How to use remove_nones method in localstack

Best Python code snippet using localstack_python

app.py

Source:app.py Github

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...69 remove_nones = lambda params: {k: v for k, v in params.items() if v is not None}70 timeout = aiohttp.ClientTimeout(total=10)71 async with aiohttp.ClientSession(timeout=timeout) as session:72 async with session.get(73 REQUEST_URL, headers=remove_nones(HEADERS), params=remove_nones(url_params)74 ) as r:75 popup_news_data: Dict[str, Any] = await r.json()76 result: PopupVaccineNews = {"text": "", "buttons": []}77 for record in popup_news_data["records"]:78 if record["fields"]["title"] == "text":79 result["text"] += record["fields"]["words"]80 else:81 result["buttons"].append(record["fields"])82 return result83async def get_hospitals_from_airtable(84 offset: str = "", city: str = "臺北市"85) -> List[Hospital]:86 formula: str = f"{{施打站縣市(自動)}}='{city}'"87 url_params: AirTableRequestParams = {88 "filterByFormula": formula,89 "offset": offset,90 "maxRecords": 9999,91 "view": "給前端顯示用的資料",92 }93 # Must make global constant locally scoped to support typechecking for94 # ternary operators for optionals95 api_key: Optional[str] = AIRTABLE_API_KEY96 REQUEST_URL: str = "https://api.airtable.com/v0/appwPM9XFr1SSNjy4/tblJCPWEMpMg86dI8"97 authorization: Optional[str] = "Bearer " + api_key if api_key is not None else None98 HEADERS: Dict[str, Optional[str]] = {"Authorization": authorization}99 timeout = aiohttp.ClientTimeout(total=10)100 return_list: list[Hospital] = []101 remove_nones = lambda params: {k: v for k, v in params.items() if v is not None}102 async with aiohttp.ClientSession(timeout=timeout) as session:103 async with session.get(104 REQUEST_URL, headers=remove_nones(HEADERS), params=remove_nones(url_params)105 ) as r:106 hospital_json_objects: Dict[str, Any] = await r.json()107 return_list = list(108 map(109 lambda raw_data: parse_airtable_json_for_hospital(110 raw_data["fields"]111 ),112 hospital_json_objects["records"],113 )114 )115 if "offset" in hospital_json_objects:116 return return_list + await get_hospitals_from_airtable(117 hospital_json_objects["offset"]118 )119 else:120 return return_list121async def get_hospitals_links(122 offset: str = "", city: str = "臺北市"123) -> List[Dict[str, List[hospitalsLinks]]]:124 formula: str = f"{{縣市(純文字)}}='{city}'"125 url_params: AirTableRequestParams = {126 "filterByFormula": formula,127 "offset": offset,128 "maxRecords": 9999,129 "view": "前端顯示用",130 }131 api_key: Optional[str] = AIRTABLE_API_KEY132 REQUEST_URL: str = "https://api.airtable.com/v0/appwPM9XFr1SSNjy4/%E9%A0%90%E7%B4%84%E9%80%A3%E7%B5%90%E6%B8%85%E5%96%AE"133 authorization: Optional[str] = "Bearer " + api_key if api_key is not None else None134 HEADERS: Dict[str, Optional[str]] = {"Authorization": authorization}135 timeout = aiohttp.ClientTimeout(total=10)136 remove_nones = lambda params: {k: v for k, v in params.items() if v is not None}137 async with aiohttp.ClientSession(timeout=timeout) as session:138 async with session.get(139 REQUEST_URL, headers=remove_nones(HEADERS), params=remove_nones(url_params)140 ) as r:141 links_json_objects: Dict[str, Any] = await r.json()142 recordsWithPrimaryKey = list(143 map(144 lambda record: parse_airtable_json_hospitals_links(145 record["fields"]146 ),147 links_json_objects["records"],148 )149 )150 if "offset" in links_json_objects:151 return recordsWithPrimaryKey + await get_hospitals_links(152 links_json_objects["offset"]153 )...

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base.py

Source:base.py Github

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...65 # Graphs66 def create_plots(self, train_recorder, save_dir):67 fig, axes = create_fig((4, 4))68 plot_curves(axes[0, 0],69 xs=[remove_nones(train_recorder.tape['episode_i'])],70 ys=[remove_nones(train_recorder.tape['train_return'])],71 xlabel='episode_i',72 ylabel='train_return')73 axes[0, 1].plot(74 remove_nones(train_recorder.tape['eval_total_steps']),75 remove_nones(train_recorder.tape['eval_return_greedy']),76 label="greedy")77 axes[0, 1].plot(78 remove_nones(train_recorder.tape['eval_total_steps']),79 remove_nones(train_recorder.tape['eval_return_sampled']),80 color='green',81 label="sampled")82 axes[0, 1].set_xlabel('eval_total_steps')83 axes[0, 1].set_ylabel('eval_return')84 axes[0, 1].legend(loc="best")85 plot_curves(axes[0, 2],86 xs=[remove_nones(train_recorder.tape['episode_i'])],87 ys=[remove_nones(train_recorder.tape['episode_len'])],88 xlabel='episode_i',89 ylabel="episode_len")90 plot_curves(axes[1, 0],91 xs=[remove_nones(train_recorder.tape['update_i_actor'])],92 ys=[remove_nones(train_recorder.tape['pi_loss'])],93 xlabel='update_i_actor',94 ylabel='pi_loss')95 axes[1, 1].plot(96 remove_nones(train_recorder.tape['update_i_actor']),97 remove_nones(train_recorder.tape['policy_entropy']),98 label="exact",99 color="orange")100 axes[1, 1].set_xlabel('update_i_actor')101 axes[1, 1].set_ylabel('policy_entropy')102 plot_curves(axes[1, 2],103 xs=[remove_nones(train_recorder.tape['update_i_actor'])],104 ys=[remove_nones(train_recorder.tape['total_policy_loss'])],105 xlabel='update_i_actor',106 ylabel="total_policy_loss")107 # extra plots axes[2:,:] to be defined by child class...

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vae_model.py

Source:vae_model.py Github

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...69 # Graphs70 def create_plots(self, train_recorder, save_dir):71 fig, axes = create_fig((3, 3))72 plot_curves(axes[0, 0],73 xs=[remove_nones(train_recorder.tape['update_i'])],74 ys=[remove_nones(train_recorder.tape['reconstruction_loss'])],75 xlabel='update_i',76 ylabel='reconstruction_loss')77 plot_curves(axes[0, 1],78 xs=[remove_nones(train_recorder.tape['update_i'])],79 ys=[remove_nones(train_recorder.tape['prior_loss'])],80 xlabel='update_i',81 ylabel='prior_loss')82 plot_curves(axes[0, 2],83 xs=[remove_nones(train_recorder.tape['update_i'])],84 ys=[remove_nones(train_recorder.tape['total_loss'])],85 xlabel='update_i',86 ylabel='total_loss')87 plot_curves(axes[1, 0],88 xs=[remove_nones(train_recorder.tape['update_i'])],89 ys=[remove_nones(train_recorder.tape['lr'])],90 xlabel='update_i',91 ylabel='lr')92 plt.tight_layout()93 fig.savefig(str(save_dir / 'graphs.png'))...

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