " 3774 | \n",
- " 3053 | \n",
- " 2937 | \n",
- " 3384 | \n",
- " 2564 | \n",
- " ... | \n",
- " 362 | \n",
- " 254 | \n",
- " 210 | \n",
- " 236 | \n",
- " 187 | \n",
- " 172 | \n",
- " 173 | \n",
- " 117 | \n",
- " 94 | \n",
- " 68 | \n",
- "
\n",
- " \n",
- " | times_used | \n",
- " 7005 | \n",
- " 5371 | \n",
- " 5216 | \n",
- " 4993 | \n",
- " 4964 | \n",
- " 4884 | \n",
- " 4726 | \n",
- " 4693 | \n",
- " 4527 | \n",
- " 3794 | \n",
- " ... | \n",
- " 525 | \n",
- " 468 | \n",
- " 404 | \n",
- " 358 | \n",
- " 346 | \n",
- " 296 | \n",
- " 239 | \n",
- " 198 | \n",
- " 160 | \n",
- " 141 | \n",
- "
\n",
- " \n",
- " | wins | \n",
- " 3535 | \n",
- " 2833 | \n",
- " 2668 | \n",
- " 2572 | \n",
- " 2582 | \n",
- " 2554 | \n",
- " 2348 | \n",
- " 2414 | \n",
- " 2379 | \n",
- " 1934 | \n",
- " ... | \n",
- " 243 | \n",
- " 215 | \n",
- " 194 | \n",
- " 192 | \n",
- " 156 | \n",
- " 134 | \n",
- " 118 | \n",
- " 99 | \n",
- " 87 | \n",
- " 68 | \n",
- "
\n",
- " \n",
- "
\n",
- "
4 rows × 46 columns
\n",
- "
"
- ],
- "text/plain": [
- " 416-C CARBINE L85A2 MP7 R4-C 556XI TYPE-89 UMP45 MP5 \\\n",
- "primaryweapon 416-C CARBINE L85A2 MP7 R4-C 556XI TYPE-89 UMP45 MP5 \n",
- "total_kills 5541 3767 3790 4209 3418 3774 3053 2937 \n",
- "times_used 7005 5371 5216 4993 4964 4884 4726 4693 \n",
- "wins 3535 2833 2668 2572 2582 2554 2348 2414 \n",
- "\n",
- " F2 MPX ... SPAS-12 SASG-12 HK417 SUPER 90 SG-CQB \\\n",
- "primaryweapon F2 MPX ... SPAS-12 SASG-12 HK417 SUPER 90 SG-CQB \n",
- "total_kills 3384 2564 ... 362 254 210 236 187 \n",
- "times_used 4527 3794 ... 525 468 404 358 346 \n",
- "wins 2379 1934 ... 243 215 194 192 156 \n",
- "\n",
- " SuperNova SR-25 G8A1 M249 ITA12L \n",
- "primaryweapon SuperNova SR-25 G8A1 M249 ITA12L \n",
- "total_kills 172 173 117 94 68 \n",
- "times_used 296 239 198 160 141 \n",
- "wins 134 118 99 87 68 \n",
- "\n",
- "[4 rows x 46 columns]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -561,160 +138,10 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "task3-maps",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " SKYSCRAPER | \n",
- " OREGON | \n",
- " KAFE DOSTOYEVSKY | \n",
- " BORDER | \n",
- " HEREFORD BASE | \n",
- " CHALET | \n",
- " YACHT | \n",
- " HOUSE | \n",
- " PLANE | \n",
- " KANAL | \n",
- " FAVELAS | \n",
- " COASTLINE | \n",
- " CONSULATE | \n",
- " BANK | \n",
- " CLUB HOUSE | \n",
- " BARTLETT U. | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | mapname | \n",
- " SKYSCRAPER | \n",
- " OREGON | \n",
- " KAFE DOSTOYEVSKY | \n",
- " BORDER | \n",
- " HEREFORD BASE | \n",
- " CHALET | \n",
- " YACHT | \n",
- " HOUSE | \n",
- " PLANE | \n",
- " KANAL | \n",
- " FAVELAS | \n",
- " COASTLINE | \n",
- " CONSULATE | \n",
- " BANK | \n",
- " CLUB HOUSE | \n",
- " BARTLETT U. | \n",
- "
\n",
- " \n",
- " | total_rounds | \n",
- " 7459 | \n",
- " 7367 | \n",
- " 7317 | \n",
- " 6970 | \n",
- " 6797 | \n",
- " 6772 | \n",
- " 6576 | \n",
- " 6572 | \n",
- " 6461 | \n",
- " 6149 | \n",
- " 6057 | \n",
- " 5812 | \n",
- " 5792 | \n",
- " 5767 | \n",
- " 5595 | \n",
- " 5235 | \n",
- "
\n",
- " \n",
- " | won_rounds | \n",
- " 3789 | \n",
- " 3761 | \n",
- " 3732 | \n",
- " 3547 | \n",
- " 3452 | \n",
- " 3449 | \n",
- " 3347 | \n",
- " 3333 | \n",
- " 3300 | \n",
- " 3114 | \n",
- " 3089 | \n",
- " 2941 | \n",
- " 2981 | \n",
- " 2947 | \n",
- " 2837 | \n",
- " 2656 | \n",
- "
\n",
- " \n",
- " | round_duration | \n",
- " 180.164097064 | \n",
- " 187.90946111 | \n",
- " 189.810714774 | \n",
- " 179.218077475 | \n",
- " 183.516698543 | \n",
- " 180.794595393 | \n",
- " 180.983880779 | \n",
- " 179.114120511 | \n",
- " 186.111437858 | \n",
- " 188.070255326 | \n",
- " 170.701337296 | \n",
- " 183.439779766 | \n",
- " 187.277106354 | \n",
- " 192.193341425 | \n",
- " 187.16997319 | \n",
- " 191.232473734 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " SKYSCRAPER OREGON KAFE DOSTOYEVSKY BORDER \\\n",
- "mapname SKYSCRAPER OREGON KAFE DOSTOYEVSKY BORDER \n",
- "total_rounds 7459 7367 7317 6970 \n",
- "won_rounds 3789 3761 3732 3547 \n",
- "round_duration 180.164097064 187.90946111 189.810714774 179.218077475 \n",
- "\n",
- " HEREFORD BASE CHALET YACHT HOUSE \\\n",
- "mapname HEREFORD BASE CHALET YACHT HOUSE \n",
- "total_rounds 6797 6772 6576 6572 \n",
- "won_rounds 3452 3449 3347 3333 \n",
- "round_duration 183.516698543 180.794595393 180.983880779 179.114120511 \n",
- "\n",
- " PLANE KANAL FAVELAS COASTLINE \\\n",
- "mapname PLANE KANAL FAVELAS COASTLINE \n",
- "total_rounds 6461 6149 6057 5812 \n",
- "won_rounds 3300 3114 3089 2941 \n",
- "round_duration 186.111437858 188.070255326 170.701337296 183.439779766 \n",
- "\n",
- " CONSULATE BANK CLUB HOUSE BARTLETT U. \n",
- "mapname CONSULATE BANK CLUB HOUSE BARTLETT U. \n",
- "total_rounds 5792 5767 5595 5235 \n",
- "won_rounds 2981 2947 2837 2656 \n",
- "round_duration 187.277106354 192.193341425 187.16997319 191.232473734 "
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -741,84 +168,10 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": null,
"id": "task3-gamemode",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " PvP SECURE AREA | \n",
- " PvP BOMB | \n",
- " PvP HOSTAGE | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | gamemode | \n",
- " PvP SECURE AREA | \n",
- " PvP BOMB | \n",
- " PvP HOSTAGE | \n",
- "
\n",
- " \n",
- " | total_rounds | \n",
- " 66034 | \n",
- " 25872 | \n",
- " 10792 | \n",
- "
\n",
- " \n",
- " | won_rounds | \n",
- " 33582 | \n",
- " 13183 | \n",
- " 5510 | \n",
- "
\n",
- " \n",
- " | total_kills | \n",
- " 46375 | \n",
- " 18364 | \n",
- " 7275 | \n",
- "
\n",
- " \n",
- " | round_duration | \n",
- " 183.826771057 | \n",
- " 185.54363791 | \n",
- " 182.205707932 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " PvP SECURE AREA PvP BOMB PvP HOSTAGE\n",
- "gamemode PvP SECURE AREA PvP BOMB PvP HOSTAGE\n",
- "total_rounds 66034 25872 10792\n",
- "won_rounds 33582 13183 5510\n",
- "total_kills 46375 18364 7275\n",
- "round_duration 183.826771057 185.54363791 182.205707932"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -857,127 +210,10 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "task4-ranks",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " Gold | \n",
- " Silver | \n",
- " Copper | \n",
- " Bronze | \n",
- " Platinum | \n",
- " Unranked | \n",
- " Diamond | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | skillrank | \n",
- " Gold | \n",
- " Silver | \n",
- " Copper | \n",
- " Bronze | \n",
- " Platinum | \n",
- " Unranked | \n",
- " Diamond | \n",
- "
\n",
- " \n",
- " | total_rounds | \n",
- " 35770 | \n",
- " 20271 | \n",
- " 13996 | \n",
- " 13611 | \n",
- " 11567 | \n",
- " 6797 | \n",
- " 686 | \n",
- "
\n",
- " \n",
- " | won_rounds | \n",
- " 18523 | \n",
- " 10395 | \n",
- " 6959 | \n",
- " 6870 | \n",
- " 5946 | \n",
- " 3174 | \n",
- " 408 | \n",
- "
\n",
- " \n",
- " | total_kills | \n",
- " 26270 | \n",
- " 13804 | \n",
- " 9014 | \n",
- " 9062 | \n",
- " 9362 | \n",
- " 3856 | \n",
- " 646 | \n",
- "
\n",
- " \n",
- " | total_deaths | \n",
- " 25039 | \n",
- " 14297 | \n",
- " 9912 | \n",
- " 9656 | \n",
- " 8078 | \n",
- " 4987 | \n",
- " 431 | \n",
- "
\n",
- " \n",
- " | round_duration | \n",
- " 187.55789768 | \n",
- " 183.711558384 | \n",
- " 173.63875393 | \n",
- " 180.108809052 | \n",
- " 190.132013487 | \n",
- " 185.866411652 | \n",
- " 187.030612245 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " Gold Silver Copper Bronze \\\n",
- "skillrank Gold Silver Copper Bronze \n",
- "total_rounds 35770 20271 13996 13611 \n",
- "won_rounds 18523 10395 6959 6870 \n",
- "total_kills 26270 13804 9014 9062 \n",
- "total_deaths 25039 14297 9912 9656 \n",
- "round_duration 187.55789768 183.711558384 173.63875393 180.108809052 \n",
- "\n",
- " Platinum Unranked Diamond \n",
- "skillrank Platinum Unranked Diamond \n",
- "total_rounds 11567 6797 686 \n",
- "won_rounds 5946 3174 408 \n",
- "total_kills 9362 3856 646 \n",
- "total_deaths 8078 4987 431 \n",
- "round_duration 190.132013487 185.866411652 187.030612245 "
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -1016,223 +252,10 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"id": "task5-pivot",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " GSG9-JAGER | \n",
- " SWAT-ASH | \n",
- " GSG9-BANDIT | \n",
- " SWAT-THERMITE | \n",
- " SAT-HIBANA | \n",
- " GIGN-TWITCH | \n",
- " BOPE-CAVEIRA | \n",
- " NAVYSEAL-VALKYRIE | \n",
- " SPETSNAZ-FUZE | \n",
- " G.E.O.-JACKAL | \n",
- " ... | \n",
- " GSG9-IQ | \n",
- " BOPE-CAPITAO | \n",
- " SAT-ECHO | \n",
- " GSG9-BLITZ | \n",
- " SPETSNAZ-TACHANKA | \n",
- " GSG9-RESERVE | \n",
- " SAS-RESERVE | \n",
- " SWAT-RESERVE | \n",
- " GIGN-RESERVE | \n",
- " SPETSNAZ-RESERVE | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | role | \n",
- " Defender | \n",
- " Attacker | \n",
- " Defender | \n",
- " Attacker | \n",
- " Attacker | \n",
- " Attacker | \n",
- " Defender | \n",
- " Defender | \n",
- " Attacker | \n",
- " Attacker | \n",
- " ... | \n",
- " Attacker | \n",
- " Attacker | \n",
- " Defender | \n",
- " Attacker | \n",
- " Defender | \n",
- " Attacker | \n",
- " Attacker | \n",
- " Defender | \n",
- " Attacker | \n",
- " Defender | \n",
- "
\n",
- " \n",
- " | operator | \n",
- " GSG9-JAGER | \n",
- " SWAT-ASH | \n",
- " GSG9-BANDIT | \n",
- " SWAT-THERMITE | \n",
- " SAT-HIBANA | \n",
- " GIGN-TWITCH | \n",
- " BOPE-CAVEIRA | \n",
- " NAVYSEAL-VALKYRIE | \n",
- " SPETSNAZ-FUZE | \n",
- " G.E.O.-JACKAL | \n",
- " ... | \n",
- " GSG9-IQ | \n",
- " BOPE-CAPITAO | \n",
- " SAT-ECHO | \n",
- " GSG9-BLITZ | \n",
- " SPETSNAZ-TACHANKA | \n",
- " GSG9-RESERVE | \n",
- " SAS-RESERVE | \n",
- " SWAT-RESERVE | \n",
- " GIGN-RESERVE | \n",
- " SPETSNAZ-RESERVE | \n",
- "
\n",
- " \n",
- " | total_rounds | \n",
- " 6999 | \n",
- " 6519 | \n",
- " 5257 | \n",
- " 5001 | \n",
- " 4960 | \n",
- " 4894 | \n",
- " 4586 | \n",
- " 4319 | \n",
- " 4222 | \n",
- " 4091 | \n",
- " ... | \n",
- " 1570 | \n",
- " 1554 | \n",
- " 1207 | \n",
- " 782 | \n",
- " 436 | \n",
- " 219 | \n",
- " 165 | \n",
- " 84 | \n",
- " 77 | \n",
- " 70 | \n",
- "
\n",
- " \n",
- " | total_kills | \n",
- " 5522 | \n",
- " 5446 | \n",
- " 3802 | \n",
- " 3441 | \n",
- " 3825 | \n",
- " 3577 | \n",
- " 3293 | \n",
- " 2926 | \n",
- " 3336 | \n",
- " 3135 | \n",
- " ... | \n",
- " 1027 | \n",
- " 1082 | \n",
- " 775 | \n",
- " 425 | \n",
- " 202 | \n",
- " 139 | \n",
- " 91 | \n",
- " 45 | \n",
- " 42 | \n",
- " 37 | \n",
- "
\n",
- " \n",
- " | total_deaths | \n",
- " 5127 | \n",
- " 4555 | \n",
- " 3833 | \n",
- " 3394 | \n",
- " 3294 | \n",
- " 3180 | \n",
- " 3362 | \n",
- " 3150 | \n",
- " 2929 | \n",
- " 2850 | \n",
- " ... | \n",
- " 1128 | \n",
- " 1105 | \n",
- " 775 | \n",
- " 585 | \n",
- " 329 | \n",
- " 162 | \n",
- " 119 | \n",
- " 66 | \n",
- " 49 | \n",
- " 57 | \n",
- "
\n",
- " \n",
- "
\n",
- "
5 rows × 35 columns
\n",
- "
"
- ],
- "text/plain": [
- " GSG9-JAGER SWAT-ASH GSG9-BANDIT SWAT-THERMITE SAT-HIBANA \\\n",
- "role Defender Attacker Defender Attacker Attacker \n",
- "operator GSG9-JAGER SWAT-ASH GSG9-BANDIT SWAT-THERMITE SAT-HIBANA \n",
- "total_rounds 6999 6519 5257 5001 4960 \n",
- "total_kills 5522 5446 3802 3441 3825 \n",
- "total_deaths 5127 4555 3833 3394 3294 \n",
- "\n",
- " GIGN-TWITCH BOPE-CAVEIRA NAVYSEAL-VALKYRIE SPETSNAZ-FUZE \\\n",
- "role Attacker Defender Defender Attacker \n",
- "operator GIGN-TWITCH BOPE-CAVEIRA NAVYSEAL-VALKYRIE SPETSNAZ-FUZE \n",
- "total_rounds 4894 4586 4319 4222 \n",
- "total_kills 3577 3293 2926 3336 \n",
- "total_deaths 3180 3362 3150 2929 \n",
- "\n",
- " G.E.O.-JACKAL ... GSG9-IQ BOPE-CAPITAO SAT-ECHO \\\n",
- "role Attacker ... Attacker Attacker Defender \n",
- "operator G.E.O.-JACKAL ... GSG9-IQ BOPE-CAPITAO SAT-ECHO \n",
- "total_rounds 4091 ... 1570 1554 1207 \n",
- "total_kills 3135 ... 1027 1082 775 \n",
- "total_deaths 2850 ... 1128 1105 775 \n",
- "\n",
- " GSG9-BLITZ SPETSNAZ-TACHANKA GSG9-RESERVE SAS-RESERVE \\\n",
- "role Attacker Defender Attacker Attacker \n",
- "operator GSG9-BLITZ SPETSNAZ-TACHANKA GSG9-RESERVE SAS-RESERVE \n",
- "total_rounds 782 436 219 165 \n",
- "total_kills 425 202 139 91 \n",
- "total_deaths 585 329 162 119 \n",
- "\n",
- " SWAT-RESERVE GIGN-RESERVE SPETSNAZ-RESERVE \n",
- "role Defender Attacker Defender \n",
- "operator SWAT-RESERVE GIGN-RESERVE SPETSNAZ-RESERVE \n",
- "total_rounds 84 77 70 \n",
- "total_kills 45 42 37 \n",
- "total_deaths 66 49 57 \n",
- "\n",
- "[5 rows x 35 columns]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -1270,178 +293,10 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"id": "task6-matches",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " matchid | \n",
- " mapname | \n",
- " gamemode | \n",
- " total_kills | \n",
- " total_rounds | \n",
- " max_duration | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | 4293620789 | \n",
- " 4293620789 | \n",
- " CHALET | \n",
- " PvP HOSTAGE | \n",
- " 57 | \n",
- " 9 | \n",
- " 232 | \n",
- "
\n",
- " \n",
- " | 1525148621 | \n",
- " 1525148621 | \n",
- " SKYSCRAPER | \n",
- " PvP SECURE AREA | \n",
- " 65 | \n",
- " 9 | \n",
- " 237 | \n",
- "
\n",
- " \n",
- " | 1577581 | \n",
- " 1577581 | \n",
- " KAFE DOSTOYEVSKY | \n",
- " PvP HOSTAGE | \n",
- " 63 | \n",
- " 9 | \n",
- " 232 | \n",
- "
\n",
- " \n",
- " | 4294842769 | \n",
- " 4294842769 | \n",
- " KAFE DOSTOYEVSKY | \n",
- " PvP SECURE AREA | \n",
- " 68 | \n",
- " 9 | \n",
- " 232 | \n",
- "
\n",
- " \n",
- " | 2886541 | \n",
- " 2886541 | \n",
- " BARTLETT U. | \n",
- " PvP SECURE AREA | \n",
- " 52 | \n",
- " 9 | \n",
- " 257 | \n",
- "
\n",
- " \n",
- " | ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- "
\n",
- " \n",
- " | 4287504149 | \n",
- " 4287504149 | \n",
- " BARTLETT U. | \n",
- " PvP BOMB | \n",
- " 3 | \n",
- " 1 | \n",
- " 153 | \n",
- "
\n",
- " \n",
- " | 4294525829 | \n",
- " 4294525829 | \n",
- " YACHT | \n",
- " PvP BOMB | \n",
- " 5 | \n",
- " 1 | \n",
- " 224 | \n",
- "
\n",
- " \n",
- " | 1523059021 | \n",
- " 1523059021 | \n",
- " YACHT | \n",
- " PvP SECURE AREA | \n",
- " 8 | \n",
- " 1 | \n",
- " 133 | \n",
- "
\n",
- " \n",
- " | 2766593549 | \n",
- " 2766593549 | \n",
- " BARTLETT U. | \n",
- " PvP SECURE AREA | \n",
- " 9 | \n",
- " 1 | \n",
- " 268 | \n",
- "
\n",
- " \n",
- " | 3281101 | \n",
- " 3281101 | \n",
- " CLUB HOUSE | \n",
- " PvP SECURE AREA | \n",
- " 7 | \n",
- " 1 | \n",
- " 186 | \n",
- "
\n",
- " \n",
- "
\n",
- "
1900 rows × 6 columns
\n",
- "
"
- ],
- "text/plain": [
- " matchid mapname gamemode total_kills \\\n",
- "4293620789 4293620789 CHALET PvP HOSTAGE 57 \n",
- "1525148621 1525148621 SKYSCRAPER PvP SECURE AREA 65 \n",
- "1577581 1577581 KAFE DOSTOYEVSKY PvP HOSTAGE 63 \n",
- "4294842769 4294842769 KAFE DOSTOYEVSKY PvP SECURE AREA 68 \n",
- "2886541 2886541 BARTLETT U. PvP SECURE AREA 52 \n",
- "... ... ... ... ... \n",
- "4287504149 4287504149 BARTLETT U. PvP BOMB 3 \n",
- "4294525829 4294525829 YACHT PvP BOMB 5 \n",
- "1523059021 1523059021 YACHT PvP SECURE AREA 8 \n",
- "2766593549 2766593549 BARTLETT U. PvP SECURE AREA 9 \n",
- "3281101 3281101 CLUB HOUSE PvP SECURE AREA 7 \n",
- "\n",
- " total_rounds max_duration \n",
- "4293620789 9 232 \n",
- "1525148621 9 237 \n",
- "1577581 9 232 \n",
- "4294842769 9 232 \n",
- "2886541 9 257 \n",
- "... ... ... \n",
- "4287504149 1 153 \n",
- "4294525829 1 224 \n",
- "1523059021 1 133 \n",
- "2766593549 1 268 \n",
- "3281101 1 186 \n",
- "\n",
- "[1900 rows x 6 columns]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
" \"*\"\n",
@@ -1486,35 +341,32 @@
"source": [
"def get_attachment_stats(field):\n",
" \"\"\"Get attachment statistics for a specific field.\"\"\"\n",
- " aggr = client.ft().aggregate(\n",
- " f\"@primaryweapontype:{TagField.field_name('*')}\",\n",
- " [\n",
- " {\n",
- " \"$group\": {\n",
- " \"_id\": f\"${field}\",\n",
- " \"count\": {\"$sum\": 1},\n",
- " }\n",
- " },\n",
- " {\"$match\": {\"_id\": {\"$ne\": \"\"}}},\n",
- " {\"$sort\": {\"count\": -1}},\n",
- " {\"$limit\": 10},\n",
- " ]\n",
+ " query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
+ " \"*\"\n",
+ " ).group_by(\n",
+ " f\"@{field}\",\n",
+ " reducers.count().alias(\"total_rounds\")\n",
+ " ).sort_by(Desc(\"@total_rounds\")) # pyright: ignore[reportArgumentType]\n",
+ " .limit(0, 35565).cursor(10, 1)\n",
" )\n",
- " return [{k: v for k, v in r.items() if k != \"type\"} for r in aggr[\"results\"]]\n",
"\n",
- "print(\"=== TOP 10 PRIMARY SIGHTS ===\")\n",
- "sights = get_attachment_stats(\"primarysight\")\n",
- "df_sights = pd.DataFrame(sights)\n",
+ " response = client.ft().aggregate(query)\n",
+ " rows = response[0][\"results\"]\n",
+ " cursor = response[1]\n",
+ " while cursor > 0:\n",
+ " response= client.ft().aggregate(Cursor(cursor))\n",
+ " rows.extend(response[0][\"results\"])\n",
+ " cursor = response[1]\n",
+ "\n",
+ " return pd.DataFrame.from_dict({attrs[\"extra_attributes\"][field]: attrs[\"extra_attributes\"] for attrs in rows})\n",
+ "\n",
+ "df_sights = get_attachment_stats(\"primarysight\")\n",
"display(df_sights)\n",
"\n",
- "print(\"\\n=== TOP 10 PRIMARY BARRELS ===\")\n",
- "barrels = get_attachment_stats(\"primarybarrel\")\n",
- "df_barrels = pd.DataFrame(barrels)\n",
+ "df_barrels = get_attachment_stats(\"primarybarrel\")\n",
"display(df_barrels)\n",
"\n",
- "print(\"\\n=== TOP 10 PRIMARY GRIPS ===\")\n",
- "grips = get_attachment_stats(\"primarygrip\")\n",
- "df_grips = pd.DataFrame(grips)\n",
+ "df_grips = get_attachment_stats(\"primarygrip\")\n",
"display(df_grips)"
]
},
@@ -1671,61 +523,30 @@
"metadata": {},
"outputs": [],
"source": [
- "def get_daily_stats():\n",
- " \"\"\"Get daily statistics using Redis aggregation.\"\"\"\n",
- " aggr = client.ft().aggregate(\n",
- " \"*\",\n",
- " [\n",
- " {\n",
- " \"$group\": {\n",
- " \"_id\": \"$dateid\",\n",
- " \"total_players\": {\"$sum\": 1},\n",
- " \"total_kills\": {\"$sum\": \"$nbkills\"},\n",
- " \"matches\": {\"$addToSet\": \"$matchid\"},\n",
- " \"avg_duration\": {\"$avg\": \"$roundduration\"},\n",
- " }\n",
- " },\n",
- " {\"$sort\": {\"_id\": 1}},\n",
- " ]\n",
- " )\n",
- " return [\n",
- " {\n",
- " \"date\": r[\"_id\"],\n",
- " \"player_actions\": r[\"total_players\"],\n",
- " \"total_kills\": r[\"total_kills\"],\n",
- " \"matches\": len(r[\"matches\"]),\n",
- " \"avg_round_duration\": round(r[\"avg_duration\"], 2),\n",
- " }\n",
- " for r in aggr[\"results\"]\n",
- " ]\n",
+ "query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
+ " \"*\"\n",
+ " ).group_by(\n",
+ " \"@dateid\",\n",
+ " reducers.count().alias(\"total_playcount\"),\n",
+ " reducers.count_distinct(\"@matchid\").alias(\"matches\"),\n",
+ " reducers.sum(\"@nbkills\").alias(\"total_kills\"),\n",
+ " reducers.avg(\"roundduration\").alias(\"avg_duration\")\n",
+ " ).sort_by(Asc(\"@dateid\")) # pyright: ignore[reportArgumentType]\n",
+ " .limit(0, 35565).cursor(10, 1)\n",
+ ")\n",
"\n",
- "print(\"Computing daily statistics...\")\n",
- "daily_stats = get_daily_stats()\n",
- "df_daily = pd.DataFrame(daily_stats)\n",
+ "response = client.ft().aggregate(query)\n",
+ "rows = response[0][\"results\"]\n",
+ "cursor = response[1]\n",
+ "while cursor > 0:\n",
+ " response= client.ft().aggregate(Cursor(cursor))\n",
+ " rows.extend(response[0][\"results\"])\n",
+ " cursor = response[1]\n",
+ "\n",
+ "df_daily = pd.DataFrame.from_dict({attrs[\"extra_attributes\"][\"dateid\"]: attrs[\"extra_attributes\"] for attrs in rows}).transpose()\n",
"display(df_daily)"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "task9-summary",
- "metadata": {},
- "outputs": [],
- "source": [
- "print(\"\\n=== DAILY ACTIVITY SUMMARY ===\")\n",
- "total_days = len(df_daily)\n",
- "avg_daily_matches = df_daily[\"matches\"].mean()\n",
- "avg_daily_kills = df_daily[\"total_kills\"].mean()\n",
- "busiest_day = df_daily.loc[df_daily[\"matches\"].idxmax()]\n",
- "calmest_day = df_daily.loc[df_daily[\"matches\"].idxmin()]\n",
- "\n",
- "print(f\"Total days in dataset: {total_days}\")\n",
- "print(f\"Average daily matches: {avg_daily_matches:.1f}\")\n",
- "print(f\"Average daily kills: {avg_daily_kills:.1f}\")\n",
- "print(f\"\\nBusiest day: {busiest_day['date']} with {busiest_day['matches']} matches\")\n",
- "print(f\"Calmest day: {calmest_day['date']} with {calmest_day['matches']} matches\")"
- ]
- },
{
"cell_type": "markdown",
"id": "task10-header",
@@ -1743,74 +564,30 @@
"metadata": {},
"outputs": [],
"source": [
- "def get_round_end_stats():\n",
- " \"\"\"Get round end reason statistics.\"\"\"\n",
- " aggr = client.ft().aggregate(\n",
- " \"*\",\n",
- " [\n",
- " {\n",
- " \"$group\": {\n",
- " \"_id\": \"$endroundreason\",\n",
- " \"count\": {\"$sum\": 1},\n",
- " \"avg_duration\": {\"$avg\": \"$roundduration\"},\n",
- " }\n",
- " },\n",
- " {\"$sort\": {\"count\": -1}},\n",
- " ]\n",
- " )\n",
- " return [\n",
- " {\n",
- " \"end_reason\": r[\"_id\"],\n",
- " \"count\": r[\"count\"],\n",
- " \"percentage\": 0,\n",
- " \"avg_duration\": round(r[\"avg_duration\"], 2),\n",
- " }\n",
- " for r in aggr[\"results\"]\n",
- " ]\n",
+ "query = (AggregateRequest( # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType, reportAssignmentType]\n",
+ " \"*\"\n",
+ " ).group_by(\n",
+ " \"@endroundreason\",\n",
+ " reducers.count().alias(\"count\"),\n",
+ " reducers.avg(\"roundduration\").alias(\"avg_duration\")\n",
+ " ).sort_by(Desc(\"@count\")) # pyright: ignore[reportArgumentType]\n",
+ " .limit(0, 35565).cursor(10, 1)\n",
+ ")\n",
"\n",
- "print(\"=== ROUND END REASONS ===\")\n",
- "round_end_stats = get_round_end_stats()\n",
- "df_ends = pd.DataFrame(round_end_stats)\n",
+ "response = client.ft().aggregate(query)\n",
+ "rows = response[0][\"results\"]\n",
+ "cursor = response[1]\n",
+ "while cursor > 0:\n",
+ " response= client.ft().aggregate(Cursor(cursor))\n",
+ " rows.extend(response[0][\"results\"])\n",
+ " cursor = response[1]\n",
+ "\n",
+ "df_ends = pd.DataFrame.from_dict({attrs[\"extra_attributes\"][\"endroundreason\"]: attrs[\"extra_attributes\"] for attrs in rows}).transpose()\n",
+ "df_ends[\"count\"] = df_ends[\"count\"].astype(\"int\")\n",
"total_rounds = df_ends[\"count\"].sum()\n",
"df_ends[\"percentage\"] = (df_ends[\"count\"] / total_rounds * 100).round(2)\n",
"display(df_ends)"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "task10-visual",
- "metadata": {},
- "outputs": [],
- "source": [
- "print(\"\\n=== ROUND END DISTRIBUTION ===\")\n",
- "for _, row in df_ends.iterrows():\n",
- " bar = \"█\" * int(row[\"percentage\"] / 2)\n",
- " print(f\"{row['end_reason']:25} | {bar} {row['percentage']:.1f}%\")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "conclusion",
- "metadata": {},
- "source": [
- "## Summary\n",
- "\n",
- "This notebook demonstrated various data analysis tasks using Redis:\n",
- "\n",
- "1. **Operator Performance Analysis** - Kill counts and win rates by operator\n",
- "2. **Weapon Analysis** - Primary and secondary weapon usage and effectiveness\n",
- "3. **Map and Game Mode Analysis** - Popular maps and game modes\n",
- "4. **Skill Rank Analysis** - Performance distribution across ranks\n",
- "5. **Role Distribution Analysis** - Attack vs Defense operator usage\n",
- "6. **Match-Level Analysis** - Individual match statistics\n",
- "7. **Weapon Attachment Analysis** - Popular attachments (sights, grips, barrels)\n",
- "8. **Redis-Side Pre-computation** - Using sorted sets for leaderboards\n",
- "9. **Time-Series Analysis** - Daily activity trends\n",
- "10. **Round End Reason Analysis** - Why rounds end\n",
- "\n",
- "All aggregations were performed directly in Redis using the FT.aggregate() command, demonstrating how Redis can handle complex analytical queries without moving data out of the database."
- ]
}
],
"metadata": {
diff --git a/notebooks/r6_load_resampled.ipynb b/notebooks/r6_load_resampled.ipynb
index da46415..4a3b9fd 100644
--- a/notebooks/r6_load_resampled.ipynb
+++ b/notebooks/r6_load_resampled.ipynb
@@ -2,39 +2,17 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "071f6969-c01a-4369-a763-871f5b9e65b3",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: redis in /opt/conda/lib/python3.13/site-packages (7.4.0)\n",
- "Requirement already satisfied: hiredis in /opt/conda/lib/python3.13/site-packages (3.3.1)\n",
- "Requirement already satisfied: fastid in /opt/conda/lib/python3.13/site-packages (0.0.5)\n",
- "Requirement already satisfied: tqdm in /opt/conda/lib/python3.13/site-packages (4.67.3)\n",
- "Requirement already satisfied: kagglehub in /opt/conda/lib/python3.13/site-packages (1.0.0)\n",
- "Requirement already satisfied: kagglesdk<1.0,>=0.1.14 in /opt/conda/lib/python3.13/site-packages (from kagglehub) (0.1.16)\n",
- "Requirement already satisfied: packaging in /opt/conda/lib/python3.13/site-packages (from kagglehub) (26.0)\n",
- "Requirement already satisfied: pyyaml in /opt/conda/lib/python3.13/site-packages (from kagglehub) (6.0.3)\n",
- "Requirement already satisfied: requests in /opt/conda/lib/python3.13/site-packages (from kagglehub) (2.32.5)\n",
- "Requirement already satisfied: protobuf in /opt/conda/lib/python3.13/site-packages (from kagglesdk<1.0,>=0.1.14->kagglehub) (6.33.5)\n",
- "Requirement already satisfied: charset_normalizer<4,>=2 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.4.6)\n",
- "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.11)\n",
- "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2.6.3)\n",
- "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2026.2.25)\n",
- "Note: you may need to restart the kernel to use updated packages.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"%pip install redis hiredis fastid tqdm kagglehub"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "526cb932-59aa-489e-bbba-954ac645b633",
"metadata": {},
"outputs": [],
@@ -66,20 +44,10 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "be4c5461-1db2-4226-b71e-cdc7f06615bd",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Downsample of full dump present: True'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"dataset = Path(kagglehub.dataset_download(\"awesomizer/rainbox-six-siege-dataset\"))\n",
"downsampled = dataset/\"downsampled_S5.csv\"\n",
@@ -88,25 +56,10 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "2efb5699-cced-4df0-9d76-278e23874436",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "2fa9c64b42394db7a5764896d7d936d0",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "0it [00:00, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"with downsampled.open(\"rb\") as f:\n",
" rows = sum(1 for _ in tqdm(f)) - 1"
@@ -114,25 +67,10 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "9177760b-eec4-4ab4-8242-0dd8df5db9dd",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "f235da3945864d409e81037d42269756",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Importing data into Redis...: 0%| | 0/102698 [00:00, ?row/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"with downsampled.open(errors=\"ignore\") as csvfile:\n",
" reader = DictReader(csvfile)\n",
@@ -144,21 +82,10 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "d8b75e35-8bef-4b2b-ae25-1982076c73fd",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'OK'"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"from redis.commands.search.field import TagField, NumericField\n",
"from redis.commands.search.index_definition import IndexDefinition, IndexType\n",
diff --git a/notebooks/r6_resample.ipynb b/notebooks/r6_resample.ipynb
index 7b98eca..9af3ad5 100644
--- a/notebooks/r6_resample.ipynb
+++ b/notebooks/r6_resample.ipynb
@@ -2,29 +2,10 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "80918139",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: tqdm in /opt/conda/lib/python3.13/site-packages (4.67.3)\n",
- "Requirement already satisfied: kagglehub in /opt/conda/lib/python3.13/site-packages (1.0.0)\n",
- "Requirement already satisfied: kagglesdk<1.0,>=0.1.14 in /opt/conda/lib/python3.13/site-packages (from kagglehub) (0.1.16)\n",
- "Requirement already satisfied: packaging in /opt/conda/lib/python3.13/site-packages (from kagglehub) (26.0)\n",
- "Requirement already satisfied: pyyaml in /opt/conda/lib/python3.13/site-packages (from kagglehub) (6.0.3)\n",
- "Requirement already satisfied: requests in /opt/conda/lib/python3.13/site-packages (from kagglehub) (2.32.5)\n",
- "Requirement already satisfied: protobuf in /opt/conda/lib/python3.13/site-packages (from kagglesdk<1.0,>=0.1.14->kagglehub) (6.33.5)\n",
- "Requirement already satisfied: charset_normalizer<4,>=2 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.4.6)\n",
- "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (3.11)\n",
- "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2.6.3)\n",
- "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.13/site-packages (from requests->kagglehub) (2026.2.25)\n",
- "Note: you may need to restart the kernel to use updated packages.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"%pip install tqdm kagglehub"
]
@@ -43,7 +24,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "ed9fdf86",
"metadata": {},
"outputs": [],
@@ -64,18 +45,10 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "8e6a156d",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Path to dataset files: /home/jovyan/.cache/kagglehub/datasets/awesomizer/rainbox-six-siege-dataset/versions/1\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"dataset = Path(kagglehub.dataset_download(\"awesomizer/rainbox-six-siege-dataset\"))\n",
"\n",
@@ -92,52 +65,10 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "30d83f96",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Full dump present: True'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'Objective picks present: True'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'Operator loadouts present: True'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "86eacf0882aa4337a32fc2ea893a4d18",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "0it [00:00, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"full_dump = dataset/\"datadump_S5\"/\"datadump_S5.csv\"\n",
"objectives = dataset/\"datadump_S5_summary_objectives\"/\"datadump_S5_summary_objectives.csv\"\n",
@@ -160,17125 +91,10 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"id": "477feac7",
"metadata": {},
- "outputs": [
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "5d34c1829a0b42649d675632071234a1",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Importing raw data into Redis...: 0%| | 0/85939712 [00:00, ?row/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'Selected 1522380841 for day 20170212'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'Selected 1522488121 for day 20170212'"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "'Selected 1522514641 for day 20170212'"
- ]
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- "'Selected 1522741281 for day 20170212'"
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- },
- {
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- "'Selected 1522760761 for day 20170212'"
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- "'Selected 1523059021 for day 20170212'"
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+ "outputs": [],
"source": [
"daily_matches: dict[str, set[str]] = {}\n",
"with full_dump.open(errors=\"ignore\") as csvfile:\n",