mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-12-30 19:39:09 +00:00
removed testing notebook,
anticipated removal of pandas requirement, added pandas and matplotlib to pyinstaller exclusion, removed unessasary option in build scripts
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parent
d798bfe7d2
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0fd24d42e1
@ -2,4 +2,4 @@ set pathtospec="../src/cli/superscript.spec"
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set pathtodist="../dist/"
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set pathtowork="temp/"
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pyinstaller --onefile --clean --distpath %pathtodist% --workpath %pathtowork% %pathtospec%
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pyinstaller --clean --distpath %pathtodist% --workpath %pathtowork% %pathtospec%
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@ -2,4 +2,4 @@ pathtospec="../src/cli/superscript.spec"
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pathtodist="../dist/"
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pathtowork="temp/"
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pyinstaller --onefile --clean --distpath ${pathtodist} --workpath ${pathtowork} ${pathtospec}
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pyinstaller --clean --distpath ${pathtodist} --workpath ${pathtowork} ${pathtospec}
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@ -1,5 +1,4 @@
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import requests
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import pandas as pd
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def pull_new_tba_matches(apikey, competition, cutoff):
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api_key= apikey
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@ -13,7 +13,10 @@ a = Analysis(['superscript.py'],
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],
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hookspath=[],
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runtime_hooks=[],
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excludes=[],
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excludes=[
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"matplotlib",
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"pandas"
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],
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win_no_prefer_redirects=False,
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win_private_assemblies=False,
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cipher=block_cipher,
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@ -1,116 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"class C1:\n",
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"\tval = 0\n",
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"\tdef __init__(self, i):\n",
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"\t\tself.val = i\n",
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"\n",
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"class C2:\n",
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"\tval = 0\n",
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"\tdef __init__(self, i):\n",
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"\t\tself.val = 2*i\n",
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"\n",
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"class C3:\n",
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"\tval = 0\n",
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"\tdef __init__(self, i):\n",
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"\t\tself.val = 3*i"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<__main__.C1 at 0x7fa84827afd0>,\n",
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" <__main__.C2 at 0x7fa84827ae80>,\n",
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" <__main__.C3 at 0x7fa8482020d0>]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"classes = [C1, C2, C3]\n",
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"initialized = []\n",
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"for c in classes:\n",
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"\tinitialized.append(c(10))\n",
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"initialized"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"import module\n",
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"module_references = {\"match\": module.Match}\n",
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"module_initialized = []\n",
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"for m in [\"match\"]:\n",
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"\tmodule_initialized.append(module_references[m](\"\", \"\", \"\", 0, []))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<module.Match at 0x7f0e47c45ee0>]"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"module_initialized"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
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},
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"kernelspec": {
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"display_name": "Python 3.8.5 64-bit",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.5"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@ -1,6 +1,5 @@
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requests
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pymongo
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pandas
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tra-analysis
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dnspython
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@ -11,7 +10,6 @@ scipy
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scikit-learn
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six
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pyparsing
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pandas
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kivy==2.0.0rc2
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