| Name | kola JSON |
| Version |
1.5.2
JSON |
| download |
| home_page | None |
| Summary | a Python Polars interface to kdb+/q |
| upload_time | 2024-11-21 14:45:07 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
q
kdb
polars
dataframe
arrow
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# kola
a Python [Polars](https://pola-rs.github.io/polars/) Interface to kdb+/q
## Basic Data Type Map
### Deserialization
#### Atom
| k type | n | size | python type | note |
| ----------- | --- | ---- | ----------- | --------------------------- |
| `boolean` | 1 | 1 | `bool` | |
| `guid` | 2 | 16 | `str` | |
| `byte` | 4 | 1 | `int` | |
| `short` | 5 | 2 | `int` | |
| `int` | 6 | 4 | `int` | |
| `long` | 7 | 8 | `int` | |
| `real` | 8 | 4 | `float` | |
| `float` | 9 | 8 | `float` | |
| `char` | 10 | 1 | `str` | |
| `string` | 10 | 1 | `str` | |
| `symbol` | 11 | \* | `str` | |
| `timestamp` | 12 | 8 | `datetime` | |
| `month` | 13 | 4 | `-` | |
| `date` | 14 | 4 | `date` | 0001.01.01 - 9999.12.31 |
| `datetime` | 15 | 8 | `datetime` | |
| `timespan` | 16 | 8 | `timedelta` | |
| `minute` | 17 | 4 | `time` | 00:00 - 23:59 |
| `second` | 18 | 4 | `time` | 00:00:00 - 23:59:59 |
| `time` | 19 | 4 | `time` | 00:00:00.000 - 23:59:59.999 |
#### Composite Data Type
| k type | n | size | python type |
| ---------------- | --- | ---- | ------------------------ |
| `boolean list` | 1 | 1 | `pl.Boolean` |
| `guid list` | 2 | 16 | `pl.List(pl.Binary(16))` |
| `byte list` | 4 | 1 | `pl.Uint8` |
| `short list` | 5 | 2 | `pl.Int16` |
| `int list` | 6 | 4 | `pl.Int32` |
| `long list` | 7 | 8 | `pl.Int64` |
| `real list` | 8 | 4 | `pl.Float32` |
| `float list` | 9 | 8 | `pl.Float64` |
| `char list` | 10 | 1 | `pl.Utf8` |
| `string list` | 10 | 1 | `pl.Utf8` |
| `symbol list` | 11 | \* | `pl.Categorical` |
| `timestamp list` | 12 | 8 | `pl.Datetime` |
| `month list` | 13 | 4 | `-` |
| `date list` | 14 | 4 | `pl.Date` |
| `datetime list` | 15 | 8 | `pl.Datetime` |
| `timespan list` | 16 | 8 | `pl.Duration` |
| `minute list` | 17 | 4 | `pl.Time` |
| `second list` | 18 | 4 | `pl.Time` |
| `time list` | 19 | 4 | `pl.Time` |
| `table` | 98 | \* | `pl.DataFrame` |
| `dictionary` | 99 | \* | `-` |
| `keyed table` | 99 | \* | `pl.DataFrame` |
> performance is impacted by converting guid to string, deserialize the uuid to 16 fixed binary list, use .hex() to convert binary to string if required
> real/float 0n is mapped to Polars null not NaN
> short/int/long 0Nh/i/j, 0Wh/i/j and -0Wh/i/j are mapped to null
```
df.with_columns([
(pl.col("uuid").apply(lambda u: u.hex()))
])
```
### Serialization
#### Basic Data Type
| python type | k type | note |
| ----------- | ----------- | --------------------------- |
| `bool` | `boolean` | |
| `int` | `long` | |
| `float` | `float` | |
| `str` | `symbol` | |
| `bytes` | `string` | |
| `datetime` | `timestamp` | |
| `date` | `date` | 0001.01.01 - 9999.12.31 |
| `datetime` | `datetime` | |
| `timedelta` | `timespan` | |
| `time` | `time` | 00:00:00.000 - 23:59:59.999 |
#### Dictionary, Series and DataFrame
| python type | k type |
| ------------------------ | --------- |
| `dict` | dict |
| `pl.Boolean` | boolean |
| `pl.List(pl.Binary(16))` | guid |
| `pl.Uint8` | byte |
| `pl.Int16` | short |
| `pl.Int32` | int |
| `pl.Int64` | long |
| `pl.Float32` | real |
| `pl.Float64` | float |
| `pl.Utf8` | char |
| `pl.Categorical` | symbol |
| `pl.Datetime` | timestamp |
| `pl.Date` | date |
| `pl.Datetime` | datetime |
| `pl.Duration` | timespan |
| `pl.Time` | time |
| `pl.DataFrame` | table |
> Limited Support for dictionary as arguments, requires `string` as keys.
## Quick Start
### Create a Connection
```python
import polars as pl
import kola
q = kola.Q('localhost', 1800)
# with retries for IO Errors, 1s, 2s, 4s ...
q = kola.Q('localhost', 1800, retries=3)
# with read timeout error, 2s, "Resource temporarily unavailable"
q = kola.Q('localhost', 1800, retries=3, timeout=2)
```
### Connect(Optional)
Automatically connect when querying q process
```python
q.connect()
```
### Disconnect
Automatically disconnect if any IO error
```python
q.disconnect()
```
### String Query
```python
q.sync("select from trade where date=last date")
```
### Lambda Query
When the first string starts with `{` and ends with `}`, it is treated as a lambda.
```python
d = {"a": 1, "b": 2}
q.sync("{key x}", d)
```
### Functional Query
For functional query, `kola` supports Python [Basic Data Type](#basic-data-type), `pl.Series`, `pl.DataFrame` and Python Dictionary with string keys and Python [Basic Data Type](#basic-data-type) and `pl.Series` values.
```python
from datetime import date, time
q.sync(
".gw.query",
"table",
{
"date": date(2023, 11, 21),
"syms": pl.Series("", ["sym0", "sym1"], pl.Categorical),
# 09:00
"startTime": time(9),
# 11:30
"endTime": time(11, 30),
},
)
```
### Send DataFrame
```python
# pl_df is a Polars DataFrame
q.sync("upsert", "table", pl_df)
```
```python
# pd_df is a Pandas DataFrame, use pl.DateFrame to cast Pandas DataFrame
q.sync("upsert", "table", pl.DataFrame(pd_df))
```
### Async Query
```python
# pl_df is a Polars DataFrame
q.asyn("upsert", "table", pl_df)
```
### Subscribe
```python
from kola import QType
q.sync(".u.sub", pl.Series("", ["table1", "table2"], QType.Symbol), "")
# specify symbol filter
q.sync(
".u.sub",
pl.Series("", ["table1", "table2"], QType.Symbol),
pl.Series("", ["sym1", "sym2"], QType.Symbol),
)
while true:
# ("upd", "table", pl.Dataframe)
upd = self.q.receive()
print(upd)
```
### Generate IPC
```python
import polars as pl
from kola import generate_ipc
df = pl.DataFrame(
{
"sym": pl.Series("sym", ["a", "b", "c"], pl.Categorical),
"price": [1, 2, 3],
}
)
# without compression
buffer = generate_ipc("sync", False, ["upd", "table", df])
# with compression
buffer = generate_ipc("sync", True, ["upd", "table", df])
```
## Polars Documentations
Refer to
- [User Guide](https://pola-rs.github.io/polars/user-guide/)
- [API Reference](https://pola-rs.github.io/polars/py-polars/html/reference/index.html)
Raw data
{
"_id": null,
"home_page": null,
"name": "kola",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "q, kdb, polars, dataframe, arrow",
"author": null,
"author_email": "Jo Shinonome <jo.shinonome@gmail.com>",
"download_url": null,
"platform": null,
"description": "# kola\n\na Python [Polars](https://pola-rs.github.io/polars/) Interface to kdb+/q\n\n## Basic Data Type Map\n\n### Deserialization\n\n#### Atom\n\n| k type | n | size | python type | note |\n| ----------- | --- | ---- | ----------- | --------------------------- |\n| `boolean` | 1 | 1 | `bool` | |\n| `guid` | 2 | 16 | `str` | |\n| `byte` | 4 | 1 | `int` | |\n| `short` | 5 | 2 | `int` | |\n| `int` | 6 | 4 | `int` | |\n| `long` | 7 | 8 | `int` | |\n| `real` | 8 | 4 | `float` | |\n| `float` | 9 | 8 | `float` | |\n| `char` | 10 | 1 | `str` | |\n| `string` | 10 | 1 | `str` | |\n| `symbol` | 11 | \\* | `str` | |\n| `timestamp` | 12 | 8 | `datetime` | |\n| `month` | 13 | 4 | `-` | |\n| `date` | 14 | 4 | `date` | 0001.01.01 - 9999.12.31 |\n| `datetime` | 15 | 8 | `datetime` | |\n| `timespan` | 16 | 8 | `timedelta` | |\n| `minute` | 17 | 4 | `time` | 00:00 - 23:59 |\n| `second` | 18 | 4 | `time` | 00:00:00 - 23:59:59 |\n| `time` | 19 | 4 | `time` | 00:00:00.000 - 23:59:59.999 |\n\n#### Composite Data Type\n\n| k type | n | size | python type |\n| ---------------- | --- | ---- | ------------------------ |\n| `boolean list` | 1 | 1 | `pl.Boolean` |\n| `guid list` | 2 | 16 | `pl.List(pl.Binary(16))` |\n| `byte list` | 4 | 1 | `pl.Uint8` |\n| `short list` | 5 | 2 | `pl.Int16` |\n| `int list` | 6 | 4 | `pl.Int32` |\n| `long list` | 7 | 8 | `pl.Int64` |\n| `real list` | 8 | 4 | `pl.Float32` |\n| `float list` | 9 | 8 | `pl.Float64` |\n| `char list` | 10 | 1 | `pl.Utf8` |\n| `string list` | 10 | 1 | `pl.Utf8` |\n| `symbol list` | 11 | \\* | `pl.Categorical` |\n| `timestamp list` | 12 | 8 | `pl.Datetime` |\n| `month list` | 13 | 4 | `-` |\n| `date list` | 14 | 4 | `pl.Date` |\n| `datetime list` | 15 | 8 | `pl.Datetime` |\n| `timespan list` | 16 | 8 | `pl.Duration` |\n| `minute list` | 17 | 4 | `pl.Time` |\n| `second list` | 18 | 4 | `pl.Time` |\n| `time list` | 19 | 4 | `pl.Time` |\n| `table` | 98 | \\* | `pl.DataFrame` |\n| `dictionary` | 99 | \\* | `-` |\n| `keyed table` | 99 | \\* | `pl.DataFrame` |\n\n> performance is impacted by converting guid to string, deserialize the uuid to 16 fixed binary list, use .hex() to convert binary to string if required\n\n> real/float 0n is mapped to Polars null not NaN\n\n> short/int/long 0Nh/i/j, 0Wh/i/j and -0Wh/i/j are mapped to null\n\n```\ndf.with_columns([\n (pl.col(\"uuid\").apply(lambda u: u.hex()))\n ])\n```\n\n### Serialization\n\n#### Basic Data Type\n\n| python type | k type | note |\n| ----------- | ----------- | --------------------------- |\n| `bool` | `boolean` | |\n| `int` | `long` | |\n| `float` | `float` | |\n| `str` | `symbol` | |\n| `bytes` | `string` | |\n| `datetime` | `timestamp` | |\n| `date` | `date` | 0001.01.01 - 9999.12.31 |\n| `datetime` | `datetime` | |\n| `timedelta` | `timespan` | |\n| `time` | `time` | 00:00:00.000 - 23:59:59.999 |\n\n#### Dictionary, Series and DataFrame\n\n| python type | k type |\n| ------------------------ | --------- |\n| `dict` | dict |\n| `pl.Boolean` | boolean |\n| `pl.List(pl.Binary(16))` | guid |\n| `pl.Uint8` | byte |\n| `pl.Int16` | short |\n| `pl.Int32` | int |\n| `pl.Int64` | long |\n| `pl.Float32` | real |\n| `pl.Float64` | float |\n| `pl.Utf8` | char |\n| `pl.Categorical` | symbol |\n| `pl.Datetime` | timestamp |\n| `pl.Date` | date |\n| `pl.Datetime` | datetime |\n| `pl.Duration` | timespan |\n| `pl.Time` | time |\n| `pl.DataFrame` | table |\n\n> Limited Support for dictionary as arguments, requires `string` as keys.\n\n## Quick Start\n\n### Create a Connection\n\n```python\nimport polars as pl\nimport kola\nq = kola.Q('localhost', 1800)\n\n# with retries for IO Errors, 1s, 2s, 4s ...\nq = kola.Q('localhost', 1800, retries=3)\n\n# with read timeout error, 2s, \"Resource temporarily unavailable\"\nq = kola.Q('localhost', 1800, retries=3, timeout=2)\n```\n\n### Connect(Optional)\n\nAutomatically connect when querying q process\n\n```python\nq.connect()\n```\n\n### Disconnect\n\nAutomatically disconnect if any IO error\n\n```python\nq.disconnect()\n```\n\n### String Query\n\n```python\nq.sync(\"select from trade where date=last date\")\n```\n\n### Lambda Query\n\nWhen the first string starts with `{` and ends with `}`, it is treated as a lambda.\n\n```python\nd = {\"a\": 1, \"b\": 2}\nq.sync(\"{key x}\", d)\n```\n\n### Functional Query\n\nFor functional query, `kola` supports Python [Basic Data Type](#basic-data-type), `pl.Series`, `pl.DataFrame` and Python Dictionary with string keys and Python [Basic Data Type](#basic-data-type) and `pl.Series` values.\n\n```python\nfrom datetime import date, time\n\nq.sync(\n \".gw.query\",\n \"table\",\n {\n \"date\": date(2023, 11, 21),\n \"syms\": pl.Series(\"\", [\"sym0\", \"sym1\"], pl.Categorical),\n # 09:00\n \"startTime\": time(9),\n # 11:30\n \"endTime\": time(11, 30),\n },\n)\n```\n\n### Send DataFrame\n\n```python\n# pl_df is a Polars DataFrame\nq.sync(\"upsert\", \"table\", pl_df)\n```\n\n```python\n# pd_df is a Pandas DataFrame, use pl.DateFrame to cast Pandas DataFrame\nq.sync(\"upsert\", \"table\", pl.DataFrame(pd_df))\n```\n\n### Async Query\n\n```python\n# pl_df is a Polars DataFrame\nq.asyn(\"upsert\", \"table\", pl_df)\n```\n\n### Subscribe\n\n```python\nfrom kola import QType\n\nq.sync(\".u.sub\", pl.Series(\"\", [\"table1\", \"table2\"], QType.Symbol), \"\")\n\n# specify symbol filter\nq.sync(\n \".u.sub\",\n pl.Series(\"\", [\"table1\", \"table2\"], QType.Symbol),\n pl.Series(\"\", [\"sym1\", \"sym2\"], QType.Symbol),\n)\n\nwhile true:\n # (\"upd\", \"table\", pl.Dataframe)\n upd = self.q.receive()\n print(upd)\n```\n\n### Generate IPC\n\n```python\nimport polars as pl\nfrom kola import generate_ipc\n\ndf = pl.DataFrame(\n {\n \"sym\": pl.Series(\"sym\", [\"a\", \"b\", \"c\"], pl.Categorical),\n \"price\": [1, 2, 3],\n }\n)\n# without compression\nbuffer = generate_ipc(\"sync\", False, [\"upd\", \"table\", df])\n\n# with compression\nbuffer = generate_ipc(\"sync\", True, [\"upd\", \"table\", df])\n```\n\n## Polars Documentations\n\nRefer to\n\n- [User Guide](https://pola-rs.github.io/polars/user-guide/)\n- [API Reference](https://pola-rs.github.io/polars/py-polars/html/reference/index.html)\n\n",
"bugtrack_url": null,
"license": null,
"summary": "a Python Polars interface to kdb+/q",
"version": "1.5.2",
"project_urls": {
"Repository": "https://github.com/jshinonome/kola"
},
"split_keywords": [
"q",
" kdb",
" polars",
" dataframe",
" arrow"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "d23cd1d05fb95a719e6999562a008752f3e90c0497e6bf7baacda8489acd353f",
"md5": "69fe2e18c1b74e4f406e0af5dbb0adcd",
"sha256": "9c631094747490a09a5129496e7b3d59c0cba9b47392d46ec7e51d86749f37bc"
},
"downloads": -1,
"filename": "kola-1.5.2-cp310-cp310-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "69fe2e18c1b74e4f406e0af5dbb0adcd",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.9",
"size": 4616386,
"upload_time": "2024-11-21T14:45:07",
"upload_time_iso_8601": "2024-11-21T14:45:07.838785Z",
"url": "https://files.pythonhosted.org/packages/d2/3c/d1d05fb95a719e6999562a008752f3e90c0497e6bf7baacda8489acd353f/kola-1.5.2-cp310-cp310-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ef7a027f38a43485cd184bae2aecbdbe230b986584b1080de6c345337c238eb3",
"md5": "ff415b5f77be0cb58e6185e731a73cda",
"sha256": "b23b777cfab3988d3b3535a47f74ff68166d0dd7a2706260380fb521b09e180e"
},
"downloads": -1,
"filename": "kola-1.5.2-cp310-cp310-manylinux_2_31_x86_64.whl",
"has_sig": false,
"md5_digest": "ff415b5f77be0cb58e6185e731a73cda",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.9",
"size": 7130463,
"upload_time": "2024-11-21T14:27:04",
"upload_time_iso_8601": "2024-11-21T14:27:04.421848Z",
"url": "https://files.pythonhosted.org/packages/ef/7a/027f38a43485cd184bae2aecbdbe230b986584b1080de6c345337c238eb3/kola-1.5.2-cp310-cp310-manylinux_2_31_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "391770d2b2c19396da8684e257e3e8b407a3470337403c4870d8b9c491e217a4",
"md5": "4965856547714b97349ae4d713a1df9a",
"sha256": "266b37b43f7a95dfd51a4fd05b6c07102fb2093e1687bda5934455f37834656e"
},
"downloads": -1,
"filename": "kola-1.5.2-cp310-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "4965856547714b97349ae4d713a1df9a",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.9",
"size": 4852867,
"upload_time": "2024-11-21T14:32:21",
"upload_time_iso_8601": "2024-11-21T14:32:21.489097Z",
"url": "https://files.pythonhosted.org/packages/39/17/70d2b2c19396da8684e257e3e8b407a3470337403c4870d8b9c491e217a4/kola-1.5.2-cp310-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "7dbe53bda0264d037da4a993f6157ac4e1de7e2ac578fdb19b37e21bba15ef53",
"md5": "4100996b567b2a23b8e42e07ad9812ae",
"sha256": "63d70d2d2fddef2fb227f62756f67e29a3e105c1a3c7e843f818ecf10fb5fc21"
},
"downloads": -1,
"filename": "kola-1.5.2-cp311-cp311-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "4100996b567b2a23b8e42e07ad9812ae",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.9",
"size": 4615741,
"upload_time": "2024-11-21T14:45:10",
"upload_time_iso_8601": "2024-11-21T14:45:10.701006Z",
"url": "https://files.pythonhosted.org/packages/7d/be/53bda0264d037da4a993f6157ac4e1de7e2ac578fdb19b37e21bba15ef53/kola-1.5.2-cp311-cp311-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ede858eb3854423385c5df0dda8f6bf2a543bb0bc11161d93c44604d7509774a",
"md5": "cde41fa5ee166328bbecfb78c755c339",
"sha256": "d1be6ca7a7d43e6c5e31197662f2acc51bb740d685faf3677f8212fe381fbeb2"
},
"downloads": -1,
"filename": "kola-1.5.2-cp311-cp311-manylinux_2_31_x86_64.whl",
"has_sig": false,
"md5_digest": "cde41fa5ee166328bbecfb78c755c339",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.9",
"size": 7130184,
"upload_time": "2024-11-21T14:27:07",
"upload_time_iso_8601": "2024-11-21T14:27:07.521088Z",
"url": "https://files.pythonhosted.org/packages/ed/e8/58eb3854423385c5df0dda8f6bf2a543bb0bc11161d93c44604d7509774a/kola-1.5.2-cp311-cp311-manylinux_2_31_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ae4792447308ab5fcbb120de1e6f95bda03d01513b1428316ed3e80720e75168",
"md5": "13c9c496a2242ca72a7f192c09366ad4",
"sha256": "7fd5d0d65f3ac8162894c9d63cff064371131d8278f0a1b5fb097dd5da41d229"
},
"downloads": -1,
"filename": "kola-1.5.2-cp311-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "13c9c496a2242ca72a7f192c09366ad4",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.9",
"size": 4853181,
"upload_time": "2024-11-21T14:32:23",
"upload_time_iso_8601": "2024-11-21T14:32:23.981724Z",
"url": "https://files.pythonhosted.org/packages/ae/47/92447308ab5fcbb120de1e6f95bda03d01513b1428316ed3e80720e75168/kola-1.5.2-cp311-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "3753d56eedc83de7acec3e3f1592b1c0a176260b12c605c0c1b2b642680901d0",
"md5": "25bff077d82eb6683665c4ebf2a60fc3",
"sha256": "41321fb42c7480e1f9d4755385e9de78c1dd664df2c9bd0ccc180cfcdb0c794a"
},
"downloads": -1,
"filename": "kola-1.5.2-cp312-cp312-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "25bff077d82eb6683665c4ebf2a60fc3",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": ">=3.9",
"size": 4615624,
"upload_time": "2024-11-21T14:45:13",
"upload_time_iso_8601": "2024-11-21T14:45:13.673903Z",
"url": "https://files.pythonhosted.org/packages/37/53/d56eedc83de7acec3e3f1592b1c0a176260b12c605c0c1b2b642680901d0/kola-1.5.2-cp312-cp312-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5c20c329e927b5bd1ab9435ee6c732e3f0981f072042d06dcaa5304670699673",
"md5": "568599f2e5ce29aecd1063e2dc7414f0",
"sha256": "7f239df39b34b5ff60cabbe38dae1412acbf8faa2e60563f49161fc19fc60054"
},
"downloads": -1,
"filename": "kola-1.5.2-cp312-cp312-manylinux_2_31_x86_64.whl",
"has_sig": false,
"md5_digest": "568599f2e5ce29aecd1063e2dc7414f0",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": ">=3.9",
"size": 7129088,
"upload_time": "2024-11-21T14:27:09",
"upload_time_iso_8601": "2024-11-21T14:27:09.742545Z",
"url": "https://files.pythonhosted.org/packages/5c/20/c329e927b5bd1ab9435ee6c732e3f0981f072042d06dcaa5304670699673/kola-1.5.2-cp312-cp312-manylinux_2_31_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "afb888c17ecc3f426c70ab55a06305996d1dc98c39fbc2f89a1e9e19e167bac0",
"md5": "d1c58e3af1693f02b3b784b89753231a",
"sha256": "4d5e4f462ee7f2c7bc7dc42d94e72401d3239920d588e48d74db9f86d29499f0"
},
"downloads": -1,
"filename": "kola-1.5.2-cp312-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "d1c58e3af1693f02b3b784b89753231a",
"packagetype": "bdist_wheel",
"python_version": "cp312",
"requires_python": ">=3.9",
"size": 4852480,
"upload_time": "2024-11-21T14:32:25",
"upload_time_iso_8601": "2024-11-21T14:32:25.776225Z",
"url": "https://files.pythonhosted.org/packages/af/b8/88c17ecc3f426c70ab55a06305996d1dc98c39fbc2f89a1e9e19e167bac0/kola-1.5.2-cp312-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "3f888c6754e1b1d080bc31ad709e389945ad829b158c2be13135faa6054ec05d",
"md5": "72cf71e6ab674a49fb94121a7e28d2e7",
"sha256": "0a81915132f2ecc405994a74139534f0b781c7a096fe928055e2092726b67d60"
},
"downloads": -1,
"filename": "kola-1.5.2-cp313-cp313-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "72cf71e6ab674a49fb94121a7e28d2e7",
"packagetype": "bdist_wheel",
"python_version": "cp313",
"requires_python": ">=3.9",
"size": 4615372,
"upload_time": "2024-11-21T14:45:17",
"upload_time_iso_8601": "2024-11-21T14:45:17.031980Z",
"url": "https://files.pythonhosted.org/packages/3f/88/8c6754e1b1d080bc31ad709e389945ad829b158c2be13135faa6054ec05d/kola-1.5.2-cp313-cp313-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "6dfe59440a3eff3d3f57f5ee0fd3d8e9acf03428e93b1f499cdfe2b24f480714",
"md5": "0c236cc95d3446b8c91743ff68428ef5",
"sha256": "38739f6bed86fab8f40703be9e9d9389ba00397e85ea45adab67859b00b6c1b6"
},
"downloads": -1,
"filename": "kola-1.5.2-cp313-cp313-manylinux_2_31_x86_64.whl",
"has_sig": false,
"md5_digest": "0c236cc95d3446b8c91743ff68428ef5",
"packagetype": "bdist_wheel",
"python_version": "cp313",
"requires_python": ">=3.9",
"size": 7128219,
"upload_time": "2024-11-21T14:27:12",
"upload_time_iso_8601": "2024-11-21T14:27:12.508755Z",
"url": "https://files.pythonhosted.org/packages/6d/fe/59440a3eff3d3f57f5ee0fd3d8e9acf03428e93b1f499cdfe2b24f480714/kola-1.5.2-cp313-cp313-manylinux_2_31_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2f76508f97baf8ffce2489fc7de062fbab1ab51c29bdd5f54d5f64b1aa264bae",
"md5": "519de885001468faa0784160adc49541",
"sha256": "483af56f1342b2c9150dfe9ff2e254196ddd90114b8e05fa48ffa7971610603f"
},
"downloads": -1,
"filename": "kola-1.5.2-cp313-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "519de885001468faa0784160adc49541",
"packagetype": "bdist_wheel",
"python_version": "cp313",
"requires_python": ">=3.9",
"size": 4851968,
"upload_time": "2024-11-21T14:32:28",
"upload_time_iso_8601": "2024-11-21T14:32:28.163976Z",
"url": "https://files.pythonhosted.org/packages/2f/76/508f97baf8ffce2489fc7de062fbab1ab51c29bdd5f54d5f64b1aa264bae/kola-1.5.2-cp313-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "73fbfb303c3cb7b7763e783920e6b5ec640c4c1ca98c7b8e6a86538cd623e9cb",
"md5": "d101c5514e73fa52ddc502f707b65aed",
"sha256": "981ba0be9377312225b84339a48b4199ebc739e97e32f05f0ddc4c1fc7eef17c"
},
"downloads": -1,
"filename": "kola-1.5.2-cp39-cp39-macosx_11_0_arm64.whl",
"has_sig": false,
"md5_digest": "d101c5514e73fa52ddc502f707b65aed",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.9",
"size": 4618173,
"upload_time": "2024-11-21T14:45:19",
"upload_time_iso_8601": "2024-11-21T14:45:19.981122Z",
"url": "https://files.pythonhosted.org/packages/73/fb/fb303c3cb7b7763e783920e6b5ec640c4c1ca98c7b8e6a86538cd623e9cb/kola-1.5.2-cp39-cp39-macosx_11_0_arm64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "68b79fa91a5e88ad2266c56c1ba24e7b2d02bc07cda8e6dd4345039ec10f3bcd",
"md5": "1588dc94ceab1e0fffcd44bf53490237",
"sha256": "5f9d337d57005d251727cde904bedbe831078bfe0bcf0e0a5a9ebf7dd19f9980"
},
"downloads": -1,
"filename": "kola-1.5.2-cp39-cp39-manylinux_2_31_x86_64.whl",
"has_sig": false,
"md5_digest": "1588dc94ceab1e0fffcd44bf53490237",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.9",
"size": 7130296,
"upload_time": "2024-11-21T14:27:15",
"upload_time_iso_8601": "2024-11-21T14:27:15.342303Z",
"url": "https://files.pythonhosted.org/packages/68/b7/9fa91a5e88ad2266c56c1ba24e7b2d02bc07cda8e6dd4345039ec10f3bcd/kola-1.5.2-cp39-cp39-manylinux_2_31_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "e70de66b990778507133341447f965d78799da2eaf29beec42f19daef9e07a39",
"md5": "41b9749847132e16b39ef4c63472e932",
"sha256": "0864f26c166a1f2d123f2ccbe577c4f37b87695147a95a70318760d179cfb090"
},
"downloads": -1,
"filename": "kola-1.5.2-cp39-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "41b9749847132e16b39ef4c63472e932",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.9",
"size": 4854464,
"upload_time": "2024-11-21T14:32:30",
"upload_time_iso_8601": "2024-11-21T14:32:30.666056Z",
"url": "https://files.pythonhosted.org/packages/e7/0d/e66b990778507133341447f965d78799da2eaf29beec42f19daef9e07a39/kola-1.5.2-cp39-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-11-21 14:45:07",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "jshinonome",
"github_project": "kola",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "kola"
}
